Arts, Faculty of
Linguistics, Department of
DSpace
UBCV
Guntly, Erin Alisa
Doctor of Philosophy - PhD
University of British Columbia
Speakers use paradoxical responses, such as `yeah, that’s not right’ and `no, I agree’, but the function of these responses is not clear. While one use of response particles (RPs) such as 'yeah' and 'no' is to signal acceptance or rejection of at-issue content into the common ground, the linguistic content that follows these RPs in paradoxical responses suggests that `yeah’ is not agreeing to at-issue content, nor is `no’ rejecting it. This raises the question, what are these responses signalling to update the common ground? This dissertation argues that the two components of paradoxical responses, the RPs and the followup content, are selecting different targets. The set of targets includes not only the at-issue content, but also speaker beliefs and the questions under discussion. Testing this hypothesis, called the Response Target Hypothesis, draws on a mix of methodologies, one experimental and one rooted in corpus data. Corpora of transcribed, unscripted conversations were searched for RPs plus followup content; 200 tokens for `yeah’ and `no’ were identified for a total of 400, 173 of which were paradoxical. In addition to accepting and rejecting the at-issue content, responses which targeted speaker belief and questions under discussion were also frequent. In paradoxical responses, the followup content almost exclusively targets the at-issue content, and RPs select the additional targets. The experiment presented two-phase scripted conversations to participants: one phase using a combination of response particle and followup content, and the second phase checking if the common ground was updated by phase one. Participants were asked to rate the acceptability of the conversation after hearing both phases. Conversations which included paradoxical responses had a likelihood of being judged `appropriate’ or `very appropriate’ similar to those conversations which included non-paradoxical responses but which varied only in the RP. In other words `yeah, it wasn’t’ patterened along similar lines as `no, it wasn’t.’ Both data streams support the hypothesis that RPs can target more than at-issue content; the results demonstate that RPs that have followup content can target speaker beliefs and questions under discussion independent of at-issue content.
‘YEAH, I DOUBT IT.’ ‘NO, IT’S TRUE.’HOW PARADOXICAL RESPONSES IMPACT THE COMMON GROUNDbyERIN ALISA GUNTLYA DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THEREQUIREMENTS FOR THE DEGREE OFDOCTOR OF PHILOSOPHYinTHE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES(Linguistics)The University of British Columbia(Vancouver)March 2021© Erin Alisa Guntly, 2021The following individuals certify that they have read, and recommend to the Faculty of Graduateand Postdoctoral Studies for acceptance, the dissertation entitled:‘Yeah, I doubt it.’ ‘No, it’s true.’ How paradoxical responses impact the common groundsubmitted by Erin Alisa Guntly in partial fulஹ஭llment of the requirements forthe degree of Doctor of Philosophyin LinguisticsExamining Committee:Lisa Matthewson, Linguistics, UBCSupervisorRose-Marie Déchaine, Linguistics, UBCSupervisory Committee MemberCarla Hudson Kam, Linguistics, UBCSupervisory Committee MemberMarcin Morzycki, Linguistics, UBCUniversity ExaminerJessica de Villiers, English, UBCUniversity ExaminerManfred Kri஺஽a, Leibniz Center for General Linguistics, Humboldt University of BerlinExternal ExamineriiAbstractSpeakers use paradoxical responses, such as ‘yeah, that’s not right’ and ‘no, I agree’, but the func-tion of these responses is not clear. While one use of response particles (RPs) such as ‘yeah’ and‘no’ is to signal acceptance or rejection of at-issue content into the common ground, the linguisticcontent that follows these RPs in paradoxical responses suggests that ‘yeah’ is not agreeing to at-issue content, nor is ‘no’ rejecting it. This raises the question, what are these responses signallingto update the common ground?This dissertation argues that the two components of paradoxical responses, the RPs and thefollowup content, are selecting diஸferent targets. The set of targets includes not only the at-issuecontent, but also speaker beliefs and the questions under discussion. Testing this hypothesis,called the Response Target Hypothesis, draws on a mix of methodologies, one experimental andone rooted in corpus data.Corpora of transcribed, unscripted conversations were searched for RPs plus followup con-tent; 200 tokens for ‘yeah’ and ‘no’ were identiஹ஭ed for a total of 400, 173 of which were paradox-ical. In addition to accepting and rejecting the at-issue content, responses which targeted speakerbelief and questions under discussion were also frequent. In paradoxical responses, the followupcontent almost exclusively targets the at-issue content, and RPs select the additional targets.The experiment presented two-phase scripted conversations to participants: one phase usinga combination of response particle and followup content, and the second phase checking if thecommon ground was updated by phase one. Participants were asked to rate the acceptability ofthe conversation afிer hearing both phases. Conversations which included paradoxical responseshad a likelihood of being judged ‘appropriate’ or ‘very appropriate’ similar to those conversationswhich included non-paradoxical responses but which varied only in the RP. In other words ‘yeah,it wasn’t’ patterened along similar lines as ‘no, it wasn’t.’Both data streams support the hypothesis that RPs can target more than at-issue content; theresults demonstate that RPs that have followup content can target speaker beliefs and questionsunder discussion independent of at-issue content.iiiLay SummarySpeakers use paradoxical responses such as ‘yeah, I don’t think so,’ and ‘no, you’re right,’ in con-versation with surprising frequency, but what do they mean? This dissertation shows how thoseresponses can have three functions: They can accept or reject the truth of what was said (“That’strue.’’ or “That’s not true.’’); they can accept another speaker’s belief in what was said (“I knowyou think that, but it’s not true.’’); and they accept or reject the topic of the discussion (“We can’tknow, so let’s not discuss it.’’ or “We already know, so let’s not discuss it.’’). The dissertationuses corpus and experimental data to show that paradoxical responses can sometimes be moreappropriate than non-paradoxical responses and that the content afிer ‘yeah’ and ‘no’ is moreimportant in determining the function of the response.ivPrefaceThis dissertation is the original, unpublished work of Erin Alisa Guntly. The experiment inChapter 4 was conducted under UBC Behavioural Research Ethics Board Certiஹ஭cate NumberH16-03338.vContentsAbstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iiiLay Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ivPreface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vContents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viList of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiList of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiiiAcknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvDedication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii1 The research question and hypothesis . . . . . . . . . . . . . . . . . . . . . . 11.1 Introduction to paradoxical responses . . . . . . . . . . . . . . . . . . . . . . 11.2 Basic background and terminology . . . . . . . . . . . . . . . . . . . . . . . 41.2.1 Semantic terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.2.2 Common ground . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.2.3 Conversational components . . . . . . . . . . . . . . . . . . . . . . 71.3 The Response Target Hypothesis and its core predictions . . . . . . . . . . . . 121.4 Evidence to test the hypothesis . . . . . . . . . . . . . . . . . . . . . . . . . . 161.5 Preview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 Tracking information through discourse . . . . . . . . . . . . . . . . . . . . 182.1 Before an utterance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192.1.1 Sources of Common Ground . . . . . . . . . . . . . . . . . . . . . . 19vi2.1.2 Context of discourse . . . . . . . . . . . . . . . . . . . . . . . . . . 232.1.3 Audience design and accomodation . . . . . . . . . . . . . . . . . . . 252.1.4 Modeling the state of information before the utterance . . . . . . . . . 262.2 The exchange, a two-step process . . . . . . . . . . . . . . . . . . . . . . . . 272.2.1 The assertion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 292.2.1.1 The at-issue content . . . . . . . . . . . . . . . . . . . . . 292.2.1.2 The question under discussion (QUD) . . . . . . . . . . . 312.2.1.3 Statements of belief . . . . . . . . . . . . . . . . . . . . . 342.2.1.4 Modelling the utterance . . . . . . . . . . . . . . . . . . . 382.2.2 The response . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 402.2.2.1 Response options . . . . . . . . . . . . . . . . . . . . . . 432.2.2.2 The use of response particles . . . . . . . . . . . . . . . . . 44RPs as anaphors and RP elipsis . . . . . . . . . . . . . . . . . 44Response polarity . . . . . . . . . . . . . . . . . . . . . . . . 482.2.2.3 Adopting a view of response particles . . . . . . . . . . . . 502.2.2.4 Modeling the response . . . . . . . . . . . . . . . . . . . . 512.3 Afிer the exchange . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 522.3.1 Updating the common ground . . . . . . . . . . . . . . . . . . . . . 522.3.2 Models of discourse . . . . . . . . . . . . . . . . . . . . . . . . . . . 562.3.2.1 The Table . . . . . . . . . . . . . . . . . . . . . . . . . . 562.3.2.2 Commitment Spaces . . . . . . . . . . . . . . . . . . . . . 582.3.3 Role of memory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 612.3.4 Modelling common ground update . . . . . . . . . . . . . . . . . . . 622.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 653 Naturally occuring data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 663.1 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 663.1.1 Selecting the data (corpus and “wild”) . . . . . . . . . . . . . . . . . 673.1.2 What was excluded from my study . . . . . . . . . . . . . . . . . . . 74Fragmented discourse . . . . . . . . . . . . . . . . . . . . . . 74Missing context . . . . . . . . . . . . . . . . . . . . . . . . . 75Broadcast genre conventions . . . . . . . . . . . . . . . . . . 75Direct questions . . . . . . . . . . . . . . . . . . . . . . . . 76Quizzes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Backchanneling . . . . . . . . . . . . . . . . . . . . . . . . . 77viiOther syntactic uses . . . . . . . . . . . . . . . . . . . . . . . 783.1.3 Distinguishing between agreeing and disagreeing content . . . . . . . 783.1.4 Determining the question under discussion . . . . . . . . . . . . . . . 833.1.5 Summarizing the methodology . . . . . . . . . . . . . . . . . . . . . 853.2 An overview of the corpus data . . . . . . . . . . . . . . . . . . . . . . . . . 863.3 Non-paradoxical responses targeting only at-issue content . . . . . . . . . . . 883.3.1 ‘Yeah’ responses accepting at-issue content . . . . . . . . . . . . . . . 893.3.1.1 Direct agreement . . . . . . . . . . . . . . . . . . . . . . . 893.3.1.2 Entailing agreement . . . . . . . . . . . . . . . . . . . . . 913.3.2 Agreeing with negative polarity . . . . . . . . . . . . . . . . . . . . . 973.3.3 ‘No’ responses rejecting at-issue content . . . . . . . . . . . . . . . . 1003.4 Accepting belief and rejecting at-issue content . . . . . . . . . . . . . . . . . . 1023.5 Targeting the question under discussion (QUD) . . . . . . . . . . . . . . . . 1053.5.1 Accepting the QUD . . . . . . . . . . . . . . . . . . . . . . . . . . 1063.5.2 Rejecting the QUD . . . . . . . . . . . . . . . . . . . . . . . . . . . 1103.5.2.1 Answer to QUD already in common ground . . . . . . . . 1103.5.2.2 QUD will not beneஹ஭t from further discussion . . . . . . . . 1123.6 Conclusions and Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . 1154 Experimental results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1174.1 Experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1174.2 Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1194.2.1 Participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1194.2.2 Stimuli design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1214.2.2.1 Exchange I: Establish the common ground . . . . . . . . . . 123Scalar versus nonscalar predicates . . . . . . . . . . . . . . . . 123Response particle and followup content responses . . . . . . . 1244.2.2.2 Exchange II: Check the common ground . . . . . . . . . . . 1254.2.3 Experimental Task . . . . . . . . . . . . . . . . . . . . . . . . . . . 1264.2.4 Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1274.2.4.1 Visual aspects of the stimuli . . . . . . . . . . . . . . . . . 1274.2.4.2 Audio aspects of the stimuli . . . . . . . . . . . . . . . . . 1314.2.5 Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1334.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1384.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151viii4.4.1 How the experimental results support the hypothesis . . . . . . . . . . 1514.4.2 Potential variables beyond the study . . . . . . . . . . . . . . . . . . 1524.4.2.1 Intonation . . . . . . . . . . . . . . . . . . . . . . . . . . 1524.4.2.2 Listener status . . . . . . . . . . . . . . . . . . . . . . . . 1534.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1545 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1555.1 Overall conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1555.1.1 Comparing the data to the predictions . . . . . . . . . . . . . . . . . 1565.1.1.1 Accepting and rejecting the at-issue content . . . . . . . . . 1565.1.1.2 Accepting belief while rejecting at-issue content . . . . . . . 1575.1.1.3 Accepting and rejecting the question under discussion (QUD) 1605.1.2 Overall conclusions from the data . . . . . . . . . . . . . . . . . . . . 1615.2 Research into ‘yeah no’ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1645.3 Opportunities for further research . . . . . . . . . . . . . . . . . . . . . . . . 1655.3.1 Intonational variation . . . . . . . . . . . . . . . . . . . . . . . . . . 1675.3.2 Responses and Information Structure . . . . . . . . . . . . . . . . . 1685.3.3 Other languages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171Appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180A Corpus response forms from Chapter 3 . . . . . . . . . . . . . . . . . . . . . 181B Corpus Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184B.1 COCA ‘yeah’ (92 examples) . . . . . . . . . . . . . . . . . . . . . . . . . . . 185B.1.1 COCA ‘yeah’ + agree (55 examples) . . . . . . . . . . . . . . . . . . . 185B.1.2 COCA ‘yeah’ + disagree (37 examples) . . . . . . . . . . . . . . . . . 204B.1.2.1 COCA ‘yeah’ + disagree, accept belief (15 examples) . . . . . 204B.1.2.2 COCA ‘yeah’ + disagree, accept QUD (22 examples) . . . . 210B.2 LDC ‘yeah’ (93 examples) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217B.2.1 LDC ‘yeah’ + agree (67 examples) . . . . . . . . . . . . . . . . . . . . 217B.2.2 LDC ‘yeah’ + disagree (26 examples) . . . . . . . . . . . . . . . . . . 233B.2.2.1 LDC ‘yeah’ + disagree, accept belief (15 examples) . . . . . . 233B.2.2.2 LDC ‘yeah’ + disagree, accept QUD (11 examples) . . . . . . 238ixB.3 COCA ‘no’ (95 examples) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240B.3.1 COCA ‘no’ + agree (negative concord) (29 examples) . . . . . . . . . . 240B.3.2 COCA ‘no’ + disagree, rejecting the at-issue content (59 examples) . . . 249B.3.3 COCA ‘no’ + agree, reject QUD (7 examples) . . . . . . . . . . . . . 270B.4 LDC ‘no’ (98 examples) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272B.4.1 LDC ‘no’ + agree (negative concord) (37 examples) . . . . . . . . . . . 272B.4.2 LDC ‘no’ + disagree, rejecting the at-issue content (33 examples) . . . . 279B.4.3 LDC ‘no’ + agree, reject QUD (28 examples) . . . . . . . . . . . . . . 286C Experimental data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293xList of Figures2.1 Gradient conception of common ground . . . . . . . . . . . . . . . . . . . . . . 422.2 Non-gradient conception of common ground . . . . . . . . . . . . . . . . . . . . 422.3 ‘Yes’ as isolated response to positive and negative questions under Kramer and Rawl-ins (2008) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 452.4 Tree of ‘yes’ response in (35) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 452.5 Updating the common ground (or not) during discourse . . . . . . . . . . . . . . 532.6 Updating the common ground (or not) during discourse, with polarity . . . . . . . 542.7 Updating the common ground (or not) during discourse, with polarity and iteration 552.8 Sample Context Structure from Farkas & Bruce . . . . . . . . . . . . . . . . . . . 572.9 Sample Context Structure from Farkas & Bruce afிer utterance is introduced . . . . 572.10 Diagrams of Commitment Spaces in (55), from Kri஺஽a (2015, p. 334) . . . . . . . . . 602.11 Updated common ground afிer line 2 . . . . . . . . . . . . . . . . . . . . . . . . 632.12 Updated common ground afிer line 5 . . . . . . . . . . . . . . . . . . . . . . . . 643.1 Flowchart for determining agreeing content . . . . . . . . . . . . . . . . . . . . . 854.1 A selection of slides from the stimuli . . . . . . . . . . . . . . . . . . . . . . . . 1284.1 A selection of slides from the stimuli (cont.) . . . . . . . . . . . . . . . . . . . . . 1294.2 Reference code location on slide . . . . . . . . . . . . . . . . . . . . . . . . . . . 1304.3 “Yeah, it was.” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1324.4 “Yeah, it wasn’t.” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1324.5 “No, it was.” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1324.6 “No, it wasn’t.” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1324.7 Sample training slide, labeled in lower right corner . . . . . . . . . . . . . . . . . 1344.8 Illustration of slide presentation overview in Tab. 4.7 . . . . . . . . . . . . . . . . 1364.8 Illustration of slide presentation overview in Tab. 4.7 cont. . . . . . . . . . . . . . 1374.8 Illustration of slide presentation overview in Tab. 4.7 cont. . . . . . . . . . . . . . 138xi4.9 Count of Ratings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1404.10 Stacked bar graph of acceptability ratings . . . . . . . . . . . . . . . . . . . . . . 1424.11 Interactions of followup content and yeah/noin convergeand diverge . . . . . 1444.12 Interactions of response particle and agree/disagreein convergeand diverge 1454.13 Interactions of three variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1464.14 Stacked bar graph of probabilities . . . . . . . . . . . . . . . . . . . . . . . . . . 1475.1 Probabilities of appropriate ratings for paradoxical and nonparadoxical responsestimuli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1635.2 Kri஺஽a’s Commitment Space Development (Kri஺஽a, 2015, p. 334) . . . . . . . . . . . 1665.3 Intonation of ‘yeah it is’ from example . . . . . . . . . . . . . . . . . . . . . . . 168xiiList of Tables1.1 Results of Google search of combinations . . . . . . . . . . . . . . . . . . . . . . 31.2 Predicted appropriate responses of The Response Target Hypothesis . . . . . . . . 151.3 Predictions of The Response Target Hypothesis . . . . . . . . . . . . . . . . . . . 152.1 Constraints on discourse contexts . . . . . . . . . . . . . . . . . . . . . . . . . . 242.2 Polarity features of response particles . . . . . . . . . . . . . . . . . . . . . . . . 482.3 Polar response particles in English and Romanian . . . . . . . . . . . . . . . . . . 493.1 Percentage of included results from total search results (est.) . . . . . . . . . . . . 703.2 Predicted appropriate responses of The Response Target Hypothesis . . . . . . . . 863.3 Distribution of Corpus examples, n=400 . . . . . . . . . . . . . . . . . . . . . . 863.4 Summary of corpus data and discussion sections . . . . . . . . . . . . . . . . . . 883.5 Accepting at-issue contentwith ‘yeah’ + agree highlighted (Table 3.4 repeated) . . . 893.6 Accepting at-issue content with ‘no’ + agree highlighted (Table 3.4 repeated) . . . . 973.7 Rejecting at-issue content with ‘no’ + disagree highlighted (Table 3.4 repeated) . . . 1003.8 Accepting belief and rejecting at-issue content with ‘yeah’ + disagree (Table 3.4 re-peated) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1033.9 Accepting the QUD with ‘yeah’ + disagree highlighted(Table 3.4 repeated) . . . . . 1063.10 Reject QUD with ‘no’ + agree highlighted (Table 3.4 repeated) . . . . . . . . . . . 1103.11 Distrubution of Corpus examples, n=400 (duplicate of Table 3.3) . . . . . . . . . . 1153.12 Summary of corpus examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1164.1 Experimental Predictions of Response Target Hypothesis . . . . . . . . . . . . . . 1184.2 Notation for results discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . 1194.3 Overview of English native speaker participants’ primary home languages, age andgender . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1204.4 Template of stimuli script . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122xiii4.5 Summary of example dialog in (1) . . . . . . . . . . . . . . . . . . . . . . . . . . 1234.6 Slide reference codes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1304.7 Slide presentation summary of Fig. 4.8, pages 136–138 . . . . . . . . . . . . . . . . 1354.8 Notation for results discussion (repeated from Table 4.2) . . . . . . . . . . . . . . 1384.9 Average and count of responses (n=324, 4 of each type per participant) . . . . . . . 1394.10 e -values of four variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1434.11 Probabilities of acceptability under experimental conditions . . . . . . . . . . . . 1474.12 Probabilities of converge, from Table 4.11 . . . . . . . . . . . . . . . . . . . . . 1494.13 Overview of participant ratings, predictions and probabilities . . . . . . . . . . . . 1504.14 Polarity of responses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1525.1 Summary of Response Target Hypothesis predictions, experimental and corpus data 162A.1 Responses to p—‘yeah’ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182A.2 Responses to p—‘no’ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183B.1 Corpus Data by outcome and corpus . . . . . . . . . . . . . . . . . . . . . . . . 184B.2 Examples in appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185C.1 Count of acceptability ratings under experimental conditions . . . . . . . . . . . . 294xivAcknowledgementsI had my doubts that I would ஹ஭nish. That I would complete my dissertation became, in my mind,an increasingly remote possibility as things went on, but here I am. Finished.The most important person who made that happen is Lisa Matthewson, my supervisor. Shesaw what was good and interesting in my work even when I didn’t. Her honesty was at the heartof my mantra, Lisa says it’s OK so it must be OK, because she was all the things I needed in asupervisor: patient, exacting, honest, encouraging, and committed to my success. I’m so honoredthat she took me on, almost on the spur of the moment, and I’m so grateful for everything she’sdone for me over the past nine years. I’m also happy that, afிer all of our conversations and upsand downs over the years, we have been able to become friends. Thank you, Lisa, for encouragingme in more ways than you know.I really did have the perfect committee, because in addition to Lisa, I had Carla Hudson-Kamand Rose-Marie Déchaine, who were incredibly supportive both intellectually and personally.Carla’s guidance through the experiment and analysis made it possible to do that work and to getmeaningful, signiஹ஭cant results. Rose-Marie has a mind like no other, razor sharp and analytical,and even when I grumbled I knew that she was usually right. I’m sorry about the grumbling,Rose-Marie, but I’m grateful for your patience. Both Carla and Rose-Marie have made me abetter scholar, and they’re the voices in my head that push me to be a better writer as well.My RAs were also instrumental in doing the experiment, Ivana Prpic, Brittany Mallet, NaimaMansuri and Bridget Patchett. They ran participants, proofread scripts, entered data, and didpretty much anything else that I asked. Ivana also made recordings and did the drawings for thestimuli, not to mention rating all of the corpus data. I could not have asked for a better group ofpeople to help me in my research.I’m also part of a wonderfully supportive cohort. Hermann Keupdijo, Adriana Osa-Gomezdel Campo, Emily Sadlier-Brown, and honorary cohort members Oksana Tkachman and NedaTodorovic, I don’t know what I can say, but I don’t think I need to say anything. You alreadyknow. There’s something about going through this experience together that creates a uniquexvkind of connection. I’m glad to have shared this time with you.Natalie Weber also understands all of the emotions that no one tells you about when you getonto the PhD roller coaster, and we’ve spent a lot of time re஺ாecting and commisserating. EllaFund-Rezniczek has also been a reliable sounding board and coஸfee companion. Thank you toboth!I must thank my oldest and dearest friend, Natalie Piispanen, who has ofிen listened patientlyto me being unreasonable, and then kindly told me just how unreasonable I was being. She’s neverexpressed even the slightest doubt that I would ஹ஭nish and that everything would work out; shejust doesn’t entertain that possibility. It’s very reassuring.My sister Kori has supported me, making recordings, reading through passages, serving as myconsultant for judgements. She also helps me ஹ஭nd down time, because sometimes it’s importantto put the computer away for an hour.Finally, and most importantly, I have to recognize my parents. My dad passed away quitesuddenly in May of 2019, and I am still heartbroken that he’s not here for this. He was always oneof my biggest supporters and best sounding boards, and he was so excited to hear about my work.I’ve dedicated the dissertation to him, and I included his artwork in the defense presentation,because he’s so much a part of this experience, even though he’s gone. His passing makes myஹ஭nishing bittersweet; I wish he were here to share this time. I miss him so much, but he’s alwayswith me.And my mom. I don’t think it’s possible to put into words how much she’s done for me,and how grateful I am for her unquestioning support. My mom has always been a bit of a mir-acle worker; she just makes things work because they can’t not work. Even when my dad passedaway, she still just made things work for me, no matter what I needed. These words are a poorexpression of the depth of my gratitude, but thank you.Thank you to all the people who have been there for all the ups and downs. I will always begrateful.xviDedicationTo my dad, who ॾ always with meIn memory of Donald Allen Guntly, 1946-2019Show me that river, take me acrossWash all my troubles awayLike that lucky old sun, give me nothing to doBut roll around heaven all dayThat Lucky Old Sun by Ray CharlesxviiChapter 1The research question and hypothesis1.1 Introduction to paradoxical responsesAs users of English, we take two things for granted: that we talk with each other in order to “es-tablish a joint understanding” (Garrod and Pickering, 2004, p 8), and that people within the sameconversation are understanding, or at least trying to understand, that conversation in roughly thesame way (Clark and Brennan, 1991; Grice, 1975, a.o.). In order to achieve that goal of understand-ing, speakers of a given language respond to each other over the course of a conversation.The understanding established during discourse can be personal (a story about last weekend),professional (a job oஸfer), informative (a report about a bus detour), re஺ாective (talking throughan emotion), humorous (an embarrasing anecdote), or re஺ாect some other purpose, but a rea-sonable assumption is that the point of most conversations, however brief, is for at least oneperson to convey a message that at least one other person might understand and accept; in otherwords, the point is to expand the common ground between the participants in the conversation.1If, for example, a conversation was intended to agree on a meeting time, then it would proba-bly not be considered a successful conversation if one person walked away thinking the meetingwould be Friday and the other person thought Thursday. To help ensure an understanding, En-glish speakers are likely to use words like ‘yeah’ and ‘no’ to manage this exchange by signalling(dis)agreement.Response particles like ‘yeah’ and ‘no’ might be thought to signal agreement and disagree-ment with the preceding utterance, respectively. One of the goals of this dissertation is to showthat the pre-theoretic notion of ‘yeah’ and ‘no’ meaning ’agree’ and ‘disagree’ needs to be un-1Other models of conversation do exist, notably ones that focus on origo ground (Déchaine et al., 2017), faultlessdisagreement (Umbach, 2014), or the interpersonal and social/interactional nature of discourse (Turnbull, 2003).1packed and examined more closely. Responses using those particles and phrases such as ‘I agree’or ‘That’s not right’ conஹ஭rm whether the speakers understood the information they have heard.Are ‘yeah’ and ‘no’ relegated only to conஹ஭rming or denying understanding? What happenswhen the response particle and the following phrase seem to disagree? Consider the followingexchange from an unscripted portion of a television show2:(1) Context: Three friends and colleaguॽ were trying to leave a beach but got lost and endedup back where they started. The one who wॼ navigating said that he did not realize therewere two seॼ in the country, to which hॾ colleaguॽ replied angrily that there weren’t; ॼ thespeakers have a history of teasing and insulting each other, they continue their conversationand use the similarity of “sea” to the letter c to suঃest an insulting description for JC. (RHsays [si:] in both instancॽ.)RH: There’s two “c”s here [gesturing at himself and JM] for believing that that “c” [indi-cating JC] could navigate!JM: no you’re right! [looking at RH]Is it a valid assumption that all of the participants have access to the same understanding atthe end of the exchange? This is unclear from this small exerpt, but it is possible, even likely, thatJC disagrees at least with the presupposition that he, JC, is a “c,” although he should at least beaware of RH’s view, even if he does not share it. Even under a generous interpretation, it is notpossible to assume that ‘no’ simply rejects RH’s assertion, because ‘no’, in a naive understanding,does not get followed with “you’re right.” Using ‘no’ to deny the accuracy of a statement, andthen following that ‘no’ with “you’re right” to conஹ஭rm the accuracy of the same statement createsa paradox. So what could the combination of ‘no’ and ‘you’re right’ mean? Afிer an exchangelike that in (1), what is the state of the common ground between these three speakers?These are essentially the questions behind this dissertation:(2) a. Is the common assumption about the ‘yeah’ signalling agreement and ‘no’ disagree-ment rejection valid?b. What do paradoxical responses, such as ‘no, you’re right,’ signal?c. What is the state of the common ground afிer such a response?2This exchange comes from The Grand Tour, produced by Amazon.2Table 1.1: Results of Google search of combinationsyeah [+] no [−]you’re right [+] 618,000 655,000it’s true [+] 588,000 648,000you’re wrong [−] 442,000 494,000it’s not true [−] 1.98m 517,000Paradoxical responses are not isolated to the particular form of ‘no, you’re right,’ and theyoccur more frequently than one might assume. That ‘yeah’ and ‘no’ can both combine with‘you’re right/it’s true’ and ‘you’re wrong/it’s not true’ is evident from a basic Google search, theresults of which are shown in Table 1.1.3 It is unclear how these paradoxical responses impact thecommon ground, which is the information shared between speakers.For purposes of framing the research question, let us think of ‘yeah’ and ‘you’re right/it’s true’as having a plus [+] value, and ‘no’ and “you’re wrong/it’s not true” as having a minus value [−]as relates to the truth of the preceding statement. Initial assumptions about how ‘yeah’ and ‘no’work would predict that the combinations would pair like with like, so that ‘yeah [+], it’s true[+]’ would be more common than responses that combine diஸferent polarities, such as ‘no [−],it’s true [+]’. But the Google results in Table 1.1 show exactly the opposite. The results show that,not only are divergent polarity responses not an anomoly, they are in fact the three most frequentresponses: ‘yeah [+] it’s not true [−]’ (1.98m), ‘no [−] you’re right [+]’ (655,000), and ‘no [−]it’s true’ [+] (648,000).Google searching a phrase hardly gives the most indicative data about language usage, butthese results force the question:when speakers use these paradoxical combinations, when JM says“no you’re right” in (1), what is being communicated? If we assume that “you’re right” is signalingagreement with RH’s statement, what is ‘no’ responding to?The question of paradoxical responses has received surprisingly little attention in the liter-ature. The work that has been done has focused on the Australian use of ‘yeah nah’ (Burridgeand Florey, 2002) or has been more informal discussion that methodical research (Liberman,2008b). Although researchers are beginning to turn their attention to the problem of paradoxi-cal responses (Tian and Ginzburg, 2016), no analysis has yet been oஸfered. The insights of these3The Google search was conducted with all eight combinations on April 21, 2017. The terms were combined inall eight permutations, so that ‘yeah you’re right’ returned 618,000 results, ‘no it’s not true’ 517,000, etc.3threads of research, while interesting and informative, are not central to informing this disserta-tion; they are discussed more fully in Ch. 5.Understanding the possible targets of response particles requires that we understand howboth the particles and their targets interact with the common ground. The common groundis the repository for information which is mutually agreed upon by discourse participants andwhich is available for both to use over the course of the conversation (Clark and Brennan, 1991;Stalnaker, 1978; Keysar, 1997). The data suggest that ‘yeah’ and ‘no’ may respond to things otherthan at-issue content, including speaker beliefs and the Question Under Discussion (QUD). Byseparating these components of discourse, we can attempt to identify what ‘yeah’ and ‘no’ areresponding to in a more demonstrable fashion.1.2 Basic background and terminologyThe purpose of this section is to provide the background and terminology necessary to discuss thehypothesis and its predictions. It is divided into three sections, which focus on general semanticterms, terms relating to the common ground, and terms from conversation analysis.1.2.1 Semantic termsWhen considering the role of response particles, the most crucial semantic term to deஹ஭ne ispropo-sition, which is the semantic content of a full sentence and represents a function from worldsto truth values. A proposition is truth-conditional and of the type <s, t>, that is, a functionfrom situation to truth-value. Many scholars (Stalnaker, 1978; Farkas and Bruce, 2010, a.o.) treatpropositions as the ‘building blocks’ of the common ground, in that the common ground can betreated as a set of propositions to which other propositions can be added as a result of discourse.The category ‘proposition’ can include several things. Presuppositions, at-issue content, not-at-issue content, speaker beliefs can all be expressed as propositions, but they each have a diஸferentstatus in the discourse. A single utterance may introduce several propositions, as well as a setof Questions Under Discussion (QUD). The question emerges about which of these types ofcontent is already in the common ground at the time of the utterance and which enter into thecommon ground as a result of the discourse.(3) Utterance: Oh my god, those Seahawks fans are so freakin’ obnoxious!prop.: at-issue content. Fans of the Seahawks are obnoxiousQUD. Are Seahawks fans obnoxious?4prop.: presupposition. There are fans of the Seahawks.prop.: speaker belief. Speaker X believes that Seahawks fans are obnoxious.The utterance in (3) introduces several propositions. The at-issue content (sometimes ab-breviated AIC) is ofிen regarded as the point of the utterance. It is frequently, though not nec-essarily, new information that the speakers have not signalled their agreement on. Tonhauser(2012) identiஹ஭es three properties which are critical in identifying at-issue content:(4) Evidence for at-issue contenta. direct agreement/dissent is possibleb. it addresses the question under discussion (QUD)c. it determines the set of alternativesItem (4.b) indicates that the at-issue content relates strongly to the Question Under Dis-cussion. The Question Under Discussion (QUD) can be thought of as the question whichthe discourse is intended to answer.4 An utterance may introduce more than one QUD, as Sec.2.2.1.2 discusses, but the QUD identiஹ஭ed in (3) is the narrowest of these QUDs. It introduces twopropositions, namely p and ¬p which answer this narrow QUD. Presuppositions are propo-sitions which are assumed to already be in the common ground; presupositions are regarded astrue, regardless of the truth the at-issue content. In (3), the utterance presupposed the existenceof Seahawks fans, which is a necessarily true if the utterance itself is true. Speaker belief or com-mitment is the publicly declared belief of a given speaker at a given moment in the discourse. Thespeaker in (3) believes in their statement concerning Seahawks fans, but their interlocutor maynot share this belief.The central question of this dissertation is which of these components ‘yeah’ and ‘no’ cantarget. To say that response particles can only respond to a proposition does not resolve the para-dox of why speakers can say “yeah no that’s right,” as one example. If the question is rephrased toask about what kind of proposition each targets, then that opens up the possibility of resolvingthe paradox.An important note about terminology concerns concerns how the term ‘proposition’ is used.This dissertation builds on the work of several researchers from several disciplines, and most ofthe work discussed in following chapters uses the term ‘proposition’ to discuss what enters the4More speciஹ஭cally, the QUD is a set of answers to a question that arises from the discourse; more details on thisin Sec. 2.2.1.2.5common ground. In order to fairly and accurately represent the work of others, I will not pre-sume to redeஹ஭ne anyone’s use of ‘proposition’, instead I will simply use the term ‘proposition’to present their work as faithfully as possible. However, my analysis relies on a consideration oftypes of propositions, in which the diஸferent types of propositions in (3) each impact the com-mon ground in a way that is distinct from the other types of propositions. I will use terms suchas those in (3) to refer to these types in my analysis.The data presented to this point suggest that it is not enough to simply say that the commonground contains “propositions,” because all of the exchanges resort to something beyond whatwas said. Without understanding the potential candidates for inclusion in the common ground,it will be impossible to understand what the common ground might therefore contain.1.2.2 Common groundA working deஹ஭nition of common ground5 is this: the repository of information that the inter-locutors have signalled is mutually shared,6 and crucially, that is available for reference at a laterpoint in the discourse. This deஹ஭nition draws from observations that certain information must beunderstood to be shared by the interlocutors (Stalnaker, 1973, 1978), combined with observationsthat the information that is placed in the common ground is managed by the interlocutors overthe course of the discourse through the minimal required eஸfort on the part of the interlocutors(Clark and Marshall, 1981; Clark and Wilkes-Gibbs, 1986; Clark and Brennan, 1991; Clark, 1996).That the information is available for reference at some later point in the conversation distin-guishes the common ground as a repository of information from the short term processing mem-ory that stores what was said verbatim (Sachs, 1967). This is an important distinction, becausepeople are capable of recalling an utterance verbatim for a short time afிer hearing it (Gurevitchet al., 2010), but the syntactic structure of an utterance is generally not persistent beyond a fewseconds whereas the gist, the semantic content, persists for longer (Anderson, 1974; Sachs, 1967).Moreover, short term memory does not take into consideration the information that might beavailable to the other discourse participant(s). Keysar (1997) points out that the common groundis essentially meta-knowledge; “it is knowledge about knowledge” (Keysar, 1997, p. 2).The notion that information that was exchanged linguistically should be available for laterreference ஹ஭nds support in experimental (Keysar, 1997; Keysar et al., 1998, a.o.) and theoretical5A fuller discussion of the deஹ஭nition of common ground is in Sec. 2.1.1.6It is fair to ask how speakers signal that information is mutually shared, and a detailed answer will be providedin Sec. 2.3.1. For the following discussion, is should be suஸஹ஭cient to recognize that speakers have several strategies,including the use of responses and response particles (Stalnaker, 1978; Clark and Brennan, 1991).6(Heim, 1982, a.o.) work on nominal referents.7 Consider the example in (5), in which a referentdescription is used in line 1, and pronouns in lines 2 and 3.(5) Example of using the common ground for discourse referents1. α: The guy who delivered my lunch to my oஸஹ஭ce today was such an unbelievable jerk!2. β: That’s awful. You should complain about him to the delivery company.3. α: I didn’t get his name, or I would!The only way that both speakers can know who “him/his” is in lines 2 and 3 is from theestablishment of a referent in line 1 with the deஹ஭nite description “the guy who delivered my lunchto my oஸஹ஭ce today.” The only source of this information about the discourse referent for β is α’slinguistic description, which was suஸஹ஭cient to place the referent in the common ground duringthe discourse, as both speakers then use the pronouns ‘him’ and ‘his’ to refer to him. If thesetwo speakers continue their discussion, they can refer back to the surly delivery guy later in theirdiscourse as well, because the referent remains available in the common ground.1.2.3 Conversational componentsNatural discourse is messy, containing false starts, self-corrections, turn management utterances,backchanneling and sentence fragments, none of which convey semantically full propositions.The motivations behind these non-sentential discourse components may be pragmatic (Trau-gott, 1982; Schegloஸf, 1992; Sydorenko et al., 2014) or concerned with managing the process ofdiscourse, such as turn taking (Schegloஸf, 1982; Fox Tree and Schrock, 1999). Though these partsof discourse are crucial to the functioning of conversations, they are not the focus here. Rather,the focus is how response particles and their followup content are used to manage the linguisticcontent of the common ground.The cooperative principle (Grice, 1975), that speakers in conversation attempt to cooperatewith each other, is important in expanding and using the common ground, in part because itdictates that speakers shape their message to be relevant to the discourse. Cooperation also rec-ognizes that speakers use knowledge beyond the discourse to shape what they say and how theysay it. Clark and Wilkes-Gibbs (1986) look at cooperation between speakers and term this coop-eration the least collaborative effort (LCE). It is the minimal amount of work that speakersmust do to communicate their message eஸfectively. Natural discourse is replete with examples of7See Chapter 2 for a detailed discussion of this evidence.7LCE, as speakers frequently use utterances smaller than a clause, and interlocutors ofிen acceptthe contribution of these utterances by ‘ஹ஭lling in the blanks,’ as in (6).(6) A: That tree has— uh— uh—B: Tentworms.A: Yeah.B: Yeah. Clark and Brennan (1991, p. 226)The LCE is the sum of the eஸfort of two (or more) speakers in conversation. Looking at (6),we can consider the alternatives to B completing A’s sentence. Had B not intervened, the eஸfortrequired of A to retrieve the word would have been much higher, and the eஸfort required of B towait patiently would possibly also have been higher.…speakers ofிen realize that it will take more collaborative eஸfort to design aproper utterance than to design an improper utterance and enlist their adresssees’help. Speakers, for example, can present a provisional utterance and add try mark-ers8 to ask for conஹ஭rmation. They can present a diஸஹ஭cult utterance in installmentsand check for undertsanding afிer each installment … They can invite addressees tocomplete an utterance they are having trouble with. And they have many other col-laborative techniques at their disposal. The principle of least collaborative eஸfort isessential for a full account of face to face conversation.Clark and Brennan (1991, p. 226)LCE accounts for facets of discourse that are necessarily cooperative, such as understandingan implicit request, providing a missing word (as in (6)), and managing the common ground.Shober and Brennan (2008) also point out that LCE and its beneஹ஭ts, namely reduced processingcosts, are conஹ஭ned to discourse because of its interactive nature. LCE will be particularly im-portant in Chapter 3, which will work through many examples of natural language taken fromcorpora, but its importance may not be obvious because speakers seem to take collaboration forgranted, which becomes clear in cases such as (7).(7) 1. A: uh about thirteen years ago uh we looked for a home and the things that wewere seeing were uh not up to my standards ʵʩʦʺ ʸʦʳʦ ʴʵʪʭʭ ʣʶʪʭʥʪʯʨ ʩʰʮʦʴ8Try markers are utterances such as “‘uh–” in (6) which signal to the interlocutor that the speaker is attemptingto complete the utterance or inviting the interlocutor to intervene, although without necessarily surrendering theirturn.8ʣʢʤʬ ʵʩʦʯ ʭʪʬʦ ʵʩʦʺ ʩʢʷʦ ʧʰʳ ʢ ʩʶʯʥʳʦʥ ʢʯʥ ʧʪʧʵʺ ʺʦʢʳʴ you know the verylittle insulation in the walls and very little insulation in the ceiling so2. B: yes um-hum that doesn’t work these days3. A: yeah and it was uh it wasn’t what we wanted so we did some research and i knewthe land there’s a lot of ledge up here so you have to be carefulLinguistic Data ConsortiumThe LCE is important in this conversation because it allows the speakers to arrive at whatappears to be a mutual understanding of what “that” means in line 2. Line 1 contains severalpossible candidates, marked in bold face, but the one that the speakers select (according to myown judgements) is the one suggested by the clause in small caps: the building of homes like theyhave for 150 years. A straightforward test of this claim is to substitute the potential referents inthe place of “that” and see which ones still make sense; (8) presents a few of these tests.9(8) Testing antecedents for “that” in (7), line 21. # yes um-hum a home doesn’t work these days.2. # yes um-hum [that] the things that we were seeing were not uh up to mystandards doesn’t work these days.3. yes um-hum the building of homes back then like they have for a hundredand fifty years doesn’t work these days.The ஹ஭nal candidate, “the very little insulation in the walls [and] very little insulation in theceiling,” are examples of how “they were still building homes back then…” Crucially, the absenseof any other negotiation for meaning, plus the absence of any evidence of misunderstanding ordisagreement, suggests that the discourse is in fact collaborative, but absent any overt discussionof what “that” means, the collaboration is also minimal. The purpose of the LCE is, afிer all, tofacilitate discourse by allowing the interlocutors to ‘ஹ஭ll in the blanks’ of what is not explicit.Response particles are a category of words that are used to respond to utterances; responseparticles do not usually have their own substantive meaning but are instead used to manage dis-course between interlocutors by signalling continued attention, turn management, acceptanceand rejection, etc. The set of English response particles includes ‘yes’, ‘yup’, ‘yeah’ and otherswhich might loosely be referred to as ‘positive particles,’ and ‘no’, ‘nope’, ‘nah’, and similar as‘negative particles.’ While particles within the positive and negative categories are frequently9The complementizer [that] in brackets has been added where necessary to ensure grammaticality.9treated as variants of each other, their distribution and restrictions suggest that they are not infact identical (Pope, 1972; Wiltschko, 2016), and this work will conஹ஭ne itself to looking at ‘yeah’and ‘no’. One reason for limiting the discussion is that ‘yeah’ and ‘no’ can appear in paradoxicalresponses, whereas other candidates, such as ‘yes’ and ‘nope’ cannot.(9) 1. Yeah, it isn’t. 2. # Yes, it isn’t.3. No, it is. 4. # Nope, it is.The term response particlॽ is preferred among the disciplines of discourse analysis and con-versation analysis, which are concerned primarily with how language is used in communication,while theoretical disciplines that are concerned with sentence level phenomena, such as syntax,generally use the term polarity particlॽ. As this dissertation is concerned with the discourse level,the term response particles will be used. Where it is important to distinguish between responseparticles that have polarity (‘yeah’ and ‘no’) from other response particles (uh–, hmm), the termpolar response particles, or prps, will be used.Several other terms are essential in discussing discourse organization, starting with the broad-est term, utterance. Anutterance is simply what a speaker says; it can be a full sentence, or even aseries of sentences, for instance as part of a lecture. Importantly, an utterance is doing some kindof work, and is usually categorized according to the type of that work: question, announcement,rejection, agreement, among many other types (Schegloஸf, 2007). The notion of utterance tiesclosely with that of the speech act, which is in essence that which an utterance is accomplishingbeyond its compositional meaning (Searle, 1969). For instance, an oஸஹ஭ciant at a wedding is notsimply saying the words “I now pronounce you…”, they are signalling the commencement of alegal union. This illustrates why my analysis rests less on the form of an utterance and more onwhat an utterance does in context (Pridham, 2001).On the other hand, an utterance can be a single response particle or something indicatingbackchanneling, such as uh-huh or mm as used for signalling continued attention (Schegloஸf,1982) and at least tacit acceptance of the preceding discourse (Tolins and Fox Tree, 2015). Backchan-neling does not place information into the common ground, however, as there is no evidence ofmutual acceptance, only evidence of cooperation in letting a speaker ஹ஭nish their turn; an inter-locutor can dispute the veracity of a previous claim in their turn. As backchanneling does notsignal the beginning of a turn, it will have no additional content afிer the backchannel itself; thisis true when ‘yeah’ is used as a backchannel as well, so that the responses of ‘yeah’ plus followupcontent cannot be considered backchannels.10Turns are the most basic unit of discourse, and a turn is simply one speaker’s opportunityto speak with the expectation that the other discourse participants will give that speaker theirattention. Turns can contain non-verbal content; when a speaker pauses to gather their thoughtsbut does not invite another speaker to contribute to the discourse, they are maintaining theirturn. Turns contain utterances, but turns and utterances are not interchangeable. To illustratethe diஸference, let us consider the hypothetical example in (10), noted with the conventions ofdiscourse analysis (Tannen et al., 2015).(10) An example of an interview1. A. How did – how did you get into this work?2. B. (laughter) Well that’s you know it’s quite a story but I just got to feeling [3 sec pause]it’s funny how s[ometimes…3. A. [yeah4. B. like you just get to the point in your life where you just have to you know changethings. and I knew this woman who…This example includes four utterances, but only two turns. The ஹ஭rst turn is Speaker A’s open-ing question, and the second turn begins when Speaker B starts to respond. Speaker B takes a 3second pause in Line 2 without ending their turn; Speaker A oஸfers a backchannel ‘yeah’ thatoverlaps most of Speaker B’s word ‘sometimes,’ but crucially Speaker B does not yield the ஺ாoorto Speaker A, nor does Speaker A make any eஸfort to begin their turn. Speaker A’s ‘yeah’ is notfollowed with any meaningful content.Turns are also frequently organized into adjacency pairs (Schegloஸf, 1982), where one turnrelates directly to the previous turn. A common type of adjacency pair is question and answer, asin (11), which contains two adjacency pairs. It is a fairly common kind of exchange, that of order-ing at a coஸfee shop. It relies on the conventional nature of the exchange, in which the questionsand responses are quite predictable for both parties. This particular example was overheard at alocal Starbucks.(11) 1 Barista: What can we get you?2 Customer: Yeah, I’d like a tall dark roast with room and a bagel.3 Barista: Toasted with cream cheese?4 Customer: Yeah, that’d be great.11Assuming that the barista and customer have little if any previous interaction, the commonground that exists before the exchange in (11) is entirely derived from the shared environmentand the shared familiarity of how ordering at a coஸfee shop works. This exchange contains twoadjacency pairs, 1 and 2, and then 3 and 4, and these in turn represent four turns as well as fourutterances.Now let us consider another exchange, this time between two friends:(12) 1 N: So I got an email from Amy2 E: yeah3 N: that I’m really excited about, in part4 E: yeah5 N: because it completely circumvents my boss…This exchange consists of ஹ஭ve utterances but only one turn; two of the utterances are backchan-neling, namely Speaker E’s contributions in lines 2 and 4. Backchanneling allows a listener tosignal their continued attention to what a speaker is saying. Crucially, backchanneling does notsignal agreement with what a speaker is saying, as the listener can still challenge the truth of whatwas said when their turn arrives. Backchanneling is also not a turn, because the speaker who isbackchanneling, Speaker E in the case of (12), is not claiming the ஺ாoor to make a contributionto the discourse, they are signalling their attention to Speaker N’s continued contribution; it isSpeaker N’s turn still. In the discourse following (12), Speaker E could use their turn to reject partor all of what N said, perhaps by questioning who Amy is or by asserting that N doesn’t seemexcited. The fact that E said ‘yeah’ here is not evidence of E’s acceptance of N’s claims.In both (11) and (12), ‘yeah’ is used to respond to the other speaker, but these uses are not theobject of inquiry of this dissertation. In (11) line 4, ‘yeah’ is used to respond to what is understoodas a yes/no question (even though it takes the form of a sentence fragment), and such a use of aprp should not be surprising. Example (12) demonstrates the use of ‘yeah’ as a backchannel.1.3 The Response Target Hypothesis and its core predictionsIn exploring the question of what can be placed in the common ground through the use of re-sponse particles, this dissertation proposes the hypothesis in (13), that the at-issue content andother propositions introduced by an utterance may be entered into the common ground, all ofwhich are managed through the use of response particles. This dissertation asserts that responseparticles can target at-issue content, belief states, and the Question Under Discussion (QUD).The Response Target Hypothesis predicts ஹ஭ve possible outcomes:12(13) Hypothesis:Response particles, and the linguistic content following response particles aspart of a response, can target (accept or reject) at least the following types of con-tent for inclusion into the common ground: at-issue content, speaker beliefs, theQuestion Under Discussion.Predicted targets and outcomes of responses and followup content:At-issue content1. β accepts the at-issue content of α’s assertion; this puts the at-issue contentin the common ground as something that both speakers agree is true.2. β rejects the at-issue content in α’s assertion; this excludes the at-issuecontent from the common ground and forces a crisis (in the terms of Farkas andBruce, 2010), the resolution of which falls to other assertions and responses.Speaker belief in at-issue content3. β accepts α’s belief in the at-issue contentwithout committing themselvesto the same belief; this signals a mutually shared agreement concerning α’s be-lief in the at-issue content and the acceptance of that belief into the commonground, and crucially does not necessarily put the at-issue content into the com-mon ground.* Rejecting speaker belief is not considered felicitous in most contexts.Question Under Discussion (QUD)4. β’s response accepts the QUD as a valid question to discuss, to which ananswer is not currently available in the common ground or in β’s contribution.5. β’s response rejects the QUD because the answer is already established inthe common ground or the answer is unattainable at that moment.The central claim of the Response Target Hypothesis is that response particles, and the lin-guistic content that follows them in responses, participate in the management of common groundby targeting diஸferent types of propositions. The response can signal the acceptance (or rejection)of speaker beliefs (an idea which draws on Kri஺஽a (2015)), as well as the inclusion or exclusion ofthe at-issue content of a triggering utterance. The response particles can also target the QUDbased on the information already conஹ஭rmed in the common ground.13Rejecting a speaker’s belief is a logical posibility, but as a conversational move, it is all butimpossible to deny another person’s belief. In researching this dissertation, I did not come acrosssuch an example, in corpora or anywhere else. The closest I have observed are parents of youngchildren saying things like, ‘No, you don’t want a cookie.’ However, these crucially rely on follow-up content which makes explicit that the belief is being challenged. Notice, moreover, that the at-issue content of the child’s utterance (‘I want a cookie’) is also being challenged here. It is diஸஹ஭cultto imagine that that the response particle ‘no’ could signal rejection of the previous speaker’sbelief, without also signalling rejection of the at-issue content.The response particles ‘yeah’ and ‘no’ can target diஸferent types of propositions, includingat-issue content, beliefs and QUD, but there is no a priori assumption that ‘yeah’ always signalsacceptance of the at-issue content into the common ground and ‘no’ always signals rejection. Tobe clear, there is no claim that ‘yeah’ and ‘no’ are radically diஸferent from how they are currentlyunderstood; ‘yeah’ is still a positive response that generally signals agreement, and ‘no’ is still anegative response that generally signals disagreement. Rather this dissertation allows the possi-bility that ‘yeah’ may be included in a response which ultimately reject the at-issue content fromthe common ground, and ‘no’ may be present in a response which accepts the at-issue contentinto the common ground, on the basis of polarity misalignment (Examples of both are in Ch. 3).To see the Response Target Hypothesis applied to utterances, let us begin by looking at anadjacency pair structure. This template will serve as the basis for the data in later chapters.(14) Adjacency pair templateα:. Utterance contains a proposition consisting of at-issue content and representingα’s belief and discourse commitment, and responding to an understood QUDβ:. response particle ‘yeah’ or ‘no’, and followup content that agrees or disagreeswith the at-issue content contained in α’s utteranceThere are four logical combinations of ‘yeah’ and ‘no’ response particles and agreeing anddisagreeing followup content, and these combinations pattern with the ஹ஭rst four predictions ofthe hypothesis, given in Table 1.2. It is important to note that this table is not claiming that, forexample, ‘yeah’ plus disagreeing content will always and only be consistent with Prediction 2, ac-cepting belief while rejecting at-issue content. It also does not claim the opposite, that Prediction2 will always and only be triggered by ‘yeah’ plus disagreeing content. Rather the table representsthe four logical combinations of particles and followup content and how those combinations aremost likely to be interpreted.14Table 1.2: Predicted appropriate responses of The Response Target HypothesisOutcome ‘yeah’ +agree‘no’ + agree ‘yeah’ +disagree‘no’ +disagree1 Accept AIC 3 7 7 72 Reject AIC 7 7 7 33 Accept Bel, Reject AIC 7 7 3 74 Accept QUD 7 7 3 75 Reject QUD 7 3 7 7Table 1.3: Predictions of The Response Target HypothesisResponse Impact on Common Ground1. Accept AIC ‘yeah’ + agree at-issue content entered into thecommon ground2. Reject AIC ‘no’ + disagree common ground is not updated3. Accept Bel, RejectAIC‘yeah’ + disagree1 belief, not at-issue content, entered intocommon ground4. Accept QUD ‘yeah’ + disagree2 common ground not updated5. Reject QUD ‘no’ + agree at-issue content already in commonground, therefore common ground notupdated1 In order to accept belief and reject at-issue content, the disagreement must reject the at-issuecontent, for example with a response of ‘that’s not true’.2 In order to accept the QUD without accepting the at-issue content into the common ground,the disagreement must be compatible with the at-issue content while not signalling acceptance,for example, ‘that’s an interesting idea’. See Sec. 3.1.3 for a more detailed discussion.Table 1.2 maps the theoretical prediction to the discourse response. The checkmarks (3 ) in-dicate that a given response, such as ‘yeah’ + agree, is predicted to be appropriate because it signalsthe corresponding outcome; the ballot cross (7) indicate that those combinations of responsesand interpretations are not predicted.Table 1.3 shows how the responses in Table 1.2 are predicted to update the common ground.15In the Response Target Hypothesis, the common ground is not limited to including onlyat-issue content, which is Outcome 1, or restricting only at-issue content, Outcome 2. Beliefscan also be placed into the common ground, as in Outcome 3. In this case, the rules concerningmutual agreement still hold, in that while the at-issue content is not mutually held to be true andtherefore not in the common ground, α’s belief in the truth of the at-issue content is mutuallyaccepted by α and β, and α’s belief can therefore be placed in the common ground and be availablefor reference at a later point. Outcome 4 can update the common ground to include a QUD forwhich there is no currently available answer, and Outcome 5 can reject a QUD because there isalready an answer.Outcome 5 does not result in an update to the common ground, even though it signals agree-ment. This is because the response is targeting something that is neither the belief nor the at-issue content. Example (1) might be understood as an example of this outcome, wherein JM’sresponse of “no, you’re right!” signals such strong agreement with the at-issue content, namelythat “there’s two [idiots] here...”, that ‘no’ dismisses the question under discussion as irrelevant,likely because it has already been established in the common ground.The analysis focuses on what is syntactically and semantically present and only discusses per-sonal or non-linguistic motivations when they are clearly present, for example if a transcript noteslaughter. However, as a native North American English speaker with a similar cultural back-ground as the speakers and participants in this dissertation, I also use widely available culturalknowledge of the context of a discourse to support my analysis. This dissertation is not con-cerned with sarcasm, irony, humor, or any other usage that might be taken as insincere or notintended literally. Finally, while politeness is one reason why speakers respond in a certain wayin certain instances, this dissertation does not focus on politeness in analyzing responses.1.4 Evidence to test the hypothesisEvidence to support this hypothesis will come from two sources: natural data from corpora,media and real-life examples; and experimental results to test for common ground inclusion usingthe template described in (14).Corpora and “wild” sources provide ample evidence of the how response particles can be usedin relation to the common ground. The Corpus of Contemporary American English (COCA)and the Linguistic Data Consortium (LDC), particularly the Fisher (Cieri et al., 2004) and Switch-board (Graஸf et al., 2001) corpora. All three provide examples from spoken, unscripted English ofspeakers using response particles and followup content which impact the common ground. The16analysis focuses on examining the relationship between the response and the at-issue content,considering interlocutor beliefs and the question(s) under discussion.Experimental data shows some of the information that a corpus study cannot, namely wherea given combination of response particle and followup content are not appropriate to speakers.By demonstrating which responses are (in)appropriate under which conditions, the experimentalresults provides additional support for the Response Target Hypothesis that the at-issue content,beliefs and questions under discussion can be placed in the common ground.1.5 PreviewChapter 2 tracks how information moves through discourse, exploring all of the components thatare necessary for speakers to meaningfully exchange information. The chapter moves sequen-tially, beginning with the components necessary for information to be exchanged, such as pre-existing common ground and a speaker’s awareness of their audience and context of discourse.The next section looks at the exchange itself, beginning with the assertion and how it shapes theQUD, then continuing to the response, including the response particle(s) and followup contentand how these components interact with the at-issue content. The third section looks at the con-sequences of the exchange, particularly whether and how the common ground is updated. Thechapter concludes with a discussion of two theoretical models of this process.Chapter 3 looks at the data from corpora, and some natural examples, which demonstratehow responses are used in unscripted discourse. It begins with the non-paradoxical responseswhich are the ஹ஭rst and second predictions of Response Target Hypothesis presented in (13) andTable 1.2, in which ‘yeah’ plus agreeing followup content places the at-issue content in the com-mon ground and ‘no’ plus disagreeing followup content does not. The rest of the corpus chapterlooks at paradoxical responses, ‘yeah’ plus disagreeing followup content and ‘no’ plus agreeingfollowup content, to address the remaining predictions of the Response Target Hypothesis pre-sented in (13) and Table 1.2.Chapter 4 discusses the experiment and its results in detail. It describes the stimuli, the vari-ables which were manipulated, and the results of the experiment and their consequences for thehypothesis.The ஹ஭nal chapter brings the discussion together by drawing uniஹ஭ed conclusions from thecorpus and experimental chapters. It also discusses the consequences of this research as well asopportunities for further research into paradoxical responses.17Chapter 2Tracking information throughdiscourseDiscourse is a complex and dynamic process which relies on several factors for speakers to suc-cessfully exchange information. All discourse participants must have an idea of what the otherparticipants may or may not know about the discourse situation—who all of the participantsare in relation to each other, what they may know about the place and time of the discourse andtopics of discussion, and how they can make a meaningful contribution to the discourse. Par-ticipants must constantly reassess each of these variables as the discourse progresses, monitoringnew information and whether the participants agree on the truth or accuracy of this information,and whether there is conஹ஭rmed disagreement. And yet, people do this constantly as they speakto each other every day, unaware of the complexity of the task.This chapter will essentially tell the story of the discourse process, beginning with how speak-ers plan an utterance. It will then look at the discourse itself, separating the utterance and theresponse as two steps in the process. It will then look at the consequences of the discourse to ex-amine what information was exchanged as a result of the discourse. To help clarify the discussionof how information moves through discourse, I will use the sample discourse in (1), which is acomposite of parts of a real conversation.(1) Sample discourse for tracking information1. Z: I’m excited about changing schools from Handsworth to Argyle.2. E: Yeah, that’ll be a good change for you. And it’s so much closer.3. Z: No, it really is.184. E: But Southerland is a good school, too.5. Z: No, it’s not, it’s full of drug dealers.This discourse will serve as a kind of case study to track information through the discourse,afிer the theoretical background has been established. It is composed entirely of assertions, noquestions, and it contains three response particles with followup content. This sample discourseis rich enough to track information through a number of conditions, but it is straightforwardenough to allow for a clear discussion of the management of information.2.1 Before an utteranceSpeakers plan their utterances based on factors such as preexisting common ground and the otherdiscourse participant(s) (Horton and Keysar, 1996; Keysar et al., 2000; Horton, 2005; Horton andGerrig, 2005; Brown-Schmidt et al., 2008, a.o). Thus before any words are spoken, speakers haveput in the eஸfort to consider what might be an appropriate contribution to the discourse, and thissection will look at that planning process.2.1.1 Sources of Common GroundStalnaker (1973) and others had observed that mutual knowledge must have some standing indiscourse, because it is clear that speakers can and do rely on information which is not introducedin the previous utterance. It is equally clear, however, that true mutual knowledge, where twospeakers have the exact same knowledge, is impossible. Clark and Marshall (1981) were the ஹ஭rst topostulate an account for the “mutual knowledge paradox.”In setting up the problem, Clark and Marshall walk through a number of scenarios to identifythe conditions under which Ann could say to Bob,(2) Ann to Bob: “Have you seen the movie showing at the Roxy tonight?”They start by supposing that Ann read the movie listings in the morning newspaper. In thatsituation, the conditions which make (2) felicitous are those in (3), which indicate that the speakerand their addressee have mutual knowledge.(3) a. Ann knows that t (ஹ஭lm title) is g (referent, e.g.Monkey Business).b. Ann knows that Bob knows that t is g.But what if the situation is diஸferent? They set up the following scenario:19(4) On Wednesday morning Ann and Bob read an early edition of the newspaper, and theydiscuss the fact that it says thatADay at the Racॽ is showing that night at the Roxy. Whenthe late edition arrives, Bob reads the movie section, notes that the ஹ஭lm has been corrected toMonkey Business, and circles it with his red pen. Later, Ann picks up the late edition, notesthe correction, and rccognizes Bob’s circle around it. She also realizes that he has no way ofknowing that she has seen the late edition. Later that day Ann sees Bob and asks, ”Haveyou seen the movie showing at the Roxy tonight?” (Clark and Marshall, 1981, pp. 12-13)That scenario needs an additional condition, that of (5).(5) Bob knows that Ann knows that Bob knows that t is R.Clark and Marshall create additional scenarios which require additional knowledge states,until arriving at that in (6).(6) Wednesday morning Ann and Bob read the early edition of the newspaper and discuss thefact that it says thatADay at the Racॽ is playing that night at the Roxy. Later, Bob sees thelate edition and notices the correction of the movie to Monkey Business, and circles it withhis red pen. Later, Ann picks up the newspaper, sees the correction and Bob’s red pen mark.Bob happens to see her notice the correction and his red pen mark. In the mirror Ann seesBob watch all this, but realizes that Bob hasn’t seen that she has noticed him. Later thatday, Ann sees Bob and asks, ”Have yo11 ever seen the movie showing at the Roxy tonight?(Clark and Marshall, 1981, p. 14)This scenario, (6), requires the conditions in (7),(7) Ann knows that Bob knows that Ann knows that Bob knows that Ann knows t is R.which the authors explain:Putting herself in Bob’s shoes again, she should reason like this: “Ann knows thatthe movie is Monkey Business, and she knows that I [Bob] know that too. Yet shebelieves that I [Bob] think she thinks the movie is ADay at the Racॽ, and so by herreference, she should think I will decide she is referring to ADay at the Racॽ.” Butif her reference gets Bob to pick out ADay at the Racॽ, then it is infelicitous (Clarkand Marshall, 1981, p. 14)20These examples may be convoluted and unrealistic, but the problem that they are demon-strating is that properly assessing another person’s knowledge state in relation to one’s own knowl-edge state is a cumbersome, if not impossible, task. In order to felicitously make any sentence, aspeaker must be able to ensure that all of the participants can use the same terms to identify thesame referents, but there always exists the possibility of doubt. Demonstrating these diஸferentstates of knowledge, and the diஸஹ஭culty in parsing them, is (8), taken from the TV show Friends.1(8) Rachel: Ugh, I knew it! Oh I cannot believe those two!Phoebe: God, they thought they can mess with us! They’re trying to mess with us! Theydon’t know that we know they know we know! (Joey just shakes his head.) Joey,you can’t say anything!Joey: I couldn’t even if I wanted to.Phoebe and her friends rely on the information mismatch to “mess with” each other, butClark and Marshall make a more principled objection that relies on processing costs. They ob-serve that for Ann to successfully account for each new level of required knowledge, she wouldneed to be able to process an inஹ஭nite number of possibilities in a ஹ஭nite (and small—-ofிen a frac-tion of a second) amount of time, and this is demonstrably impossible. But equally demonstrableis the fact that people say things exactly like Ann’s question all the time. They rely on their ownknowledge and their assessment of their interlocutor’s knowledge, based on information whichmay have changed or may otherwise be misaligned between the speakers; essentially they expecttheir interlocutor to get their meaning despite any indication that that is a reasonable expectation.That means that an explanation for this paradox must be possible.Clark and Marshall observe that the analyses and terminology are essentially one sided, focus-ing on the speaker and their knowledge; such a focus is perhaps understandable, as the speakeris the source of an utterance, and speakers do not have access to everything that another personknows. To truly solve the paradox requires a reference to shared, or mutual knowledge, and Clarkand Marshall go on to identify three potential sources for this mutual knowledge: community,co-presence and discourse. Community is the source of shared experience or identity; examplesof community range from a married couple (a community of two) to all of humanity, and includemembers of a profession, citizens of a country, or residents of a neighborhood as intermediateexamples. Co-presence is derived from the speakers and other objects at the same place and time;this includes the physical environment and the moment in time where the discourse happens.1This exerpt comes from Season 5, Episode 17, ‘The one where everyone ஹ஭nds out.’21Discourse is the information added to the common ground as part of the conversation. Thesethree sources are now broadly accepted as sources for information in the common ground.The crucial insight of Clark and Marshall was that communication relies not on an inஹ஭niteset of speaker-oriented conditions, but on identiஹ஭able sources of mutual knowledge. This wassigniஹ஭cant, as it created the possibility of addressee-oriented speech acts in which the message wascrafிed with some awareness of the addressee’s knowledge. This insight has informed much of thesubsequent research on common ground and related theories. These identiஹ஭able sources of com-mon ground are important for this dissertation for a number of reasons. These discourse externalsources allow for realistic experimental stimuli which mimic something that participants mighthear in everyday situations, and for an interpretation of corpus examples that would otherwisebe impossible without conjecture and stipulation. The reliance on shared rather than exclusiveinformation not only solves the inஹ஭nite recursion problem, it also places the common groundsquarely at the center of discourse management.Building on Clark’s work, particularly Clark and Marshall (1981), Horton and Gerrig (2005)propose two slightly diஸferent labels for describing discourse: commonality assessment and mes-sage formation. In looking at simple exchanges between friends, they observed that informationexchanged relies on extensive shared information.(9) A: I got a letter from Tamar.B: Yes, I told her to write to you.Even these two lines are notable, they observe, because:simply having information in common may not be enough—on the surface it wouldseem that interlocutors must also believe that this information is mutually known.For example, Speakers A and B might both independently have knowledge of Tamar,but for Speaker A to felicitously refer to Tamar in conversation, she would also haveto believe that Speaker B knows Tamar as well. Horton and Gerrig (2005, p. 6)Horton and Gerrig invoke Clark and Marshall’s (1981) idea of co-presence, including withinthat description the physical, community,2 and linguistic sources of common ground, but theyexplain that it is not quite suஸஹ஭cient because interlocutors still need to think about what infor-mation is “co-present” between them, because it may not be immediately present. For instance,one speaker may observe other people present which the interlocutor may be unaware of; it is2Horton and Gerrig (2005) depart from Clark and Marshall (1981) by including community membership inco-presence, rather than using co-presence in a strictly spatio-temporal sense.22also common that one person does not know what another has in their pockets or bag, but thesethings are still co-present. The evidence for checking awareness comes from exchanges in whichspeakers express uncertainty about shared information. This suggests that physical co-presence isnot suஸஹ஭cient, that speakers must also activate, or recall, the information in the common ground,and interlocutors crafி their message with this process in mind. The crucial point is that, while itmay seem obvious that speakers operate with the knowledge of their common ground, it is not apriori true. Even if speakers believe that information should be in the common ground, they can-not automatically assume that it is, which is why they must attempt to validate that assumptionby checking the common ground.Clark and his many collaborators used data from natural conversations and corpora to under-stand the sources of common ground beyond what is established during discourse. Horton andGerrig build on this foundation to show that, even with information from these three sources, itstill is necessary for interlocutors to check the common ground and to verify that the informationis in fact shared.2.1.2 Context of discourseClark and Brennan (1991) raise the issue of the physical constraints on conversations, pointing outthat the medium and environment both in஺ாuence how responses are interpreted. They identifyseveral constraints which can in஺ாuence discourse, and Table 2.1 deஹ஭nes these constraints and listsexamples in which the given constraint plays a role and examples where it does not. The context ofa discourse impacts how speakers assess shared information and how they plan their contribution.Clark and Brennan go on to point out that each of these constraints has a potential cost toovercome. Audibility, to take the most relevant constraint for spoken discourse, has a low cost ina quiet oஸஹ஭ce with the door closed, for example, but it has a much higher cost in a crowded sportsstadium during a game. In other words, it is easy to carry on a conversation in one context andmuch harder in the other. The higher cost environment also increases the possibility of misun-derstandings and, by extension, the need for the speakers to signal mutual agreement suஸஹ஭cientto update the common ground. This matters for responses, because even if an interlocutor said‘yeah’ in response to an utterance, a speaker still needs to consider whether they can truly considerthe information to be in the common ground, given the context in which it was shared.The context of the discourses in Chapters 3 and 4 are conஹ஭ned to spoken contexts, and as aresult there is no Reviewability or Revisability. In some of the corpus data, such as multipersonbroadcast conversations, even Sequentiality may not be maintained, as speakers speak over eachother and respond to one another out of sequence. As two of the corpora are exclusively from23Table 2.1: Constraints on discourse contextsConstraint Definition Present in Absent inCopresence A and B share a physicalenvironmentface to face social mediadirect messagesVisibility A and B can see each other video chat phone callsAudibility A and B can hear each other phone calls emailCotemporality B receives the message as soon as Aproduces itface to face, textmessagesemail,voicemailSimultinaeity A and B can send and receivemessages simultaneouslytext messages lettersSequentiality A and B’s turns cannot get out ofsequenceconversation* text messages*Reviewability B can reread or replay A’s message voicemail,emailface to face,video chatRevisability A can revise the contributionbefore B receives itemail face to faceTable adapted from Clark and Brennan (1991, p. 229-230) to include modern forms of communication.*Conversations may have overlap and other interruptions, but these are usually repaired so that speakers arenot “talking over” each other (Sacks et al., 1974). In contrast, text messages can become out of sequence whenA and B both introduce, and then respond to, diஸferent topics of discussion.telephone calls, these conversations did not have Copresence or Visibility. They may have alsohad signal disruptions that may have required more eஸfort on the part of both speakers to acceptinformation into the common ground.Register and genre are also part of the context of a conversation, as they in஺ாuence how speak-ers shape their message based on audience and purpose (Yule, 2017). Although there is consider-able disagreement about the divisions between registers,3 Joos’s 1961 “ஹ஭ve clocks” is still regardedas a baseline division of registers: intimate (inside jokes, declarations of love), casual (conversa-tions between friends), consultative (interviews, teacher/student discussions), formal (lectures,sermons) and frozen (biblical quotes, national constitutions). The ஹ஭rst two registers, intimate3The most recent register categorization scheme is that of the International Standardization Organization (ISO,2018), which lists, by my count, 18 registers, including baby talk, vulgar register, bench register, royal register, andothers.24and casual, assume a large common ground between the interlocutors, while the next two, con-sultative and formal, rely essentially on a common ground based on a shared community based ona subject or topic, although they do not rule out co-presence. The frozen register is for texts andutterances that never vary. The data in the remaining chapters is overwhelmingly of the casualand consultative registers, which shapes the context in which a discourse is happening2.1.3 Audience design and accomodationExperimental research into audience design4 shows that speakers mentally “check” that certaininformation is shared (Galati and Brennan, 2010; Keysar et al., 1998; Pickering and Garrod, 2004,a.o.).In adapting a communicative task to a speciஹ஭c audience, speakers are necessarily drawing onthe common ground that exists between them and their audience. Galati and Brennan (2010)demonstrated that speakers repeating the same narrative will simplify that narrative when theyare repeating it for the second time to the same audience. This simpliஹ஭cation was in evidenceat all communicative levels: the number of words used, the level of detail, even the clarity ofpronunciation. Speakers know that the audience has already heard the story, which allows themto attenuate the retelling; in other words, they know that the story is in the common ground.There is experimental evidence that speakers resort to “checking” the common ground duringdiscourse, or verifying information contained in the common ground, for example an identity.Keysar et al. (1998) demonstrate that addressees resort to the common ground to verify the iden-tity of potential referents in discourse. Brown-Schmidt et al. (2008) demonstrated that both par-ticipants (their experiments used two speakers) in unscripted discourse use the common groundto crafி their message. Speakers will direct questions to a person that they know to have the an-swer, and addressees, i.e. speakers who answer said questions, will consider the available commonground in indicating the correct answer to the question, for example by using a name from thecommon ground to refer to an individual. Hanna et al. (2003) used eye tracking to determinethe extent to which privileged ground, that is information known only to one speaker, interef-ered with common ground interpretation of named objects, and they found that while there islimited interference, when speakers had several potential physical referents available, they almostalways looked at the object that was in common, rather than priveleged, ground. This indicatesthat speakers attend to the common ground in discourse, relying on the information that theyknow to be shared between both interlocutors.4I am using “audience design” here as an envelope term to capture the many ways in which interlocutors adjusttheir language usage and understanding around those to whom they are speaking.25Pickering and Garrod’s (2004) work on backchanneling also demonstrates the reliance oncommon ground, in that the signals that a speaker of a monologue receives from their interlocu-tor can help them to direct attention to previous information or to future utterances; in essencespeakers are constantly adjusting their message based on (ofிen non-verbal) signals of their in-terlocutors, such as nods or even simply continued attention. Pickering and Garrod term thisprocess alignment, in that the interlocutors are aligning the information that is shared betweenthem, checking that previous information is in fact established as shared—in other words, thatit is in the common ground. The mechanism of how this works will be explored more fully inthe following section, but the use of alignment checks that previously mentioned information isindeed established in the common ground through the use of backchanneling and other signs ofacceptance.These studies, and others like them, provide evidence that speakers are aware of shared infor-mation as they construct their utterances. They also demonstrate the extent to which this sharedinformation—the common ground—is used to communicate with those with whom this in-formation is shared. This research demonstrates, through the use of methodologies such as eyetracking, that speakers can and do use cues beyond propositions, including previous shared ex-perience and continued attention, to shape how they speak to others. While the data in Chapters3 and 4 will not allow for these cues to be used in my analysis, the research into audience designsuggests that considering information beyond the utterance, perhaps evidence of the emotionalstate or the dispositions of the speaker(s), may allow for a richer understanding of how responseparticles are involved in managing the common ground.2.1.4 Modeling the state of information before the utteranceRecalling the sample conversation in (1), the state of the discourse before anything is said is asindicated in (10) line 0; no one has spoken. This is the planning stage, in which the ஹ஭rst speaker isassessing the common ground, time and place, and their interlocutor in order to plan an appro-priate contribution.(10) Sample discourse for tracking information—Before the utterance0. No speaker; Z is planning her contribution to the discourse1. Z: I’m excited about changing schools from Handsworth to Argyle.2. E: Yeah, that’ll be a good change for you. And it’s so much closer.3. Z: No, it really is.264. E: But Southerland is a good school, too.5. Z: No, it’s not, it’s full of drug dealers.In order for Z to plan a successful utterance, she must have some expectation, and a basis forthat expectation, about what E knows. This is the pre-existing common ground, and since thediscourse is about schools in a given community, then the source for this pre-existing commonground is shared community. The setting of the discourse also shapes how Z will prepare herutterance; Z may hesitate to make these statements at Handsworth or Southerland, where some-one overhearing the conversation would likely be oஸfended. The register is also fairly informal,as if Z and E are friends, or at least friendly acquaintances. Z also considers her larger audience,not only E but anyone else who may reasonably be considered as part of this conversation (therewas a third participant in the conversation from which this is extracted, namely N.), and Z mustalso consider these other discourse participants’ available information.In order to ensure that her utterance is felicitous, Z must consider all of these factors. Shecannot felicitously make the same utterance to people who do not share community membership,for example. This utterance would also be infelicitous in another context, for example if Z werea customer in a restaurant and E were her server; even shared community membership and afriendly relationship between the speakers would not make that utterance appropriate in thatsituation.2.2 The exchange, a two-step processConversation is necessarily cooperative, in that the expansion of the common ground is the resultof speakers taking turns to make contributions, accept or reject new information and build onthe information previously established in the common ground; crucially, this process requires atleast two speakers. The evidence of cooperation appears throughout the discourse. Clark andWilkes-Gibbs (1986) look more speciஹ஭cally at how discourse participants arrive at a mutuallyshared interpretation of nominal referents, but they draw on the work of conversation analysts(Schegloஸf, 1982; Sachs, 1967; Sacks and Schegloஸf, 1973; Sacks et al., 1974; Gazdar, 1979; Kamp,1981, a.o.) that shows how conversation is constructed. If, for example, two speakers are talkingin a loud environment, and the listener does not hear the information that established a discoursereferent, the listener can stop the conversation and conஹ஭rm the identity, or they can wait untilthe speaker’s turn is ஹ஭nished. Alternatively, they can infer the identity of the referent and sig-nal their understanding through back-channeling, explicit repetition, or other means. Crucially,Clark and Wilkes-Gibbs observe, the process is collaborative. They continue:27To some it may appear self-evident that the process is collaborative, but it is onething to assume it is and quite another to understand why it is and how it works.The goal here is important, since, if conversation is fundamental, its processes arelikely to underlie or shape those in other uses of language as well.Clark and Wilkes-Gibbs (1986, p. 3)Clark and Wilkes-Gibbs also observe a bit of a paradox, in that speakers use the least amountof eஸfort to achieve their communicative goals. So how do they manage collaboration when bothare conserving their eஸforts?Clark and Wilkes-Gibbs propose that the collaboration happens in a two phase process: pre-sentation and acceptance. One speaker must present a referent, and the other speaker must acceptit in such a way that it is clear to both that the referent is mutually accepted. This may be donepassively, by allowing the conversation to continue with the referent unchallenged, or it can bedone more actively, with a signal such as a response particle. Both represent collaboration strate-gies on the part of the interlocutors.Clark and Wilkes-Gibbs also demonstrated this mutual establishment of referents experi-mentally by having pairs of speakers sit on opposite sides of a partition, each with a set of tangramsthat they would then direct each other in arranging so that the two sets matched, according toa set of provided images. The speakers could not see their partner’s set of tangrams, but theywere able to speak back and forth across the screen wtih no diஸஹ஭culty. When the director (thespeaker instructing the other speaker) ஹ஭rst described a ஹ஭gure, they used an average of over 40words per image (the referent). During the second description, they used half as many words,and by the sixth description they used an average of less than 10 words per image. While Clarkand Wilkes-Gibbs do not provide transcripts of their data, the speakers might use descriptionssimilar to those in (11).(11) 1. the one that’s kind of a blue color, kind of medium size, with a big slope on the sidesso that if it were sitting on the table upright it would lean, but there’s a big slope anda little slope (41 words)2. the blue kind of medium size one with the diஸferent size sloping sides, the one thatwould lean if it stood up (22 words)3. the medium size blue one with the sloping sides (9 words)The researchers’ conclusion was that such a reduction in eஸfort was possible because the speak-ers knew the referent to be in the common ground by virtue of having mutually agreed to a map-28ping between a discourse referent and the object it refers to over the course of the conversation(Wilkes-Gibbs and Clark, 1992, p. 13). Crucially, the experiment also demonstrated that the in-formation contained in the common ground may be utilized at a later part of the discourse. Inlater chapters of this dissertation I will rely on the fact that speakers take the common groundinto account when formulating their utterances and responses, when I investigate the use of re-sponse particles in discourse. We will see that, by taking the common ground into consideration,speakers are able to respond to targets other than the at-issue content; for example, speakers mayaccept or reject a question under discussion based on whether an answer is already available inthe common ground.That discourse is collaborative is crucial to many of the models that follow (see in particularFarkas and Bruce (2010); Malamud and Stephenson (2014)), and to the claims in this disserta-tion. The responses that may impact the common ground are all part of the acceptance phase ofthe discourse; without some signal of information being accepted into the common ground, itcannot be concluded that the common ground has been expanded.2.2.1 The assertionThe contribution that a speaker prepares can take the form of a question, exclamation or asser-tion, and it may represent an illocutionary act (for example, intended to inform or persuade) ora perlocutionary act (intended to indirectly invoke an action on the part of the listener). Thecurrent inquiry will conஹ஭ne itself to illocutionary assertions, that is statements (not questions)that are intended to share information and not suggest action.The speciஹ஭c assertive statements that a speaker oஸfers constrains the course of the subsequentdiscourse by contributing diஸferent kinds of information, such as presuppositions, at-issue con-tent, and question(s) under discussion. The information in the assertion is the result of the plan-ning phase which considers the pre-existing common ground and the context of the discussion,and it limits how the interlocutor can respond while honoring the maxim of relevance. This sec-tion will consider how speakers use these types of information to re஺ாect and shape the commonground.2.2.1.1 The at-issue contentA declarative utterance may introduce at least two types of propositional material, presupposi-tions and at-issue content. Presuppositions are the information which is assumed to be true inorder to evaluate the truth conditions of the proposition, while the at-issue content is considered29the “main point of the utterance” (Abbott, 2000). One of the most signiஹ஭cant diஸferences is howpresuppositions and at-issue content interact with the common ground.Two of the key diagnostics to assess at-issueness are the ability to respond directly to the at-issue content and the ability to directly challenge the at-issue content, properties not shared bypresuppositions (Tonhauser, 2012).The example in (12) demonstrates that a direct response willtarget the at-issue content.(12) A: Juan lives in Maria’s house.B: Yeah.Interpretations: 3 Yeah (it’s true that Juan lives in a house owned by Maria)7 Yeah (it’s true that Maria owns a house)adapted from Tonhauser (2012)The at-issue content in A’s utterance is that Juan lives in a speciஹ஭c house, the preusppositionis that the house is owned by Maria. If an interlocutor simply responds with ‘yeah’ or ‘yeah,it’s true,’ that response will be interpreted as accepting the at-issue content concerning Juan’sresidence. This holds true with ‘no’ responses as well.(13) A: Juan lives in Maria’s house.B: No.Interpretations: 3No (it’s not true that Juan lives in a house owned by Maria)7No (it’s not true that Maria owns a house)adapted from Tonhauser (2012)Rejection in response to the assertion will again target the information concerning Jaun’s resi-dence, not Maria’s ownership of a house. In fact it may be well established in the common groundbetween A and B that Maria does indeed own the house in question. The at-issue content, themain point of Speaker A’s utterance, is whether Juan lives in the house in question, and bothpositive and negative responses target this information.Negative responses represent a challenge to the truth of the at-issue content, and they can befollowed by contrary claims, as (14) demonstrates.(14) A: Juan lives in Maria’s house.B: No, he lives in his father’s house.30This is not to say that a presupposition cannot be challenged, but doing so usually requiressomething beyond direct agreement or denial, for example a “wait a minute!” response (vonFintel, 1994; Tonhauser, 2012, a.o.). In order to challenge a presupposition, a speaker needs tosignal a shifி away from the at-issue content, as in (15).(15) A: Juan lives in Maria’s house.B: Wait a minute! Maria doesn’t own a house, she sold it last year.This dissertation is agnostic on whether all presuppositions are necessarily in the commonground, but it treats presuppositions as shared information unless they are explicitly challenged.For example, if a man and a woman are guests in a hotel and the desk clerk says to the woman, “Apackage came for you; I gave it to your husband.” the clerk is presupposing that the man is thewoman’s husband. However, even if the man is not the woman’s husband, the at-issue content isstill clear, and the referent of “your husband” is clearly the man traveling with the woman, evenif that label is not applicable to him. Whether the false presupposition is challenged or not isup to the woman, but it does not impact the at-issue content concerning the package. Unlesschallenged directly, presuppositions similar to this one can at least be considered as part of theshared information for the immediate discourse, even if they are not mutually agreed to as true.In other instances, presuppositions are based on information already in the common ground,ofிen as a result of shared community membership. As an example, if a person says to their co-worker, “The boss will be late today, she totaled her pick-up.” the presuppositions concerning theboss’s gender and ownership of a pick-up truck are based on their shared community membershipas employees of the same organization. These presuppositions still cannot be directly respondedto or challenged.2.2.1.2 The question under discussion (QUD)The question under discussion (QUD) results from the work of Roberts (1996, 2011) to recon-cile several previous ideas in the literature, chie஺ாy that of relevance from Grice (1975), Ginzburg’s(1996) notion of QUD as a partially ordered set, and Stalnaker’s (1978) idea that the goal of conver-sation is to exchange information about the world, i.e. to discover “the way things are” (Roberts,2011, p. 64). The claim is that discourse intended to exchange information does so in answer to anunspoken question, the QUD, and this question constrains the discourse by requiring relevantcontributions in response to said question. Roberts recognizes that within the big question goalare smaller, more immediate goals, which she terms domain goals, that constrain the questionunder discussion to be something more immediately relevant to the agenda of the conversation31at hand. She goes on to develop the QUD as an important tool in understanding informationstructure at the semantic and pragmatic level.To clarify the QUD, let us consider an example, (18), in which the utterance in line 1 estab-lishes the Domain Goal QUD in line 2. Under Roberts’ theory, the Doman Goal QUD is themost immediate QUD which stems from an uttterance; it is the QUD to which the speakers havecommitted to ஹ஭nding an answer, as it is a mutually agreed to QUD.(16) An illustration of QUDs in relation to utterances and responses1. Utterance: Carole was invited to the party.2. QUDDG: Was Carole invited to the party? Domain GoalBecause the QUD is actually a partially ordered set (Ginzburg, 1996), it becomes necessaryto discuss the questions in that set separate from one another. To this end, Roberts and hercollaborators use the term Current Question (Simons et al., 2016; Beaver et al., 2017), which theydeஹ஭ne as:(17) Current Question (CQ) for an utterance: The CQ for an utterance is a privileged subsetof the focal alternative set of the uttered sentence which meets the following conditions:1. The proposition expressed is a member of the CQ and2. The CQ has at least one additional member (Simons et al., 2016, p. 8)In answering the Domain Goal QUD, the utterance in line 1 also provides partial answers tothe higher level goals in lines 3 and 4. The potential responses in lines 5-7 are felicitous becausethey respond to the higher, or Current, QUD, whereas the answers in lines 8 and 9 do not respondto the QUD and therefore violate the maxim of Relevance.32(18) An illustration of QUDs in relation to utterances and responses1. Utterance: Carole was invited to the party.2. QUDDG: Was Carole invited to the party? Domain Goal3. QUDCQ Who was invited to the party? Higher (Current) Level4. QUDSoW What is the state of the world? State of the World5. Response: 3 But Linda wasn’t.6. 3 Sharon was too, but she didn’t come.7. 3That’s surprising that Carolewas invited instead of Jen.8. 7The champagne was excellent.9. 7 I hate parties dance music.Answer QUDCQDon’t answer QUDCQSimons et al. (2016) also point out that discourse is, by its nature, restricted contextually,pointing out that if Mark’s daughter went on a bird watching trip during the day, and then heasked her, “What did you see?” he is asking about the birds that she saw that day, not the otherrandom objects that she likely sees every day. With this analysis in mind, it becomes apparent howthe question expressed in (18) line 3 can be classiஹ஭ed as a Current Question. This set is representedin (19)(19) CQx = {p1, p2, p3, p4, …}, wherex = “Carole was invited to the party.” andp1 = “Sharon was invited to the party.” andp2 = “Diego was invited to the party.” andp3 = “Stevie was invited to the party.”and other potential answers.One challenge for using QUD in analysis is that there can be more than one QUD that satis-ஹ஭es the criteria of a Current Question; “Carole was invited to the party” also provides an answerto the CQ “What has Carole been invited to?” Roberts (2011) provides an example from a pos-sible world which contains only two people, Robin and Hillary, and only two foods, bagels and33tofu. She illustrates the possible QUD Stack, that is the ordered set of potentially answerableQuestions Under Discussion. In the tightly constrained world of this example, the number ofquestions is necessarily constrained, the maximal being “Who ate what?” and the minimal beingalong the lines of “Did Hillary eat tofu?”Roberts (2011) demonstrates that the QUD must be accepted by both interlocutors, and thisopens up the possibility of targeting the QUD without answering it. One of my core proposalsin this dissertation builds on this idea of accepting a QUD and takes it further to become a hy-pothesis about the role of RPs. My proposal is that RPs can target the QUD, in the sense thatthey can not only signal an answer to the QUD (agreement/disagreement with the at-issue con-tent of the previous utterance), but they can also directly target the legitimacy of the QUD itself.They can either accept it as a good QUD to which an answer is not available (yeah), or they canreject it as a QUD because it is either not relevant or has already been answered (no).2.2.1.3 Statements of beliefAn important question for this dissertation is whether RPs can respond to an opinion as wellas a fact. Convertino et al. (2008) calculated that, out of 13 potential dialog acts, the three mostcommon in their data were signalling a speaker’s judgement, a speaker’s agreement with a priorjudgement, or were acknowledging receipt of information; these were signiஹ஭cantly more fre-quent than conversational moves which may be regarded as typical, such as introducing newinformation, querying another speaker or replying to a query. Speakers can felicitously disagreewith statements of opinion (Umbach, 2014), signalling that they hold a diஸferent opinion, notthat another’s opinion is wrong. Responses can resolve statements of fact (Ginzburg, 1995a,b)for inclusion into the common ground, and the question here is whether and how response cantarget statements of belief for inclusion into (or exclusion from) the common ground.An answer to this question requires in inquiry into the nature of beliefs in language. Laser-sohn (2005) demonstrates that beliefs need to be indexed to an individual. Lasersohn describeshow the truth of an utterance such as “The chili is tasty.” necessarily relies on whether or not thespeaker does in fact ஹ஭nd the chili tasty; this proposition may be true for John but not for Mary(Lasersohn, 2005, p. 649). Crucially, John’s utterance of “The chili is tasty.” and Mary’s utteranceof “The chili is not tasty.” can both be true, because the utterances index to diஸferent individualswho may evaluate the chili diஸferently, resulting in faultless disagreement (Umbach, 2014).The importance of this insight for the Response Target Hypothesis is that it provides a the-oretical basis for positing beliefs for inclusion into the common ground. If John claims that thechili is tasty and Mary disagrees, it is intuitively correct that both beliefs should enter into the34common ground. This becomes apparent when one of the speakers accesses the common groundconcerning the chili at a later point in the discourse, as in the hypothetical conversation in (20).(20) John: The chili is tasty.Mary: No, the chili is not tasty!John and Mary have discussed the chili, and then their friend Peter arrivॽ and asks themabout the chili.Peter: What do you guys think of the chili?John: It’s tasty, although Mary doesn’t think so.If we applied a conventional model of common ground update, and did not adopt a Lasersohn-style approach in which taste predicates are relativized to the beliefs of individuals, John’s responseto Peter should be impossible. Mary disagrees with John, and this should result in a crisis andleave the common ground un-updated. John’s response is felicitous, however.5 Contrast thiswith the response in (21), which would re஺ாect an un-updated common ground, i.e. in whichJohn’s and Mary’s individual beliefs about the tastieness of the chili were not entered into thecommon ground. The example includes two potential responses that John could give to Peter.Although Mary has indicated that she does not ஹ஭nd the chili to be tasty, John has indicated thathe does, and therefore it would be awkward for him to answer that he does not know what hethinks of the chili. It still might be awkward for him to respond that the chili is tasty when heknows that this is not a universally held view, but it does at least re஺ாect what he thinks of the chili.Peter’s question in (21) concerns the opinion(s) of the group, and we can understand that there isno single opinion because we know that John and Mary do not agree. So niether of the responsesis entirely felicitous.(21) John: The chili is tasty.Mary: No, he chilly is not tasty!John and Mary have discussed the chili, and then their friend Peter arrivॽ and asks themabout the chili.Peter: What do you guys think of the chili?John: ??I don’t know. / ?It’s tasty.But let us consider the predictions of a theory that did not allow information about individualbeliefs to be entered into the common ground. The disagreement would mean that the common5The experimental stimuli in 4 are similar to (20), and the data show that other speakers also ஹ஭nd such an ex-change felicitous.35ground would not be updated with any information about the chili’s tastiness according to eitherJohn or Mary. Therefore if Peter asks a question that requires information from the commonground to answer, then an answer of “I don’t know” should be appropriate. This will be trueof any question that requires information from the common ground. The obvious problem isthat English speakers will expect that John can answer Peter’s question with something other than“I don’t know.” This suggests that, not only is the common ground updated during John andMary’s exchange, it is updated to include both of their evaluations of the chili. That would meanthat the common ground is updated to include two beliefs, both indexed to an individual speakerand the time of utterance.If an utterance including a taste predicate is indexed to a group, then it should be true of allof the members of a group. Therefore, if John and Mary and others are on a roller coaster, andJohn says, “This is fun!”, that cannot apply to the group if Mary then says, “This is not fun!” Itis for this same reason that John cannot respond as in (22).(22) John: The chili is tasty.Mary: No, the chili is not tasty!John and Mary have discussed the chili, and then their friend Peter arrivॽ and asks themabout the chili.Peter: What do you guys think of the chili?John: (?)We think it’s tasty. / (?)We think it’s not tasty.Both of John’s potential responses are infelicitous here, because he knows that the group iden-tiஹ஭ed by “we,” namely Mary and himself, do not collectively ஹ஭nd the chili to be tasty (or not tasty).John can felicitously respond to Peter’s question in one of three ways, either by reporting his ownevaluation of the chili, reporting Mary’s evaluation, or reporting both of their evaluations.Lasersohn (2005) proposes a detailed analysis of the semantics of belief, in which expressionswhich encode belief, such as scalar predicates, are indexed to a person, usually the speaker. TheResponse Target Hypothesis proposes a more generalized version, that in (23), whereby not justscalar predicates, but any assertion at all, places information about the speakers’ beliefs into thecommon ground.(23) Belief{speaker, time}So just as when John says ‘the chili is tasty’, the common ground gets updated with ‘Johnthinks the chili is tasty to him,’ similarly when John says ‘it’s raining,’ the CG gets updated with36‘John thinks it’s raining’. Belief can be placed in the common ground, including through theuse of response particles, as in the exchange in (24), a real exchange between two anonymousmembers of a popular online forum about cars.(24) Context: Two individuals are discussing a news story in which a stunt motorcyclist namedKats wॼ injured while attempting to jump hॾ motorcycle between two buildings while amoving train occupied the gap between the buildings.α: Truth is, the only person who’s [sic] life is at risk [with the stunt] is Kats himself .β: Yeah, no. This shit is obviously potentially dangerous to others. Want to do insanejumps that’s ஹ஭ne, but do it in a location where there aren’t other people around.β’s response of ‘yeah’ seems to be targeting α’s belief that no other people are at risk fromKats’s stunt, because β then says ‘no’ and follows up with content that unabiguously disagreeswith α’s assertion. This example is also illustrative in that it does not include a taste predicate, butit still shows that a speaker (in this case, α) may hold a belief that others may identify as objectivelywrong while still accepting α’s belief.Lasersohn (2005) also discusses situations in which the truth is externally veriஹ஭able and re-quires no indexing to an individual or group.For example, if I taste the chili, I might conclude from the ஺ாavor that it containspork, and utter (25):(25) The chili contains pork.In saying this, I am in some sense expressing my personal opinion; but it is a verydiஸferent case from [previous] examples…, because there is a fact of the matter as towhether the chili contains pork. Lasersohn (2005, p. 644)Regardless of whether the chili contains pork or not, the speaker of (25) may believe, againstany evidence, that it does contain pork. Under my proposal, this belief, if uttered in discourse,may become part of the common ground, and the data in Chapters 3 and 4 demonstrate howresponse particles help to achieve this.That speaker beliefs are entered into the common ground as shared information ஹ஭nds sup-port in Kri஺஽a’s (2015) concept of commitment space. Even if the at-issue content of a given ut-terance is not entered into the common ground, the speaker’s discourse commitment is.372.2.1.4 Modelling the utteranceTo revisit the sample discourse (1), the state of the discourse has moved from planning to speaking;the utterance in line 1 has been uttered.(26) Sample discourse for tracking information—Afிer the utterance0. No speaker; Z is planning her contribution to the discourse1. Z: I’m excited about changing schools from Handsworth to Argyle.2. E: Yeah, that’ll be a good change for you. And it’s so much closer.3. Z: No, it really is.4. E: But Southerland is a good school, too.5. Z: No, it’s not, it’s full of drug dealers.The assertion in line 1 contains several components, summarized in (26’).(26’) The components of (26) line 1Utterance: Z: I’m excited about changing schools from Handsworth to Argyle.Presuppositions: 1. There are two schools, Handsworth and Argyle.2. Z currently attends Handsworth.3. Z will attend Argyle.at-issue content Z is excited about changing schools from Handsworth to Argyle.QUDDG Is Z excited about changing schools from Handsworth to Argyle?QUDCQ1 What is Z’s attitude about changing her schools?QUDCQ2 What is the attitude of students when they change their school?Z’s belief Z believes that changing schools from Handsworth to Argyle is ex-citing.The Domain Goal QUD is the most immediate QUD to which the at-issue content providesan answer. However, this does not mean that the at-issue content can only answer the DomainGoal QUD; it can answer the slightly broader QUDCQ1, but so can other assertions. Answersto QUDCQ1 are limited to assertions which re஺ாect Z’s attitude to changing schools and which donot contradict the answer to the Domain Goal QUD, such as those in (27).38(27) Potential utterances which answer QUDCQ11. Z: But I’m a little nervous because it’s a much harder school.2. Z: I am dreading catching the bus at 6:15 though.3. Z: Finally going to the same school as my boyfriend will be great.4. and other possible utterancesExtending the QUD to QUDCQ2, the potential assertions which answer this question mustre஺ாect the attitude of students who may or may not be Z towards changing their schools, such thatthey do not contradict the answers of QUDCQ1; this is part of the denotation of the question.This does not mean that no other student can express apprehension or fear or something elseother than excitement; it means that, within this conversation, an answer to QUDCQ2 cannotcontradict the at-issue content that Z is excited.(28) Potential utterances which answer QUDCQ21. Z: I’m really excited.2. M: I’m exhausted with changing schools so ofிen.3. N: Changing schools is exhausting but also kinda fun. You get to meet new people,it’s good.4. O: I don’t want to change schools, I love my school!5. P: I’m really happy to get to go to a school that focuses on the arts.6. and other potential utterancesAs the QUD becomes broader, the set of utterances which can provide an answer to theQUD becomes larger. The broadest or highest level QUD is “What is the state of the world?”,to which the answers are inஹ஭nite.What this all demonstrates is that even a simple utterance introduces several components thatanother speaker can respond to. Z introduces several propositions, including at-issue content,presuppositions, her belief, and several QUDs, all of which are available for an interlocutor torespond to. The next section will focus on how interlocutors assess the various propositions andrespond to one or more p with the use of response particles.392.2.2 The responseClark and Schaefer’s (1989) work on common ground has in஺ாuenced all subsequent work on thetopic, mine included. Their seminal article on the development of common ground was the ஹ஭rstto describe the grounding criterion: “The contributor and the partners mutually believe thatthe partners have understood what the contributor meant to a criterion suஸஹ஭cient for currentpurposes.” (Clark and Schaefer, 1989, p 262). This means that, in order for the informationto be considered as in the common ground, it is necessary for all of the conversational partici-pants to believe that they all share at least some level of shared understanding. In addition to thenon-linguistic information in the common ground developed by Clark and Marshall (1982), thisdeஹ஭nition stipulates that the common ground includes the linguistically negotiated informationthat has met the grounding criterion. The criterion is intentionally lefி fairly malleable so thatit may be adaptable to a wide range of discourse contexts, but crucially it relies on some kind ofevidence of suஸஹ஭cient understanding, each dependent on how that understanding is signalled. Tothat end, Clark and Schaefer propose ஹ஭ve levels of evidence:1. Continued attention. B shows he is continuing to attend and therefore remains satisஹ஭edwith A’s presentation.2. Initiation of the relevant next contribution. B starts in on the next contributionthat would be relevant at a level as high as the current one.3. Acknowledgement. B nods or says “uh huh,” “yeah,” or the like.4. Demonstration. B demonstrates all or part of what he understood A to mean.5. Display. B displays verbatim all or part of A’s presentation.(Clark and Schaefer 1989, p 268)These ஹ஭ve types of evidence can be captured in one simple generalization, that expantion ofthe common ground is a two phase process (Clark and Brennan, 1991):(29) a. Presentation phase: A presents utterance u for B to consider. He does so on the as-sumption that, if B gives evidence of e or stronger, he can believe that she understandswhat he means by u.b. Acceptance phase: B accepts utterance u by giving evidence e that she believes sheunderstands what A means byu. She does so on the assumption that, once A registersthat evidence, he will also believe that she understands.Following on the work of Clark and his collaborators, it is not suஸஹ஭cient to view the commonground as a monotonic data set in which each element is included as the result of x or x + y,40where x is an utterance and y is a response. Rather its construction relies on the evidence that thediscourse participants provide that the information is mutually shared. Moreover, the strengthof evidence has consequences for the extent to which a speaker may conclude that information isin the common ground. If my interlocutor repeats what I say verbatim, I can have a high degreeof certainty that the common ground has indeed been updated, but if my interlocutor simplysits quietly and continues to listen, I may expect that the common ground has been updatedbut cannot rule out the possibility that their mind was wandering and they missed what I said.Therefore, while I may assume that the common ground has been updated, and proceed basedon that assumption, conversations such as that in (30),6 in which Emma is “continuing to attend”to the speaker’s monolog but clearly misses parts of it, cannot be ruled out.(30) Context: Holden ॾ talking about hॾ personal background with Emma, who ॾ listeningquietly and appearing attentive by looking at Holden while he speaks.Holden: […]I’ll just tell you about this madman stuஸf that happened to me around lastChristmas just before I got pretty run-down and had to come out here and takeit easy. I mean that’s all I told D.B. about, and he’s my brother and all.He’s in Hollywood. That isn’t too far from this crumby place, and he comes overand visits me practically every week end. He’s going to drive me home when Igo home next month maybe. He just got a Jaguar. One of those little Englishjobs that can do around two hundred miles an hour. It cost him damn near fourthousand bucks. He’s got a lot of dough, now. He didn’t use to. He used tobe just a regular writer, when he was home. He wrote this terriஹ஭c book of shortstories, The Secret Goldஹ஭sh, in case you never heard of him. The best one in itwas “The Secret Goldஹ஭sh.” It was about this little kid that wouldn’t let anybodylook at his goldஹ஭sh because he’d bought it with his own money. It killed me.Now he’s out in Hollywood, D.B., being a prostitute. If there’s one thing I hate,it’s the movies. Don’t even mention them to me.Emma: Wait, who’s D.B.? Is D.B. why you hate the movies?To visualize the diஸference between a common ground based on levels of evidence versus onethat is not, consider Figs. 2.1 and 2.2, in both of which xT represents information, green is thecommon ground, and pink is the priviledged ground of Speakers A and B. In both ஹ஭gures, bothA and B can safely regard x4 as being in the common ground. In the gradient common ground,6The narrative text is the second half of the opening paragraph of J.D. Salinger’s The Catcher in the Rye, origi-nally published in 1951.41A x1 x2 x3 x4 x5 x6 x7 BFigure 2.1: Gradient conception of common groundA x1 x2 x3 x4 x5 x6 x7 BFigure 2.2: Non-gradient conception of common groundFig. 2.1, it is likely x3 and x5 are in the common ground as well, but x2 and x6 may not be, andx1 and x7 are almost certainly not in the common ground. This contrasts with the conceptionof the common ground depicted in Fig. 2.2, in which x2 and x6 are deஹ஭nitely excluded from thecommon ground and x3 and x5 are deஹ஭nitely included.For information where there is some degree of doubt about its inclusion in the commonground, speakers can then check whether xT is in the common ground or not; one strategy is tosimply ask, “We agreed about xT, right?” This checking function also conditions responses, asSpeaker A may believe that information is not in the common ground even though it is; in suchcases Speaker B’s response will re஺ாect that they’ve checked the common ground. An example ofsuch a dialog is that in (31).(31) 1. Nina: My date last Saturday went really well.2. Jane: Yeah, you were saying.3. Nina: Oh that’s right! I told you yesterday…In line 2 of (31), Jane tells Nina that the information in line 1 is already in the common ground,but in order to tell Nina this, Jane must herself must be certain of what is already in the commonground; in short she must check the common ground. In (31) it is as simple as remembering thatNina already told her about the date. But the simplicity does not invalidate the necessity.The discussion to this point has demonstrated how the response operates to provide evidencefor accepting information into the common ground. The next section will explore an interlocu-tor’s options for responding to an utterance.422.2.2.1 Response optionsBare response particles, ‘yeah’ and ‘no’, can accept or reject information from a previous utter-ance. This may sound trivial, but the mechanisms behind response particles are more compli-cated, not least because a successful theory must account for paradoxical responses. Two ideas,the ellipsis and anaphor theories, have explained many of the features of response particles. Thissection will consider both before demonstrating the utility of the anaphor based theory.Example (32) builds on the previous section’s notions of a two phase expansion of the com-mon ground, but this is an example of the common ground failing to be updated.(32) A: Did you know mother had been drinking?B: I don’t think mother had been drinking at all. (Clark and Brennan, 1991, p. 225)B signals that she has understood A, because she oஸfers a relevant next turn. But the contentof her turn makes clear that she has not accepted the content of A’s utterance. A’s utteranceis a question about B’s knowledge, but A introduces the presupposition that mother had beendrinking. Instead of answering the question directly, B challenges the presupposition containedwithin the utterance. B’s response makes it clear that she did indeed hear what A said, but whetherthe common ground has been updated, and if so with what, is not certain.The presentation and acceptance phases are central to testing the claims of this dissertation,in that the template in (33) is the structure of the exchanges used in the experimental stimuli andin collecting the corpus data (see Chapters 3 and 4 respectively).(33) Adjacency pair templateα:. Utterance contains a proposition consisting of at-issue content and representing α’sbelief and discourse commitment, and responding to an understood QUDβ:. response particle ‘yeah’ or ‘no’, and followup content that agrees or disagreeswith the at-issue content contained in α’s utteranceThe presentation phase, the Utterance, introduces the information, and the acceptance phase,including the response particle and followup content, responds to that utterance. The compo-nents of the response target the content of the utterance. The insight from Clark and Brennan(1991) is that, while the response signals comprehension by default, this is not the same as accep-tance.The distinction between the response particle and the followup content is recognized by Pas-quereau (2018), in his discussion of response particles and what he terms as coda. In discussing43the use of response particles and their codas in European French, he points out that the codadoes not equal the answer; this is consistent with my analysis in which the two components, theresponse particle and content, can respond to diஸferent targets.2.2.2.2 The use of response particlesThe previous section explored the nature of responses in general, and this section will turn toresopnse particles in particular. Response particles are frequently used in isolation in response toan utterance or question, such as in (34).(34) 1. Ben: I think the movie starts at 8.2. Matt: Yeah.3. Ben: So we’ll leave in an hour.4. Matt: No.5. Ben: Why not?6. Matt: I’ve seen it already.The response particles in lines 2 and 4 are suஸஹ஭cient to accept information into the com-mon ground (the movie starts at 8) and reject information (and a suggestion) from the commonground (they will not leave in an hour). How this is possible with bare response particles will bediscussed in this section.A feature of English response particles is that both ‘yeah’ and ‘no’ can respond to utteranceswith negation (Pope, 1972; Umbach, 2014, a.o.). This relates to the properties of relative andabsolute polarity, a feature which will also be explored in this section.RPs as anaphors and RP elipsisIn examining prps in isolation, Kramer and Rawlins (2008) oஸfer an account of how ‘yes’ and‘no’ respond to questions. Responding to positive questions, ‘Is Alfonso coming to the party?’ isstraightforward enough, in that, as shown in Fig. 2.3a, the response particle ‘yes’ is what remainsafிer the rest of the sentence is elided. Accounting for ‘yes’ as a response to a negative questionrequires a bit more structure, as shown in Fig. 2.3b. The [e] in P is a feature that allows for TPto be elided while ‘yes’ remains.Holmberg (2012) expands this proposal with the idea that , which he terms Pol(arity), canhave one of three values: aஸஹ஭rmative, negative, and open (that is, neither aஸஹ஭rmative nor negative).44(a) ‘Is Alfonso coming to the party?’Kramer and Rawlins (2008, p. 1)(b) ‘Is Alfonso not coming to the party?’Kramer and Rawlins (2008, p. 4)Figure 2.3: ‘Yes’ as isolated response to positive and negative questions under Kramer and Rawlins(2008)Under his analysis, the response in (35) has undergone movement, as in Fig. 2.4, which depicts apositive response.(35) Q: Is Alfonso coming to the party?A: Yes. (Holmberg, 2012, p. 58)Figure 2.4: Tree of ‘yes’ response in (35)Holmberg also makes the point that diஸferent languages employ diஸferent strategies for of-fering polar responses. For positive responses, a language may employ a dedicated particle(s) likeEnglish and French, or it may repeat the content verb to signal agreement with p, like Russianand Mandarin. Negative responses are also implemented diஸferently in diஸferent languages, withsome languages like Romanian employing multiple negative particles that are in complementarydistribution (Roelofsen and Farkas, 2015). Pasquereau (2018) builds on Holmberg’s analysis byproposing that response particles instantiate a Pol head in the syntax which can then move intofocus position to scope over the entire clause.The ellipsis approach captures the facts of bare response particles, but it struggles to accountfor paradoxical responses. Because the two parts of the response contradict each other, it seemsproblematic that they could both have the same phrase elided, which is what Figs. 2.3 and 2.4would predict. In essence, paradoxical responses are a problem for the ellipsis approach, becauseit tries to assert the truth of two mutually exclusive ps, a problem which is clear in (36).45(36) Paradoxical response to an utterance, with elided content spelled outQ. Alfonso is coming to the party.yes. #Yeah [he is coming to the party] he isn’t [coming to the party].no. #No [NEG he is coming to the party] he is [coming to the party].The alternative hypothesis is an anaphor based account of bare response particles, but it is notimmediately clear that it provides a solution to the paradox problem. Using (37) as an illustration,an anaphor based account still requires that Sylvia’s response contain con஺ாicting information,that the dinner was both terrible and alright.(37) Situation: Gustav and Sylvia went to a friend’s home for a meal. Gustav did not care forthe food, but Sylvia found it appropriate.1. Gustav: That dinner was terrible.2. Sylvia: YeahthGt JiTTKX wGs tKXXiHRK, I thought it was alright.Kri஺஽a (2013) oஸfers a solution to this problem by developing an analysis which allows re-sponses to be anaphors for more than one potential target. Kri஺஽a demonstrates that clauses in-troduce a number of discourse referents that anaphors can be anchored to, demonstrating eachwith the use of ‘it’ or ‘that’:(38) event: Ede stole the cookie. Bill saw it.proposition: Ede stole the cookie. Bill knows it.speech act: A: Ede stole the cookie. B: That’s a lie!The referents of these diஸferent anaphors are speciஹ஭ed below.(39) [AItP ASSERTdsVKKIhGIt[TP Ede steal-PASTd’VXoV[vP tEJK tstKGR the cookie]]]d”KvKTtFor the purposes of putting forward a proposal concerning the usage of polar response parti-cles, Kri஺஽a oஸfers two critical points: polar response particles are anaphoric, and utterances createmore than one referent. Therefore, building on this framework that Kri஺஽a has developed, a polarresponse particle should be able to target any of the available referents of an utterance. Not onlyis there no evidence that a response particle must respond to the at-issue content, in fact there isevidence that a response particle can target the same components identiஹ஭ed in (38).46One question, however, is whether the list of referents that Kri஺஽a puts forward is necessarilyexhaustive, or whether an utterance could contain other potential referents, such as speaker orhearer belief. Consider the following example, overheard in a restaurant.(40) Context: A couple entered a local restaurant, and their body language and facial expressionssuঃested that they had been fighting. They were seated at a booth, and the waitress broughtthem each a glass of water. The woman drank from a glass.Man: You totally just drank from my water!Woman: Yeah. I did NOT just drink from your water!The proposition in the man’s utterance is clear, that the woman drank from a glass of waterwhich belonged to him. The at-issue content is the same, that the woman drank from a glass ofwater which belonged to the man. Neither party seems to dispute that the woman took a drink;as they were both present at the event, this should be in their common ground. Both people hadtheir own glasses of water, so the presupposition triggered by the man’s use of the pronoun ‘my’stands. The accusation is that she drank from hॾ water instead of her own. The semantics ofthese three potential referents (event, proposition, speech act) is similar to that in (39).(41) Utterance: You totally just drank my water!event: [vP twoSGT tJXiTQ water]at-issue content (p): [TP you drink-PAST [vP twoSGT tJXiTQ water]]speech act: [AItP ASSERT[TP you drink-PAST [vP twoSGT tJXiTQ water]]]belief in p: x commits to the truth of p, where p=y drank x’s waterQUD: {p,¬p}, where p=y drank x’s waterThe man’s utterance, ‘You totally just drank my water!’ introduces all of these components,including the original three (event, at-issue content and speech act) and the belief and QUD.The response particle in woman’s response, ‘yeah’, selects one of these as its target. Because theresponse is ‘yeah’, it signals agreement to something, but because both the target of ‘yeah’ and thefollowup content must simultaneously enter the common ground, the target cannot contradictthe followup content, ‘I did not just drink your water.’ This rules out the event, the at-issuecontent, and the speeech act of assertion, all of which require that the at-issue content be true.But the belief state, where x believes that y drank x’s water, does not require the at-issue contentto be true. The woman’s ‘yeah’ response can signal acceptance of the man’s belief in the at-issuecontent while the followup content can reject the truth of the at-issue content.47Table 2.2: Polarity features of response particlesAbsolute Polarity [+] non-negated prejacent[−] negated prejacentRelative Polarity [agree] preserves polarity[reverse] reverses polarityCrucially, under the Response Target Hypothesis, response particles and followup can havediஸferent anaphors, which is an essential property for understanding responses like ‘no, it’s true.’This is an advantage over the ellipsis approach, under which paradoxical responses should beimpossible. By adopting an anaphoric approach, the response particles and the followup contentare able to respond to diஸferent components of an utterance, allowing one response componentto accept one utterance component, and the other response component to reject something elsefrom the utterance.Response polarityIn addition to the anaphoric dimension, response particles have annother important prop-erty which determines how they contribute to the common ground, namely that of polarity. Thetriggering utterance and the response followup content also have polarity, and the alignment ofthese elements’ polarity contributes to common ground management.This section will look at the polarity of response particles, speciஹ஭cally using the polarity fea-tures in Table 2.2.Polarity exists in two forms, absolute and relative. Absolute polarity, under Roelofsen andFarkas (2015), is a component of the prejacent clause which is then ascribed to the particle, whilerelative polarity re஺ாects the agreement of the response particle to the preceding utterance.Table 2.3 presents the response particles and their polarities in English and Romanian. Thetable highlights the con஺ாation of diஸferent properties in English particles that does not hold inRomanian; it provides for properties of these response particles, rather than a deஹ஭nition.This separation between absolute and relative polarity can help explain things like Englishanswers to questions with negation, such as in (42). Where the triggering utterance does notinclude negation, only one response is available to instantiate the appropriate combination ofrelative and absolute polarity.48Table 2.3: Polar response particles in English and RomanianEnglish [agree] and [+] can be realized by ‘yes’[reverse] and [–] can be realized by ‘no’Romanian ‘da’ can realize [+]‘nu’ can realize [–]‘ba’ can realize [reverse](42) a. Peter called. Yes he did. \ *No he did. [agree,+]b. Peter called. *Yes he didn’t \No he didn’t. [reverse,−]c. Peter didn’t call. Yes he didn’t. \ No he didn’t. [agree,−]d. Peter didn’t call. Yes he did. \ No he did. [reverse,+](Roelofsen and Farkas, 2015, p. 32)Importantly, the relative polarity of both responses in (42c) is [agree]. The relative polarityis identical between the two particles because they both signal agreement with the p on the lefி.Both responses also have the identical absolute polarity, because they derive this polarity from theprejacent. This is also why the responses in (42d) have the same absolute and relative polarity.It follows from Roelofsen and Farkas’s system of the realization of polarity features by re-sponse particles that in (42c,d) either response particle is possible. In the case of (42c), ‘yes’ islicensed because it is realizing the relative polarity feature [agree] and ‘no’ is licensed becauseit is realizing the absolute polarity feature [−]. In (42d), ‘yes’ is licensed because it is realizingthe positive absolute polarity feature [+], and ‘no’ is licensed because it is realizing the relativepolarity feature [reverse].The question which emerges concerns the extent to which these polarity features accountfor the distribution of paradoxical responses and their interpretation. Crucially, Roelofsen andFarkas (2015) predict that paradoxical responses are ungrammatical when responding to utter-ances without negation, but the data disprove this prediction. One other crucial point is that theiranalysis builds on ‘yes’ and not ‘yeah’, but these are not the same in their uses and distribution(Pope, 1972; Wiltschko, 2016). This is part of what obscures the grammaticality of paradoxicalresponses, as (43) demonstrates.(43) a. Peter called. *Yes he didn’t.Yeah he didn’t.492.2.2.3 Adopting a view of response particlesThe consensus among all accounts is that, at their core, ‘yeah’ is an agreeing particle and ‘no’ is arejecting particle, and there is no evidence to suggest that this is incorrect. In fact, looking at baseuses of ‘yeah’ and ‘no’, with no followup content or other particles, their agreeing and disagreeingproperties are diஸஹ஭cult to argue with.The contribution of the Response Target Hypothesis is that ‘yeah’ can agree to the inclusionof semantic content beyond the at-issue content into the common ground, while ‘no’ can dis-agree to the inclusion of semantic content beyond the at-issue content into the common ground.In short, both response particles have a greater range of potential targets, and both particles caninclude (or exclude) most of those targets into the common ground. The Response Target Hy-pothesis draws inspiration from Kri஺஽a (2013) and adopts the polarity system of Roelofsen andFarkas (2015), and it suggests that responses can target several components that are introduced byan utterance, namely at-issue content, QUD, and beliefs and commitments. If ‘yeah’ is targeting,for instance, a speaker belief, then all else being equal, that ‘yeah’ is agreeing to, or accepting, thatbelief into the common ground.7Thus the view of response particles that I adopt is not really a departure from that of otherscholars, but given the limited work on paradoxical responses, my goal is to account for whyresponse particles can be used in instances where the intended meaning of the response seeminglydisagrees with the core function of the response particle. The conclusion that I come to is that thefollowup content has a signiஹ஭cant eஸfect on how response particles contribute to the managementof the common ground.My analysis makes predictions about what can and cannot be included in the common groundbeyond the at-issue content: ‘yeah’ can accept belief (‘I know you think that, but…’) and theQUD (‘That’s a good question, to which I have no answer…’), and ‘no’ can reject the QUD asinvalid (‘We don’t need to discuss that, because there’s already an answer…’) based on the answeralready being in the common ground.7A note about terminology, speciஹ஭cally ‘(dis)agree,’ ‘accept,’ and ‘reject.’ It is important to remember that theseare all terms that re஺ாect the action of a given response component (a response particle or additional content) towardthe inclusion of something into the common ground as part of the Acceptance phase of discourse. Clark (Clark andBrennan, 1991; Clark and Marshall, 1978; Clark and Wilkes-Gibbs, 1986) uses the terminology of accept and reject,whereas, Roelofsen and Farkas (2015) use agree and reject. The experiment that I discuss in Ch. 4 uses agree anddisagree, and in the name of consistency I will endeavor to use those terms unless I am citing or discussing speciஹ஭cother work.502.2.2.4 Modeling the responseThe sample discourse used for tracking contains several responses; in fact every utterance exceptthe ஹ஭rst one is a response to something.(44) Sample discourse for tracking information—Afிer the response0. No speaker; Z is planning her contribution to the discourse1. Z: I’m excited about changing schools from Handsworth to Argyle.2. E: Yeah, that’ll be a good change for you. And it’s so much closer.3. Z: No, it really is.4. E: But Southerland is a good school, too.5. Z: No, it’s not, it’s full of drug dealers.The response contains a response particle and followup content. The response particle ‘yeah’has positive absolute polarity, which derives from the polarity of the triggering utterance in line1. The followup content begins with “that,” an anaphor referring to “changing schools” in line1. This is reinforced by the predicate which refers again to “a good change.” The evidence of thefollowup content demonstrates that the response in line 2 has the relative polarity of [agree].In line 5, ‘no’ is realizing [reject,−], because the at-issue content is being rejected, or disagreeing,and the prejacent contains negation and is therefore [−].The response in line 3 is the paradox which the Response Target Hypothesis is intended toexplain. The triggering utterance has a positive polarity, the response has a relative polarity of[agree], at least based on the content “it really is.” The followup content targets the at-issuecontent and agrees to its inclusion in the common ground (for empirical evidence to supportthis claim, see the experimental results in Ch. 4), leaving ‘no’ to target something else. It cannottarget the at-issue content without creating a paradox. But it can signal disagreement with theQUD based on the assumption that community membership (the same school district) has al-ready placed an answer in the common ground. Therefore, ‘no’ should signal either [reject] or[−] to at least one target. The alternative would be that the response in (44) line 3 has the same[agree,+] polarity of the responses in (42), which would amount to saying that any responsecan have any polarity combination. Such an open ended theory would not oஸfer much predictivepower.The remedy is the Response Target Hypothesis, in which relative polarity can be relative todiஸferent targets in diஸferent contexts. Consider the example in (45).51(45) Utterance: α: I don’t care what you say, there are Martians living in LA!at-issue content: There are Martians living in LA.Belief: Bel(α)(p = ∃x Martians(x) and lives in LA(x))Response: β: Yeah, there are no Martians living in LA!absolute polarity: [−]relative polarity: Bel(α)(p): [agree] β agrees to the belief.The response particle is targeting the belief for acceptance into the common ground, becauseit cannot be targeting the at-issue content. The followup content is incompatible with the at-issue content from the triggering utterance.The contents of the common ground will be changed afிer (45); the following section willlook at how the common ground is updated for both speakers and what this means for the nextphase of the discourse.2.3 After the exchangeThis section will look at how the common ground can be impacted by an exchange and howspeakers process these updates in memory. It will take the previous information about the pre-sentation and acceptance phases of discourse, and look at the consequences of that exchange onthe common ground.2.3.1 Updating the common groundThe previous sections looked at the two step process of updating the common ground and therole of response particles in that process. Fig. 2.5 allows us to visualize this process so that we mayconsider its various stages and processes in relation to each other.The polarity of the triggering utterance, and whether that polarity matches that of the re-sponse, matters in updating the common ground, both in terms of how relative polarity targetsthe at-issue content and in the other potential targets available for responses and followup con-tent. This is why updating the common ground is a separate node from the response itself; theresponse does not on its own update the common ground. The crucial feature of response par-ticles that allows them to select targets other than the at-issue content is their relative polarity.By referring to the diagram in Fig. 2.5 and carefully exploring each path, the interaction of thesefeatures will become clear.52CG Utterance Response Update CG?CG+pCG+∅CG’YESNOFigure 2.5: Updating the common ground (or not) during discourseWhere the utterance has [agree] polarity, as in (46), it is clear that the at-issue content in thetriggering utterance will be entered into the common ground.(46) a. Speaker K: Julia has a really cute dog. absolute [+] polarityb. Speaker L: Yeah, she does. absolute [+] and relative [agree] polarityc. OUTCOME: Common ground updated (CG + pJ hGs G XKGRRy IutK JoM = CG’)This contrasts with (47), in which the relative polarity is [reject] and the response followupcontent has absolute polarity of [−].(47) a. Speaker K: Julia has a really cute dog. absolute [+] polarityb. Speaker L: No, she doesn’t. absolute [−], relative [reject] polarityc. OUTCOME: Common ground not updated (CG +∅ = CG’)This is not to say that the at-issue content introduced by Speaker K, that Julia has a reallycute dog, can never be placed in the common ground; it simply means that the information isnot placed in the common ground as a result of this exchange. In the terminology of Farkasand Bruce (2010), the negative response in (47) puts the conversation in “crisis”, constraining thediscourse until the questions of Julia’s ownership of a cute dog can be resolved. The key pointhere is that this resolution is the work of other pairs of utterances and responses.In considering Fig. 2.5 again, the importance of separating the process of update from theresponse particles becomes clearer in (48) and (49). Both of the triggering utterances have anabsolute negative polarity, and both ‘yeah’ responses have an absolute positive polarity. But oneexchange (48) does update the common ground, while the other, (49), does not. The diஸferenceis the relative polarity.53(48) a. Speaker K: Julia doesn’t have a dog. absolute [−] polarityb. Speaker L: Yeah, she does KRiJKJ(have a dog).absolute [+], relative [reject] polarityc. OUTCOME: Common ground not updated (CG +∅ = CG’)(49) a. Speaker K: Julia doesn’t have a dog. absolute [−] polarityb. Speaker L: Yeah, I know KRiJKJ(that she doesn’t have a dog).absolute [−] polarity, relative [agree] polarityc. OUTCOME: Common ground updated (CG + pJ JoKsTothGvK G JoM = CG’)The crucial diஸference between (48) and (49), is the relative polarity of the responses. Whenthe relative polarity of the response is positive, the common ground is updated, as in (49), andwhere the relative polarity is negative, as in (48), the common ground is not updated. The relativepolarity in these cases is signalling the agreement of the interlocutor to the update of the commonground. Thus it becomes possible to update the diagram of common ground update to that inFig. 2.11.CGUtterance:absolute[+/−]Response:absolute[+/−] &relative[agr/rej]Update CG?CG+pCG+∅CG’YES: relative [agr]NO: relative [rej]Figure 2.6: Updating the common ground (or not) during discourse, with polarityWhat happens if the response is ‘no’, as in (50) and (51)?(50) a. Speaker K: Julia doesn’t have a dog. absolute [−] polarityb. Speaker L: No, she doesn’t KRiJKJ(have a dog).absolute [−] polarity, relative [agree] polarityc. OUTCOME: Common ground updated (CG + p = CG’)54(51) a. Speaker K: Julia doesn’t have a dog. absolute [−] polarityb. Speaker L: No, she does KRiJKJ(have a dog).absolute [+] and relative [reject] polarityc. OUTCOME: Common ground not updated (CG +∅ = CG’)Example (50) has a relative polarity of [agree], in that the response signals agreement withthe triggering utterance. Therefore the common ground gets updated with the at-issue contentasserted in that utterance. This contrasts with (51), in which the relative polarity is [reject], sig-nalling that the common ground should not be updated with the triggering utterance.The process of updating the common ground is dynamic and tractable, in that the speakerand addressee both make their contributions, and then they assess what was said to know whetherthe common ground is updated or not. It is also iterative, because the state of the commonground afிer the exchange, CG’ in Fig. 2.12 becomes the basis for the next update cycle; it be-comes the state of the common ground before the next part of the conversation.CGUtterance:absolute[+/−]Response:absolute[+/−] &relative[agr/rej]Update CG?CG+pCG+∅CG’CG’ becomes CGYES: relative [agr]NO: relative [rej]Figure 2.7: Updating the common ground (or not) during discourse, with polarity and iterationThe key takeaway is that, despite the strengths of the Roelofsen and Farkas (2015) analysis, itcannot account for paradoxical responses. It will either undergenerate by predicting that para-doxical responses are ungrammatical (they are not), or it will overgenerate by allowing all polaritycombinations to occur in essentially free variation. By providing a richer set of targets for responsepolarities, the Response Target Hypothesis addresses this shortcoming.The next section will look at the theoretical models that are intended to capture the facts ofthis process, particularly the Table model (Farkas and Bruce, 2010), and Commitment Space Se-mantics (Kri஺஽a, 2015). These models provide the tools necessary to bring together the processof the common ground detailed above with the Presentation and Acceptance phase of discourse55presented in Sec. 2.2, the QUD, at-issue content and beliefs described in Sec. 2.2.1, and the prop-erties of response particles and the common ground in Sec. 2.2.1.2.3.2 Models of discourseBy now all of the components of discourse and common ground management have been deஹ஭nedand described. At this point the question turns to pulling all of these disparate componentstogether into a single system that can illuminate the process of discourse based common groundupdate through the use of response particles.Two models will be discussed below, both of which respond to the question of how this wholeprocess works. The ஹ஭rst will be the Table model of Farkas and Bruce (2010), which proposes thatcontributions go on a Table and are resolved from there. The second is the Commitment Spacemodel of Kri஺஽a (2015), which proposes a process by which utterances and their components areadded (or not) to the common ground, or commitment space, incrementally. Both models oஸfervaluable tools which contribute to understanding the process of discourse.2.3.2.1 The TableThe Table model represents the ஺ாow of information from the initial assertion through to thecommon ground, by way of the Table and the Stack. The Table contains “items that are stillunder discussion” (Farkas & Bruce, 2010 p. 89) and is represented as a Stack, in that these itemsare “stacked” so that only the topmost item is accessible.8 In their model, information begins asa discourse commitment of a participant (A or B in Fig. 2.8) which is conveyed by the utterancethat an individual speaker publicly states, which creates the projected set, that is “the set of futurecommon grounds relative to which the issue on the Table is decided.” (Farkas and Bruce, 2010,p. 87).The Farkas and Bruce (2010) framework was developed to represent propositions throughthis process, and response particles are speciஹ஭cally assumed to target only propositions, to ei-ther accept or reject the proposition at the top of the Stack’s inclusion into the common ground.Moreover, the model was designed around fairly simple adjacency pairs such as (52).8Kim Bruce is a computer scientist by training, and the Stack is likely derived from the term ‘stack’ as it is usedin object oriented programming, that is a vertical assembly of data in which only the topmost element is accessibleand must be resolved before accessing what is underneath (this is called “popping” the stack in computer science,though Farkas & Bruce (2010) have modiஹ஭ed this terminology to be “popping the top” of the stack).56A Table BDCA S DCBCommon Ground cg Projected Set psFigure 2.8: Sample Context Structure from Farkas & BruceA Table BDCA p p=Sam ॾ home. DCBCommon Ground cg Projected Set ps{xg∪ p/¬p/∅ }Figure 2.9: Sample Context Structure from Farkas & Bruce afிer utterance is introducedThe proposition p is placed on the Table, and the placeholder p is placed in A’s discourse commitments.(52) A: Sam is home. This utterance leads to the Table in Fig. 2.9B: Yes, Sam is home./ No, Sam isn’t home.adapted from (Farkas and Bruce, 2010, p. 82)In this example, A’s utterance asserts a proposition, that Sam is home, and B’s response in-cludes a response particle and followup content which agrees with the response particle. That isto say that the followup content afிer ‘yes’ signals agreement with the proposition, and the con-tent afிer ‘no’ signals disagreement. In terms of polarity, ‘Yes, Sam is home.’ is [+,agree], and‘No, Sam isn’t home.’ is [−,reject].Under the Table framework, Speaker A makes a discourse commitment ‘Sam is home,’ whichgoes in the cell labeled DCA (or A’s Discourse Commitment), and it goes on top of the Stack, la-beled S, on the Table; in Fig. 2.9, the proposition p goes in two cells, DCA and the Stack onthe Table. At that point the common ground is unchanged, but the projected set includes a fewpossibilities, as indicated in Figure 2.9; the common ground can either be updated with p, ¬p,or nothing. Moreover, the addition of p to the Table makes it possible for B to then act on theproposition introduced by A by accepting it or rejecting it. If B accepts the proposition intro-duced in DCA, then the common ground is updated to include the new information. If B rejectsthe proposition, then the common ground is not updated, and a “crisis” is created. That crisismight be resolved by further discourse, which will involve the addition of other propositions, butcrucially, the common ground will not be updated with the proposition in DCA at that point inthe discourse.There are two potential outcomes from this exchange:571. The proposition “Sam is home” is asserted as being true by A and accepted as being trueby B, and therefore the common ground is expanded by the inclusion of this proposition.2. The proposition “Sam is home” is asserted as being true by A and rejected as being not trueby B, and therefore the common ground is not expanded and the conversation is in crisis.The exchange in (52) can only resolve the Projected Set in one way: ”Yes, Sam is home” selects{xg ∪ p} as the updated common ground. Otherwise ”No, Sam isn’t home” leaves the Tableunchanged while the matter is decided in further discourseIn contrast to (52), (53) presents a paradoxical response. Under the Table model, the responseparticle should create a crisis, but the followup content is consistent with xg∪ p.(53) : I think we need to be meeting at least once a month. : No, you’re right.When says, “No, I think you’re right,” what are they signaling? Is ‘no’ leaving the Tableunchanged, as in (52)? Or is it selecting p for inclusion, based on “you’re right.”? Intuitively, weunderstand the response as signalling support for the suggestion that the group meet at least oncea month. The problem is, how do we model that? While the Farkas & Bruce model capturesthat expanding the common ground is a mutual process, it does not seem able to account forparadoxical—but entirely natural—responses.The strength of the Table model is that it creates a system to model the ஺ாow of informationfrom utterance to common ground. It is a theoretical model that accounts for the data by for-malizing the relationship between an utterance and the common ground. By creating a Tableto capture the proposition introduced in an utterance, the model also creates a link between theresponse and the update of the common ground. Moreover, the recognition that ‘no’ does notnecessarily place ¬p into the common ground is important, because it reinforces the idea thatcommon ground is mutual. The Table model allows this disagreement to be resolved by lettingthe discourse continue, using the same Table model to capture subsequent turns, but cruciallythe Table does not allow the exchange to be resolved at that point. However, under the ResponseTarget Hypothesis, (53) can be resolved. Thus the table provides an elegant model on which tobuild, but it needs supplementing with the Response Target Hypothesis.2.3.2.2 Commitment SpacesKri஺஽a’s commitment space model (Kri஺஽a, 2014, 2015) sets out to capture the semantic informa-tion of an utterance as well as to track discourse, including which speaker commits to which58information. It relies on two unique stages: the commitment state, which is the set of proposi-tions c (and not possible worlds) that are non-contradictory to what is in the common ground;and Commitment Spaces C, which is the set of commitment states that represent the future de-velopment of the common ground (Kri஺஽a, 2015, p. 329). Let us look at each of these stages inturn.Commitment states represent what one individual has publicly committed to believing. Anassertion takes the notational form of (54.1), in which S1 is the speaker of the utterance, ⊢ is thatspeaker’s commitment to the truth of φ, and φ is the proposition of the utterance. This resultsin the proposition becoming part of the commitment state. The commitment state is updatedto (54.2). Importantly, commitment states are non-contradictory, i.e. they cannot contain bothp and ¬p.(54) Commitment States (c)1. Assertion: S1 ⊢ φ2. Commitment state c afிer assertion: { S1 ⊢ φ ∈ c }Commitment spaces take this assertion and map all of the possible future commitment states,which is notated as in (55). At the time of assertion, S1 publicly commits to the truth of a propo-sition φ, which is depicted in (55.1). Assuming that the interlocutor, S2, accepts the truth of φbased on the evidence of S1’s belief, C is then updated to (55.3), indicating that the CommitmentSpace includes φ and S1’s commitment to the truth of φ. If S2 signals that they do not committo the truth of φ, then a retraction is required, which is characterized in (55.4).(55) Commitment Spaces (C)1. S1 commits to truth of φ: {x ∈ C | S1 ⊢ φ ∈ x}2. S2 acknowledges S1’s commitment: {x ∈ C | S1 ⊢ φ ∈ x ∧ φ ∈ x}3. S2 agrees with φ: {x ∈ C | S1 ⊢ φ ∈ x ∧ φ ∈ x} + [S2 ⊢ φ] S24. S2 rejects φ: {x ∈ C | S1 ⊢ φ ∈ x} + ℜ + [S2 ⊢ φ] S2 (Kri஺஽a, 2015, p. 334-335)Kri஺஽a helpfully includes schematics of these various progressions, reproduced in Fig. 2.10,which correspond to the representations in (55); these visuals help to demonstrate what infor-mation is contained in the commitment space and under what conditions. In Fig. 2.10a, theCommitment Space includes S1’s commitment toφ (in the lightly shaded box) and S2’s acknowl-edgement of this commitment in the innermost box. To put this in comparison with Clark and59(a) acknowledgement (55.2) (b) agreement (55.3) (c) rejection (55.4)Figure 2.10: Diagrams of Commitment Spaces in (55), from Kri஺஽a (2015, p. 334)Brennan (1991), this Commitment Space is only slightly more advanced than the presentationphase, but it does not approach the level of the acceptance phase. Acceptance occurs in Fig. 2.10b,in which the innermost box includes S2’s commitment toφ as well as S1’s commitment toφ in theoutermost shaded box. Fig. 2.10c also proceeds from the acknowledgement state, representingS2’s rejection ofφ and, by extension, their commitment to ¬φ, in the innermost shaded box. Im-portantly, however, S1’s commitment persists in this commitment space, regardless of the truthof φ, as indicated by the dashed-line rectangle in the lower lefி.Even this brief sketch of Kri஺஽a’s Commitment Space Semantics presents properties that arerelevant for the hypothesis in this dissertation, including the persistence of one speaker’s commit-ment to the truth ofφ regardless of the other speaker’s agreement. Figure 2.10c and (55.4) providea mechanism whereby S2 can disagree with φ introduced by S1 without completely removing φfrom the realm of shared information between the two speakers. If, as I argue in this dissertation,responses can be used to simultaneously accept a speaker’s belief in at-issue content and reject thetruth of the at-issue content, then any model of shared information must be able to capture bothof these properties simultaneously. Kri஺஽a’s Commitment Space model seems able to do just that.The model assumes a one-to-one correlation between response particles and their impact onthe common ground. For example, in his discussion of what I have labeled Fig. 2.10, Kri஺஽asays the rightmost image corresponds to ‘no’, and the middle one corresponds to ‘yes’, and byextension ‘yeah’. But the previous sections of this chapter have provided numerous exampleswhere the correlation, of ‘no’=rejection of the at-issue content and ‘yeah’=agreement, does nothold. Therefore, while I will adopt Kri஺஽a’s Commitment Space model to a large extent, I willallow for a loosening of the relation between the response particle and how the common groundis updated.602.3.3 Role of memoryThe previous discussions on the nature and update of the common ground discussed many ofthe mechanics of common ground use in discourse, but there are some important questions lefிunanswered. Where is the common ground stored? Why is it impossible to be absolutely certainof what is in the common ground? Such questions speak to the role of memory in commonground management.Common ground is conceived of as a repository of shared information, and the only possibleplace for this repository to be stored is in the minds of interlocutors. Where physical copresenceis the source of common ground, interlocutors may rely on their senses to update the commonground. For community membership and discourse-created common ground, the informationmust be stored in the memory of individuals. If utterances were stored verbatim, then this wouldhave implications for the common ground, as systems such as Kri஺஽a’s and Farkas & Bruce’s wouldnot need to track discourse commitments; it would come “for free” as part of speaker memory.9The reason for this is that, if each utterance is stored verbatim in memory, that is if speakers haveavailable in their memory an exact transcript of the previous discourse, then there is no need tomodel why the common ground captures semantic information without preserving its syntacticshape; both the shape and the information would simply be functions of memory. However, ex-tensive and long-standing research has shown that this is untrue, that rather than storing a word-for-word transcript of discourse, interlocutors retain the gist of a discourse in their memory, aneஸfect which holds true for both short- and long-term memory retention (Sachs, 1967; Anderson,1974; Reyna and Kiernan, 1994, and works cited therein, among many others). Others take amore nuanced view, demonstrating that some utterances may be stored verbatim in limited cir-cumstances (Keenan et al., 1977; Reyna and Kiernan, 1994; Gurevitch et al., 2010, among others).Sachs (1967) showed in her seminal dissertation that, rather than storing the verbatim con-tent of an utterance, interlocutors stored only the gist of what was said; in other words, mem-ory records the semantic content and not the syntactic form. Her conclusions found support inAnderson (1974), who found that the verbatim form of a sentence may be stored in short termmemory, but when participants’ long term memory was tested, they could conஹ஭rm the veracityof a sentence, but not the form of the sentence. Reyna and Kiernan (1994) showed that the inter-vention of even one other sentence could be suஸஹ஭cient to degrade a speaker’s short term verbatimrecollection of a sentence, but that the semantic content could be retained over much longer pe-9That discourse is stored verbatim seems to be an assumption ascribed to the ஹ஭eld of conversation analysis (Sche-gloஸf, 1968; Sacks et al., 1974), but this is neither a claim nor a question for conversation analysis, which instead focuseson turn-taking, overlap, and other factors concerned with the process of conversation, not necessarily the output.61riods. These and other works seem to oஸfer exceptionally strong evidence that semantic content,and not syntactic constructions, are stored in memory; this seems to work nicely with the ideathat the common ground is the repository of propositions, which are by deஹ஭nition semantic innature.As speakers of language though, we have the experience of remembering an utterance ver-batim, and we might therefore wonder how that impacts the common ground. A body of lit-erature within psycholinguistics provides some nuance to the claim that verbatim utterances arenever stored in memory by demonstrating that there are conditions under which verbatim ut-terances are stored in memory, speciஹ஭cally when listeners are instructed to remember or whenthere is some personal value attached to words. Johnson-Laird and Stevenson (1970) were amongthe ஹ஭rst to demonstrate that syntactic constructions were not stored in memory, but their laterwork showed that, if participants were warned that they would be tested on their retention ofsentences, participants were in fact able to store sentences in their memory; Reyna and Kiernan(1994) also found that participants’ recall ability was increased if they knew beforehand that theywould be tested on certain sentences.Without a reliance on verbatim memory, the common ground becomes an important toolin modeling the exchange of information between interlocutors. Models such as Kri஺஽a’s Com-mitment Space provide a mechanism for how speakers are able to manage several componentswhich are introduced by a single utterance. Relying on memory to capture the gist of an utter-ance without preserving its shape allows us to store the information in the common ground, sothat ‘p is true’ becomes ‘α and I both know that p is true.’2.3.4 Modelling common ground updateThe sample discourse used throughout this chapter includes both possible outcomes of commonground update: updated and not updated. The response in line 2 accepts the at-issue contentintroduced in line 1, which adds the at-issue content to the common ground.62(56) Sample discourse for tracking information—Afிer the response0. No speaker; Z is planning her contribution to the discourse1. Z: I’m excited about changing schools from Handsworth to Argyle.2. E: Yeah, that’ll be a good change for you. And it’s so much closer.3. Z: No, it really is.4. E: But Southerland is a good school, too.5. Z: No, it’s not, it’s full of drug dealers.The common ground at the very least contains information regarding the context of the dis-course and that which results from shared community. This is the common ground that exists inline 0. Afிer the response in line 2, the common ground is updated to include the at-issue contentin line 1, as indicated in Fig 2.11.CG0 Utterance1 Response2 Update CG?CG0+paic1CG’YESFigure 2.11: Updated common ground afிer line 2The sample discourse also includes a rejection of the at-issue content in a previous utterance,in which case the common ground is not updated. This is the result of lines 4 and 5; line 4 intro-duces the at-issue content that Southerland is a good school, and line 5 rejects this assertion.(57) Sample discourse for tracking information—Afிer the response0. No speaker; Z is planning her contribution to the discourse1. Z: I’m excited about changing schools from Handsworth to Argyle.2. E: Yeah, that’ll be a good change for you. And it’s so much closer.3. Z: No, it really is.4. E: But Southerland is a good school, too.5. Z: No, it’s not, it’s full of drug dealers.63Because there is no content that has been mutually agreed to for entry into the commonground, the common ground is not updated; CG” is identical to CG”’as re஺ாected in Fig. 2.12.CG” Utterance4 Response5 Update?CG0+∅CG”’NOFigure 2.12: Updated common ground afிer line 5This is not to say that the at-issue content introduced in line 4, that Southerland is a goodschool, can never be introduced into the common ground. Subsequent turns can potentiallyestablish that information in the common ground, once both speakers signal their acceptance ofit as true. But crucially, this pair of utterances does not alter the common ground, because thenegative response signals a lack of agreement to the inclusion of any information introduced bythe utterance.The pairs that have been discussed thus far, lines 1 and 2 and lines 4 and 5, are clear instancesof the responding speaker accepting or rejecting the at-issue content. What they say afிer the re-sponse particle reinforces the response particle. The utterance pair of lines 2 and 3 is potentiallyambiguous, because the response particle and the followup content of the utterance are not con-sistent with each other. ‘No’ seems to signal disagreement, while ‘it really is’ signals agreement.So which is it?(58) Sample discourse for tracking information—Afிer the response0. No speaker; Z is planning her contribution to the discourse1. Z: I’m excited about changing schools from Handsworth to Argyle.2. E: Yeah, that’ll be a good change for you. And it’s so much closer.3. Z: No, it really is.4. E: But Southerland is a good school, too.5. Z: No, it’s not, it’s full of drug dealers.As a speaker of English, my own intuition is that the response is agreeing with the assertionthat the new school is closer. Examining both parts of the response in isolation supports thisjudgement, as (59) illustrates.64(59) a. E: It’s so much closer.Z: #No.b. E: It’s so much closer.Z: it really is.A bare ‘no’ response, as in (59a), seems infelicitous to my intuition, as the location of thetwo schools and the location of Z’s home are both in the common ground (based on their sharedcommunity and prior history); this intuition is tested in similar discourses in Ch. 4. The responsein (59b) ‘it really is’, signals agreement to the information in the triggering utterance, and Ch. 4supports this as well.The Response Target Hypothesis oஸfers an answer to the question of why ‘no’ is being usedin this example, when it is apparently paradoxical to the followup content. I argue that it dis-misses the QUD concerning the location of the school. This information is already in the com-mon ground because of the shared community membership of the speakers and their existingrelationship, and therefore it is not a meaningful question under discussion. Therefore the im-pact of this pair of utterances on the common ground is one of conஹ஭rming the presence of thisinformation, rather than updating it to include something new.2.4 SummaryThis chapter broke a complex process into smaller components, but it is important to remem-ber that this process is constant and cumulative. Taking the sample discourse again as a model,it contains three adjacency pairs—assertions and responses—and takes less than 15 seconds fortwo speakers to complete. That means that these two speakers are considering their interlocu-tor, planning the utterance, delivering and interpreting the response, and updating the commonground in a matter of seconds, and then immediately repeating that process.Moreover, the process is managed with a versatile set of tools which interact with each other.Agreement is not signalled solely by the use of a “positive” response particle; a response whichsignals agreement in one context can signal disagreement in another. Because we cannot directlyaccess the mental processes that speakers use in discourse, we must rely on the linguistic infor-mation in each utterance and response to support our understanding of the process. Importantfactors for consideration are the sources of pre-existing common ground; the polarity of the ut-terance and response, and whether those polarities match; the person(s) for whom the messageis intended; the type of predicate; levels of evidence of agreement or attention. The followingchapter will look at how evidence of these factors is found in corpora.65Chapter 3Naturally occuring dataThe Response Target Hypothesis claims that response particles in paradoxical responses can tar-get something other than the at-issue content. This chapter tests this claim through the use ofcorpora which make unscripted conversations available to use as data.Where corpora identify a broadcast source or an individual speaker, the time and setting arerecoverable, and therefore available as part of the context for the analysis. In addition to the datafrom corpora, a few additional examples are taken from my own experience and observation; asa native English speaker living in an English speaking community, I am positioned to observenatural exchanges in natural settings.This chapter begins by discussing the methodology for processing corpus data (Sec. 3.1) ,including how tokens were selected for inclusion and a summary of the patterns that emergedfrom examining responses within the corpora (Sec. 3.2). The balance of the chapter is devotedto presenting data which tests the hypothesis (Secs. 3.3–3.5). The ஹ஭nal section summarizes theஹ஭ndings of this inquiry.3.1 MethodologyThe use of paradoxical responses is a discourse phenomenon, and it is important to use unscripteddiscourse to examine the phenomenon in situ. Cataloging instances from listening to broadcastsources and observation does yield results, but not enough to draw robust conclusions. Withthese constraints in mind, corpus data was used to identify a suஸஹ஭cient quantity of examples fromwhich I might be able to discern patterns of use to support (or challenge) the Response TargetHypothesis.Selecting a set of tokens for further analysis, almost as a mini-corpus, is atypical of corpus66studies, which are usually driven by a quantitative analysis, perhaps of word frequencies or de-mographic information. For formal semantic analysis, one reason why corpus data is not typicallyused as the exclusive source of data is the perceived risk of “mindreading,” in which assumptionsabout the speakers’ viewpoints and knowledge are projected onto the conversation and used toexplain the speakers’ motivations. To mitigate this possible problem, the analysis will focus onwhat is linguistically present in the conversation coupled with what is broadly available in thecommon ground of North American cultural knowledge.1This section will walk through the process of analyzing the tokens from corpora, beginningwith the selection criteria. It will then consider the criteria for determining whether the followupcontent of a response signals agreement or disagreement, and the criteria for determining theQuestion Under Discussion (QUD). An overview of the whole process will conclude this section.3.1.1 Selecting the data (corpus and “wild”)Three corpora were used as sources for data:(1) Corpora used in analysis(i) Linguistic Data Consortium:– Fisher Corpus (Cieri et al., 2004)– Switchboard Corpus (Graஸf et al., 2001)(ii) Corpus of Contemporary American English, or COCA (Davies, 2008)These three were chosen because they include unscripted, spoken English which has beentranscribed and is searchable. The LDC corpora make the audio ஹ஭les available to researchers,while COCA annotates its data with the information necessary to search for a recording.The corpora all present transcriptions of spoken discourse, and they each have their own tran-scription conventions. I have kept the examples as faithful to the corpora as possible, meaningthat I have not corrected misspellings, capitalization errors, false starts, or any other “errors” inthe transcription. The only exception was to correct the spelling of names to avoid the impres-sion that the diஸferent spellings might refer to diஸferent individuals. In isolated cases, I removeda long section of false starts, overlaps or backckannels so as to focus on something speciஹ஭c in thedialog; these cases are always noted with […].1For a discussion of the various sources of common ground, see Sec. 2.1.1.67The Fischer and Switchboard corpora consist of recorded phone calls between strangers whovolunteered to be part of the corpus. The participants were given some suggested topics of con-versation, but they were not required to discuss anything in particular and were free to conversenaturally. A strength of these corpora for this dissertation is that the preexisting common groundbetween the participants was minimal; they were usually from diஸferent states and held diஸferentoccupations, so that there was no prior community membership. The common ground that ex-ists between them derives from their shared community membership as late 20th century NorthAmericans. While they do sometimes discuss national events or politics, they also discuss moremundane topics where there can be little preexisting common ground, such as their pets, neigh-borhoods and eating habits. As the conversations were all recorded over the phone, they wererestricted to being conversations between two individuals with no expectation of an audience oroverhearers as part of the immediate conversation. Participants did know that the conversationswere being recorded for inclusion in the corpus, but they were the only participants at the timeof the conversation. The signiஹ஭cance of this is that the common ground need only be concernedwith those two individuals. The format also means that there was no physical source for commonground. Thus everything had to be negotiated linguistically over the phone.The full COCA includes novels, newspapers, magazines, scripted and unscripted televisionprograms, talk radio and several other sources; the corpus comprises over half a billion words andcontinues to grow. I conஹ஭ned my use of this corpus to unscripted spoken exchanges that werebroadcast on television or talk radio. As these conversations were broadcast, they diஸfer fromthe LDC corpora in that there was an immediate audience beyond the discourse participants,sometimes including an in-studio audience and always including the listeners/viewers for whomthe program was made. Most of the exchanges are interviews, and they range from formal, one-on-one, in-depth conversations between a host and a guest, to panel discussions on news or sportsbroadcasts, to the banter of multiple hosts with one or more guests. This corpus provides a widerange of registers and speakers, and the conversations are on widely accessible, contemporarytopics; thus the pre-existing common ground for both discourse participants and audience isbased on shared community membership, namely that of early 21st centry North Americans. AsCOCA is continually updated, many of the most recent examples concern the 2016 U.S. election,recent sporting events, prize winning novels, etc. from the recent past, approximately 2010 to2018; I imposed no further restrictions on when the exchanges took place.Finally, some of the examples discussed below are from the wild, in that they are exchangesthat I have personally encountered. Some were from broadcasts or podcasts that I listened to,others were overheard in a public place. Where they were broadcast, I have included a source if68possible, and where I knew the speakers, their identities have been anonymized; no examples weretaken from private conversations for which the speakers could expect privacy. When I did hearparticularly relevant examples, I wrote them down or otherwise recorded them immediately soas to retain the original wording and context; I did not use examples where there was a signiஹ஭cantgap between when I heard them and when I recorded them. I have also not included these wildexamples in tables in which instances of the various uses were tallied. These examples are includedbecause they are either particularly strong examples of a phenomenon or are easier to extract fromtheir original setting than corpus examples were; because some corpus examples rely on severalminutes of preceding conversation, they were unwieldy as examples in this chapter. It is alsoimportant to recall that the corpora were used as a source for tokens of data, not as the primarydata; in other words, no analysis was done on every instance of ‘yeah’ in the COCA, for example,such that changing the corpus would have changed the analysis. No analysis was done using theentire corpora, so that using additional tokens does not undermine a corpus based analysis.To constrain my search, I used the same template for corpora exchanges (and wild conversa-tions) as I used for the experimental design, ஹ஭rst introduced in Chapter 1 and repeated in (2). Inlimited instances I have included extra prior turns to provide necessary context; in cases where thecontext is developed over an extensive timeframe, I have summarized the relevant context priorto the example.(2) Adjacency pair templateα:. Utterance contains a proposition consisting of at-issue content and representing α’sbelief and discourse commitment, and responding to an understood QUDβ:. response particle ‘yeah’ or ‘no’, and followup content that agrees or disagreeswith the at-issue content contained in α’s utteranceSpeakers ofிen kept speaking afிer the response particle and followup content, and I haveincluded the rest of these turns, provided they were on the same topic as the original utterance.Where they switch topics, I have not included the new topic information. An example of this isin (3), where speaker A uses their turn to switch the topic of conversation away from obituariesand onto work; the light grey portion represents the topic switch and would not be included inmy analysis.69Table 3.1: Percentage of included results from total search results (est.)yeah noCOCA 21% 11%LDC (Fisher and Switchboard) 24% 10%(3) Participants are discussing the people listed in obituariॽ1. B: well what i mean is do you if your [sic] in a strange city you certainly don’t knowthem2. A: yeah that’s true what type of work are you in Switchboard CorpusMy procedure followed two steps, a corpus search and then a content-based analysis. In theஹ஭rst step, I entered ‘yeah’ or ‘no’ into the search ஹ஭eld, and for COCA I conஹ஭ned the search tothe unscripted spoken portion of the corpus. From the results, I selected examples that ஹ஭t thetemplate above and were not excluded by other criteria (exclusion criteria, and examples, are inSec. 3.1.2 below). The results of the ‘yeah’ and ‘no’ searches numbered in the millions; I startedat the beginning of the search results as presented by the default algorithm of the database andchecked each result for inclusion or exclusion. Because ‘yeah’ and ‘no’ are used in a number ofcontexts in English, the percentage of instances which qualiஹ஭ed for this study was relatively small.While I did not keep an exact count of the excluded examples, the results were presented in pagesof 50, and I tracked how many pages were needed to extract 100 examples of ‘yeah’ and 100 of ‘no’from both the COCA and LCD corpora. Table 3.1 shows the percent of responses of my searchwithin the results from each corpus that were included in my dataset to give an approximatepercentage of included results out of total results. In other words, 21% of the search results thatI examined for ‘yeah’, or 21% of 950 returned results (19 pages of results, 50 results per page) ஹ஭tthe template for inclusion in my data set. The LDC results are from two corpora, the Fisherand Switchboard corpora, but they are classed together under the LCD, because they are bothcomprised of unscripted telephone calls between strangers.The response ‘no’ was excluded more frequently than ‘yeah’, because it ofிen appears as amodiஹ஭er in other environments, such as those in (4) and (5).(4) CHUCK TODD: No matter how you slice this thing, the GOP tax plan is going to be abig boom for the wealthy and speciஹ஭cally the Trump family. COCA70(5) 1. SASAY: We appreciate you being with us.2. VAUSE: No worries COCAThe central research question asks what goes into the common ground as a result of the use ofresponse particles; the followup content which comes afிer the response particle is an importantindication of what, if anything, is added to the common ground. In considering the 200 ‘yeah’and 200 ‘no’ examples extracted from the corpora, the ஹ஭rst step was to determine whether thefollowup content agreed or disagreed with the at-issue content of the preceding utterance; thegoal was to determine whether the followup content on its own was suஸஹ஭cient to place the at-issue content in the common ground.In order to test the Response Target Hypothesis, the analysis of the corpus data needed to beclear and consistent. Therefore I looked for explicit evidence to support my initial judgements. Ialso reviewed the data several times and had a research assistant review the data as well, to ensureconsistent classiஹ஭cation. In cases where the diagnostic criteria is inconclusive but where the judge-ments were clear, for example dialogs with indirect or suggestive language, I describe how the datais consistent with the ஹ஭nal classiஹ஭cation by presenting additonal information and discussion.Conversation is necessarily messy, as mentioned previously, so it will be helpful to use a“messy” example to illustrate the process of analyzing tokens from conversations. Consider (6),which comes from a broadcast interview.(6) 1. MEGYN KELLY: But I love that you want little girls to know too that this is availableto them and – and – and boys, like, young people need to realize this is an option foryoung women.2. JUDALINE CASSIDY: Yeah. that we did a disservice to our country, by the images weportray of tradespeople. COCAThe ஹ஭rst speaker, Megyn Kelly, utters a sentence that includes several clauses, each of whichhas the potential to introduce at-issue content, and presuppositions:(7) Clauses in (6) line 11. MK loves that2. ↰JC wants3. ↰girls to know that4. ↰this (trade career) is available to them (girls)715. and young people need to realize that6. ↰this (trades) is an option for young women.In considering what a response might be targeting, my analysis begins with the last clauseand its at-issue content, and not the at-issue content from other clauses within the utterance.This allows for a systematic examination of the data, motivated by the structure of discourse. Byselecting the ஹ஭nal clause, in this example line 6 of (7), it becomes possible to see speciஹ஭cally howthe common ground is expanded, as in (8).(8) at-issue content. ThistXGJKs is an option for young women.CG’. CG ∪ at-issue contentJC’s response accepts the overall sentiment of MK’s utterance, but it is diஸஹ஭cult to assess specif-ically what, if anything, from MK’s utterance has entered the common ground.The value of selecting the ஹ஭nal full clause as the response target is particularly clear in a caselike (9),2 where Speaker A’s utterance contains several clauses that have little if any syntactic orsemantic relationship to one another, as is clear in (10). The followup content in Speaker B’sutterance responds directly to the ஹ஭nal clause of the Speaker A’s utterance.(9) 1. A: i worked for the TI plant in Abilene and and i sure enjoyed the Southwest it wasreally neat but uh that that’s an interesting concept that this is going to be your yourpermanent home or okay2. B: yeah we we bought this land out here we’re going to we’re going to retire on itLCD(10) Clauses in (9)(i) ISVKGQKX A worked for the TI [Texas Instruments] plant in Abilene [Texas](ii) ISVKGQKX A sure enjoyed the Southwest(iii) ItSouthwKst was really neat(iv) That? is an interesting concept(v) This? is going to be your permanent home2The original transcription records “… concept that is this going…”; I transcribed it as “… concept that this isgoing…” based on the audio.72An exception to using the last clause of an utterance as the at-issue content is when the lastclause is oஸfered as evidence, or in support of, a previous clause, such as in example (11). The ஹ஭nalclause begins with “Like,” suggesting that it is being oஸfered as evidence in support of a previousstatement.(11) 1. Traஸஹ஭c is just nuts in the rain! Like yesterday people were all panicking because of alittle water on the road!2. Yeah, it’s insane.Two clauses are introduced in line 1 of (11), listed in (12). At-issue content in this case wouldbe hypothesized to be ‘Traஸஹ஭c is insane when the weather is bad.’(12) Clauses in (11) line 1(i) Traஸஹ஭c is just nuts in the rain.(ii) ↰Like yesterday people were panicking because of a little water on the road.Because the second clause is oஸfered as evidence to support the ஹ஭rst clause, the ஹ஭rst clausecontains the at-issue content that the second clause is supporting. This understanding is rein-forced with the response followup content, “it’s insane.” The pronoun ‘it’ refers to traஸஹ஭c, andnot people, and ‘insane’ and ‘nuts’ are synonyms in colloquial speech.The other main exception to using the last clause as the source of the at-issue content is whenthe ஹ஭nal clause is an object of a previous clause, as in (13).(13) 1. Dogs act like every person on Earth exists to pet them.2. Yeah, that’s why we love them.The matrix clause, “Dogs act like…” takes the second clause, “every person on earth exists topet them,” as its object. The at-issue content in this example would derive from the matrix clauseand would include the embedded clause, ‘Dogs act like all people exist to pet them.’ It would notbe the ஹ஭nal clause. The response supports this analysis as well, as ‘them’ refers to dogs, not “everyperson on earth.” This becomes clear when the pronouns are spelled out in the response, as in(14).(14) a. Yeah, that’s why we love dogs, because dogs act like every person on the earth existsto pet them.b. #Yeah, that’s why we love every person on earth, because every person on earth existsto pet them?.73Ambiguous examples such as (6) are present in the corpus data; the template and exclusionsused to select the tokens have limited the number of ambiguous examples present. While the pri-mary focus is understanding the role that responses play in constructing common ground, theseambiguous examples are interesting in other ways, because, as in (6), their interpretation ofிenrelies on information already established in the common ground, demonstrating the importanceof the common ground as a repository for information.3.1.2 What was excluded from my studyThis section provides examples of the kinds of tokens that were excluded from the study de-spite appearing to ஹ஭t the template. These exclusions fall into seven categories: fragmented dis-course, missing context, broadcast genre conventions, direct questions, quizzes, backchanneling,and other syntactic uses.Fragmented discourse In selecting the exchanges to include in this study, I looked for utter-ances that had content that could be expressed in a single paraphrased sentence. I did not includeexchanges where the initial utterance might be said to be fragmented. This is not a term ingeneral use in discourse analysis3, but I use it to refer to utterances such as that in (15).(15) Fractured discourse1. SHEINELLE஡JONES-: Because you wake up at –2. JENNA஡BUSH஡HAGER-: See, I have –3. AL ROKER: You don’t have water rings on your coஸfee table?4. SHEINELLE஡JONES-: No.5. AL ROKER: On your night stand?6. SHEINELLE஡JONES-: You wake up and – because it’s not cold.7. DYLAN஡DREYER-: Yeah, that’s true. COCAOther than the ஹ஭nal response in line 7, no other utterance in (15) includes a complete, declar-ative sentence. Lines 3 and 4 are an adjacency pair in the form of a question and answer, butlines 1, 2, 5 and 6 are all partial utterances spoken by three diஸferent speakers and from which nosingle paraphrased sentence can emerge to capture the content. Given this level of fragmenting,3Of course discourse analysis refers to sentence fragments, but to the best of my knowledge, discourse itself isnot generally referred to as ‘fragmented’.74it is diஸஹ஭cult to say with any conஹ஭dence what the response in line 7 (spoken by a fourth speaker)might be responding to. Examples like this are not included in my analysis.Missing context Some discourses were missing context, so that although there were completesentences, the lack of surrounding information made it diஸஹ஭cult to say with any certainty whatthe responses were intending to respond to. A typical example is in 16, in which it is impossibleto tell what the speakers are discussing. There are four speakers, and there is mention of prices inline 2, a backpack in line 4, and “the idea” in line 5. What that idea is, and how it relates to pricesand backpacks, is unclear. Although line 5 does include ‘yeah’ and followup content, it comesimmediately afிer “Wow” and may be intended to respond to lines 2 or 3. In short, this exampleis missing too much information to draw any conclusions about usage, and it, and others like it,are excluded from the study.(16) Missing Context1. HODA஡KOTB: Yeah.2. SAVANNAH஡GUTHRIE: That’s the price and pretend to like it.3. CARSON஡DALY: I’ll take the backpack4. AL ROKER: Wow.5. SAVANNAH஡GUTHRIE: Yeah. I don’t know. But we asked our viewers at homewhat they thought of the idea.6. HODA஡KOTB: What did they say?7. SAVANNAH஡GUTHRIE: They’re split –8. HODA஡KOTB: Oh. COCABroadcast genre conventions As most of the corpora examples in COCA are from the genreof broadcast interviews, they re஺ாect certain conventions of the genre, and conventions of saluta-tions and break segues have been excluded from this study. An example of such a salutationsequence is in (17), in which a speaker is narrating a story in line 1, and the other two speakers,mindful of the time, respond in lines 2 and 3 in ways that are short and agreeable but invite nofollow-up from the original speaker. Line 4 begins with a response particle and agreeing fol-75lowup, but the speaker immediately thanks the speaker of line 1 and addresses the audience with‘you,’ directing them to further action,4 which essentially ends the discourse prematurely.(17) Salutations1. PETER VAN SANT: …So prosecutors believe because she has some wealth that she isa ஺ாight risk.2. VLADIMIR஡DUTHIERS: All right.3. GAYLE஡KING: Once again I’m intrigued. Very good tease.4. VLADIMIR஡DUTHIERS: Yeah, I’m intrigued. Peter, thank you very much. Youcan watch Peter’s full report, The Psychiatrist and the Selஹ஭e on 48 HOURS, that istomorrow night at ten, nine Central right here on CBS. COCADirect questions Examples which deviated from the template were not included. This in-cludes responses that were responding to overt questions that take the form of an interrogative,such as in (18.2).(18) Questions1. PETER SAGAL: And Melania decorated the White House to look like a satanist sexclub. Did you see this?2. LUKE BURBANK: Yeah. Somebody needs to leave some Eggo Waஸ஺ாes behind oneof those trees for Melania COCAThese excluded examples comprise a large portion of the corpora, especially COCA, and theywere excluded immediately and were therefore not counted towards my target number of 100of each response particle from each corpus source, for a total of 400 examples. These excludedconversations comprise the majority of exchanges and explain why in Table 3.1 over 75% of ‘yeah’responses were excluded from COCA, for example.Quizzes Another speciஹ஭c type of use for ‘yeah’ and ‘no’ is in quiz-type discourses, in whichSpeaker A poses a question to the other speaker(s) to determine whether they know the correctanswer. An example of a quiz-type discourse containing ‘yeah’ plus agreeing content is in (19).4That ‘you’ refers to the audience is not apparent from the example text, but it is a convention of the genre ofbroadcast inverviews, which frequently conclude by thanking the guest and directing the audience to some speciஹ஭caction.76(19) Quizzes1. OPHIRA EISENBERG: This is your last clue. According to the Hass Avocado Board,in 2016, Americans were expected to eat 278 million avocados during the week of whatmajor televised event?2. JASON MRAZ: That would be the Super Bowl.3. OPHIRA EISENBERG: Yeah, that’s right. Yep. COCALine 3 contains ‘yeah’ plus agreeing content, but given the context, the primary purpose ofthe response is not to enter the at-issue content in line 2 into the common ground, it is to conஹ஭rmthat the speaker of line 2 correctly answered the question posed in line 1. This will likely impactthe common ground by including not only the at-issue content but also the fact that Mr. Mrazanswered the question correctly.Backchanneling Backchanneling is used to signal continued attention while another speakerhas the ஺ாoor, and it is common particularly in the Fisher and Switchboard corpora. In (20),Speaker A uses ‘yeah’ and ‘is that right’ as backchannels while Speaker B continues to speak.(20) 1. B: i guess there’s the other side of the issue that uh there need to be facilities for pro-cessing all this stuஸf and a market for recyclable goods2. A: yeah3. B: and that was something they brought up on the show i listened to was uh you knowthere’s all kinds of you know recycled paper but you know nobody’s wanting to use it4. A: is that right5. B: you know how many people are using how many people do you know that userecycled paper in the oஸஹ஭ce6. A: yeah7. B: you know you can you can buy your your Moore’s computer forms for your com-puter paper or whatever you can buy it with regular paper or recycled and i’ll guaran-tee you in my building i haven’t seen recycled paper yet8. A: yeah9. B: so at the same time we’re we’re doing all this eஸfort to throw it a way and recycleit we ought to be working on the other end and and paying the extra dime on on adollar for that recycled stuஸf7710. A: i’ve always wondered why they haven’t taken some of these recycled plastics andmade them into like uh plastic boards to build a house with instead of making it outof wood lumber make it out of out of plastic boards LDCOther syntactic uses In addition to its use as a response particle, ‘no’ is also frequently usedas a modiஹ஭er, a use which was also excluded from the study. Examples of such use are collectedin (21); this list is by no means exhaustive.(21) no kidding no matterno show no jokeno way no oneThough ‘yeah’ is not used as a modiஹ஭er in the same way as ‘no’ is, it can nonetheless be ex-cluded on syntactic grounds, as in (22), where it serves as the subject of the sentence and is a directquote of another speaker. It therefore does not re஺ாect the speaker’s agreement or point of view.(22) “Yeah” was all she said.3.1.3 Distinguishing between agreeing and disagreeing contentA crucial part of assessing the corpus data is identifying whether followup content agrees or dis-agrees with the at-issue content of the triggering utterance, independent of the response particle.The clearest examples are (near) verbatim repititions of the at-issue content and claims that standin direct opposition to the at-issue content. Using the example5 of (23) as the triggering utteranceand (24) as examples of response followup content, the diஸference between the two becomes clear.(23) Utterance and at-issue contentUtterance: Game of Thrones is the best show ever made.at-issue content: Game of Thrones is the best (television) show ever made.QUDDoSGiT GoGR: Is Game of Thrones the best television show ever made?5The examples in this section are constructed so that I could create minimal sets based on tokens from thecorpora. The value is in ensuring an apples to apples comparison with as little contextual variation as possible as thecriteria for evaluating are explicated.78(24) Response followup content (what comes afிer the response particle)Utterance: Game of Thronॽ ॾ the best show ever made.Agreeing: It (Game of Thrones) really is the best show ever.Disagreeing: Game of Thrones is nowhere near the best show ever made.The confound is that, in natural language, hundreds of other responses are possible that willnot be so neatly categorized. In order to make this problem tractable, I looked to Clark andBrennan (1991) for guidance, determining that answers which took up the conversational thread,as it were, would be considered agreement, provided that agreement with the at-issue content is atleast an implicature of the response, as in the examples in (25). Such a conversational move couldrespond to the same QUD as the at-issue content, as line 1 does, or it could oஸfer an explanationwhy the at-issue content is true, as in line 2. Something that presupposes the truth of the at-issuecontent in the triggering utterance would also signal agreement, as in line 3. Lines 4 and 5 alsosignal agreement, albeit weaker than in lines 1-3; line 4 uses a hedging modiஹ஭er, and line 5 expressesacceptance of the claim, although not whole-hearted agreement.(25) Followup content signalling agreementTriggering Utterance: Game of Thrones is the best show ever made.1. take up the thread: Everything about it was just so good!2. explanation for truth: Well the writing was so much better than anything else.3. presuppose truth: Mad Men is a close second when it comes to general goodness.4. modify scope: It kinda is.5. evaluate and concede: I can see that.Similarly, disagreeing, or more accurately lack of agreeing, followup content can take manyforms as well, as shown in (26). A response can simply claim something diஸferent, as in line 1, orit can constrain the truth of the at-issue content as in line 2. By supporting the narrower claimthat Game of Thrones is the best fantasy show ever, the speaker declines to accept the truth of theat-issue content, that Game of Thrones is the best show ever, bar none. Line 3 displays a similarstrategy of disagreement, where the response makes no comment on the greatness of the showin question, claiming only knowledge of its popularity. Similarly, line 4 is ambivalent in that, ifbeing “very adult” is considered a good quality then it might signal agreement, but if not then thecomment signals disagreement. Line 5 fails to signal agreement by simply declining to commit.79These responses are insuஸஹ஭cient to demonstrate that both interlocutors have signalled agreementto the truth of the at-issue content.(26) Followup content signalling lack of agreementTriggering Utterance: Game of Thrones is the best show ever made.1. diஸferent claim: M*A*S*H* is the best show ever, but Game of Thrones is great.2. constrain claim: It (Game of Thrones) is certainly the best fantasy show ever.3. avoid agreement: I’ve heard it’s really popular.4. ambivalent comment: It’s very adult.5. decline to commit: I don’t really know.Many of these examples are not overtly disagreeing per se, but crucially they are not agreeing.Responses such as those in (26) do not signal that the speaker accepts the validity of the at-issuecontent suஸஹ஭cient to consider it as included in the common ground. For this reason, they areconsidered to be disagreeing.While the constructed examples about Game of Thrones are more or less easy to analyze,for the analysis of the corpus data we need a way to robustly categorize followup content as ei-ther agreeing or disagreeing. One way to operationalize this distinction is to consider the QUD.The QUDs in (27) illustrate a potential set of QUDs for the utterance, ranging from narrow towide and including a “presupposing” QUD, which includes the utterance’s at-issue content as apresupposition.(27) A sample of QUDs concerning Game of ThronesUtterance: Game of Thrones is the best show ever made.1. narrowest QUD (QUDDG): Is Game of Thrones the best show ever made?2. slightly wider QUD: Is Game of Thrones a high quality/entertaining televisionshow?The utterance in (27) directly answers the two QUDs listed. A related QUD, in (28), pre-supposes a positive answer to the domain goal QUD in (27) when it is answered.(28) Related QUD: Why is Game of Thrones the best show ever made? (This QUD presup-poses that Game of Thrones is the best show ever made.)80The exchange in (29) uses the response to answer a QUD from line 2 in (27), namely thenarrowest QUD, and this response is picking up the conversational thread suஸஹ஭cient to representagreement, consistent with the use of an explanation of truth to signal agreement ((25), line 2).(29) 1. α: Game of Thrones is the best show ever made.2. β: The writing, the cinematography, the casting, all of it’s just so perfectly done.The response in (29) does not answer the narrowest QUD (Is Game of Thrones the bestshow ever made?), but it does answer another QUD, (28) (Why is Game of Thrones the bestshow ever made?). This is one way of picking up the conversational thread, giving evidence thatpresupposes an agreeing answer to the previous QUD.An example of a disagreeing response is in (30), where there is not the same implicature ofagreement because of the criticism that the speaker introduces.(30) 1. α: Game of Thrones is the best show ever made.2. β: It is an amazing show, although the violence does get a bit gratuitous at times.It is not at all clear that the response in line 2 of (30) represents agreement to the at-issuecontent. Speaker β says the show is “amazing” but then critiques the “gratuitous” violence. Itmay still be the case that Speaker β agrees that Game of Thrones is the best show ever made, butthat is not clear from their response. The response in (30) does not answer any of the QUDs in(27); instead it raises a negative feature of the show, namely the “gratuitous” violence. Thereforeit must be interpreted as disagreement, because it is insuஸஹ஭cient to update the common groundwith the at-issue content of the triggering utterance.There are also examples in which the content of the response on its own would not be con-sidered suஸஹ஭cient to place the at-issue content into the common ground, but the intuition ofspeakers (such as myself and those I have discussed this with) is that the response does in factsignal agreement; to see such an example in action, consider (31)6.(31) 1. α: Game of Thrones is an outstanding show.2. β: Peter Dinklage is so amazing in everything he does.In a literal sense, someone who had no knowledge of Game of Thrones or Peter Dinklagecould not be expected to make the connection between these two statements and would neces-sarily conclude that β’s comment did not signal agreement. But those who are familiar with both6Peter Dinklage was one of the primary cast members of Game of Thrones and won an Emmy for his perfor-mance on the show.81the show and the actor would understand that the two statements are related, and their judge-ment would be that β’s comment does signal suஸஹ஭cient agreement to place the information inthe common ground. Correctly interpreting the response as signalling agreement requires thatthe listener(s) have suஸஹ஭cient pre-existing common ground with the speaker to see the relation-ship between the two statements. Speaker β signals agreement by repsonding to a broader QUDwhich relies on this pre-existing common ground; (32) illustrates these requirements.(32) Required information for a correct interpretation of (31)Required CG: Peter Dinklage portrayed a major protagonist on Game of Thrones.Broader QUD: Why is Game of Thrones an outstanding show? (This QUD presup-poses that Game of Thrones is in fact an outstanding show.)This is not to say that the common ground cannot be expanded any further; in (31), the pre-existing common ground includes the existence of the show and that it stars that actor. That itis the best show ever made is not in the pre-existing common ground; it is only entered into thecommon ground with β’s response in line 2.To continue with the example of Game of Thrones and (31), the preexisting common groundmust include the existence of the show and the actor’s role therein; the at-issue content concernsthe quality of the show, and that needs to be negotiated. That the at-issue content is not in thepreexisting common ground can be tested by β extending their turn to include information thatcontradicts the at-issue content, such as in (33).(33) 1. α: Game of Thrones is the best show ever made.2. β: Peter Dinklage is such an outstanding actor that he makes everything he’s in better.Which is good for Game of Thrones, because the rest of the cast is so abysmal thatPeter Dinklage is the only good thing about that show.Finally, it will be observed that there is no “middle option” between agreement and disagree-ment in coding of my data. This is because the question is essentially binary: Does the followupcontent signal suஸஹ஭cient agreement, without any additional information, such that the at-issuecontent may be understood to be accepted into the common ground? If the answer is no, thisdoes not necessarily mean that the information is excluded from the common ground forever; itsimply means that more discussion is required ஹ஭rst, discussion which will expand the commonground.823.1.4 Determining the question under discussionIdentifying the QUD for a given utterance is important because, in addition to supporting anunderstanding of whether the at-issue content enters the common ground, the QUD itself canbe a target for a response. However, identifying the QUD is not as straighforward as simplyselecting a question that is answered by a given utterance. By using the concepts discussed in Sec.2.2.1.2 of Domain Goal (Roberts, 2011) and Current Question (Simons et al., 2016), it is possibleto operationalize this variable. Operationalization begins with providing working deஹ஭nitions forboth terms in such a way that it is possible to evaluate clearly whether a given question meets thatdeஹ஭nition or not.(34) Operational definitions of types of Questions Under Discussion (QUDs)Domain Goal (DG): The narrowest QUD which can be answered by theutterance in question, and to which one other answeris possible; usually a yes/no question.Current Question (CG): A question to which a set of answers is possible, in-cluding the utterance in question and at least one al-ternative answer.State of the World QUD: The maximal question to which any utterance can pro-vide an answer; the set of all other QUDs.To illustrate these deஹ஭nitions in action, I will use the ஹ஭rst complete clause of Jane Austen’sPersuasion, edited to remove most adjuncts:(35) Opening of Persuasion: Sir Walter Elliot, of Kellynch Hall, in Somersetshire, was a manwho, for his own amusement, never took up any book but the Baronetage.Simplifying the sentence yields a single clause which identiஹ஭es the at-issue content.(36) Abridged opening of Persuasion: Sir Walter Elliot was a man who never took up any bookbut the Baronetage.Under the criteria for Domain Goals speciஹ஭ed in (34), the QUDDG for (36) is in (37).83(37) DGx = “Was Sir Walter Elliot a man who took up any book but the Baronetage?”= {p;¬p}, wherep = “Sir Walter Elliot was a man who takes up at least one book other than theBaronetage.”This is the narrowest, i.e. the most specifc, question to which (36) can provide an answer,satisfying the ஹ஭rst criterion for identifying the Domain Goal QUD. The set of possible answersincludes two members, p and ¬p, and that is enough to satisfy the second criterion. Taking theanswer provided in the “utterance” in (36), the answer to the QUDDG is¬p.The Current Question is less speciஹ஭c in the sense that there is not a binary set of answers, pand ¬p, but it is still a question to which the utterance in question can provide an answer. Asthe discussion in Sec. 2.2.1.2 highlighted, a given utterance can usually provide an answer to morethan one question, and all of these questions meet the deஹ஭nition of the Current Question. Aselection of Current Questions for (36) is in (38).(38) Current Questions for (36)CQ1:What book(s) did Sir Walter Elliot read?CQ2:What kind of man was Sir Walter Elliot?CQ1:Who only read the Baronetage?CQ4:Who was Sir Walter Elliot?This set of Current Questions is not exhaustive; they are generated because the at-issue con-tent of (36) provides one potential answer, in addition to other potential answers beyond thenegated at-issue content. For example, (39) oஸfers several answers to the fourth CQ in (38).(39) Potential answers for CQ: Who is Sir Walter Elliot?a. Sir Walter Elliot was a man who never took up any book but the Baronetage.b. Sir Walter Elliot was the father of Elizabeth, Anne and Mary.c. Sir Walter Elliot was a cash-strapped minor member of the nobility.d. Sir Walter Elliot as a widower.The importance of operationalizing the QUD is twofold: the QUD can contribute to theanalysis of whether or not the at-issue content has entered the common ground, and the QUDcan itself serve as a target for response particles. The bulk of this chapter, particularly Secs. 3.3and 3.5, will provide evidence to support these claims.84Figure 3.1: Flowchart for determining agreeing content3.1.5 Summarizing the methodologyApplying an analytical methodology to natural data is a complex but necessary task to ensure aconsistent analysis. The utterance generates the at-issue content and the QUD, including the setof Current Questions. The response generates the response particle and the followup content.These four components are the key ingredients for interpreting the discourse.The at-issue content is generally straightforward to determine, as it is the main thrust of theutterance (see Sec. 2.2.1.1 for further discussion), and in any event I have excluded unclear utter-ances from my study (see Sec. 3.1.2, particularly the discussion on Fragmented Discourse). Sec.3.1.3 describes the criteria for determining whether followup content is labeled ‘agreeing’ or ‘dis-agreeing’, and 3.1.4 explains how the QUD is determined. Fig. 3.1 brings all of these componentstogether in one procedural ஺ாowchart.85Table 3.2: Predicted appropriate responses of The Response Target HypothesisOutcome ‘yeah’ +agree‘no’ + agree ‘yeah’ +disagree‘no’ +disagree1 Accept AIC 3 7 7 72 Reject AIC 7 7 7 33 Accept Bel, Reject AIC 7 7 3 74 Accept QUD 7 7 3 75 Reject QUD 7 3 7 7Table 3.3: Distribution of Corpus examples, n=400‘yeah’ +agree‘no’ + agree ‘yeah’ +disagree‘no’ +disagree1 Accept AIC 132 69* 0 02 Reject AIC 0 0 0 953 Accept Bel, Reject AIC 0 0 32 04 Accept QUD 0 0 35 05 Reject QUD 0 37 0 0* ‘No’ plus agreeing followup content signals acceptance of the at-issue content whenthe triggering utterance has negation.3.2 An overview of the corpus dataThe Response Target Hypothesis made the predictions presented in Table 3.2, repeated fromTable 1.2 in Ch. 1. To see how the data in the corpora pattern in comparison with the ResponseTarget Hypothesis, let us look at the distribution of the examples from my extracted data set,re஺ாected in Table 3.3.The columns represent the four possible response combinations, the response particle plus(dis)agreeing followup content; the rows are what is entered into the common ground as a resultof the responses. The cells with checkmarks in 3.2 re஺ாect the predictions that the Response TargetHypothesis makes; these are the cells that are predicted not to be empty.7 The two most frequent7Rejecting belief while accepting the at-issue content is a logical possibility, but it is not predicted because of the86outcomes, that ‘yeah’ plus agree accepts the at-issue content and ‘no’ plus disagree rejects the at-issue content, are the predictions that most theories make regarding ‘yeah’ and ‘no’, re஺ாectingtheir most familiar use.The other three highlighted outcomes are the novel predictions of the Response Target Hy-pothesis. The data provides evidence that ‘yeah’ plus disagreeing followup content can acceptan interlocutor’s belief while rejecting the at-issue content and that speakers can both accept andreject the QUD based on the information already established in the common ground.The presentation of the data begins with non-paradoxical responses, Sec. 3.3, which is brokeninto three subsections. The ஹ஭rst, Sec. 3.3.1, presents instances of ‘yeah’ plus agreeing content,which are accepting the at-issue content of the triggering utterance; this section corresponds tothe upper lefி cell in Table 3.3. The second subsection, Sec. 3.3.2, looks at the data correspondingwith the third cell of the ஹ஭rst row of Table 3.3, where ‘no’ accepts the at-issue content of thetriggering utterance because it includes negation. The third subsection, Sec. 3.3.3, discusses ‘no’with disagreeing content and corresponds to the second row on the far right column in Table 3.3.The next section, Sec. 3.4, presents data of accepting belief and rejecting at-issue content withthe use of ‘yeah’ plus disagreeing content; this is one of the novel predictions of the ResponseTarget Hypothesis, and there are 32 instances in Table 3.3. As the rejection of belief and acceptanceof the at-issue content is unattested in the tokens used in this study, no section of such data canbe included for that outcome.The ஹ஭nal section of data, Sec. 3.5, discusses responses which target the QUD and is dividedinto two subsections to present data where the QUD is itself a target of the response. The ஹ஭rst,Sec. 3.5.1, shows ‘yeah’ plus disagreeing content signalling acceptance of the QUD, for whichthere were 35 examples in the data set. The second section, Sec. 3.5.2, shows how ‘no’ plus agreeingcontent is used to reject the QUD, for which there were 37 examples in the data set.Table 3.4 summarizes the presentation of the data within the balance of this chapter. Thistable is repeated at the beginning of each of the sections which are included in it, with the relevantrow highlighted.Finally, for each data point below, a breakdown will follow which clearly identiஹ஭es the at-issuecontent, QUD, belief, response particle and followup content, with colored text correspondingto the original evidence and taking into consideration the context of the utterance, especially thespeaker’s utterance before the at-issue content. The QUD is the narrowest QUD available, andwhere a broader QUD is needed, one is provided. The QUDs provided are not exhaustive; eachdata point can answer other QUDs as well. What is provided is only what is necessary for theconstraints against rejecting another person’s mental state, about which a speaker has no access. Rejecting another’sbelief is also not attested in the corpora tokens. Therefore, for the sake of clarity, that row is not present in the table.87Table 3.4: Summary of corpus data and discussion sectionsOutcome Response Count Sec.Targeting only at-issue contentAccept AIC ‘yeah’ + agree 132 3.3.1(Neg) Accept AIC ‘no’ + agree 69 3.3.2Reject AIC ‘no’ + disagree 95 3.3.3Targeting beliefAccept bel, reject AIC ‘yeah’ + disagree 32 3.4Targeting QUDAccept QUD ‘yeah’ + disagree 35 3.5.1Reject QUD ‘no’ + agree 37 3.5.2analysis. This breakdown spells out all of these features based on what is linguistically presentand with no further interpretation or analysis. No polarity or common ground information isadded to this breakdown, and no abbreviations or placeholder variables are used. This is to makethe data maximally clear for presenting an analysis of how the responses target the components,without imposing any assumptions concerning the relationship between the at-issue content,beliefs and QUD.3.3 Non-paradoxical responses targeting only at-issue contentNon-paradoxical responses are those in which the response particle and followup content are inagreement. Responses of ‘yeah’ will be followed by followup content such as ‘it’s true’, ‘you’reright’, ‘I agree’ or a repetition of the utterance or at-issue content; all of these responses, indepen-dently and in tandem, signal agreement. Responses of ‘no’ will be followed by followup contentsuch as ‘that’s not right’, ‘I don’t think so’ or a repetition of the utterance or at-issue content withnegation added, all of which signal disagreement.The impact of non-paradoxical responses on the common ground is predicted to correspondto the polarity of the response; positive polarity responses will update the common ground, andnegative polarity responses will not. However, under certain conditions, these responses can havea diஸferent impact on the common ground, in particular if the triggering utterance has negation.88In these cases of negative concord, the absolute polarity is [−], but then the relative polarity is[agree].3.3.1 ‘Yeah’ responses accepting at-issue contentTable 3.5: Accepting at-issue contentwith ‘yeah’ + agree highlighted (Table 3.4 repeated)Outcome Response # Sec. Outcome Response # Sec.Targeting only at-issue content Targeting beliefAccept AIC ‘yeah’ + agree 132 3.3.1 Accept bel not AIC ‘yeah’ + disagree 32 3.4(Neg) Accept AIC ‘no’ + agree 69 3.3.2 Targeting QUDReject AIC ‘no’ + disagree 95 3.3.3 Accept QUD ‘yeah’ + disagree 35 3.5.1Reject QUD ‘no’ + agree 37 3.5.2The examples in this section are non-paradoxical and represent the most frequent use of‘yeah’ and agreeing followup content, which signals acceptance of the at-issue content into thecommon ground (Pope, 1972; Ginzburg, 1995a; Farkas and Bruce, 2010, and this current study).The corpus data set I am using includes 132 examples of this type.3.3.1.1 Direct agreement‘Yeah’ plus agreeing content signals agreement with the previous utterance, as in (40), from theLDC. The token is taken from a larger discourse about special interest groups in small towns.Speaker A makes an abstract example of construction interests building a swimming pool, and“it” refers to this hypothetical pool. Also of note is the fact that “scream” is likely not meant tobe taken literally here; rather it likely is a hyperbolic reference to anger or frustration.(40) 1. A: you know and one you can you can only build it in one place you know and nomatter where you build it somebody else is going to scream well you didn’t build oneover here2. B: yeah that’s true unfair or something yeah yeah LDC(40’) At-issue content: No matter where you build it somebody else is going to scream…QUD: Will a building in any location cause someone to “scream” (be un-happy)?89Belief: Speaker A believes a building in any location will cause someone to“scream” (be unhappy)Response particle: YeahFollowup content: ThatGiI’s true.Another straightforward example is (41), in which a simple response of ‘yeah’ plus agreeingfollowup content is enough to signal that the at-issue content introduced in the previous utter-ance has been accepted into the common ground by both speakers. In the ஹ஭nal clause, ‘it’ isreferring to the diஸferences in ownership between dogs and cats as established previously in theturn, when Speaker A is discussing the diஸferences between dogs and cats. For the purposes ofthis dissertation, (40) and (41) have the added advantage of most closely matching the templateused in the experimental data in Ch. 4.(41) 1. A: dogs are real high maintenance you got to take them for walks and you’ve got topay a lot you know you need to pay attention to cats and everything but it’s not quitethe same thing um and um2. B: yeah that’s true LDC(41’) At-issue content: It’sowTKXshiVoLJoMsvs:IGts not the same thingQUD: Is itowTKXshiVoLJoMsvs:IGts the same thing?Belief: ItowTKXshiVoLJoMsvs:IGts is not the same thing.Response particle: YeahFollowup content: That’sGiI true.The ஹ஭nal example from the corpora included here shows how ‘yeah’ plus agreeing followupcontent can work with negation present. Line 1 in (42) includes the proposition “I never thoughta clutch was disposable,” in which a dependent clause “(that) a clutch was disposable” is the objectof the matrix clause. The agreeing followup content repeats this sentiment. While this exampledoes include negation in the triggering utterance, the response is nonetheless consistent with theanalysis of ‘yeah’ and agreeing followup content; the followup content includes negation as well,signalling that the at-issue content, complete with negation, is entered into the common ground.90(42) 1. A: and they just said well you know clutches are disposable and i said since when,brake pads are disposable you know we know that but i never thought a clutch wasdisposable2. B: yeah i wouldn’t have thought so either LDC(42’) At-issue content: ISVKGQKX A never thought a clutch was disposableQUD: Are clutches disposable?Belief: Speaker A did not believe that clutches were disposable (and pre-sumably now believes that they are).Response particle: YeahFollowup content: ISVKGQKX B wouldn’t have thought soAIC either (but presumably nowdoes)3.3.1.2 Entailing agreementThe examples in this section all include ‘yeah’, and they all seem to signal agreement. However,the agreement is not as absolute as in the previous set of examples, in which the followup contentclearly answers the domain goal QUD in the aஸஹ஭rmative. The examples below signal agreementby taking up the thread of the conversation, responding to a broader QUD so that agreement tothe at-issue content is entailed.In (43), line 2 uses ‘yeah’ plus agreeing followup content, although there are ஹ஭llers in betweenthe response particle and the content. The use of “I mean” in line 2 is not used to deஹ஭ne a term,but rather to pause the discourse before delivering a potentially controversial or diஸஹ஭cult answer.This is a common use of hedges or ஹ஭llers and is not inconsistent with the Response Target Hy-pothesis or the template used to constrain the data. It is also important to note that “you” in line1 is not impersonal; it refers speciஹ஭cally to the interlocutor, Jamie Shupe.(43) 1. UNIDENTIFIED SPEAKER: …but this was the late 1970s, so you took a girl to thequeen of hearts dance, and drove a big-wheel Camaro , and cut tobacco and [you] feltnothing at all like a real boy.2. JAMIE SHUPE: Yeah, I mean, I just - I’ve never been connected to identifying as amale. I’ve never agreed that I was a male. And yeah, I just had - I had no connectionto masculinity. COCA91(43’) At-issue content: [Jamie Shupe] felt nothing like a real boyQUD: Did JS feel like a boy?Belief: Speaker believes that JS did not feel like a boy.Response particle: yeahFollowup content: JS has never been connected to identifying as a maleExample (44)8 presents ‘yeah’ apparently responding to a question, but the question shouldbe understood as rhetorical instead of literal, insofar as no answer is expected or required. Syntac-tically the question is embedded as a quotation in another sentence. The followup content afிer‘yeah’ also looks like questions, and syntactically they are questions. But again they are intendedrhetorically as a re஺ாection of the speaker’s mental state; no response is expected or required. Line 1provides evidence of that in saying that the speakers had to “reality check with each other,” mean-ing that the experience they are describing felt unreal; in this situation, rhetorical questions like“did it happen?” and “is this a dream?” are appropriate.(44) 1. LIANA HEDGE: We had to reality check with each other…2. TAMARYN YODER: Yeah.3. LIANA HEDGE: – because you’re, like , did it happen or did it not?4. TAMARYN YODER: Yeah, is this a dream? What’s going on?5. LIANA HEDGE: You feel like, all of a sudden, somebody dropped you in the middleof hell and you can’t ஹ஭nd your way out. LDC(44’) At-issue content: We had to reality check with each other because youiSVKXs:’re like,RhKtoXiIGR QuKstioT[did it happen or did it not?]QUD: Did the experience described by Liana Hedge have the quality ofbeing unreal?Belief: Liana Hedge believes that the experience in question had the qual-ity of being unreal.Response particle: Yeah8This example includes two ‘yeah’s, but the ஹ஭rst one, in line 2, is an independent response or perhaps a backchan-nel with no followup and therefore has not been considered for the purposes of this dissertation.92Followup content: RhKtoXiIGR QuKstioTs[is this a dream? What’s going on?]Given the rhetorical nature of the questions in line 4, afிer ‘yeah’, these can be consideredas agreeing content. They echo the rhetorical question9 in line 3, which introduces the at-issuecontent, ‘you [an experiencer of event] question whether it [the experience] happened,’ in thatthey rhetorically ask similar questions. Ms. Yoder in line 4 is not trying to ascertain if she and Ms.Hedge are at that moment experiencing a literal dream state, nor is she requesting clariஹ஭cationabout the current circumstances. Instead she is using rhetorical questions to provide informationabout the surreal nature of the event in question, which agrees with the assessment of LH.By presupposing the at-issue content, the followup content in (45) signals suஸஹ஭cient accep-tance of the at-issue content to enter it into the common ground.(45) Context: This exchange is decribing a situation that the Unidentiஹ஭ed Woman (Speaker A)experienced at work1. UNIDENTIFIED WOMAN (SPEAKER A): But what happened was a few weekslater, I had noticed that he was on my ஺ாoor speciஹ஭cally, right outside our oஸஹ஭ce everyday instead of three times a week.2. MELISSA BLOCK: Wow. So he was there more than he had been before.3. UNIDENTIFIED WOMAN (SPEAKER A): Yeah. And so my perception of it, eventhough I doubt that this is what went into it - but my perception was like, oh, this feelspunitive just for reporting something (laughter). COCA(45’) At-issue content: HeMGTX was there more ofிen than heX had been before.QUD: Was Man X in the vicinity of Speaker A more than before?Belief: Melissa Block believes that Man X was there [in the vicinity of SpeakerA] more than he had been before.Response particle: YeahFollowup content: … mySVKGQKXA perception of itAIC was that itAIC was punitive…9That the question is not literal is clear by the quotitive “you’re like” which introduces it; no literal answer isrequired.93Speaker A in line 1 says “…he was on my ஺ாoor… every day instead of three times a week.”In line 2, the other speaker says, “…he was there more than he had been before.” Speaker A uses“yeah” to agree with the p in line 2, because it, in eஸfect, oஸfers the same information as the at-issuecontent that Speaker A introduced in line 1. Because the at-issue content of line 1 is mirrored inline 2, it is natural that the speaker of line 1 would signal agreement with “yeah” in line 3. More tothe point, the followup signals agreement through presupposing the at-issue content by referringto it with an anaphoric pronoun ‘it.’The small exchange in (45) is also an example of least collaborative eஸfort and the creation ofcommon ground, in which Speaker A introduces a description of a phenomenon, namely theincreased presence of the unnamed ‘he,’ and the explanation includes extra information aboutlocations. Ms. Block in line 2 eliminates the information about the locations, which may rea-sonably be presupposed given the setting of the event. She distills the at-issue content from line1 into line 2, and Speaker A agrees to enter it into the common ground. The followup contentsignals that the information is now in the common ground, as Speaker A refers to “it” and “this”in line 3, which refer to the information captured in line 2.Finally, consider (46), in which the at-issue content in the triggering utterance is ‘you canrelate to some of what she says,’ and the followup content is ‘she is awesome.’(46) Context: This is an interview on a news broadcast in which the two speakers are discussingJudaline Cassidy, referred to here as ‘she.’ The previous conversation had identiஹ஭ed Cas-sidy’s accomplishments as an advocate for women in trades and the challenges that Cassidyand Ogles have confronted as women in trades.1. MEGYN KELLY: So, you two have that in common. I’m sure you can relate. I – I’msure you can relate to some of what she says.2. MALA OGLES: Yeah. She is awesome. Way to go.3. MEGYN KELLY: Yes. COCA(46’) At-issue content: You [Mala Ogles] can relate to some of what she [Judaline Cassidy]saysQUD: Can MO relate to some of what JC says?Belief: Megyn Kelly believes that MO can relate to some of what JC says.Response particle: YeahFollowup content: SheJC is awesome.94In the strictest sense, the followup content cannot be said to signal agreement to the at-issuecontent, for the simple reason that, in their most literal sense, they are about diஸferent things;the at-issue content is about the relatability of what JC says, and the followup content is about aquality of JC herself. We can understand the response as agreement, however, because it respondsto a broader QUD, namely ‘Does MO think that JC is awesome?’ By taking up the thread of thediscussion in this way, through response to a broader QUD which includes the narrower QUD,MO signals acceptance of the at-issue content into the common ground.Natural conversations are not always clear, and interlocutors may signal agreement in moresubtle or hedged ways, as in examples (47) and (49). In the ஹ஭rst of these examples, (47), SpeakerA hedges their agreement by saying, “I could see …”(47) Context: two speakers are discussing pets in general and rats in particular1. B: and then she grew to be you know i had pictures of her when she would sit on myhand and then she grew to be pretty big you know like a pound or something i don’tknow how much and i had her for over two years and she was very aஸfectionate… shewould you know crawl on me and she would sit like on my neck or my shoulder whilei was working and things like that yeah much more than you would think2. A: yeah i mean you know if you get them young and everything before they go kindof nuts so yeah rats are not my favorite animals in the world but i could see gettingone from birth and everything LDC(47’) At-issue content: She (the pet rat) was very aஸfectionate, more than youiSVKXsoTGR wouldthink.QUD: Was Speaker B’s rat an aஸfectionate pet?Belief: Speaker B believes that her rat was an aஸfectionate pet.Response particle: YeahFollowup content: Rats are not mySVKGQKX A favorite animals, but ISVKGQKX A could seegetting one [as a pet] from birth…This hedged followup content signals agreement because it responds to a broader QUD, theanswer to which may presuppose an aஸஹ஭rmative answer to the narrowest QUD, the Domain GoalQUD, as shown in (48)95(48) At-issue content of (47): She (the speaker’s pet rat) was very aஸfectionate.QUDDG of (47): Was the speaker’s rat an aஸfectional pet?QUDCQ of (47): Are rats aஸfectionate pets?If the answer to the QUDCQ is positive, then that at least creates the implicature that theanswer to the QUDDG is also positive.Example (49) signals agreement through explanation; rather than simply agreeing with theat-issue content, Speaker A oஸfers information which speaks to a broader QUD.(49) 1. B: oஸfered that our forefathers wouldn’t have even crossed their brains to have ex-pected you know a dishwasher or a disposal or uh uh track lighting or garage dooropener you know those ki- the fancy bathrooms and stuஸf and yet the sturdiness ofthem doesn’t a- al- doesn’t always measure up2. A: yeah i think they’re they’re trying to lower costs by cheapening in a lot of areasLDC(49’) At-issue content: The sturdiness of [modern homes] doesn’t measure up [to the stan-dards of our forefathers]QUD: Does the sturdiness of modern homes measure up [to the standardsof our forefathers]?Belief: Speaker B believes that the sturdiness of modern homes does notmeasure upResponse particle: yeahFollowup content: ISVKGQKX A thinks they [builders] are trying to lower costs by cheap-ening in a lot of areasThe followup content provides an answer to a broader QUD, identiஹ஭ed as the Current Ques-tion in (50). The answer to why modern homes are not up to previous standards entails thatmodern homes are not up to previous standards. It is important to recognize that the broaderQUD could not be included in the set of questions comprising the original QUD associatedwith the triggering utterance; but the answering to this broader QUD entails agreement withthe narrower QUD, by which Speaker A is signalling their agreement.96(50) At-issue content of (49): The sturdiness of [modern homes] doesn’t measure up [to thestandards of our forefathers]QUDDG of (49): Does the sturdiness of modern homes measure up to the stan-dards of our forefathers?QUDCQ of (49): Why don’t modern homes meet the standards of previous gen-erations?Response followup content:ISVKGQKX A thinks they [builders] are trying to lower costs by cheap-ening in a lot of areas3.3.2 Agreeing with negative polarityTable 3.6: Accepting at-issue content with ‘no’ + agree highlighted (Table 3.4 repeated)Outcome Response # Sec. Outcome Response # Sec.Targeting only at-issue content Targeting beliefAccept AIC ‘yeah’ + agree 132 3.3.1 Accept bel not AIC ‘yeah’ + disagree 32 3.4(Neg) Accept AIC ‘no’ + agree 69 3.3.2 Targeting QUDReject AIC ‘no’ + disagree 95 3.3.3 Accept QUD ‘yeah’ + disagree 35 3.5.1Reject QUD ‘no’ + agree 37 3.5.2The examples in this section contain negation in the triggering utterance, and the ‘no’ in theresponse agrees with this negation; it is negative concord. The agreeing followup content alsocontains negation and also agrees in absolute polarity with the triggering utterance negation.To illustrate the point, the followup content in the examples in this section is almost a ver-batim repitition of the triggering utterance, an unambiguous signal that the followup contentagrees with the at-issue content. Consider (51):(51) 1. A: well i guess it wasn’t a situa- i mean i guess the mother wasn’t really asked to to lieanyway i guess it was you know2. B: no she wasn’t asked to lie mhm she just was asked um what they were just sayingyou know um what how did she feel about it and she said that her daughter they werenot going to put up any bail and her daughter would just have to um suஸfer the con-sequences97(51’) At-issue content: The mother wasn’t really asked to to lieQUD: Was the mother not asked to lie?Belief: Speaker A believes the mother was not asked to lieResponse particle: noFollowup content: she wasn’t asked to lieThe last full clause in the utterance in line 1 is “the mother wasn’t really asked to […] lie,”which contains negation in the form of the contracted “was not.” The use of negation changesthe at-issue content’s absolute polarity to negative; because the absolute polarity of the responseis also negative, the relative polarity is [agree] (Roelofsen and Farkas, 2015). A stronger aஸஹ஭rma-tion of the at-issue content is the nearly exact repetition of the at-issue content afிer the utterance.In line 2 B says “she [the mother] wasn’t asked to lie.” This agreeing followup content is itselffollowed by a signal of agreement, namely “mhm,” which is used conversationally to signal agree-ment (Tolins and Fox Tree, 2014).Similarly, (52) shows ‘no’ being used to respond to an utterance which contains negation.The followup content agrees with the at-issue content contained in the initial utterance, eventhough it is not quite so verbatim as in (51).10(52) Peter Sagal is interviewing the astronaut Scott Kelly about Kelly’s recent stay on the Inter-national Space Station.1. PETER஡SAGAL: You had cable. You watched CNN all day.2. SCOTT஡KELLY: Yeah, we had CNN on while we were working. We weren’t, like, justwatching TV all day.3. PETER஡SAGAL: No, the astronauts don’t do that. The president [Donald Trump]does that. The astronauts have a job.(52’) At-issue content: WeGstXoTGuts weren’t just watching TV all day.QUD: Were the astronauts not just watching TV all day?Belief: SK believes the astronauts (himself included) werenot just watchingTV all day.10Example (52) also includes a response with ‘yeah’ and followup content in line 2; this response is discussed inSection 3.4.98Response particle: NoFollowup content: The astronauts don’t do thatwGtIh TV GRR JGy.In line 3 Peter Sagal responds to the at-issue content from line 2, “We [the astronauts] weren’tjust watching TV all day.” As in (51), the presence of negation licenses a ‘no’ response that infact signals agreement with the at-issue content. The followup content agrees with the at-issuecontent, as “that” refers to the event of astronauts watching TV all day, which is marked withsentential negation in the triggering utterance in line 2. The result is that the at-issue content“[Astronauts] were not watching TV all day.” is placed in the common ground between Sagaland Kelly, as both have signalled their agreement with this proposition.The upshot from these examples is that ‘no’ plus agreeing content11 can signal that inter-locutors agree to the truth of a statement suஸஹ஭cient to place the at-issue content in the commonground, provided that the original utterance contains negation. This is of course negative con-cord. Of the 69 instances of ‘no’ plus agreeing content signalling agreement with the at-issuecontent, every one of them contains negation in both the trigger and the followup content. Con-sider (53).(53) 1. B: the big ten didn’t fair too well in the tournament2. A: no they sure didn’t LDC(53’) At-issue content: The Big Ten didn’t fare too well in the tournament.QUD: Did the Big Ten not fare too well in the tournament?Belief: Speaker B believes the Big Ten did not fare too well in the tourna-mentResponse particle: NoFollowup content: theyBiM TKT sure didn’tThe followup content in A’s response can only be agreeing, as it is almost identical to theat-issue content when the elided predicate is included, which is shown in (54).11For a discussion of the categorization of “agreeing” and “disagreeing” content, see Sec. 3.1.399(54) Followup content in (53): [[they (the Big Ten teams) [did [ not [fare too well ]]]]]These examples support a conclusion that ‘no’ + agreeing followup content is able to signalacceptance of the at-issue content into the common ground, and that such a use is triggered bythe presence of sentential negation in the triggering utterance.3.3.3 ‘No’ responses rejecting at-issue contentTable 3.7: Rejecting at-issue content with ‘no’ + disagree highlighted (Table 3.4 repeated)Outcome Response # Sec. Outcome Response # Sec.Targeting only at-issue content Targeting beliefAccept AIC ‘yeah’ + agree 132 3.3.1 Accept bel not AIC ‘yeah’ + disagree 32 3.4(Neg) Accept AIC ‘no’ + agree 69 3.3.2 Targeting QUDReject AIC ‘no’ + disagree 95 3.3.3 Accept QUD ‘yeah’ + disagree 35 3.5.1Reject QUD ‘no’ + agree 37 3.5.2Responses with ‘no’ and disagreeing followup signal that a speaker rejects the at-issue contentasserted by another speaker. This combination is quite common, accounting for 95 out of 400examples in my extracted corpus.In the analysis of Farkas and Bruce (2010), rejecting the at-issue content results in the commonground remaining unchanged by the immediate rejection (though further update is possible).Under Kri஺஽a (2015), the common ground is not updated to include the at-issue content but itdoes at least record the fact of the exchange, that Speaker α said x, and Speaker β disagreed. In (55),Kurtz’s utterance contains the at-issue content “Mueller did the right thing,” which Hemingwayrejects with both the response particle and the followup content in line 2.(55) 1. KURTZ: OK. Robert Mueller did the right thing by taking this agent oஸf the investi-gation.2. HEMINGWAY: No, he did not do the right thing because actually congressional in-vestigators have been asking for months what happened there. COCA(55’) At-issue content: RM did the right thing by taking this agent oஸf the investigation.QUD: Did RM do the right thing by taking the agent oஸf the investigation?Belief: Kurtz believes that RM did the right thing by taking this agent oஸfthe investigation.100Response particle: NoFollowup content: heRM did not do the right thingKurtz may still hold his original belief, but the response in line 2 has rejected the at-issue con-tent from inclusion in the common ground, and it has also not signaled any kind of acceptanceinto the common ground of Kurtz’s belief in the at-issue content.The exchange in (56) is from a morning chat show, and it shows an example of ‘no’ plusdisagreeing followup content rejecting the at-issue content.12(56) 1. KATHIE LEE GIFFORD: And I heard that this morning, so I said, (unintelligible)I’m going to go commando.2. HODA KOTB: No, you did not.3. KATHIE LEE GIFFORD: I’m commando right in the very moment.4. HODA KOTB: No, you are not.5. KATHIE LEE GIFFORD: I am too. And I likey.6. HODA KOTB: No, you are not. COCA(56’) At-issue content: IKLG am commando right in the very momentQUD: Is KLG commando at the time of utterance?Belief: KLG believes that she is “commando”.Response particle: NoFollowup content: youKLG are notThe exchange does not result in the update of the common ground with the at-issue content,because the speakers do not mutually agree on this information. Under the Table model of Farkasand Bruce (2010), the disagreement in (56) would create a “crisis” which could only be resolvedby further discourse. In these several lines of discourse, the disagreement—and “crisis”—persistswith no resolution.Rejecting the truth of the at-issue content does not require that it be restated with negation,as happens in (55) and (56). The implication in (57) line 6, that liberal arts is an appropriate course12“Going commando” is a colloquialism meaning that the speaker is not wearing underwear.101for those without a profession in mind, disagrees with the at-issue content that Speaker A assertsin line 5, that “he [Speaker B’s son] must have a profession in mind.”(57) 1. A: okay he did where’d he decide to go2. B: um to Williams College in Massachusetts3. A: uh-huh sure i’m familiar with it4. B: and that he was he was uh trying to decide between University of Pennsylvania andWilliams and it was a very diஸஹ஭cult choice and uh5. A: and he well he must know is he interested in law or medicine he must have a deஹ஭niteprofession in mind6. B: no but that’s one of the reasons why he chose Williams that it has solid liberal arts7. A: oh okay COCA(57’) At-issue content: he [Speaker B’s son] must have a deஹ஭nite profession in mindQUD: Must [Speaker B’s son] have a deஹ஭nite profession in mind?Belief: Speaker A believes that [Speaker B’s son] must have a deஹ஭nite pro-fession in mind.Response particle: NoFollowup content: ThatsoRiJ RiHKXGR GXts is one of the reasons why he [Speaker B’s son]chose WilliamsSpeaker B rejects the at-issue content with no and disagreeing followup content, and the com-mon ground is not updated to inlcude the proposition that he must have ‘a deஹ஭nite professionin mind’ afிer line 6.3.4 Accepting belief and rejecting at-issue contentOne of the core predictions of the Response Target Hypothesis is that paradoxical responses cansimultaneously accept a speaker’s belief while rejecting the information itself as false. This pre-diction is supported with the presence of 32 examples of this type from the extracted corpus.102Table 3.8: Accepting belief and rejecting at-issue content with ‘yeah’ + disagree (Table 3.4 re-peated)Outcome Response # Sec. Outcome Response # Sec.Targeting only at-issue content Targeting beliefAccept AIC ‘yeah’ + agree 132 3.3.1 Accept bel not AIC ‘yeah’ + disagree 32 3.4(Neg) Accept AIC ‘no’ + agree 69 3.3.2 Targeting QUDReject AIC ‘no’ + disagree 95 3.3.3 Accept QUD ‘yeah’ + disagree 35 3.5.1Reject QUD ‘no’ + agree 37 3.5.2Example (58)13 includes ‘yeah,’ where ‘yeah’ plus the disagreeing followup is used to signal anaceptance of belief without accepting the at-issue content as true.(58) Peter Sagal is interviewing the astronaut Scott Kelly about Kelly’s recent stay on the Inter-national Space Station.1. PETER஡SAGAL: You had cable. You watched CNN all day.2. SCOTT஡KELLY: Yeah, we had CNN on while we were working. We weren’t, like,just watching TV all day.3. PETER஡SAGAL: No, the astronauts don’t do that. The president [Donald Trump]does that. The astronauts have a job. COCA(58’) At-issue content: You [the astronauts] watched CNN all dayQUD: Did the astronauts watch CNN all day?Belief: PS believes that the astronauts watched CNN all dayResponse particle: YeahFollowup content: We [the astronauts] had CNN on while we were working.This example highlights that beliefs are also time sensitive, as Sagal’s response in line 3 is in-consistent with his stated belief in line 1. This requires that a belief be indexed to a speaker and amoment, as in (59).13This example was also discussed above as (52) in this chapter.103(59) Indexing beliefsIndexes: Belief(speaker, p, time)From (58): Belief(Peter Sagal, p=astronauts watch CNN all day, utterance time of line 1)The followup content disagrees because watching CNN is not part of the work of astronauts;therefore if they were working, then they were not “watching” CNN. It is common, however, forpeople to have music or TV on as background noise while they work.Line 1 contains Sagal’s utterance, with the at-issue content of “You [the astronauts on theInternational Space Station] watched CNN all day.” The response in line 2 begins with ‘yeah’but then oஸfers a correction which also responds to the QUD established in line 1.(60) QUD and answers in (58)QUD: Did the astronauts on the ISS watch CNN all day?Sagal’s answer: Yes—he asserts this (watching CNN all day) in line 1.Kelly’s answer: No—he denies this (watching CNN all day) in line 2.The followup content in line 2, “we had CNN on while we were working” is a diஸferent asser-tion than the at-issue content in line 1; Kelly further clariஹ஭es by explicitly denying Sagal’s assertion,namely that the astronauts were “watching” CNN.Kelly introduces his response in line 2 with ‘yeah’ to indicate an acknowledgement of Sagal’s(mistaken) belief as expressed in line 1. Such an understanding is supported by an understandingof where the expertise resides and reasonable assumptions concerning TV habits. The expertiseis on the side of Kelly, who resided at the ISS at the time in question; as such, Sagal’s assertion canonly represent his belief in information he’s received, he cannot verify this information himself.Kelly accepts that Sagal believes this, but then rejects the associated at-issue content as being false.That the at-issue content does not enter into the common ground is evident from Sagal’s ஹ஭nalutterance, which agrees with Kelly’s assertion in line 2 that astronoauts don’t watch TV all day.A similar expression and acceptance of belief is in (61), where Speaker A bases their belief ontheir understanding of Texas as being hot year round. This belief is again rooted in their lack ofexpertise and their reliance on general knowledge and assumptions.(61) Two speakers are discussing climate control in Texas homes1. A: well i would imagine all you need is just air-conditioning2. B: yeah we we have heat and some have air-conditioning units i i i have an all electrichouse but uh it’s ஹ஭fிy ஹ஭fிy LDC104(61’) At-issue content: All you [impersonal] need [in Texas homes] is just air-conditioningQUD: Is air-conditioning all you [impersonal] need [in Texas homes]?Belief: Speaker A believes that all that is needed [in Texas homes] is air-conditioningResponse particle: YeahFollowup content: We [Texans] have heat and some have air conditioningThe followup content includes two clauses conjoined by “and,” one of which oஸfers a personalexperience which is at odds with the at-issue content, not all and the other agrees with the at-issuecontent in a reduced way (some have air conditioning).The response contains ‘yeah’ and followup content that is incompatible with the at-issue con-tent in that it makes a claim that cannot be true if the at-issue content is true. If all Texans needis air conditioning, then it cannot be the case that “it’s ஹ஭fிy ஹ஭fிy,” which Speaker B includes intheir turn. In order for the response not to be paradoxical, the two components must be target-ing diஸferent types of propositions contained in the original utterance, and because the followupcontent contradicts the at-issue content, it must be the case that ‘yeah’ targets something otherthan the at-issue content for inclusion into the common ground. Given that (61) line 1 also re஺ாectsthe belief of Speaker A, ‘yeah’ can felicitously accept this belief into the common ground.3.5 Targeting the question under discussion (QUD)The data to this point has illustrated how responses target the at-issue content and the interlocu-tor’s belief in the at-issue content, both of which can be entered into the common ground. Butthis does not account for other combinations found in natural language. This section will showhow ‘yeah’ and ‘no’ can target the QUD without necessarily answering it. In the case of ‘yeah’,the followup content is not incompatible with the at-issue content, nor does it signal agreementto the at-issue content suஸஹ஭cient to place it into the common ground. In the terminology ofFarkas and Bruce (2010), the stack remains unpopped. In these cases, ‘yeah’ is used to signal thatthe QUD is appropriate and valid for discussion, as there is not currently an answer in the com-mon ground. In contrast, ‘no’ is indicating that the question is either invalid because there isalready an answer in the common ground, or it is irrelevant to the discussion in the view of theresponding speaker. The ஹ஭rst subsection will explore the use of ‘yeah’ to accept the QUD, and105the second section will explore the use of ‘no’ to reject the QUD, including the two reasons forrejection.3.5.1 Accepting the QUDTable 3.9: Accepting the QUD with ‘yeah’ + disagree highlighted(Table 3.4 repeated)Outcome Response # Sec. Outcome Response # Sec.Targeting only at-issue content Targeting beliefAccept AIC ‘yeah’ + agree 132 3.3.1 Accept bel not AIC ‘yeah’ + disagree 32 3.4(Neg) Accept AIC ‘no’ + agree 69 3.3.2 Targeting QUDReject AIC ‘no’ + disagree 95 3.3.3 Accept QUD ‘yeah’ + disagree 35 3.5.1Reject QUD ‘no’ + agree 37 3.5.2In cases where ‘yeah’ is accepting the QUD, the followup content does not signal agreementto the at-issue content or a belief; if the triggering utterance and the followup content were ex-tracted and placed in isolation, it would not be possible to conclude that the followup contenteither agrees or disagrees with the at-issue content. This is not to say that the followup content iswholly unrelated, and in fact it will usually speak to a related QUD with a broader scope. The useof ‘yeah’ is to target a narrow QUD, perhaps the domain goal QUD as it is the narrowest QUD.This is an important point, because each utterance introduces several questions under discussion,but ‘yeah’ is not accepting every one of these as being valid but unanswered. The QUD which‘yeah’ targets is narrow.Example (62) provides a clear example from a natural exchange. The example presents a ques-tion and response, but the response is notable because the speaker of line 2, Gingrich, says ‘yeah,’and then answers the question. The fact that ‘yeah’ is not his answer to the question is clear fromthe followup content, in which he identiஹ஭es his answer explicitly as ‘sure.’(62) 1. BARBARO: Does he [Trump] have the mental ஹ஭tness, the kind of psychological suit-ability to the oஸஹ஭ce of the presidency?2. GINGRICH: [pause] Yeah, and my answer would be, sure. COCA(62’) At-issue content: Trump has the mental ஹ஭tness or psychological suitability to be thepresident.QUD: Does Trump have the mental ஹ஭tness or psychological suitability tobe the president?106Belief: Barbaro believes that Trump may or may not have the mental ஹ஭t-ness or psychological suitability to be the presidentResponse particle: YeahFollowup content: myGiTMXiIh answer would be, sureGingrich explicitly separates the acceptance of the QUD with ‘yeah’ from the proposed an-swer to the question, prefaced with a tag that the followup is the answer, not the ‘yeah’. Here‘yeah’ is accepting the QUD, as expressed in the question in line 1, as a valid, unanswered ques-tion under discussion. The question of Trump’s psychological suitability to the presidency isappropriate in the sense that it is related to the previous QUDs concerning a candidate for thepresidency; a higher level QUD for the discourse is something similar to ‘Who should be presi-dent?’ or ‘Should Trump be president?’ This higher level QUD is unresolved in the sense thatthere is no information that would answer the question and that has been entered into the com-mon ground between those two speakers prior to this exchange.The example in (63) also shows how a response can target the QUD, even one beyond theimmediate domain goal QUD. The speakers are discussing Whitney Wolfe’s14 social media com-pany, and her utterance in line 1 establishes that she is a leader in the company through her re-peated use of ‘we’ to describe the work that the company is doing.(63) 1. WHITNEY WOLFE: … We now have a whole new set of moderators looking for hatesymbols and hate speech on our platform. We ’re really just trying our best to build aclean, safe community.2. GUY RAZ: Yeah. It’s been 2 1/2 years since you launched this company.3. WHITNEY WOLFE: Correct.4. GUY RAZ: And you have how many active users now?5. WHITNEY WOLFE: Twenty million registrations, nearly. COCA(63’) At-issue content: We’re [WW and the managers of Tinder] really just trying our bestto build a clean, safe communityQUD: Are you [WW and the managers of Tinder] really just trying yourbest to build a safe, clean community?14Whitney Wolfe is the founder of Tinder and Bumble, two of the most successful dating apps. The platformshe is discussing in this exerpt is Tinder.107Belief: WW believes that [WW and the managers of Tinder] are really justtrying their best to build a safe, clean communityResponse particle: YeahFollowup content: It’s been 2 1/2 years since youWW launched [Tinder].Broader QUD: How has Tinder developed since its inception?The followup content invokes a broader QUD concerning the development of Tinder sinceits inception, and this QUD includes the domain goal QUD, that is the narrowest QUD. It isimportant to remember that utterances don’t introduce only one QUD, they each respond to arange of QUDs from the most narrow ({p,¬p}) to the state of the world QUD (What is the stateof the world?). A range of questions relating to are illustrated in (64), with the ones from (63’)in bold.(64) a. State of the world QUD: What is the state of the world?b. ↰High level QUD: What is the state of online dating apps?c. ↰How signiஹ஭cant is Tinder in the world of online dating apps?d. ↰How has Tinder developed since its inception?e. ↰What has Tinder done since its inception to grow its community of users?f. ↰Are [WW and the managers of Tinder] trying to build a clean,safe community?However, the followup content does not respond to the at-issue content concerning the cre-ation of a safe, clean community. This leaves the question of what ‘yeah’ is doing. One possibilityis that it is accepting the at-issue content concerning a ‘clean, safe community,’ but the fact thatthe at-issue content is neither accepted or explicitly rejected argues against that analysis. How-ever, ‘yeah’ can accept WW’s belief in the at-issue content, and GR accepts this belief while notsignalling agreement with the at-issue content.The triggering utterance in (65) is a question“What are you going to do [with AWOL sol-diers]?”, and two potential—but crucially not literal— answers. Speaker A is not suggesting thatAWOL soldiers should be shot or put in jail, rather those are two non-literal suggested answerswhich show the real diஸஹ஭culty of providing a real answer to the QUD. The question in line 1 isnot a polar question, meaning that ‘yeah’ cannot answer it.108(65) 1. A: yeah well if they went awol what are you going to do shoot them put them in jail2. B: yeah i don’t know send them over to Iraq have a vacation in Iraq for a year LDC(65’) At-issue content: If they [soldiers] went awol [absent without leave], what are you[impersonal, societal] going to do, shoot them [the awol soldiers],put them [the awol soldiers] in jail? (Rhetorical question)QUD: What can be done with awol soldiers?Belief: Speaker A believes that ‘what are you going to do [with awol sol-diers?’ is a fair quesitonResponse particle: YeahFollowup content: I don’t knowSpeaker A’s initial utterance contains an if/then statement and a rhetorical question, but thespeech act in the initial utterance is not a question. The eஸfect of the utterance may suggest thatthe speaker sees the question as unanswerable, similar to (66), in which the question seems toindicate the answer, in that there is nothing to be done about worsening forest ஹ஭res.(66) Forest ஹ஭res seem to be getting worse every year, but what are you going to do?That the questions are rhetorical derives from context and cultural knowledge, as the sug-gestion that shooting is an appropriate punishment under any circumstances is wholly unappro-priate in early 21st century North American culture. Moreover, neither speaker is in a positionto decide on the punishment for awol soldiers. Speaker A knows not to expect a literal answerwhen they frame the question, and by oஸfering an equally implausible suggestion (send the soldierto Iraq for a year) they are signalling their agreement to the unanswerable nature of the question.The use of a rhetorical question signals that the speaker believes that something should bedone, but they do not have an answer as to what should be done and may doubt that anythingcan or will be done.Speaker A suggests two potential answers to the QUD they introduced, that soldiers be ei-ther shot or jailed. Speaker B then oஸfers a third suggestion, sending the soldiers to Iraq, afிertheir initial followup content gives the truthful answer, “I don’t know.” That Speaker A oஸfersrhetorical questions in answer to their own QUD suggests that they do not expect a genuine an-swer from Speaker B; they do not give Speaker B time to oஸfer an answer. The upshot of all ofthese answers means that there is not, and cannot be, one agreed upon answer to the QUD.109As the QUD is not a yes/no question, ‘yeah’ in line 2 must be doing something other thananswering the QUD. As the “at-issue content” is essentially a restatement of the QUD, thereis no content which could be placed in the common ground. The only remaining function of‘yeah’ in line 2 is to accept that the QUD is a valid QUD, one to which no answer is available inthe common ground.3.5.2 Rejecting the QUDTable 3.10: Reject QUD with ‘no’ + agree highlighted (Table 3.4 repeated)Outcome Response # Sec. Outcome Response # Sec.Targeting only at-issue content Targeting beliefAccept AIC ‘yeah’ + agree 132 3.3.1 Accept bel not AIC ‘yeah’ + disagree 32 3.4(Neg) Accept AIC ‘no’ + agree 69 3.3.2 Targeting QUDReject AIC ‘no’ + disagree 95 3.3.3 Accept QUD ‘yeah’ + disagree 35 3.5.1Reject QUD ‘no’ + agree 37 3.5.2The Response Target Hypothesis claims that ‘no’ plus agreeing content will signal that theQUD has been rejected because the answer is already in the common ground. This can be becausethe information has been discussed and there is complete agreement, as in (67), or because, in theview of at least one speaker, the question will not arrive at an answer with further discussion,as with (69). The extracted corpus provides 37 examples of the QUD being rejected for thesereasons.3.5.2.1 Answer to QUD already in common groundWhereas a QUD is accepted as valid if there is no immediately available answer to it, a QUD isrejected as invalid if there is already an answer available. Consider (67). The at-issue content andQUD are about hurricanes, but the conversation, importantly, is about evacuees.(67) Context: The speakers are discussing the implications of ஺ாooding in Florida and neigh-boring states.1. HARI஡SREENIVASAN The other thing that concerns me is, where do they evacuateto? If they go to South Florida, that’s where the hurricane could land.2. CRAIG஡CATES No, you’re absolutely right. And we have concerns over that. Wewere going to start running buses tomorrow to our shelter, which is in Miami at110Florida International University. And that’s where our shelter is. But the hurricanemay hit there. So we’re looking at that COCA(67’) At-issue content: South Florida is where the huricane could land (which could pre-sumably impact evacuees).QUD: Could a hurricane land in South Florida (which could presumablyimpact evacuees)?Belief: HS believes that a hurricane could land in South Florida (whichcould presumably impact evacuees).Response particle: NoFollowup content: you’re.S absolutely rightThe at-issue content introduced in line 1 is that, if evacuees go to South Florida, then a spe-ciஹ஭c hurricane developing in the Atlantic could land in the place where the evacuees went, SouthFlorida. It is important to observe that this is not a claim of a causal relationship; rather it estab-lishes that the at-issue content concerns not only the hurricane landing, but rather the relation-ship of that landing event to the evacuees. The evidence is the content of the discourse before thetriggering utterance and afிer the followup content, all of which is concerned about the plightof ஺ாood evacuees and not the meteorology of hurricane landings. Moreover, the literal questionwhether a hurricane can land in South Florida is answered by shared knowledge about the world,much like “Could it rain in the Amazon?” or “Could it be hot in the Sahara?” The answer isyes to all of these questions; the only thing that makes the discussion of hurricanes salient is itsrelation to the discussion of evacuees.The followup content in line 2 is “you’re absolutely right,” which is agreeing. Therefore the‘no’ response cannot be rejecting the at-issue content or the belief of Ms. Sreenivasan expressedin line 1.The answer to this QUD is clearly yes, made clear by Mr. Cates’s response in line 2. Hecontinues his turn to indicate that he and others have concerns over the possibility that evacueesin South Florida could be hit by a hurricane. He even provides more detail about the truth ofthe at-issue content and answer to the QUD by stating that the shelter is in Miami, a city on theAtlantic Ocean in southern Florida. This strong evidence of shared concern over evacuees andhurricanes in southern Florida is also evidence that the information required to answer the QUDis already available in the common ground.111How did this information about evacuees get into the common ground of these two individ-uals? The source is community membership, those with a professional interest in weather relateddisasters: Sreenivasan is a journalist, Cates a disaster response manager. The community extendsto people familiar with the norms of hurricane season in south Florida. This shared commu-nity membership means that both speakers can reasonably be expected to agree on the dangersof placing evacuees in south Florida during hurricane season.This function of ‘no’ rejecting the QUD also explains (68),15 repeated from Ch. 2.(68) : I think we need to be meeting at least once a month. : No, I think you’re right. heard in a meeting(68’) At-issue content: We [the group] should meet at least once a month.QUD: Is it the case that we [the group] should meet at least once a month?Belief: α believes that they [the group] should meet at least once a monthResponse particle: NoFollowup content: I [β] think you’re [α] right.Speaker β signals explicit agreement with their followup content, “I think you’re right.” Be-cause the topic had already been discussed, it would be reasonable for Speaker β to believe theQUD in (68) had been resolved and that further discussion was unnecessary; thus, they dismissthe QUD with ‘no’.This usage of ‘no’ plus agreeing followup is particularly important, because there were 32instances of such examples in my extracted corpus. In the Google search results in Ch. 1, Table1.1, there were over 1.3 million examples of ‘no that’s true’ and ‘no you’re right,’ compared to justover 1 million examples of ‘no that’s not true’ and ‘no you’re not right.’ A paraphrase of this usagemight be “We don’t need to discuss that, because we already both know it.”3.5.2.2 QUD will not benefit from further discussionSpeakers may also dismiss a QUD because, at least in their view, the QUD will not beneஹ஭t fromfurther discussion because they believe that there will never be suஸஹ஭cient agreement to establish15This example is not from corpora and is not included in Table 3.4 or its iterations.112the answer in the common ground. Consider (69), in which the speakers16 disagree on mosttopics and may be unable to resolve an answer to the QUD.(69) 1. CARLSON: Were they sexist for voting for Donald Trump over a feminist?2. AREU: Well, three million people voted for Hillary Clinton. More voted for HillaryClinton than Donald Trump.3. CARLSON: Right.4. AREU: So, she did get more voters.5. CARLSON: No, but just with the sexism. I mean, I want to re-litigate the wholeelection.6. AREU: Right. Right.7. CARLSON: But just to address the question of sexism COCA(69’) At-issue content: She [Hilary Clinton] did get more votesQUD: Did HC get more votes?Belief: Areu believes that HC got more votes.Response particle: NoFollowup content: But just with the sexism.Broader QUD: To what extent did sexism factor into HC losing the election eventhough she got more votes?The followup content here does not respond directly to the QUD introduced in line 4, butit does speak to a broader QUD about sexism in the election. This broader QUD is related to thenarrow QUD identiஹ஭ed in (69’), in that an answer to a broader QUD concerning sexism—anyanswer—presupposes that the answer to the narrow QUD is aஸஹ஭rmative. In (70), the relationshipbetween the two QUDs, the narrower domain goal and the broader current question, is depicted(70) Broader QUD (QUDCQ) VXKsuVVosKs−−−−−−−→Narrow QUD (QUDDG)16Tucker Carlson is a well-known, extremely conservative cable news host, and Cathy Arau is a Latina journalistwho frequently appears as a guest on Carlson’s show.113QUDCQ: To what extent did sexism factor into HC losing the election even thoughshe got more votes?QUDDG1: Did HC get more votes?Line 1 of (69) introduces a narrow QUD that is directly linked to the broader QUD identi-ஹ஭ed in (69’) and referred to as QUDCQ in (70). In line 2 Areu introduces the at-issue contentthat “More people voted for Hillary Clinton than Donald Trump,” to which Carlson respondswith agreement by saying “Right.” This is suஸஹ஭cient to place the at-issue content in the commonground. The response particle ‘no’ in line 5 is not disagreeing with information in the commonground, it can only be rejecting the QUD because it has already been answered. The followupcontent in line 5, ‘But just with the sexism,’ conஹ஭rms that Carlson does not view the QUD as onethat will beneஹ஭t from discussion..In cases where there is no possibility of answering the QUD, responses may also reject theQUD. In (71), the at-issue content concerns personal preferences between strangers. While speak-ers can accept the at-issue content based solely on the assertion of their interlocutor, they can alsoreject the QUD as invalid for discussion, for the simple reason that they have nothing else tosay—or discuss—once the assertion is made.(71) 1. B: yeah see my husband’s one of these that will switch from game to game to catch alittle bit of every one you know2. A: no i like to stick to one game LDC(71’) At-issue content: TheirSVKGQKX A husband switch from game to game.QUD: Does Speaker A’s husband switch from game to game?Belief: Speaker A believes that their husband switches from game to game.Response particle: No.Followup content: ISVKGQKX B like to stick to one game.Broader QUD: Do people switch from game to game or stick to one game?Speaker A is in no position to discuss the at-issue content concerning Speaker B’s husband,because they have no knowledge of the husband other than what Speaker A shares. Thereforethe QUD that the at-issue content responds to is not valid for discussion, because Speaker A can114Table 3.11: Distrubution of Corpus examples, n=400 (duplicate of Table 3.3)‘yeah’ +agree‘no’ + agree ‘yeah’ +disagree‘no’ +disagree1 Accept AIC 132 69* 0 02 Reject AIC 0 0 0 953 Accept Bel, Reject AIC 0 0 32 04 Accept QUD 0 0 35 05 Reject QUD 0 37 0 0* ‘No’ plus agreeing followup content signals acceptance of the at-issue content whenthe triggering utterance has negation.never respond to the at-issue content in line 1, making “discussion” impossible. This is not tosay that Speaker A cannot continue the conversation by oஸfering an answer to a similar QUD;Speaker A does just that in (71), answering the same QUD about their own habits rather thanthose of Speaker B’s husband.3.6 Conclusions and SummaryThe data presented in the previous sections covers all of the non-zero cells in Table 3.3, repeatedin Table 3.11 for convenience. It demonstrates that all of the examples in the extracted corpus arepredicted by the Response Target Hypothesis.The data demonstrate that ‘yeah’ can felicitously combine with disagreeing followup content,and ‘no’ can similarly combine with agreeing followup content. The explanation for this has todo with the role that response particles play in discourse. Their use is not restricted to acceptingor rejecting at-issue content; they can also target beliefs and QUD. This is summarized in Table3.12.Tokens from corpora can provide ample evidence of what speakers say, but they cannot pro-vide evidence of why speakers say those things. Also unanswered is the question concerning theupdate of the common ground. Demonstrating that these combinations have the hypothesizedimpact on the common ground requires an experimental approach. These are the questions thatthe next chapter intends to answer.115Table 3.12: Summary of corpus examplesOutcome Condition and ExplanationAccept AIC yeah + agreeCount: 132Section: 3.3.1• ‘yeah’ and agreeing followup accept at-issue content• positive absolute polarity and [agree]• response accepts at-issue content into common groundNegation:Accept AICno + agreeCount: 69Section: 3.3.2• negation in triggering utterance• negative absolute polarity and [agree] relative polarity• response accepts at-issue content into common groundReject AIC no +disagreeCount: 95Section: 3.3.3• rejects at-issue content• positive absolute polarity and [reject] relative polarityAccept Bel,Reject AICyeah +disagreeCount: 32Section: 3.4• ‘yeah’ accepts belief of interlocutor• disagreeing followup signals rejection of the at-issue content both as aresponse to the narrow QUD (Domain Goal) and the broader QUD(Current Question)Accept QUD yeah +disagreeCount: 35Section: 3.5.1• ‘yeah’ accepts a QUD to which both the at-issue content and followup canbe responses• requires suஸஹ஭cient pre-existing common ground for both speakers torecognize the relationship between the at-issue content and followupcontent to satisfy Relevance• followup content can coexist in common ground with at-issue contentReject QUD no + agreeCount: 37Section: 3.5.2• ‘no’ dismisses QUD (Domain Goal) because the answer is already in thecommon ground• agreement targets either the at-issue content (which is already established) orthe Current Goal.116Chapter 4Experimental resultsThe examination of natural data in Chapter 3 demonstrated that ‘yeah’ and ‘no’, in tandem withagreeing and disagreeing followup, are both able to target not only at-issue content, but alsobeliefs and QUDs for inclusion in the common ground. However, one of the limitations ofnatural data is that it cannot usually provide direct comparison of response combinations, norcan it demonstrate conclusively whether or not the common ground is in fact updated. Thesequestions are best answered by experimental means.This chapter will describe the experiment in detail, as well as the results and what they demon-strate concerning the hypothesis. An overall discussion of both experimental and natural datawill be reserved for Chapter 5.4.1 ExperimentIf response particles are able to target information other than the at-issue content, then informa-tion other than the at-issue content can be included in the common ground, and the followupcontent of a response can target the at-issue content independent of the response particle. Basedon the Response Target Hypothesis, the checkmarks in Table 4.1 indicate combinations whichare predicted to be appropriate and how those combinations impact the common ground.The goal of the experiment was to determine the extent to which speakers found paradoxicalresponses appropriate in comparison to non paradoxical responses, and to determine whetherparadoxical responses resulted in an updated common ground. Participants were asked to listento conversations with two exchanges and to rate the acceptability of those conversations. The twoexchanges consisted of an updating exchange and a common ground checking exchange, and eachexchange had two lines. In the updating exchange, the triggering utterance had either a scalar or117Table 4.1: Experimental Predictions of Response Target Hypothesis‘yeah’ + agree ‘no’ + agree ‘yeah’ + disagree ‘no’ + disagreeAccept AIC 3 convergence 3* 7 7Reject AIC 7 7 7 3 divergenceAccept Bel,Reject AIC7 7 3 divergence 7Accept QUD 7 7 3** 7Reject QUD 7 3 convergence 7 7The highlighted responses are predicted to be judged appropriate to experimental participants.*Although ‘no’ plus agreeing content is predicted to be judged appropriate when negation is in thetriggering utterance, the experiment did not test negation. See Sec. 3.3.2 for examples and discussion.**Although ‘yeah’ plus disagreeing followup content is predicted to accept the QUD when the followupcontent is compatible with the at-issue content, this was not tested experimentally because no followupcontent was compatible with the at-issue content See Sec. 3.5.1 for examples and discussion.nonscalar predicate. The response contained either ‘yeah’ or ‘no’, and the followup content eitheragreed or disagreed with the at-issue content of the triggering utterance. The common groundcheck exchange of the discourse signalled that either the common ground was updated (a movewhich I term convergence) or that it was not (divergence).The purpose of the two exchange stimulus was to test which combinations of responses couldimpact the common ground and in what way. The Response Target Hypothesis makes predic-tions concerning what should be considered appropriate and what should not, and these predic-tions are re஺ாected in Table 4.1. The highlighted cell in the ஹ஭rst row signals that ‘yeah’ plus agree-ing followup content will accept the at-issue content into the common gound when the speakersagree to the truth of the at-issue content, a condition which I term convergence. Conversely, aresponse of ‘yeah’ plus disagreeing followup content is predicted to be appropriate when the dis-course shows that speakers do not agree on the at-issue content, when there is divergence. Twoother conditions are predicted to be appropriate: ‘no’ plus agreeing content with convergence,and ‘no’ plus disagreeing content with divergence.In terms of notation, this chapter describes the experimental design in Sec. 4.2 in the text bysimply using the terminology, supplemented with abbreviations based on the ஹ஭rst letter of eachvariable primarily in tables and graphics; these two notations are listed in Table 4.2. The results118Table 4.2: Notation for results discussionVariables y ‘yeah’ a agree c converge s scalarn ‘no’ d disagree d diverge n nonscalarFeature labels yeah agree converge scalarno disagree diverge nonscalarsection uses a typeface style notation to refer to the variables used in a given presentation of thestimuli, employing the notation as a kind of shorthand for ‘a discourse which included yeah andagree,’ as an example. This notation, also included in Table 4.2 will be used primarily in Sec.4.3.4.2 Method4.2.1 ParticipantsA total of 141 participants took part in the experiment; all participants ஹ஭lled out a language ques-tionnaire where they were asked to identify if they were native speakers of English and if theyspoke another language at home with their family. Nativeness was self-selected; no proஹ஭ciencytest or other criteria were applied. The international composition of the UBC student bodymeant 59 participants, or 42%, were non-native speakers of English. Of the 82 remaining par-ticipants, 35 were native English speakers with no other language spoken in their home, and 47participants were native English speakers who spoke a language other than, or in addition to,English in the home with family.As the study was primarily concerned with the judgements of English speakers, these non-native speakers were not included in the ஹ஭nal results. The students were recruited as part of theLinguistics Outside of the Classroom program at UBC, and since participation in an experimentis ofிen a course requirement, researchers cannot prohibit their participation, even if they donot otherwise meet the selection criteria. Afிern English, the largest second home language wasCantonese (14 participants), followed by Mandarin (6 participants), French (5 participants), andthen Korean, Punjabi and Vietnamese with 4 each. The full list of participant languages, alongwith breakdowns by age and gender, are included in Table 4.3. Participants were given coursecredit for their participation.Age categories were in 10 year increments, except for the top age range, which was 55+; this119Table 4.3: Overview of English native speaker participants’ primary home languages, age andgenderLanguage 18-25 years 26-35 years 36-45 years TOTALF M F M F MEnglish 22 7 4 1 1 35Arabic 2 2Cantonese 11 3 14Farsi 2 2French 2 2 1 5German 1 1Gujarati 1 1Hebrew 1 1Korean 3 1 4Mandarin 5 1 6Punjabi 3 1 4Russian 1 1Spanish 1 1Vietnamese 4 4Yoruba 1 1TOTAL 58 17 5 0 1 1 82Where no participant matched the criteria, spaces were lefி blank for ease of reading.category and 45-55 had no participants and are not included in Table 4.3. The bottom age rangebegins at 18, rather than 16, to re஺ாect the age of ஹ஭rst year UBC students at the time of the experi-ment.1204.2.2 Stimuli designAt its core, the experiment needed the stimuli to accomplish two things: (potentially) update thecommon ground, and then check the common ground for this (potentially) updated informa-tion. The word ‘potentially’ is present because one possible outcome is non-update of the com-mon ground, that is, the common ground could remain unchanged. As the common groundalready has information from the shared community membership and previous discourse;1 addi-tional information must be agreed upon to enter the common ground2, but this does not alwayshappen. One of the goals of this experiment was to show that information was not added to thecommon ground. The stimuli would need to allow for all of these possibilities to be tested byconஹ஭rming the understanding of the participants.As an overview, stimuli comprised two brief exchanges of two sentences each. The ஹ஭rst ex-change was a two utterance conversation that took place between speakers α and β and consistedof a declarative utterance, and then a response with ‘yeah’ or ‘no’ and followup content whichsignalled agreement or disagreement with the at-issue content of the triggering utterance. Theresponse (comprising two components) signalled whether information was to be added to thecommon ground between α and β. Afிer a written description identifying a third person, ɣ,this person enters the conversation and asks a generic question relating to the previous exchange.Speaker ɣ does not have access to the common ground between α and β and their presence isstrictly to test for common ground update by forcing α or β to report on the outcome of theprevious discourse. The answer to ɣ’s question re஺ாects the information in the common ground.Table 4.4 summarizes the two exchange dialogs.Presenting two small dialogs was intended to replicate the discourse process for updatingand then accessing the common ground. The ஹ஭rst exchange is an adjacency pair which includesa presentation phase and an acceptance phase (Clark, 1996) where the acceptance may or maynot update the common ground. Under the Response Target Hypothesis, a response of ‘yeah’followed by agreeing content (‘Yeah, it was.’) should result in the common ground being up-dated with the at-issue content of the presentation phase utterance. A response of ‘no’ followedby disagreeing content should not add the presentation phase at-issue content to the commonground. The central question that the Response Target Hypothesis attempts to answer is howmixed responses, that is ‘yeah’ with disagreeing content (‘Yeah, it wasn’t’) and ‘no’ with agreeingcontent (‘No, it was.’) aஸfect the common ground, whether the common ground is updated withthe at-issue content, a belief of one or the other interlocutors, or whether there is no update to1See Sec. 2.1.1 for more details.2See Sec. 2.3.1 for more details.121Table 4.4: Template of stimuli scriptPurpose Speaker Utterance Variable ExampleBrief written information describing the context and identifying the speakersUpdatecommongroundα <declarative utterance(at-issue content, α’s belief,and response to implicitQUD)>Scalar or NonscalarpredicateThe car chasescene was long.β <response particle> and<followup content>{‘yeah’ or ‘no’} plus{agreeing or disagreeingcontent}No, it was.Brief written information updating the context to introduce the third speakerCheckcommongroundɣ <open ended question> none How was themovie?α or β <answer to question> Convergent answer (‘Weboth think…) or Divergentanswer (She thinks… but Idon’t.)We both think thecar chase scene waslong.the common ground because the responses are targeting something other than at-issue contentor beliefs.In the second adjacency pair, the common ground has to be checked by one of the speak-ers to see whether it was updated as a result of the ஹ஭rst exchange, and if so, with what. Underother analyses, such as that of Farkas and Bruce (2010), if the response in the ஹ஭rst exchange con-tains a ‘no’, then the common ground would not have been updated and the discourse would bein “crisis.” The logical consequence of this lack of update, however, is that the response in thesecond exchange would be unable to signal either convergence or divergence, because no suchinformation would be available. However, by allowing responses to target multiple componentsof an utterance, the Response Target Hypothesis allows for felicitous followup answers; for ex-ample, even in cases of divergence, the common ground can be updated to include α’s belief inthe at-issue content.The dialog in (1) will be helpful in providing an overview example, as it contains all of thecomponent parts of the stimuli, while Table 4.5 summarizes the components of this sample ex-change.122(1) Sample of stimulus dialog with labels to show structure1. α: The car chase scene was long. scalar predicate2. β: Yeah, it was. / No, it was. response plus followup content3. : How was the movie? checking question4. : We both think the car chase scene was long. –OR– convergenceβ: She thinks the car chase scene was long, but I don’t. divergenceTable 4.5: Summary of example dialog in (1)Line Utterance part Variable Purpose1 ‘…scene was long’ (non)scalar establish at-issuecontent2 ‘yeah’ / ‘no’ response particle response part 12 ‘it was’* followup content response part 23 ‘How was the…?’ promptingquestioncheck commonground4 ‘We both think…’ / ‘Shethinks … but I don’t.’convergent/divergent responsereport commonground4.2.2.1 Exchange I: Establish the common groundThe establishment of common ground is one of the central purposes of discourse, and the objectof inquiry in this dissertation. This establishment relies on several features of discourse, manyof which were discussed in Chapter 2. Many factors that can aஸfect interaction in discourse wereheld constant in this experiment, including intonation and sociological factors, but scalar andnonscalar predicates were used as a variable to examine responses under diஸferent conditions.Scalar versus nonscalar predicates The primary purpose of the initial, or triggering, utter-ance was to establish the at-issue content, question under discussion (QUD), speaker beliefs andother components which the responses may have targeted. Predicates in the triggering utterancewere either scalar (including taste predicates) or nonscalar. The reason for this was to test whether123expertise or objective falsiஹ஭ability in஺ாuenced the acceptability of ratings when the responses wereheld constant.The scalar predicates were all either taste predicates that would be indexed to an evaluator,namely the speaker, or they relied on a contextually-given standard for what counts as ‘long,’ etc.but about which individuals can still disagree. These predicates, in addition to the written contex-tual information, controlled for expertise, as each speaker would be the ‘expert’ on their opinion,and no other information was given. For example, when the speakers were discussing whetherthe car chase scene was ‘long,’ there was no indication of exactly how long it lasted, meaning thatexperimental participants could not draw their own conclusions about the length of the scene.Non-taste scalar predicates do diஸfer from taste predicates in that, with the former, the truth isnot wholly a matter of personal opinion; no one would consider a 1 second car chase scene to be‘long.’ But whether a 1 minute or a 5 minute or a 23 minute car chase scene is ‘long’ is, at leastto some extent, a matter of personal opinion. The contexts of the stimulus items indicated thatboth speakers had access to the same experience but had not discussed it prior, so that the speakershave no knowledge of their interlocutor’s opinion before the conversation that is presented.A similar context was created for the nonscalar predicates, but the key diஸference was that noexpertise was presented, so that both interlocutors were drawing from the same limited knowl-edge as to the veracity of the claim. In other words, the non-scalar predicates did not rely on theopinions of the participants, only their (lack of) knowledge and assumptions about what mayor may not have happened. All of the nonscalar predicates describe “life events,” such as gettingmarried or buying a house, and they were all essentially binary in that either the event did or didnot happen. The context is generally that the speakers are all friends with two people, for exam-ple Bill and Kathy, and they’re discussing whether Bill and Kathy (neither of whom are part ofthe discourse) got engaged. The text on the slide speciஹ஭cally indicates that none of the discourseparticipants have any expertise on the question, none know for sure, but they all have the sameknowledge of Bill and Kathy to suppose (or not) that the given life event did (or did not) occur.Response particle and followup content responses Afிer the initial utterance, β respondedwith a two part response that included a response particle (‘yeah’ or ‘no’) and appropriate agree-ing or disagreeing content (e.g. ‘it was’ or ‘it wasn’t’). The exact agreeing or disagreeing contentdepended on the previous utterance, so that if the ஹ஭rst utterance was ‘Bill and Kathy got marriedthis weekend,’ the agreeing/disagreeing content was ‘they did’ or ‘they didn’t’, whereas if the ஹ஭rstutterance was ‘The car chase scene was really long,’ the agreeing/disagreeing content would be ‘itwas’ or ‘it wasn’t’. While the speciஹ஭c wording varied, the shape and length of that content was124held constant as much as possible. This was to create responses that were as minimally diஸferent aspossible while still allowing the responses to disambiguate what the response particles are doing.This disambiguation was the key reason why the responses have two parts; without the fol-lowup content afிer the response particle, it is impossible to distinguish which types of proposi-tions —at-issue content, belief, QUD, etc.—a response may be targeting. If, for example, thejudgements of the experimental participants indicate that at-issue content is in the commonground afிer a response of ‘no, it was’, this tells us that ‘no’ must be doing something otherthan rejecting the at-issue content from the common ground. To complete the paradigm, someexchanges include only the response particle with no followpu content, or only the followupcontent with no response particle.4.2.2.2 Exchange II: Check the common groundOne of the central claims concerning the common ground is that it is a repository of informa-tion that can then be accessed at a later point in the discourse. If something has successfullyentered the common ground, then that information is necessarily available for the participants,and overhearers, to access at a later point. If information is available in the common ground, thena participant should be able to access that information in order to report it to a new interlocu-tor. This availability of information is essential to the idea of the common ground, and it is thisavailability and access that forms the theoretical basis of the second exchange of the dialogs, thechecking phase.The addition of a third interlocutor who poses an open-ended question allows the originaltwo speakers to report on the contents of the common ground. The scenarios were set up forparticipants so that no additional time has passed between the ஹ஭rst conversation and the secondso that it was clear that no additional information would have been exchanged oஸf the record,as it were. The context described says that the only interaction between the speakers, outside ofthe adjacency pairs, was greetings, with no additional information being exchanged. The thirdinterlocutor shares less common ground with the initial two interlocutors, and the purpose ofher question is to expand the common ground between the three.The third discourse participant asks an open-ended question that is as neutral as possiblewhile still pertaining to the previous exchange. As an example, if the ஹ஭rst exchange is aboutwhether Bill and Kathy got married this weekend, the question is ‘What happened this week-end?’ If the exchange is about whether a movie scene was long or not, the question is ‘How wasthe movie?’ (with the context that the asker knows that the other two speakers went to a moviethat the asker has not seen). The key point is that nothing concerning the at-issue content is125presupposed by the question asked by the third speaker.The response to the open-ended question signals that the original two speakers, α and β, ei-ther agreed or disagreed to the inclusion of the at-issue content into the common ground, andthe response takes one of two forms: ‘We both think that …’ or ‘<α’s name> thinks that …, butI don’t.’, where … is the at-issue content from the ஹ஭rst exchange. All combinations of responseparticles, agreeing/disagreeing content, and convergence/divergence were used, so that partici-pants evaluated ‘yeah, it was’ followed by ‘Dana thinks that … but I don’t’ as well as ‘No, theydidn’t’ followed by ‘We both think that …’ and all other combinations.4.2.3 Experimental TaskThe task of the experiment participants is to rate the overall acceptability of each set of exchanges.Each stimulus consists of four utterances consistent with Table 4.4; the variables are re஺ாected inthe sample of exchanges re஺ாected in (2)–(4).(2) Yeah agree converge nonscalarα. The car chase scene was long. nonscalar predicateβ. Yeah it was. yeah agree update common groundγ. How was the movie? to check common groundα. We both think the car chase scene was long. converge common ground updatedQ. Experimental participants rate the acceptability of this exchange.(3) No disagree converge nonscalarα. The car chase scene was long. nonscalar predicateβ. No it wasn’t. no disagree common ground not updatedγ. How was the movie? to check common groundα. We both think the car chase scene was long. converge common ground updatedQ. Experimental participants rate the acceptability of this exchange.(4) Yeah disagree diverge nonscalar126α. The car chase scene was long. nonscalar predicateβ. Yeah it wasn’t. yeah disagree common ground updated?γ. How was the movie? to check common groundβ. She thinks the car chase scene was long, but I don’t.diverge common ground not updatedQ. Experimental participants rate the acceptability of this exchange.Participants in the experiment have the role of overhearers, in that they are not expected togenerate a reponse to any question themselves, they are only evaluating the acceptibility of whatthey hear. The question they are asked is ‘How appropriate is the previous conversation?’ andthey are provided with a 4-point Likert scale with ‘very appropriate’, ‘appropriate’, ‘inappropri-ate’, and ‘very inappropriate.’4.2.4 MaterialsParticipants completed the experiment on a computer that was present in the experiment room;they were also provided with headphones and a mouse to control the progression of stimuli.The slides were presented as a Powerpoint presentation, and participants clicked to begin audioand to advance to the next slide; other components, such as advancing the visual stimuli, wereautomated in relation to the audio components. The audio played when the participant clickedanywhere on the screen so that the participant could control the pacing.This section will discuss the visual aspects of the stimuli and then the audio aspects.4.2.4.1 Visual aspects of the stimuliFigure 4.1 presents four slides from the presentation. The audio icons to the lefி of the imageswere not displayed to participants, but they represent the embedded audio ஹ஭les which played thetwo parts of the stimuli. The slides in Fig. 4.1 are a semi-random selection of slides which showfour of the scenarios which were presented to participants.The images were drawn by a research assistant, Ivana Prpic, and included to help participantstrack the speakers across the exchanges. Each of the two illustrations shows a clock in the upperlefி corner with a time of approximately 3:00 on both illustrations; this is to signal that little if anytime has passed between the ஹ஭rst and second exchanges. This is important to signal that no otherexchange of information has taken place, that the only discussion of, for example, the movie waspresented to the experiment participant and no other (relevant, i.e. about the movie) source of127Figure 4.1: A selection of slides from the stimuli128Figure 4.1: A selection of slides from the stimuli (cont.)129common ground exists. The speech bubbles were lefி empty so that the participants only had thespoken discourse to rely on. The coloring of the ஹ஭gures’ clothing (and sometimes hair and ஺ாoor)changed between slides to signal that the speakers had changed between slides.At the bottom right of each slide is the question number in fairly large, bold typeface to helpparticipants answer in the correct blank on their response sheets. In the bottom lefி corner, insmaller, paler typeface, is a code to the content of the slide for our reference; Fig. 4.2 highlightsthe location of this code.Table 4.6: Slide reference codesCode Meaningb/f scalar/nonscalar predicates1, 3 convergent reply2, 4 divergent replyy/n yeah/no responsea/d agreeing/disagreeing contentb/f and 1-4 are identiஹ஭ers to track predicates andreplies throughout the experiment. Scalar=b,nonscalar=f. (The use of b and f were held overfrom the planning phase of the experiment, inwhich the stimuli were held in columns b and f on aspreadsheet.)Figure 4.2: Reference code location on slideThe description of the contexts consistently identiஹ஭es the discourse participants as friendswho have seen the same movie, know the same people, or have whatever shared knowledge is re-quired for the exchanges. They are placed in settings that are neutral, in that they are having lunchor meeting for coஸfee; these are activities that are common for friends to participate in together.They are not placed in settings that suggest a power dynamic, such as a workplace or classroom.The illustrations despict the speakers in a minimal way, as they are not meant to be lifelikerepresentations. However, the illustrations depict all speakers as women of indeterminate age.Their ethnicity is not depicted in the illustrations,3 although the written contexts do provide3Hair color is depicted, including black, brown, yellow and white; green blue and pink are also used as hair130given names; the names are drawn from students at UBC and come from a variety of cultural andethnic backgrounds, re஺ாecting the multicultural character of the UBC campus. The illustrationsalso depict neutral locations, adorned essentially with a ஺ாoor and a clock, and all speakers areshown standing. By using neutral depiction intended as a participant aid, the illustrations weredesigned not to create implicit power dynamic between the speakers, and to depict them in anunbiased, if simplistic, way.4.2.4.2 Audio aspects of the stimuliAll speakers who recorded the stimuli are themselves young women between 20 and 30 years ofage who are all native speakers of North American English from middle class backgrounds; a totalof six voices were used, with an initial of F, H, K, M, N and S. The voices sounded distinctive tome and to the speakers themselves. However, the same cohort of voices are heard on all of therecordings.For each stimulus, three speakers were used, one each for Speaker , Speaker and Speaker. Intonation was as consistent as possible across all stimuli. In addition to being young womenof similar backgrounds, all of the voice volunteers were trained linguists themselves and under-stood the importance of ஹ஭nding an intonational contour that was at once natural to the contextand consistent across the experiment. The volunteers were recorded together to create naturalconversations whenever possible, and all volunteers recorded all conversations and all roles. Con-versations were then selected for use based on the clarity of the recording, the consistency of theintonation, and a balanced presentation of voices across the stimuli, so that no single voice wasdominant in the presentation. The recordings were then arranged so that no voice was heard intwo adjacent conversations. The exception was that, for example, Voice F could be Speaker inone recording and Speaker or in an adjacent recording; this is because Speaker had onlyone line and it was neither the beginning or the end of the recording.Of particular importance was the intonation of the response particle and the followup con-tent. To maintain consistency, recordings were chosen that displayed similar contours in Praat.Figures 4.3 and 4.4 are one speaker, and Figures 4.5 and 4.6 are another speaker, but the overallshape of all four responses is quite similar. The response particle, ‘yeah’ or ‘no’, shows the samesteep rise to an early peak and a more gradual descent to the followup content, and the responseparticle is close to half of the length of the entire response. The peak on ‘it’ in all four responses isclose to the peak of the response particle, and the followup content trails oஸf on both the agreeingcolors. None look natural, and all are seen on the UBC campus, on women of various ethnic backgrounds.131Figure 4.3: “Yeah, it was.” Figure 4.4: “Yeah, it wasn’t.”Figure 4.5: “No, it was.” Figure 4.6: “No, it wasn’t.”and disagreeing content with a falling intonation. These samples represent each combination ofresponses and are indicative of the set of stimuli as a whole.132(5) Sample minimal pairs of stimuli demonstrating the contrasts of convergence/divergence,agreement/disagreement and yeah/noContrasting convergence and divergenceyeah agree converge yeah agree divergea. A: The car chase scene was really long. A: The car chase scene was really long.B: Yeah it wॼ. B: Yeah it wॼ.C: How was the movie? C: How was the movie?A: We both think the car chase scenewas long.B: She thinks the car chase scene waslong, but I don’t.Contrasting agreeing and disagreeing contentyeah agree converge yeah disagree convergeb. A: The car chase scene was really long. A: The car chase scene was really long.B: Yeah it was. B Yeah it wasn’t.C: How was the movie? C: How was the movie?A: We both think the car chase scenewॼ long.A: We both think the car chase scenewॼ long.Contrasting response particlesyeah agree converge no agree convergec. A: The car chase scene was really long. A: The car chase scene was really long.B: Yeah it was. B: No it was.C: How was the movie? C: How was the movie?A: We both think the car chase scenewॼ long.A: We both think the car chase scenewॼ long.All eight logical combinations were included in the stimuli: yeah agreeconverge; yeah agree diverge; yeah disagree converge; yeah disagree diverge; noagree converge; no agree diverge; no disagree converge; no disagree diverge.4.2.5 ProcedureAll participants were required to complete the experiment at a central location at the Universityof British Columbia. All participants were greeted by myself or one of four research assistants,133Figure 4.7: Sample training slide, labeled in lower right cornerand then informed of their right to withdraw their participation and briefed on the task with ascript read by the researcher.Stimuli were presented as a Powerpoint slide presentation over which participants had somemeasure of control. Participants were able to advance between slides when they were ready, andthey were able to begin the audio when they were ready, but the presentation of text and graphicswas otherwise automated. The were allowed to hear the audio one time, which is why they wereallowed to control when the audio played. The ஹ஭rst ஹ஭ve slides were training slides (Fig 4.7), clearlyindicated in the lower right corner, and the training slides were followed by written instructionspresented over two slides.During the presentation of the stimuli, distractors were included afிer every four slides, andparticipants were asked to answer a question about a given image, such as ‘What color is this஺ாower?’ and ‘Who is this man?’ with images that required participants to choose from morethan one potential candidate. Participants recorded their responses on a paper response sheet,including responses for the practice slides and distractors. They were allowed to take as muchtime as they required up to an hour, and a research assistant was present the entire time to answerquestions.Finally, slides were presented in a semi-random selected ஹ஭xed order. That is, the slides werevaried for response particle, followup content, and convergence/divergence, but the same orderwas presented to each participant. There was no pattern to the randomization, and participants134Table 4.7: Slide presentation summary of Fig. 4.8, pages 136–138Subfig. Slide action Stimulus Trigger/delay1 Initial context Text}Beginning of slideFirst situation drawing Illustration2 First exchange (declarative and response) Audio On click3 Next context Text 4 sec. delay4 Second situation drawing Illustration}On clickSecond exchange (question and reply) Audio5 Instructions for participant Text 4 sec. delaycould not use the current or previous slide to predict any subsequent slide. Most participantscompleted the experiment in well under the alloted hour. Afிer they completed the experimentthey were given a demographic questionaire which gathered information about their gender, ageand linguistic background. Responses were then entered into a spreadsheet with their participantID and demographic information, as well as the date when they completed the experiment andthe research assistant who worked with the participant and entered the data.Fig. 4.8 summarizes how each slide was presented to the participants. The audio icons in theillustrations of the slides were not visible to participants; they are included here to represent theaudio component and when the participants heard the stimuli in relation to the visual presenta-tion. Table 4.7 appears afிer all ஹ஭ve subஹ஭gures and summarizes the timing of the images, audioand slide progression.135(1) Initial context & illustration(2) Audio on clickFigure 4.8: Illustration of slide presentation overview in Tab. 4.7136(c) Next context(d) Illustration & audio on clickFigure 4.8: Illustration of slide presentation overview in Tab. 4.7 cont.137(e) Instructions for participantFigure 4.8: Illustration of slide presentation overview in Tab. 4.7 cont.4.3 ResultsThe discussion of results, including tables, graphics and the statistical analysis, will use the nota-tion introduced at the opening of the chapter in Table 4.2, repeated below.Table 4.8: Notation for results discussion (repeated from Table 4.2)Variables y ‘yeah’ a agree c converge s scalarn ‘no’ d disagree d diverge n nonscalarFeature labels yeah agree converge scalarno disagree diverge nonscalarTable 4.9 presents the means of the responses, arranged by conditions. The counts of eachrating for each condition are also included in Table 4.9 and depicted graphically in Fig. 4.9. The138Table 4.9: Average and count of responses (n=324, 4 of each type per participant)Converge DivergeAgree Disagree Agree DisagreeYeah No Yeah No Yeah No Yeah Noyac nac ydc ndc yad nad ydd nddMean 1.769 1.608 3.040 3.201 3.509 2.907 2.198 1.765SD 0.937 0.864 0.901 0.967 0.831 0.933 1.010 0.989Count of ratingsappropriate{1 165 192 19 22 14 32 94 1762 92 84 68 59 23 61 117 77inappropriate{3 44 31 118 75 67 136 68 424 23 17 119 168 219 95 45 29average ratings for converge and diverge seem to be the inverse of each other for the identi-cal response conditions.4 This patterning is an expected outcome of the experiment; when thediscourse includes yeah agree and concludes with a claim of disagreement, as with divergeconditions, it is predicted that this information mismatch should be considered inappropriate.Similarly, if the discourse signals that the speakers agree, as with converge, then a high ratingof acceptability would be expected if the discourse also included yeah agree. The results inTab. 4.9 support these expectations. The mean rating of yeah agree diverge is 3.509, whichis inappropriate, and the mean of yeah agree converge is 1.769, appropriate. The moresigniஹ஭cant questions concern the acceptability of responses that are paradoxical, such as yeahdisagree and no agree.Drawing on ஹ஭rst impressions, it is apparent that participants found that ‘no, it was/it did.’(no agree) was at least as appropriate at signalling convergence of opinion (average 1.608 for noagree converge) than ‘yeah, it was/ it did’ (average of 1.769 for yeah agree converge). Inother words, the paradoxical response was more appropriate than the non-paradoxical response,a ஹ஭nding which current theories do not predict. To look at this from another angle, Table 4.9presents the raw count of ratings, and no agree converge was judged to be appropriate 2764Lower ratings are more appropriate.139Figure 4.9: Count of Ratingstimes, or in 85% of responses.Most accounts of response particles would suggest that ‘no’ plus agreeing followup contentis felicitous only when there is negation somewhere in the triggering utterance. But there is nonegation in the triggering utterance. All of the triggering utterances in the experiment were pos-itive assertions, and the results indicate that ‘no’ can still be a felicitous response in a convergentcontext. Similarly the Table model (Farkas and Bruce, 2010) would suggest that the use of ‘no’would trigger a crisis and prevent the update of the common ground; in that case ‘it was’ wouldplay no role and the ஹ஭nal line of (6), indicating converge, could not be considered felicitous.However a ஹ஭nal line encoding diverge would be equally infelicitous if the conversation werein crisis, so that both converge and diverge would result in ratings of inappropriate. But thedata clearly do not signal that the discourse is in crisis, because converge results in an averagerating of appropriate. How is this to be interpreted?(6) Example of no agree convergea. : The car chase scene was long.b. : No, it was.c. : How was the movie?d. : We both think the car chase scene was longThe upshot is that ‘no’ plus agreeing content is in fact able to signal agreement, and this resultis predicted and explained by the Response Target Hypothesis. It predicts that ‘no’ can target140something other than the at-issue content concerning the length of the car chase scene, that ‘no’in this case would target the QUD, dismissing it because it is already in the common ground.Convergence indicates that the at-issue content in the ஹ஭rst utterance has been suஸஹ஭cientlyagreed upon that it has been placed in the common ground, despite the use of the response par-ticle ‘no’. Of the two response components, only the agreeing followup content has signalledagreement, and therefore we must conclude that the followup response, and not the response par-ticle, has had the eஸfect of placing the information in the common ground. Where the responsein (6) is ‘no’ plus agreeing followup, there were 276 ratings of very appropriate or appropriate,or 85% of responses to this condition.That no agree is appropriate seems to support the prediction of the Response Target Hy-pothesis that responses can target something other than the at-issue content, as a paradoxicalresponse cannot simultaneously accept and reject the at-issue content, as no agree would seemto do. The Response Target Hypothesis predicts that the second target in this condition is theQUD; by hypothesis, the response particle rejects the QUD while the followup content acceptsthe at-issue content into the common ground. The next question that emerges concerning para-doxical responses is whether yeah disagree, as in (7), functions in a similar way.(7) Example of yeah disagree diverge1. : The car chase scene was long.2. : Yeah, it wasn’t. ‘yeah’ plus disagreeing followup3. : How was the movie?4. : She thinks the car chase scene was long, but I don’t. divergent responseThe bar graphs in Fig.4.10 provide a visual illustration of the relation betweenconverge anddiverge on the x axis and agree and disagree on the y axis.As Fig. 4.10 shows, in almost all experimental conditions, agree and disagree seem tohave the most profound in஺ாuence on acceptability, and not the use of a particular responseparticle. The sets of bar graphs are arranged along the four combinations of two conditions,agree/disagree andconverge/diverge. The upper lefி quadrant, bars 1-2, representagreeand converge, and they show a high degree of acceptability. This seems to support two predic-tions of the Response Target Hypothesis. The ஹ஭rst is prediction 1, which aligns with most workon response particles in claiming that a response such as ‘yeah’ can signal agreement suஸஹ஭cientto place information in the common ground, shown in bar 1 representing yeah agree. Thesecond prediction is an innovation of the Response Target Hypothesis and attempts to explain141Figure 4.10: Stacked bar graph of acceptability ratingsthe paradox of no agree in speech and in the corpora. The ratings of no agree convergeare represented in bar 2, which shows that it was mostly rated as appropriate. The hypothe-sis explains this by claiming that the followup content agree accepts the at-issue content whilethe response particle no rejects the QUD. The evidence for this analysis is that no agree hashigh acceptability ratings under converge, signaling that the at-issue content has entered thecommon ground. The lower right quadrant is similar in that it re஺ாects the high acceptability ofdisagree diverge, regardless of the response particle. The remaining two quadrants showthat the followup content, agree/disagree, are also crucial in in஺ாuencing unacceptability rat-ings, as neither converge disagree or diverge agree are inappropriate regardless of theresponse particle.The overview of the results to this point has provided an interesting snapshot of the accept-ability of diஸferent conditions, and one of the key takeaways is that paradoxical responses are asappropriate as non-paradoxical responses in the right circumstances. The statistical analysis willbegin by looking at the factors that were most signiஹ஭cant in in஺ாuencing the acceptability ratingsdescribed above; it will then look at how those factors interact, producing a more nuanced under-standing of the conditions that led to acceptability ratings. Finally the analysis will consider theprobabilities of acceptability in similar conditions, and what these probabilities indicate aboutparadoxical responses.The ஹ஭rst step is determining which of the four variables—the response particle, the followupcontent, the converge/diverge condition, and the predicate type—has a statistically signiஹ஭cantimpact on the acceptability ratings. To that end, the p-values of all four variables are presented142Table 4.10: e -values of four variablesp adjusted p t yfyeah no 2.509E-04 1.003E-03 3.749 153.815agree disagree 2.995E-16 1.198E-15 9.125 159.605converge diverge 2.202E-05 8.809E-05 -4.373 159.365scalar nonscalar 1.365E-02 5.462E-02 2.496 150.105in Table 4.10. These p-values were obtained with Welsh two-tailed t-tests, and the Bonferronicorrection was used to adjust the p-values to reduce the possibility of falsely rejecting the nullhypothesis.The only criterion which has a corrected p larger than 0.05 is the predicate type, scalarnonscalar, with a corrected p of 0.05462. Because predicate type is not statistically signiஹ஭cant,the analysis will focus on the other three variables: response particle, followup content and con-vergences/divergence.The independent variables interact with each other to produce the acceptability ratings, butconverge/divergehave the biggest eஸfect. This is because one shows that the common groundhas been updated while the other shows that it has not. All else being equal, something that isappropriate under converge should be unappropriate under diverge. Therefore the interac-tions will be separated ஹ஭rst by converge/diverge, as in Fig. 4.11. This and the other interac-tions ஹ஭gures were generated with R Core Team (2019) using Wickham (2016) and Long (2019)packages.Fig. 4.11 depicts converge on the lefி and diverge on the right. The top of both graphsre஺ாects the rating of 4, very unappropriate, and the bottom of both graphs re஺ாects the ratingof 1, very appropriate, with appropriate and unappropriate falling in between. The lefி edge ofeach graph re஺ாects yeah, and the right edge of each re஺ாects no. The lines represent the followupcontent, with agree corresponding to the mean and disagree corresponding to +1SD, or thesolid line. Disagree is fairly stable in both graphs, indicating that neither yeah nor no has anin஺ாuence on the interaction ofagree/disagree andconverge/diverge. It is unappropriateunder converge and approximating appropriate under diverge, but the stability across thegraph indicates that the rating is not in஺ாuenced by the response particle. This contrasts withagree, the dashed line, which is more sensitive to the presence of a response particle, especiallyunder diverge. The sensitivity is not extreme, in that neither line is sloped to the point of spanning143Figure 4.11: Interactions of followup content and yeah/no in converge and divergea step in the rating. But it is enough to indicate that, under bothconverge anddiverge,agreeis slightly more appropriate with no than with yeah.The interactions appear more signiஹ஭cant in Fig. 4.12, in which the lines represent the re-sponse particle, with the mean corresponding to yeah and +1SD corresponding to no. In bothconverge and diverge, the lines converge on disagree, which matches with the inelastic ac-ceptability of disagree in Fig. 4.11. The tighter distribution of the lines in Fig. 4.12 indicatesthat the response particle has a weaker interaction than the followup content with convergeand diverge. Under converge, the presense of agree or disagree is enough to push theacceptability rating an entire step with both yeah and no. This suggests that agree/disagreehas a stronger in஺ாuence on the acceptability rating than yeah/no. The same pattern holds to alesser degree under diverge, in that the presense of disagree is enough to push the responseparticle mean, corresponding to yeah, approximately half a step, from just below unappropriateto just above appropriate.Fig. 4.13 shows the interactions of all three variables in terms of their mutual in஺ாuence andstatistical signiஹ஭cance. The graph on the lefி isconverge, and the graph on the right isdiverge,and the x axis is the response particles. The y axis does not represent acceptability ratings, ratherit represents the slope of agree/disagree. The thick band between (0, 0) and (2, 0) on thex axis of both graphs indicates the range of observed data: 0 for no RP (just agree/disagreewas used in these tokens), 1 for ‘yeah’ and 2 for no; all three options were included in the data for144Figure 4.12: Interactions of response particle and agree/disagree in converge and divergecompleteness. The bands do not correspond to the values of agree/disagree; they indicatethe interactions that will be statistically signiஹ஭cant.The bands, both pink and blue, indicate the area of interactions with a 95% conஹ஭dence in-terval, and the constricted areas of the bands indicate a narrower range of outcomes. This meansthat, where the band under converge constricts to the right of ‘yeah’, the range of values ofagree/disagree is small. In practical terms, because there are only three values to begin with,this means that the followup content is clustered around one particular value, likely agree. Theconstriction is tighter under diverge to the lefி of no, meaning that the range of followup con-tent is clustered more tightly around one value.What may be the most interesting ஹ஭nding concerns the strength of the interactions. Theslope under converge is positive, meaning that the interaction of the response particle and thefollowup content is more signiஹ஭cant than the eஸfects of the two variables on their own. Inter-estingly, the slope under diverge is negative, meaning that, while the eஸfect of the interactionis statistically signiஹ஭cant, it is not as signiஹ஭cant as the eஸfects of the response particle and the fol-lowup content. In other words, the eஸfect is less than the sum of its parts.Comparing Figs. 4.11 and 4.12 provides some insight into why the interactions between theresponse particle and followup content are diஸferent with converge and diverge. The linesunder diverge pattern similarly between the two ஹ஭gures, with a spread of approximately onestep on yeah and meeting just above appropriate on no. Because they are already patterning145Figure 4.13: Interactions of three variables(converge/diverge, yeah/no, agree/disagree)n.s. = not signiஹ஭canttogether, the three-way interaction is not as signiஹ஭cant as the two two-way interactions betweendiverge and the response particle and diverge and the followup content.This patterning contrasts with the lines under converge in Figs. 4.11 and 4.12, where thediஸferences are considerable. In Fig. 4.11, agree/disagree shows a wider range between themean and +/-1SD but fairly small variation in angle. In Fig. 4.12, yeah/no has a much smallerrange but a much sharper angle. Because these two variables pattern so diஸferently, it follows thatthe interaction between them is signiஹ஭cant in determining the overall rating.The interactions illuminate how the system works, while statistical probabilities provide in-sight into the larger implications of the experimental results. Using R (R Core Team, 2019) andthe Modern Applied Statistics with S package (MASS, Venables and Ripley 2002), an orderedprobit model was used to account for the variation between participants and the four variableswhich were used in the stimuli: response particle, followup content, convergent or divergentchecking, and scalar or nonscalar predicates. The resulting coeஸஹ஭cients were used to generate theprobabilities presented in Table 4.11 and Fig. 4.14.Fig. 4.14 highlights the importance of the followup content and converge and diverge.Within converge, probabilities pattern along the lines of the agree or disagree, and not146Table 4.11: Probabilities of acceptability under experimental conditionsStimuli ProbabilitiesPRP FollowupCondition Veryappropriateappropriate Unappro-priateVery Unap-propriate1yeah8>>>>>><>>>>>>:agree{converge 0.552 0.261 0.137 0.0502 diverge 0.0314 0.103 0.229 0.6373disagr.{ converge 0.0812 0.180 0.285 0.4544 diverge 0.299 0.292 0.247 0.1635no8>>>>>><>>>>>>:agree{converge 0.548 0.262 0.139 0.0516 diverge 0.112 0.211 0.293 0.3837disagr.{ converge 0.080 0.178 0.284 0.4598 diverge 0.547 0.262 0.139 0.052“Condition” refers to the experimental conditions of convergence or divergence.Figure 4.14: Stacked bar graph of probabilities147yeah or no. This indicates that the followup content is a stronger predictor of acceptability thanresponse particle.A signiஹ஭cant factor aஸfecting acceptability judgements was convergence,converge anddiverge.This is unsurprising, because exchanges that are otherwise identical should elicit opposite accept-ability based on convergence. The two sample stimuli in (8) and (9) illustrate this point; if theresponse signals convergence in one instance, the identical response cannot signal divergence inthe other instance. The ஹ஭rst three lines are identical, which means that they should either be suf-ஹ஭cient to place the at-issue content into the common ground, or they should not be suஸஹ஭cient.The statistical model supported this expectation. The no disagree converge example of (8)corresponds with Bar 6 in Fig. 4.14 and the seventh row of Table 4.11, and the no disagreediverge example of (9) corresponds to Bar 8 of Fig. 4.14 and row 8 (the last row) of Table 4.11.(8) Sample of convergence :. The car chase scene was long. :. No it wasn’t.:. How was the movie? :. We both think the car chasescene was long.(9) Sample of divergence :. The car chase scene was long. :. No it wasn’t.:. How was the movie? :. She thinks the car chasescene was long, but I don’t.The acceptability ratings for converge and diverge pattern together along the dimensionof followup content. The groupings in Fig. 4.14 make this relationship graphically clear, in thatthe columns are grouped according to convergence, and the rows are grouped according to fol-lowup content. The two bars within each quadrant bear striking similarity to each other, eventhough one represents yeah and the other no. Indeed, within agree converge, the probabili-ties of the four ratings are almost identitical for yeah and no, as is clear from the ஹ஭rst two rows inTable 4.12. The second two rows show the same pattern, in that, within disagree converge,yeah and no are almost identical.The takeaway from this ஹ஭nding is that the followup content plays the central role in updatingthe common ground, moreso than the response particles. Under converge, yeah agree has aprobability of 0.813 of being rated appropriate or very appropriate. While this is consistent withpredictions that ‘yeah’ signals agreement to the at-issue content being entered into the commonground, it does not explain why the identical condition withnohas a probability of 0.810 of beingrated appropriate or very appropriate. This result, however, is consistent with the prediction of148Table 4.12: Probabilities of converge, from Table 4.11Response Very accept. Accept. Unaccept. Very unaccept.yeah agree 0.552 0.261 0.137 0.050no agree 0.548 0.262 0.139 0.051yeah disagree 0.0812 0.180 0.285 0.454no disagree 0.080 0.178 0.284 0.459the Response Target Hypothesis that the response particle is able to target something other thanthe at-issue content, especially in a paradoxical response.The pattern persists in the condition of diverge as well. The non-paradoxical response ofyeah agree would not be expected to be appropriate, and the probability of being rated asunappropriate or very unappropriate is 0.866 (Table 4.11 row 2); compare that to the probabilityof no agree diverge (Table 4.11 row 6) being rated as unappropriate or very unappropriate,which is 0.743. The paradoxical response of yeah disagree is predicted to be appropriateor very appropriate in almost 6 out of 10 times (probability of 0.591, Table 4.11 row 5) underdiverge; in other words, the acceptability again lines up with the followup content and notthe resopnse particle. This also patterns with the non-paradoxical response of no disagreediverge, which has a probability of being appropriate or very appropriate of 0.809 (Table 4.12row 8).Examples (10)–(13) are samples of the conversations which are predicted to be appropriate bythe Response Target Hypothesis, and they correspond to highlighted columns in Table 4.13.(10) yeah agree converge :. The car chase scene was long. :. Yeah it was.:. How was the movie? :. We both think the car chasescene was long.(11) no agree converge :. The car chase scene was long. :. No it was.:. How was the movie? :. We both think the car chase scenewas long.149Table 4.13: Overview of participant ratings, predictions and probabilitiesConvergence DivergenceYeah No Yeah NoAgr. Disagr. Agr. Disagr. Agr. Disagr. Agr. Disagr.Avg 1.769 3.040 1.608 3.201 3.509 2.198 2.907 1.765Probabilities of:v. accept. 0.552 0.081 0.548 0.080 0.031 0.299 0.112 0.547accept. 0.261 0.180 0.262 0.178 0.103 0.292 0.211 0.262Total 0.813 0.261 0.807 0.258 0.134 0.591 0.323 0.809Participants rated each stimuli as a whole on a 4-point Likert scale, with 1 being very appropriate and 4 being veryunappropriate. They recorded their ratings on a paper response sheet which clearly labeled the four possibleratings. Red averages in the top row are under responses that were predicted to be appropriate; lower averagessignal higher acceptability.(12) yeah disagree diverge :. The car chase scene was long. :. Yeah it wasn’t.:. How was the movie? :. She thinks the car chase scenewas long, but I don’t.(13) no disagree diverge :. The car chase scene was long. :. No it wasn’t.:. How was the movie? :. She thinks the car chase scenewas long, but I don’t.The overall results are in Table 4.13, and the highlighted entries re஺ாect where the ResponseTarget Hypothesis predicts that the conversations in the stimuli would be rated as ‘appropriate’or ‘very appropriate’. The average ratings correspond to the probabilities in acceptability, as allthree of the average ratings below 2 also have a probability of above 0.8 for being rated appro-priate or very appropriate. These are all three predicted by the Response Target Hypothesis tobe appropriate. The fourth predicted appropriate outcome had an average of just above 2, anda combined appropriate probability of 0.591, meaning that it is more likely to be rated as appro-priate than unappropriate.The outcomes that were predicted by the Response Target Hypothesis to be unappropriateall had average ratings of over 3, except for no agree diverge which had an average rating of2.907. The combined probability for being rated appropriate is below 0.333 for each of these fourconditions, includingno agree diverge. In summary, where the Response Target Hypothesispredicted the outcomes would be appropriate, the data indicate that this prediction is borne out,and where unappropriate outcomes were predicted, this was also borne out.1504.4 Discussion4.4.1 How the experimental results support the hypothesisOverall, the experimental results seem to support the Response Target Hypothesis. That yeahagree converge and no disagree diverge should both have high rates of acceptabil-ity is not surprising, and indeed such an outcome would be predicted by most theories. Thenovel predictions of the Response Target Hypothesis concern the paradoxical responses, yeahdisagree and no agree, and both of them are appropriate under certain conditions. Thatthey are appropriate suggests that listeners are viewing the response particle and followup, not ascontradictions, but as components that have their own purpose.The Response Target Hypothesis predicts that when the relative polarity of the followup ut-terance is [agree], resulting in the update of the common ground, then stimuli with convergein the ஹ஭nal utterance should be rated as appropriate. Conversely, in discourses in which the rel-ative polarity is [reject], these stimuli should be rated as appropriate when the ஹ஭nal utterancere஺ாects diverge. Such a result would indicate that the followup content is the crucial compo-nent in updating the common ground to include the at-issue content. Table 4.14 shows how thepolarity of the followup patterns with update of the common ground; the red ஹ஭elds were ratedas appropriate, consistent with the predictions of the Response Target Hypothesis.Table 4.14 presents the correlation between the experimental conditions and the theoreticallygrounded analysis of polarity. The conditions labeled in red were predicted to be appropriate bythe Response Target Hypothesis, and this prediction was supported by the experiment. Thepolarity marks [+] and [−] re஺ாect the attribute noted underneath them; Roelofsen and Farkas(2015) claim that response particles get their polarity from their referent, which were all positiveassertions in the experiment, which in turn establishes the polarity. To facilitate comparison be-tween the three sets of conditions in Table 4.14, let us represent all three variable with [+] and [−](not to be confused with absolute polarity). Within the followup content, [agree] correspondsto a plus value [+] and [reject] corresponds to a minus value [−]; these represent agree anddisagree within the experiment. Within the common ground check column, [+] correspondsto an updated common ground and [−] corresponds to an unchanged common ground. Whatthe use of [+] and [−] highlights is the relationship between the response particles (yeah andno), followup content (agree and disagree) and checking the common ground for updates(converge and diverge): where the polarity of the followup content and the common groundcheck are the same, the discourse is likely to be judged (very) appropriate, and where they do notmatch the discourses are likely to be judged (very) unappropriate.151Table 4.14: Polarity of responsesConvergence Divergenceprp followup CG check prp followup CG checkyac + + + yad + + −‘yeah’ [agree] updated ‘yeah’ [agree] not updatednac − + + nad − + −‘no’ [agree] updated ‘no’ [agree] not updatedydc + − + ydd + − −‘yeah’ [reject] updated ‘yeah’ [reject] not updatedndc − − + ndd − − −‘no’ [reject] updated ‘no’ [reject] not updatedyac =yeah agree converge; yad =yeah agree diverge;nac =no agree converge; nad =no agree diverge;ydc =yeah disagree converge; ydd =yeah disagree diverge;ndc =no disagree converge; ndd =no disagree diverge.4.4.2 Potential variables beyond the study4.4.2.1 IntonationThe importance of intonation for information structure in English has received extensive atten-tion in recent years, as it plays a signiஹ஭cant role in English language discourse, particularly inquestions (Pope, 1972; Gunlogson, 2001, 2008; Truckenbrodt, 2009; Pruitt and Roelofsen, 2011;Tubau et al., 2015), and in response particles (Goodhue et al., 2013; Goodhue and Wagner, 2015;Tubau et al., 2015; Goodhue and Wagner, 2016; Tian and Ginzburg, 2016). Many have observedthat responses to sentences or questions containing negation will carry a distinctive intonationalcontour, variably referred to as a verum focus prominence (Roelofsen and Farkas, 2015), a reject-ing accent (Kri஺஽a, 2013), a rising-falling intonation (Liberman and Sag, 1974) or a rising-falling-rising intonation (Pope, 1972).Experimentally, intonation is entirely possible to control, and I held intonation constant byusing a “neutral” intonation. By neutral, I mean an intonation that could be consistent witha range of interpretations that would be suggested by what follows. However, “neutral” doesnot mean identical. The set of intonational contours used in this experiment share many similarfeatures: the high points are approximately equal and at a modest level of amplitude; the contourshave similar shapes in terms of where they rise and fall; the duration is similar (see Sec. 4.2.4.2 fordetails).152Despite the variety of possible intonations and the known interaction between intonationand interpretation, holding intonation as constant as possible has nonetheless yielded robust re-sults. By setting aside the diஸஹ஭cult question of intonation and focusing on the content of utter-ances, this dissertation is able to oஸfer valuable insights into the nature of response particles indiscourse, insights which may then inform further work exploring intonation.4.4.2.2 Listener statusMost work on discourse focuses on speakers and addressees and their interpretations of the dis-course. However, my experiment relies on overhearers, not interlocutors, in that it asks themto listen to conversations and assess how appropriate the response is. It is fair to ask, therefore,about whether that sets up a clear test of common ground. To what extent can overhearers accesscommon ground information to make assessments about its contents?Based on work by Fox Tree and her colleagues (Fox Tree and Mayer, 2008; Tolins and FoxTree, 2015), overhearers can actually recover a substantial amount of information from an over-heard dialog. They will obviously not have access to the preexisting common ground, but theycan access the updates to the common ground that occur over the course of dialog. Fox Treeand Mayer (2008) ஹ஭nds that overhearers are better at identifying a speciஹ஭c object when they haveheard the object being discussed as part of a dialog than when they only hear a monologue de-scription, even if the monologue description is more detailed. This highlights the collaborativenature of discourse and the management of the common ground. This work on what overhear-ers understand about common ground management suggests that an experiment that relies onwhat are essentially overhearers’ responses is an empirically valid method for testing how responseparticles are used to manage the common ground, especially as the object being tested is a dialog.The choice to rely on overhearers was therefore motivated by reasons that support that design,as well as reasons against relying on interlocutors. A methodology that has the participants pro-viding responses in the role of interlocutors immediately runs into the challenges of controllingfor content, intonation and sociolinguistic factors, including age, gender and other interspeakerdynamics. Moreover, speakers regularly vary their intonation, and this intonational variationmay carry signiஹ஭cant meaning, or it may be idiosyncratic to the speaker, or it may be optional inthe context of that response, or it could be explained with some other reasoning. The problemis that none of these motivations would have been recoverable from a simple recorded response,making it impossible to identify what the response particle–assuming one was used–contributedto the common ground management.1534.5 SummaryTwo of the key takeaways from the experimental results are the strong link between the followupcontent and the update of the common ground, and the acceptability of paradoxical responsesin the appropriate convergent/divergent condition. Taken together, these two outcomes suggestthat the paradoxical response of ‘yeah, it wasn’t’ (or similar followup content) will not result inthe at-issue content being entered into the common ground, while the paradoxical response of‘no, it was’ (or similar) will place the at-issue content into the common ground.154Chapter 5ConclusionsThis chapter has three major goals: to consider the data as a whole, including both corpus andexperimental data, and what it means for the Response Target Hypothesis; to look at what otherresearch says about paradoxical responses and similar phenomena and how the Response TargetHypothesis contributes to this understanding; and to think about the limitations of this studyand the opportunities these create for future research.5.1 Overall conclusionsThe Response Target Hypothesis makes several predictions, which are repeated in (1). This sec-tion will walk through each of these predictions and look at the data from both sources whichbears on those predictions.(1) Hypothesis:Response particles, and the linguistic content following response particles as partof a response, can target (accept or reject) at least the following types of con-tent for inclusion into the common ground: at-issue content, speaker beliefs, theQuestion Under Discussion.Predicted targets and outcomes of responses and followup content:At-issue content1. β accepts the at-issue content of α’s assertion; this puts the at-issue contentin the common ground as something that both speakers agree is true.1552. β rejects the at-issue content in α’s assertion; this excludes the at-issuecontent from the common ground and forces a crisis (in the terms of Farkas andBruce, 2010), the resolution of which falls to other assertions and responses.Speaker belief in at-issue content3. β accepts α’s belief in the at-issue content without committing themselvesto the same belief; this signals a mutually shared agreement concerning α’s be-lief in the at-issue content and the acceptance of that belief into the commonground, and crucially does not necessarily put the at-issue content into the com-mon ground.* Rejecting speaker belief is not considered felicitous in most contexts.Question Under Discussion (QUD)4. β’s response accepts the QUD as a valid question to discuss, to which ananswer is not currently available in the common ground or in β’s contribution.5. β’s response rejects the QUD because the answer is already established in thecommon ground or the answer is unattainable at that moment.5.1.1 Comparing the data to the predictionsThe Response Target Hypothesis suggests three components introduced by the triggering ut-terance which can serve as the targets for responses: at-issue content, which can be accepted orrejected; speaker beliefs, which can be accepted; and QUD, which can be accepted or rejected.The following three sections will look at each potential target in turn, considering what the cor-pus and experimental data suggest about these targets. The purpose here is to bring the two datastreams together and consider their overall implications.5.1.1.1 Accepting and rejecting the at-issue contentOne of the core functions of responses in discourse is to accept the at-issue content into the com-mon ground, or to reject it. These are the ஹ஭rst two predictions of the Response Target Hypoth-esis, lines 1 and 2 of (1). Both the corpus data and experimental data showed ample support that‘yeah’ plus agreeing content accepts the at-issue content and ‘no’ plus disagreeing content rejectsit.156In terms of accepting the at-issue content into the common ground (line 1), the corpus datapresented 132 cases of this, ranging from clear examples with responses of ‘yeah you’re right’ toexamples with hedged responses such as ‘yeah I can see that…’ The experimental data also sup-ported this prediction; the combination of yeah agree converge, as in (2), had an averagerating of 1.769, where 1 is very appropriate and 2 is appropriate.(2) Example of ‘yeah’ ‘agree’ ‘converge’ (yac)1. α The car chase scene was really long.2. β Yeah, it was. yeah agree3. How was the movie?4. α We both think the car chase scene was long. convergeSimilar results support the claims of ‘no’ and disagreeing followup acting to reject the at-issuecontent from the common ground. The corpora provide 95 examples of ‘no’ and disagreeingcontent being used to reject the at-issue content. The experiment resulted in an average rating of1.765 for no disagree diverge, as in (3).(3) Example of no disagree diverge (ndd)1. α The car chase scene was really long.2. β No, it wasn’t. no disagree3. How was the movie?4. β She thinks the car chase scene was really long, but I don’t. divergeThe corpus also provides evidence of ‘no’ plus agreeing followup content placing the at-issuecontent in the common ground when the triggering utterance contains negation. The experi-ment did not include negation in the triggering utterances, making this an area for further inves-tigation.5.1.1.2 Accepting belief while rejecting at-issue contentOne of the central claims of the Response Target Hypothesis concerns the use of paradoxical re-sponses, where the response particle and followup content seem to contradict each other. Thehypothesis proposes that a response can accept belief while rejecting the truth of the at-issue con-tent, line 3 of (1), and this claim is supported in the data. The corpus data contains 32 examples of157‘yeah’ plus disagreeing followup content, and these examples seem to be accepting a belief whilerejecting the at-issue content.The experimental data also support this claim of accepting belief. If speakers can accept be-lief and reject at-issue content, then stimuli with yeah disagree diverge should be rated asappropriate, and they have an average rating of 2.198, where 2 is appropriate and 1 is very appro-priate. The combined probability that yeah disagree diverge will be rated as appropriateor very appropriate is 0.591 (see Table 4.11), which supports the claim this paradoxical response isnonetheless able to keep the at-issue content out of the common ground.It is logically possible to reject a belief while accepting the at-issue content, but I have oper-ated under the assumption that this is conversationally impossible, on the grounds that a speakercannot know what is in another speaker’s head suஸஹ஭cient to reject the truth of that speaker’s be-lief. However, this is a testable claim, and in discussions with others I have identiஹ஭ed two areaswhere it might be felicitous to reject a belief while accepting the at-issue content. They are pre-sented in (4) and (5). The confound is that the responses which whould be able to reject thebelief and accept the at-issue content seem to get the interpretation of rejecting the QUD andaccepting the at-issue content. Testing for a rejection of belief would require a way to eliminatean interpretation which rejects the QUD.(4) Context: A parent is speaking to a small child. The parent knows that the child had a ஹ஭llinglunch only a few hours ago, but that it is also approaching dinner time and the child isbehaving irritably.1. CHILD: I’m hungry.2. PARENT: ??No, you are. No=reject belief, ‘you are’=accept at-issue content3. PARENT:3No, you are. No=reject QUD, ‘you are’=accept at-issue content(5) Context: A couple are discussing their romantic relationship. B believes the relationship isover, but does not think that A shares that view.1. A: This relationship has run its course.2. B: ??No, it has. No=reject belief, ‘it has’=accept at-issue content3. B:3No, it has. No=reject QUD, ‘it has’=accept at-issue contentSeparating these readings is tricky. An answer of ‘no, you’re not/it hasn’t.’ does not help,because that simply signals disagreement with the at-issue content, as in the previous section. Ananswer of ‘yeah, you are/it has.’ similarly signals agreement.158That raises the question of whether there is any response that can have the desired eஸfect; (6)and (7) use explicit responses without any response particles to see if the desired readings canemerge.(6) Context: A parent is speaking to a small child. The parent knows that the child had a ஹ஭llinglunch only a few hours ago, but that it is also approaching dinner time and the child isbehaving irritably.1. CHILD: I’m hungry.2. PARENT: You can’t be hungry, but we’ll eat soon.reject belief, accept at-issue content(7) Context: A couple are discussing their romantic relationship.1. A: This relationship has run its course.2. B: You don’t think that, but maybe it has. reject belief, accept at-issue contentThe reading of rejecting belief while accepting at-issue content is at least possible with theseresponses, but crucially these responses do not use response particles to achieve this eஸfect. Theystate outright that they are rejecting the belief and accepting the at-issue content. Whether thissame eஸfect can be achieved with response particles can be tested with dialogs similar to those usedin the experiment, with a third person asking, ‘How is <child>?’ or ‘How is your relationship?’(or something more natural).The other area where rejecting beliefs could be tested is in languages with evidentials, such asCheyenne. In responding to (8), could a speaker challenge the speaker’s belief that Annie wonthe race, given that the evidential indicates indirect knowledge? And crucially, could a responsechallenge that belief, while also accepting the at-issue content that Annie did win the race?(8) É-hó’táheva-séste3-win-rpt-3sgAnnie.Annie.Annie won, I hear. (Murray, 2017, p. 71)This is an empirical question that is valid for future research.1595.1.1.3 Accepting and rejecting the question under discussion (QUD)The ஹ஭nal prediction of the Response Target Hypothesis is line 4 of 1, that the response can targetthe QUD itself. The QUD can be accepted as valid but unanswerable at that moment, or it canbe rejected because the information is either already in the common ground or it cannot be agreedupon at that moment, and therefore the question is not valid for discussion.The corpus data provides 35 examples of acceptance and 37 of rejection of the QUD. Theacceptance examples include ‘yeah’ and disagreeing content, a combination which can also sig-nal the acceptance of the belief. The diஸference between the two outcomes lies in the followupcontent. When the response accepts a belief and rejects the at-issue content, the followup con-tent is incompatible with the at-issue content; the at-issue content and the belief cannot both beaccepted into the common ground, only the belief of the speaker. This is the common trait ofresponses which reject the at-issue content while accepting the belief. Responses where ‘yeah’ ac-cepts the QUD have followup content which is not at odds with the at-issue content, but whichnonetheless cannot signal agreement to the at-issue content on its own. An example, (9), that Iheard afிer the rest of the data was gathered shows this distinction quite clearly.(9) Two people are discussing COVID-19 at an outdoor table in summer 2020.1. α: But with my job and working with the public I’ve probably already been exposedand just haven’t gotten sick.2. β: Yeah I wonder about whether I’ve sorta “gotten it” and been ஹ஭ne. (speaker usedhands to create air quotes)The original at-issue content is that Speaker α has been exposed to COVID-19 and has ex-hibited no symptoms, and Speaker β’s followup content is not incompatible with that at-issuecontent. At the same time, Speaker β’s followup content does not signal acceptance of the at-issue content into the common ground; it expresses curiosity about whether β has been exposedand says nothing about α’s exposure. It disagrees insofar as it does not overtly agree. Ultimatelythough, the common ground is able to contain both propositions, one concerning α’s exposure,the other concerning β’s.The experiment did not test for accepting a QUD, because agree/disagreewere designedto be minimally contrastive; therefore they are only “it was/it wasn’t,” “they did/they didn’t” andsimilar. Testing the acceptance of the QUD would require a third option, something noncom-mital like “I don’t know” or “That may be.”160The Response Target Hypothesis predicts that, in the experiment, no agree convergeshould be appropriate, because ‘no’ is dismissing the QUD because the information is alreadyestablished in the common ground. This prediction is supported by the data, as this combinationhad an average rating of 1.608 with 1 being very appropriate. The probabilities of no agreeconvergebeing rated as very appropriate or appropriate are 0.548 and 0.262; in other words, thiscombination is expected to be appropriate in 8 out of 10 cases. That a paradoxical response shouldbe so appropriate indicates that speakers are able to recover meaning from the apparent paradox.The corpus data suggest that this meaning is to reject the QUD, as it included 37 examples of ‘no’plus agreeing followup rejecting the QUD.5.1.2 Overall conclusions from the dataData from both the experimental and corpus sources supports the Response Target Hypothesis,with evidence that responses can target beliefs and QUDs in addition to the at-issue content;Table 5.1 presents the predictions and the data together. The table also captures the importance ofusing two data streams to test the hypothesis, as the experiment on its own could not provide datafor accepting the QUD or using ‘no’ to accept the at-issue content when the triggering utterancecontains negation. Conversely, the corpus data on its own would be unable to demonstrate thestrength of the acceptability of the paradoxical responses.One surprising outcome was the level of acceptability that experimental participants assignedto the apparently paradoxical responses when compared to the non-paradoxical responses, allof which are summarized in Fig. 5.1. The ஹ஭gure presents the probabilities of appropriate rat-ings for apparently paradoxical responses, ydd yeah disagree diverge and nac no agreeconverge and their non-paradoxical counterparts, ndd as a counterpart to ydd, and yac as acounterpart to nac. The graph reveals that for both pairs (ndd and ydd, nac and yac), the proba-blility that they will be rated as appropriate or very appropriate is high. It also reveals that theseprobabilities are consistent across conditions; indeed, for three of the four conditions, the accept-ability is almost identical. The paradoxical response ydd has a lower probability than the otherconditions of being rated as appropriate or very appropriate. I suspect that ydd would be moreappropriate to speakers with a richer followup, one that perhaps explained the reason for reject-ing the at-issue content, similar to what is found in the corpora examples; intonation may alsofactor into the acceptability ratings.On balance, the Response Target Hypothesis ஹ஭nds support from the evidence, both exper-imental and from corpora. The key points from this hypothesis are that responses can targetmore than the at-issue content, including the QUD and another speaker’s beliefs, and that the161Table 5.1: Summary of Response Target Hypothesis predictions, experimental and corpus dataPrediction ofHypothesisExperimental Data Corpus DataPredictions Result Predictions Result1. Accept at-issuecontent intocommon groundyeah agreeconverge with ahigh probability ofbeing ratedappropriate orvery appropriateyac with combinedprobability of0.813 appropriateratinghigh incidence of‘yeah’ plus ‘agree’examples132 examples of‘yeah’ and ‘agree’Accept at-issuecontent intocommon groundwith ‘no’whentrigger containsnegationnot tested in experiment, ॼ negationwॼ not included in any triঃeringutterancॽregular incidenceof ‘no’ plus ‘agree’examples whentrigger includesnegation69 examples of‘no’ plus ‘agree’with negation intriggeringutterance2. Reject at-issuecontent fromcommon groundno disagreediverge with ahigh probability ofbeing rated asappropriate orvery appropriatendd withcombinedprobability of0.809high incidence of‘no’ plus ‘disagree’examples95 examples of ‘no’plus ‘disagree’3. Accept belief andreject at-issuecontentyeah disagreediverge with ahigh probability ofbeing rated asappropriate orvery appropriateydd withcombinedprobability of0.591 appropriateratingregular incidenceof ‘yeah’ plus‘disagree’32 examples of‘yeah’ plus‘disagree’4. Accept the QUDas valid butunanswerednot predicted in experiment, ॼfollowup content either explicitlyaccepted or rejected the at-issue contentno compatible response that did notagreeregular incidenceof ‘yeah’ plus‘disagree’ that wascompatible withthe at-issuecontent35 examples with‘yeah’ plus‘disagree’ that wascompatible withthe at-issuecontentReject the QUD no agreeconverge with ahigh probability ofbeing rated asappropriate orvery appropriatenac withcombinedprobability of0.810 appropriateratingregular incidenceof ‘no’ plus ‘agree’37 examples of ‘no’plus ‘agree’162Figure 5.1: Probabilities of appropriate ratings for paradoxical and nonparadoxical response stim-uliresponses can function independently of the followup content. Under alternative hypothesesin which a response particle can only targe the at-issue content, paradoxical responses would bepredicted to unappropriate, meaning that the outermost columns in Fig. 5.1 should be empty.Outside of the Response Target Hypothesis, the paradoxical responses ‘nac’ and ‘ydd’ would bepredicted to be empty; there should be no probability that a paradoxical response should be ap-propriate. But the probability is in fact greater than 50% for both of these responses, an outcomewhich the Response Target Hypothesis predicts and explains. Similarly, alternative hypotheseswould predict that paradoxical response, ‘yeah’ plus ‘disagree’ and ‘no’ plus ‘agree’, would notbe present in corpora, but my research identiஹ஭ed 173 paradoxical responses out of 400 total to-kens. Not only does the Response Target Hypothesis predict that paradoxical responses will havea robust presence in the corpora, it explains that presence by identifying what they are targetingbeyond the at-issue content.An important question that emerges is what this all means for theories of responses and com-mon ground. It is important to notice that the Response Target Hypothesisis not incompatiblewith the basic structure of the Table model and the Commitment Space model, both discussedin Chapter 2. In the Table model, the projected set would simply need to be explanded, perhapsas in (10).(10) ps = {xg ∪ pP¬pP ∅P Bel(p)P fUD}163The Commitment Space model would only need a way to record that a QUD was acceptedas unresolved and unresolvable.Perhaps the most important impact is on the nature of response particles, in that in light ofthe data presented here, response particles cannot be regarded as variations of each other or evenone type of category with a variety of entries. Some response particles, such as ‘yeah’ and ‘no’,are compatible with paradoxical responses, and others (I believe most others) are not. It is notcoincidental that these two are also able to be used as backchannels (‘no’ in the case of negationin the triggering utterance), while other response particles cannot. This suggests that there maybe at least two classes of response particles, and that more research is needed to consider how elsethey may diஸfer.5.2 Research into ‘yeah no’The prevalence of ‘yeah no’ in natural discourse provides the clearest example of prps being usedin paradoxical responses. The theoretical question is obvious: how can one response simultane-ously accept and reject the content of a previous utterance? One possibility is that it does notsimultaneously accept and reject anything, that one of the response particles is doing somethingelse entirely. ‘Yeah’ is commonly used in backchanneling, but backchanelling does not mark thebeginning of a turn, making this explanation unlikely. The most plausible solution to the para-dox is that the response as a whole accepts one thing and rejects something else (Guntly, 2016).Work on ‘yeah no’ (or ‘yeah nah’) in Australian English focuses on discourse function. Bur-ridge and Florey (2002) found 29 total tokens from 25 speakers in recordings of various length,but they observe that two individual speakers, both men in their 40s, account for 10 of those to-kens, suggesting that a larger sample is needed to draw more robust conclusions. The authorsfocus on functional distribution, noting that it extends beyond the assent/rejection function of‘yeah’ and ‘no’ in isolation.Moore (2007) uses multiple corpora and observes that the discourse marker ‘yeah no’ serves“multiple functions simultaneously, as is characteristic of a discourse marker.” (Moore, 2007,p. 56). She concludes that ‘yeah no’ is a discourse marker that is frequently used “to preface sum-maries and evaluations” (Moore, 2007, p. 68) and to “create cohesion” and “perform an expressivefunction” (Moore, 2007, p. 58-59).Linguists have explored the use of ‘yeah no’ informally as well. In a series of blog posts, Liber-man (Liberman, 2008a,b,c) speculates that in the data he presents, both ‘yeah’ and ‘no’ are felic-itous on their own. A typical example is that in (11), which does not come from a corpus and is a164hypothetical example.(11) 1. A: Did you like Colombia?2. B: Yeah no, I loved it. Liberman (2008a)Liberman’s explanation is that ‘yeah’ can mean ‘Yeah, I liked it so much that I loved it.’ andthat ‘no’ can mean ’No, I didn’t like it, I loved it.’ But the critical point is that B does not use either‘yeah’ or ‘no’ with the followup content of “I loved it,” the speaker uses ‘yeah no’ together, plusthe followup content. Why? I would contend that the response does not really communicate thesame thing as the two options with the single response particle.Liberman oஸfers an additional insight into the distribution of response particles.The null hypothesis, I think, would be that yeah, yes, no, oh, etc. each has its ownfunction, and speakers emit instances of such words randomly as functionally ap-propriate, sometimes more than one in a row. This is probably false, if only be-cause the various diஸferent orders of pairs are typically diஸferent in frequency: “yeahyeah’’ and “no no’’ are about equally common, but “yeah no’’ is about ஹ஭ve timescommoner than “no yeah.’’ Liberman (2008b)These accounts focus on describing the use of ‘yeah no’ to “manage discourse” or perform“its own function.” The observations are interesting, and they suggest a pattern that is consistentwith the analysis I have proposed here. Previous work observes that there is a constrained set ofpossible uses and interpretations for paradoxical responses, which suggests that a constraint isoperating somewhere. Previous work also suggests that response particles may accept or rejectinformation based on criteria other than the truth value of the at-issue content; this raises thequestion of what those criteria might be. It seems that there is something systematic about theway response particles—and followup content—are used in tandem with one another.5.3 Opportunities for further researchThe ஹ஭nding that response particles can operate independantly from the followup content raisesseveral important questions that are nonetheless beyond the scope of this dissertation. The mostimportant questions concern the workings of the system: How do response particles select theirtargets? How does the followup content select its target? What constraints operate on the sys-tem?165Figure 5.2: Kri஺஽a’s Commitment Space Development (Kri஺஽a, 2015, p. 334)Part of understanding the overall system of responses and common ground management isunderstanding how response particles select their target when multiple potential targets are avail-able. Kri஺஽a (2015) might point to a potential answer, in that the components of commitmentspaces are nested, as in Fig. 5.2. The ஹ஭gure contains three boxes arranged one inside the other.The outermost box is the Commitment Space, the midlevel box represents S1’s assertion of ϕ,and the innermost box representes the “conventional implicature ϕ” (Kri஺஽a, 2015, p. 334). Whatif this nested arrangement suggests a sequence in which targets are selected by response compo-nents? If an outer box represents belief, for example, and an inner box the at-issue content, thenwhen the paradoxical response targeting beliefs, ‘yeah’ ‘disagree’, will target the outer layer, thebelief, with ‘yeah’ and the inner layer with the followup content. This is a vague suggestion builton nothing more than my own thoughts about the problem, and it certainly is not meant to im-ply an analysis by Kri஺஽a. It is simply a conjecture for a system other than randomness which mayplay a role in selecting the targets of response particles.One alternative is that there is a greater degree of freedom in the system in which responsesmay have preferred targets but can have alternative targets as well. Under such a system, ‘yeah’would be able to target belief if the absolute polarity of the triggering utterance and the followupcontent are not identical, it could target QUD if there was no possibility of answering it, and itcould target the at-issue content in other circumstances.The challenge for both of these systems would be make testable predictions that can disam-biguate between them. A hierarchical system would need to allow for the followup content totarget the at-issue content ஹ஭rst, which would allow ‘yeah’ to target the next layer; a potential testwould be when the “followup content” is something like “huh”, which neither agrees or dis-agrees. The degree of freedom system would need allow the response particle to test the variousconditions, perhaps by removing one of them. For example, an experiment could remove the166QUD by presenting two potential triggering utterances, each [+], and then a response of ‘yeah’plus ‘disagree’ (therefore with [−]) that could respond to either trigger.The key takeaway here is that the Response Target Hypothesis shows that the system of re-sponse is more complicated than previously assumed, and it creates the opportunity to exploreresponses in discourse in much greater detail.5.3.1 Intonational variationIt is well known that intonation impacts how an utterance is interpreted (Gunlogson, 2001;Goodhue and Wagner, 2015). We also know that intonational contours are highly variable (Liber-man and Sag, 1974). Goodhue and Wagner (2016) observe that intonational contours can signalimportant information such as contradiction. The variability in meaning may be due to severalpotential factors, including syntax, semantics, context or the demographics of the speaker andaddressee. And we also know that research continues into questions of intonation and its im-pact on discourse. Given all of that information, the question becomes: How do we deal withintonation in a study like this one?To take an example, (13) includes a simple adjacency pair. Fig. 5.3 depicts several diஸferentintonational contours of ‘yeah it is’ that are consistent with the message of the followup contentin (13). The intonational contours are very diஸferent; Fig. 5.3e has three peaks, for example, whileFig. 5.3b has a signiஹ஭cant dip. These contours are diஸferent enough to where it may be possibleto recover the meaning of the content afிer ‘it is’ without it being said explicitly.(12) 1. A: The chocolate marquis cake at Thierry is delicious.2. B: Yeah it is (plus additional followup)The question is how these various contours interact with the response particles and followupcontent to condition interpretation. The response of ‘yeah’ plus ‘agree’, which the contours inFig. 5.3 represent, is expected to signal agreement to the at-issue content. But to take Fig. 5.3e asan example, the explanation content, ‘And burnt coஸfee that’s been reheated in the microwave isdelicious too’, uses sarcasm to suggest that the speaker actually disagrees with the at-issue content.In terms of the Response Target Hypothesis, the question is whether intonation can out-weigh the polarity of the response particle and followup content. Let us consider (13).(13) The discourse associated with Fig. 5.3e1. A: The chocolate marquis cake at Thierry is delicious.2. B: Yeah it is. And burnt coஸfee that’s been reheated in the microwave is delicious too.167(a) Yeah it is, and so is thetiramisu.(b) Yeah it is, it’s literallythemost amazing thing youcan do with chocolate.(c) Yeah it is, but it’s so richit’s impossible to eat morethan a bite(d) Yeah it is, …I’ve neverhad anything from Thierrybefore.(e) Yeah it is, And burntcoffee that’s been reheatedin themicrowave is delicioustoo.(f) Yeah it is, but the triplechocolate mousse is a mil-lion times better.(g) Yeah it is, I’ve just eatenit so much lately I’m justtired of it.Figure 5.3: Intonation of ‘yeah it is’ from (12)(followup content written below each contour)As mentioned, the extended followup content afிer ‘it is’ suggests that Speaker B actuallydisagrees with the at-issue content. The question is whether the intonation alone can commu-nicate this suஸஹ஭ciently to outweigh the message of ‘yeah’ plus ‘agree’. If Speaker B just says ‘yeahit is,’ can the intonation alone communicate that this utterance is actually rejecting the at-issuecontent? My suspicion is no, but this is a testable prediction.5.3.2 Responses and Information StructureThe interaction of responses and information structure in conversation was set aside for this dis-sertation, but it is not because there is no relationship between the two. The role of focus, given-ness, newness and alternative ps and QUDs is well documented (Rooth, 1992; Stalnaker, 2002;Portner, 2007; Kri஺஽a, 2008; Brown et al., 2012; Beaver et al., 2017; Ozerov, 2018), as is the inter-action of information structure and intonation (Gunlogson, 2001; Rochemont, 2013; Goodhueand Wagner, 2015). Much of this work looks at how responses encode information beyond theat-issue content of an utterance, particularly alternatives to the at-issue content, as in (14).(14) a. α: Paul was driving. at-issue contentb. β: CHLOE was driving. alternative at-issue content, based on focus intonation168But what if a response particle is present? The Response Target Hypothesis adds another di-mension on which to analyze these scenarios by providing a mechanism to allow the response par-ticle and the followup content to have independent targets. An interesting question is whetherthere is a diஸference between the two responses in (15).(15) a. β: Yeah, CHLOE was driving. focus intonationb. β: Yeah, Chloe was driving. no focus intonationThe question is, do 9a and 9b diஸfer in terms of what the response particle is targeting? Doesfocus interact with the targets of response particles? If so, then this raises questions for howresponse particles select targets when focus is present.5.3.3 Other languagesMany languages use response particles to respond to questions and to utterances, and each lan-guage’s system of response particles is unique. Chapter 2 mentions the Romanian system of da,nu and ba (Roelofsen and Farkas, 2015; Farkas, 2010) and how they instantiate absolute and rel-ative polarity. In addition to the widely known oui and non, European French also has si, whichis used to contradict an assertion that contains negation (Pasquereau, 2018). Similarly, Germanhas ja, nein and doch (Kri஺஽a, 2013; Holmberg, 2012; Repp et al., 2019), where doch is also used tocontradict an assertion. In English, the evidence is mounting that ‘yes’ and ‘yeah’ are not inter-changeable (Guntly, 2016; Wiltschko, 2016, and this dissertation).A positive development in the study of response particles is the expanding body of researchinto understudied and non-Eurpoean languages around the world, including Japanese (Philips,1998; Hayashi, 2010; Sudo, 2013), Lao (Enஹ஭eld, 2010), Catalan (Batllori and Hernanz, 2013), WestFlemish (Haegeman and Weir, 2015), Cheyenne (Murray, 2009), Emb́si (Ndongo Ibara, 2011)and others.The Response Target Hypothesis predicts that other languages might also have paradoxicalresponses. In particular, it predicts that we might ஹ஭nd other languages where ‘yeah’ plus disagree-ing content can be understood as conveying acceptance of the belief and rejection of the at-issuecontent. Preliminary evidence from Gitksan suggests that this might be the case.(16) A Guksbackjok-tlive-PNClarissaClarissaga’a=hlLOC=CNArizona.ArizonaClarissa moved to Arizona.169B Ee’,yesnee=diiNEG=FOCwil-t.do-3SG.IIYes, she didn’t.’Consult [Laughs] “It’s an agreement when you say ee’, that’s an agreement. Yes, she didn’t… I’ve heard this when I was younger when the elders were talking and they were sayingsimilar things like this ... Ee’ needii wilt. B knows that she didn’t. A believes she did. Asays Guks jokt Clarissa ga’ahl Arizona but B knows that it’s not right. B is agreeingabout the person, not about the whole thing.” (emphasis mine)Matthewson (2020, with Hector Hill)The consultant’s comment at the end is illuminating, because he oஸfers an explanation of hisintuition. He is clear that “the whole thing,” the at-issue content, is rejected, but that the speakeragrees to “the person”. 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Cambridge University Press.179Appendices180Appendix ACorpus response forms from Chapter 3The following two tables, Table A.1 and A.2, include all of the responses from the corpus datapresented in Chapter 3. Their purpose is to consider the extent to which form alone can accountfor the impact of these responses on the common ground.The column labeled Stance in both tables of responses indicates what the speaker seems tobe rejecting or accepting. In Table A.1, the cases where the stance is labeled as commit q ≠ p, thisindicates that the followup content cannot be understood as signalling unambiguous agreementwith the previously introduced at-issue content. In Table A.2, where stance is labeled reject p, itcould as easily be labeled accept ¬p.What emerges from these tables is the observation that form alone is unable to account forthe status of the common ground at the end of the followup content. The crucial semantic infor-mation is missing, particularly polarity. As an example of what is missing, the data show that ‘no’plus agreeing content can enter information into the common ground, but only if the triggeringutterance contains negation; however, the presence or absence of negation in the triggering ut-terance is not re஺ாected in the form of the response. The form of the utterance does not preservethe original at-issue content or QUD either. The absence of information beyond the responseentails that an analysis based solely on response form will be unable to successfully account forall paradoxical responses.181Table A.1: Responses to p—‘yeah’RP Followup content Surface formcommitmentEx. Analysisyeah that’s true commit to p 409>>>>>>>>>>>>>>>>>>>>>>>=>>>>>>>>>>>>>>>>>>>>>>>;‘Yeah’+agree=aicincgyeah that’s true commit to p 41yeah i wouldn’t have thought so either commit to p 42yeah I’ve never been connected to identifying as amalecommit to q ≠ p 43yeah is this a dream? what’s going on? (rhetorical) commit to q ≠ p 44yeah and so my perception of it […] was like […] thisfeels punitive just for reporting somethingcommit to q ≠ p 45yeah She is awesome commit to q ≠ p 46yeah Rats are not mySpeaker A favorite animals, butISpeaker A could see getting one [as a pet] frombirth…commit to q ≠ p 47yeah ISpeaker A thinks they [builders] are trying tolower costs by cheapening in a lot of areascommit to q ≠ 49yeah we had cnn on while we were working commit to p 58} ‘Yeah’ + dis-agree, bel incg, reject aicyeah we have heat and some have air conditioningunitscommit to p 61yeah and my answer would be sure commit to p 629>>>=>>>;‘Yeah’ + dis-agree, acceptQUDyeah it’s been 2 1/2 years since you launched thiscompanycommit to q ≠ p 63yeah i don’t know (send them over to Iraq…[rhetorical suggestions])paradox 65182Table A.2: Responses to p—‘no’RP Followup content Surface formcommitmentEx. Analysisno he did not do the right thing reject p 559>>>=>>>;‘No’ + dis-agree, aic notin cgno you are not reject p 56no but that one of the reasons why he choseWilliams, that it has a solid liberal arts programreject p 57no she wasn’t asked to lie reject p 51 9>=>; ‘No’ + agree,aic in cgno the astronauts don’t do that reject p 52no they sure didn’t reject p 53no you’re absolutely right paradox 67}‘No’ + agree,reject QUDno but just with the sexism reject p 69183Appendix BCorpus DataThe corpus data included 100 examples of ‘yeah’ and 100 of ‘no’ from both the Linguistic DataConsortium (LDC) Fisher and Switchboard corpora and from the Corpus of ContemporaryAmerican English (COCA), for a total of 400 examples. Of these, 22 were included in the di-cussion of Ch. 3. The remainder are presented here.Table B.1 breaks down the number of examples by corpus. It includes the predicted outcomein the lefிmost column, the corresponding resopnse in the rightmost column, and the totals over-all and by corpus in between. The ஹ஭rst number in each cell is the overall number, and the numberin parentheses indicates how many of these were discussed in Ch. 3.The ஹ஭nal table, Table B.2, corresponds most closely to the data presented below. The table,like the data, is organized by corpus and ‘yeah’ or ‘no’, for a total of four sections. The numbersTable B.1: Corpus Data by outcome and corpusParentheses indicate the number of examples which were included in Ch. 3Outcome Total COCA LDC Response1 Accept AIC 132 (10) 60 (5) 72 (5) ‘yeah’ + agreeAccept AIC (negation) 69 (3) 31 (2) 38 (1) ‘no’ + agree2 Reject AIC 95 (2) 61 (2) 34 (1) ‘no’ + disagree3 Accept Bel, Reject AIC 32 (3) 16 (1) 16 (1) ‘yeah’ + disagree4 Accept QUD 35 (3) 23 (2) 12 (1) ‘yeah’ + disagree5 Reject QUD 37 (2) 9 (2) 28 ‘no’ + agree184Table B.2: Examples in appendixOutcomeCorpus and response 1 2 3 4 5 TotalCOCA ‘yeah’ 55 – 15 22 – 92LDC ‘yeah’ 67 – 15 11 – 93COCA ‘no’ 29 59 – – 7 95LDC ‘no’ 37 33 – – 28 98in Table B.2 exclude examples which were discussed in Ch. 3.The organization of the data follows Table B.2, in that sections are organized by corpus andresponse. Each section is further organized by whether the followup content agrees or disagrees;these subsections are organized according to the predicted outcome. No further analysis or dis-cussion is oஸfered; the organization is simply intended to re஺ாect the analysis oஸfered in the bodyof the dissertation. Within these smaller sections, there is no further organization.As with all other data, transcription conventions re஺ாect what is used in the corpus. The re-sponse particle for each data point has been bolded. As some exchanges contain more than oneresponse particle, one exchange may serve as more than one data point. The data in this sectionare also not “cleaned up,” in that the data is essentially in the same form as it was presented inthe database. Spaces may have been omitted between words, ‘n’t’ is ofிen separated in contrac-tions, capitalization and punctuation is ofிen missing, time stamps may be present, and otheranomalies may be found. I have, however, arranged the text on lines re஺ாecting the turns betweenspeakers, and where a speaker label was provided, I have included it.B.1 COCA ‘yeah’ (92 examples)This section includes 55 examples with agreeing followup content and 37 with disagreeing con-tent. Of these 37, ஹ஭fிeen were coded as accepting belief while rejecting at-issue content, and 22were coded as accepting the QUD.B.1.1 COCA ‘yeah’ + agree (55 examples)185(1) 1. JILL஡MARTIN- (08#41:36): You actually –2. SAVANNAH஡GUTHRIE- (#41:36): Or the kids.3. JILL஡MARTIN- (08#41:37): No. But you wear that purple tinsel in your hair.4. SAVANNAH஡GUTHRIE- (#41:39): Yeah That pink glitter in your hair.5. JILL஡MARTIN- (08#41:40): There you go. Okay. So over twenty collections again ontoday.com. The retail, forty-ஹ஭ve to ஹ஭fிy. The deal, twenty. Up to sixty percent oஸf.(2) 1. SMITH: How much does it have to do with power? How much of it is adventure andhow much of it is I’m the big politician, the head of whatever corporation, blah, blah,blah’?2. Dr-FISHER: Well, they get a lot of opportunities.3. SMITH: What’s that?4. Ms-BARASH: That’s right.5. Dr-FISHER: They get enormous number of opportunities, powerful men.6. Ms-BARASH: And we live in a patriarchal culture.7. Mr-TITUS: And power is sexy.8. Dr-FISHER: Yeah, power – women love-yeah.9. Ms-BARASH: Yeah.10. Mr-TITUS: And women are – women are ready to, you know, make some sacriஹ஭ces...11. Ms-BARASH: Yeah.12. Dr-FISHER: So do mice and sheep.13. Mr-TITUS:... to sleep with some important person.14. Ms-BARASH: And also there’s...15. SMITH: What’d she say?16. Dr-FISHER: So do mice and sheep. I mean, they – females of – both female speciesare attracted to the male with the best piece of real estate,186(3) 1. Mr-ORWOLL: Get hundreds of dollars of discounts. Go to londontown.com, youcan buy that.2. HOLT: Seventy-ஹ஭ve dollars. Then a great air fare and hotel deal.3. Mr-ORWOLL: For – yes. That’s oஸfered by Liberty Travel, libertytravel.com. You’restaying at the Sheraton Belgrade, ஹ஭ve-star hotel, your air fare from the East Coast andthree nights at the hotel.4. HOLT: And – and another deal, air fare, six nights in a hotel at 429 per person.5. Mr-ORWOLL: Yeah, from oஸfpeaktraveler.com. And that’s a budget hotel deal, butit’s six nights, if you want to stay.6. HOLT: But – but if you want to save a few bucks and see London. Let me quickly askyou about a warm-weather destination, because I’m afraid that’s what’s on my mindafிer coming in oஸf the plaza.7. Mr-ORWOLL: Sure. OK.8. HOLT: Puerto Rico and a place – Paradores. These are guest houses. Mr-ORWOLL:That’s right.(4) 1. LAUER: That’s right.2. CURRY: And I got to tell you, I loved you guys. You guys are so much fun.3. Ms-BETTY஡CHAVES: Hi. Ann.4. LAUER: It was fun having you here. Thank you so much.5. Ms-CHAVES: TODAY has just been wonderful.6. Mr-CHRISTOPHER஡HAS: Yeah.7. Ms-CHAVES: We thank everybody at NBC, we’ve had marvelous experience.8. Mr-HASLIP: Yeah. We had a great time.9. CURRY: I hope you’ve had fun.10. LAUER: We had a great time getting to know you. And good luck in your lives to-gether.11. CURRY: I know, and you will always be in my mind forever doing that one dance thatyou were doing. It was so much fun.18712. LAUER: When we come back, we’re going to play the Nearly-Wed Game right here.But ஹ஭rst, these messages. Thanks very much.(5) 1. CHRIS஡WRAGGE: Education?2. JENNIFER஡HARTSTEIN: Education, why not? Go ஹ஭gure out ways to learn more.Theres always opportunities. Maybe you cant go back to school full-time, but you cantake evening classes. They now have weekend classes. Theres online learning coursesthat you can take. So there really are new ways to expand the educational horizon. Andyou can take that chance, too.3. CHRIS஡WRAGGE: All right. And career and ஹ஭nance. Well put those in the samecategory.4. JENNIFER஡HARTSTEIN: Yeah, career and ஹ஭nance are tough. And you really haveto ஹ஭gure out what it is you want to do. We ofிen think that in our twenties we havethe opportunity to switch and move our careers a lot. The fact is there are people now,especially in the economic changes that are changing careers in their ஹ஭fிies and sixties.If theres something you love to do, ஹ஭gure out how to make sure your ஹ஭nances are inshape, so that you can switch gears and do something else(6) 1. while he may have been President for everyone, he wasn’t doing enough for the African-American community. So can you square the two and looking back, do you think Pres-ident Obama made some missteps with regards to the African-American communitynow seeing what President Trump’s being accused of doing?2. TA஡NEHISI஡COATES#Yeah. black people in this country make up I believe thirteen,fourteen percent of the population. Trump – that’s (INDISTINCT) –3. BIANNA஡GOLODRYGA#Thirteen percent.4. TA஡NEHISI஡COATES#Yeah. Trump’s base is a lot bigger, you know, so the numberof people, the sheer number of voters(7) 1. DAVE஡DAVIES#You had a memorable episode recently where you went to Vietnam.And you - I ca n’t remember whether you said this in an episode or whether I read itsomewhere else - you said the world tilted for you in a Vietnamese rice farmer’s home.1882. ANTHONY஡BOURDAIN#Yeah. the ஹ஭rst time I went to Vietnam, I just - I remem-ber comingaway from it thinking, I just - I have to have more of this. This is what Iwant to do with the rest of my life...3. DAVE஡DAVIES#More of Vietnam or more of that kind of(8) 1. …but I did hang out a lot with some teenagers who were sort of there long-term forvarious chronic health problems, mostly playing video games, to be honest, (laughter).I was 22 at the time.2. TERRY஡GROSS#That was probably really helpful.3. JOHN஡GREEN#(Laughter), Yeah. And so if somebody had an X-box, I would playvideo games withthem.4. TERRY஡GROSS#Did it feel awkward to be 22 and trying to help parents through aperiod when their child was, you know, dying or possibly dying? Did you feel like,who am I to(9) 1. WATTERS#Right, naturally. And Juan brings up an interesting point. So NBC hadno problem leaking the access Hollywood tape to the Washington Post, but accordingto Ronan Farrow, maybe had sat on this explosive story about Weinstein, Greg.2. GUTFELD#Yeah. The funny thing is Trump is basically making the same – in thatvideois making the exact observation that we are making. If you’re in a position ofpower you can grab whatever. Anyway, I came up with a theory – I did n’t ஹ஭nish it. Icame(10) 1. KJ APA (10:56:44): I know. I know.2. KATHIE஡LEE஡GIFFORD#56:45): Do you ever do anything about the nostril hair?Never mind.3. KJ APA (10:56:49): No, but they dye my eyebrows, as well.4. KATHIE஡LEE஡GIFFORD#56:51): Yeah, we can see.5. HODA஡KOTB- (10#56:51): They do.6. KATHIE஡LEE஡GIFFORD#6:51): It’s a lovely matching, yeah. KJ APA (10:56:53): Yeah.Yeah.1897. KATHIE஡LEE஡GIFFORD#56:54): How long did it take to get used to that, that lookfor you(11) 1. … we had upwards of a hundred men sending us threats. We actually had to have policeat our oஸஹ஭ce all week.2. GUY஡RAZ#Wow.3. WHITNEY஡WOLFE#They were emailing my employees, calling my employees, call-ing me, leaving the most vulgar messages.4. GUY஡RAZ#Because you’re self-proclaimed feminist organization.5. WHITNEY஡WOLFE#Yeah, female empowerment is not something that they believein, unfortunately. So,you know, we get this too. The bullying - now I don’t let - thatdoes n’t hurt my feelings anymore because I know these people are just atrocious. Butit fuels me. The anger(12) 1. GUY஡RAZ#OK. So I want to ask you ஹ஭rst about this idea of information asymme-try because, basically, your argument is that without pay transparency, the power dy-namic is heavily weighted in favor of the employer - right? - because they’ve got moreinformation.2. DAVID஡BURKUS#Yeah, exactly. So - and they have - I mean, it’s sortof like - it usedto be this way in buying cars, and that’s why we we’re all sort of so worried. But nowin an age of transparency of information, you can know everything(13) 1. … he’s the secretary of state of the United States. It’s - he’s pretty frustrated with that,that he feels like he ca n’t do his job.2. TERRY஡GROSS#One oஸஹ஭cial told you, the only reason why Tillerson has stayed thislong is loyalty to the country.3. DEXTER஡FILKINS#Yeah, you know, he’s an Eagle Scout. And there’s a lotof EagleScouts in the president’s cabinet, and there’s a lot of generals around him. And some-body said to me, the only people lefி around the president are generals and Boy Scouts.And they190(14) 1. …They should get an allowance regardless of what they do.2. KATHIE஡LEE஡GIFFORD#04:01): Hmm.3. HODA஡KOTB- (10#04:02): And it will help them learn to manage money and thingslike that. Chores, should just be part of what they do without getting paid.4. KATHIE஡LEE஡GIFFORD#04:07): Yeah. If they’re – if they’re getting the great bless-ing of being ina home and having there everything provided for them, then somethingshould be required of them.5. HODA஡KOTB- (10#04:15): Right.6. KATHIE஡LEE஡GIFFORD#04:15): My kids had to clear oஸf the table afிer –(15) 1. … the next couple of years will help doctors and lawmakers decide how to use thistechnology responsibly. Now, I’ve got to say I would do it all things considered.2. GAYLE஡KING#Yeah.3. CHARLIE஡ROSE#Absolutely. Knowledge is power.4. GAYLE஡KING#I agree with that mom, knowledge is power.5. CHARLIE஡ROSE#Yeah. And – and the more they are ஹ஭nding out, the more possi-bilities thereare to miss certain diseases.6. GAYLE஡KING#Right.7. CHARLIE஡ROSE#Sickle cell anemia, for example –8. GAYLE஡KING#Right.9. CHARLIE஡ROSE#– is one those that they’re ஹ஭nding out a lot about.10. TONY஡DOKOUPIL#Mm-Hm.11. CHARLIE஡ROSE#How you can(16) 1. MARA஡LIASSON#Thank you.2. STEVE஡INSKEEP#That’s NPR’s Mara Liasson.3. STEVE஡INSKEEP#OK, so the president seems open to at least temporarily undoinghis executive order on Obamacare. But he’s not at all happy with courts blocking histravel ban, which happened again.1914. DAVID஡GREENE#Yeah. for the third time, President Trump’s travel ban has beenput onhold. The latest version of the ban barred travelers from eight countries, six ofwhich are majority Muslim. This, of course, led to lawsuits. And among those whosued was the state of Hawaii(17) 1. CARSON஡DALY- (08#22:52): Afிer Selena paused for the applause from the crowd,she continued with her speech as she thanked her friends and family and for all thosesupport this past year. I know you interviewed them both.2. SAVANNAH஡GUTHRIE- (#23:01): Yeah I mean, there’s nothing surprising aboutthat moment. Those two womenare such close friends. And, I mean, Selena’s grati-tude to Francia is endless.3. HODA஡KOTB- (08#23:10): Yeah.4. CARSON஡DALY- (08#23:10): Yeah.(18) 1. SAVANNAH஡GUTHRIE- (#42:20): Putting the steal in Steals&Deals. I like that.Ooh, nail polish. These are cute little manicure sets, too.2. JILL஡MARTIN- (08#42:23): Yeah these are great for all ages. The NCLA nail polish.The retail, sixty-four dollars. Now, it’s a ஹ஭ve piece toolkits, the pouch and the twolacquers so you get everything you see here with the pouch. And I like that they’rethemes. So Troublemaker(19) 1. ANTHONY஡BOURDAIN#No way, Philly?2. ROBERT஡LUCAS#Oh, yes, for sure.3. ANTHONY஡BOURDAIN#Wow, that’s treason. Do they, like, change the plates ontheir car and, like, wear a disguise ? I mean...4. ROBERT஡LUCAS#It’s diஸferent. The poppy seeds help.5. ANTHONY஡BOURDAIN#Yeah, and I like this roll. It’s awesome. That’s delicious.Well, we’ve learned something here today. Jersey cheesesteaks - I’m not saying they’rebetter than Philadelphia - yeah, I am, actually, so there. This is great.6. ROBERT஡LUCAS#Glad you enjoyed192(20) 1. … passport, her birth certiஹ஭cate, her child’s passport and she was staying at a friend’shouse in Upstate New York. So prosecutors believe because she has some wealth thatshe is a ஺ாight risk.2. VLADIMIR஡DUTHIERS#All right.3. GAYLE஡KING#Once again I’m intrigued. Very good tease.4. VLADIMIR஡DUTHIERS#Yeah, I’m intrigued.(21) 1. … outஹ஭t I was wearing was, like, a knee-length dress with a cardigan and tights andboots. I just never wore that again. And I did n’t wear any form-ஹ஭tting clothes afிerthat.2. MELISSA஡BLOCK#You never wore it again to work because he had commented aboutyou in it.3. UNIDENTIFIED஡WOMAN##Yeah. And where I’m coming from is, like, OK, ifthesystem is n’t going to help me, what can I do to help myself? And this is what Ihave control over - is how I dress and ways in which I present myself.4. MELISSA஡BLOCK#She says(22) 1. …or I don’t want to be with just one woman. And your life, for years, was kind ofan echo of those songs. But you wrote about that kind of life in your songs in such adiஸferent way than all the other people who wrote about that.2. LOUDON஡WAINWRIGHT-#Yeah, I was - I had a chaotic, you know, ramblinglife.And it was interesting. And it was the life that I chose, but I did n’t feel goodabout it. I mean, I did n’t have a lot of bravado, you know? It was(23) 1. ROBERT஡SMITH#It sounds insane.2. STACEY஡VANEK஡SMITH#(Laughter) Yes, it does.3. ROBERT஡SMITH#And you have to love the folks at Genscape because they listenedto this, and they treated it like it was the most normal idea in the world.4. JOSEPH஡SPELINKA#Yeah. Probably, we can look at a diஸferent part of the visiblespectrum ora diஸferent part of the light spectrum to see growth quality the same waythey do for corn and other crops in the United States, yeah.5. ROBERT஡SMITH#What else can we do? Count trucks - avocado trucks193(24) 1. But in the things that were most important in life I ofிen went to her in my darkestmoments and she was the one that had the wisdom and the – and the guidance. Andso we both learned a lot in this experience.2. KATHIE஡LEE஡GIFFORD#30:32): Yeah, it’s a beautiful book. And Hoda and I areboth very,very close to our sisters. I ca n’t imagine being at odds with her.3. HODA஡KOTB- (10#30:38): Right.4. KATHIE஡LEE஡GIFFORD#30:38): She’s such a life force in our lives.5. IDINA஡MENZEL- ((25) 1. …of a screaming pig and live with that much more comfortably than I did the ஹ஭rsttime. And I can lie and say it tormented me forever and since, but, you know, I feltthat ugly emotion or lack of it, and I thought I should mention it.2. DAVE஡DAVIES#Yeah. You said, I did it this time without hesitation or remorse.3. ANTHONY஡BOURDAIN Yeah.4. DAVE஡DAVIES#But it was a relief when the screaming stopped.5. ANTHONY஡BOURDAIN#Well, yes, no one - no good person likes to hear or see ananimal in pain. That is monstrous. I mean(26) 1. …obsessive detective that we have in the popular imagination. Obsessiveness is ofிenlinked to this, like, genius of observation that just is not my experience at all. Like, Iஹ஭nd that my OCD makes me a terrible detective.2. TERRY஡GROSS#Because you’re focused on the wrong thing obsessively.3. JOHN஡GREEN#Yeah because I can’t notice the world outside of myself in the waythat Iwant to because I’m so deeply and irrationally focused on stuஸf that’s happeningkind of within me.4. TERRY஡GROSS#So the characters in your new book are also dealing with the deathsof parents. And in The194(27) 1. JOHN஡GREEN#Yeah.2. TERRY஡GROSS#So - and I really just kind of sympathized with her and admiredhow hard she was trying to have the right amount of connection with her daughterwithout being too pushy or smothering her or being overprotective.3. JOHN஡GREEN#Yeah, it’s really hard. it’s so - you know, parenting ateenager - I canonly imagine how hard it is. The great thing about having little kids is that at leastyou can solve their problems, you know? At least you know how to change a diaper(28) 1. In fact, what is interesting is, in the past 18 months or so, several states have actuallypassed state laws that forbid companies from asking prospective hires what your salaryat your previous job was. They’re trying to actually reduce the information asymme-try.2. GUY஡RAZ#Yeahbecause if they ask you that, you tell them the truth. In theirminds,they might be thinking, oh, well, that’s awesome. That’s like 20 percent less than wepay.3. DAVID஡BURKUS#Yeah, no. When I was teaching full-time, I used to tell(29) 1. …more with one person and less with another person. You know, you’re more quietand introverted with one person than another. So, like, did your parents change whenthey became couples with diஸferent people , and did you change when you becamepart of those diஸferent units?2. NOAH஡BAUMBACH#Yeah, I’m sure they did. And I mean, I observed it,and I’msure they did in ways that at that time I did n’t even see. I mean, I remember, like, theஹ஭rst Christmas afிer they separated and both of them got these big,(30) 1. DEIRDRE஡ALPHENAAR#We have been described as the James Bond of commodi-ties and energy markets by The Wall Street Journal, no less.2. ELIZABETH஡KULAS#Oh. That’s a pretty good pull quote . That’s the pull quoteyou want from The Wall Street Journal,3. DEIRDRE஡ALPHENAAR#Yeah. So that was pretty exciting.4. ROBERT஡SMITH#Deirdre explains that in the ஹ஭nancial world, everyone wants anedge - a little piece of data that no one else has. And Genscape sells them that data.195According to public documents, the company brings in around a hundred milliondollars a year(31) 1. …at the time, they were focused on one app, which was a consumer loyalty app calledCardify - kind of like a digital punch card for your favorite coஸfee shop, for your favoritewhatever it is.2. GUY஡RAZ#And he just told you about this at this dinner party.3. WHITNEY஡WOLFE#Yeah, we were just at a restaurant having dinner, just a few ofus. And I said, well, that sounds really interesting. And when he asked what I wasdoing, I said, you know, I’m really looking for a job. I could probably help you(32) 1. … like bars or clubs. It was all ages, people sitting, drinking warm beverage, listeningto singer-songwriters.2. OPHIRA஡EISENBERG#Yeah. I mean...3. JASON஡MRAZ#It was...4. OPHIRA஡EISENBERG#And this is before...5. JASON஡MRAZ#Perfect.6. OPHIRA஡EISENBERG#... You had to, like, promote yourself on Instagram or what-ever.7. JASON஡MRAZ#Yeah. We did have the Internet.8. OPHIRA஡EISENBERG#Sure.9. JASON஡MRAZ#But...10. JASON஡MRAZ#But itwas very basic. I mean, you had to hook it up to a phone line,but it worked. And I did have to hand out ஺ாyers. So it did require real legwork. Even-tually,(33) 1. …is undercutting these other strong, proud African-American men and using the mostracist images to do so. So that was Ali, you know? There was - there were no easy196answers. He was very complicated in these ways, and he didn’t really care about thecontradictions.2. DAVE஡DAVIES#Yeah, and some of these opponents admired him until he workedout on them verballylike that. Was he tougher verbally on black opponents than whiteones?3. JONATHAN஡EIG#That’s another one of the great puzzles. He absolutely was. Heshowed more respect for his white opponents. It’s almost(34) 1. KEIR஡SIMMONS- (08#35:29): – in many ways. The same kinds of struggles.2. VANESSA஡KIRBY- (08#35:31): Yeah.3. KEIR஡SIMMONS- (08#35:32): She is royal but doesn’t get to be the boss.4. VANESSA஡KIRBY- (08#35:35): Yeah, which she hates. Because she’s naturally, youknow?5. KEIR஡SIMMONS- (08#35:38): And she is naturally the boss.6. VANESSA஡KIRBY- (08#35:39): Yeah, naturally the boss. She’s a boss. (Excerpt fromThe Crown)7. KEIR஡SIMMONS- (08#35:42)(35) 1. …I was just a product of the culture of the’ 60s and’ 70s. But what’s really been mostdisturbing is liberal Hollywood, who has been very aggressive about promoting femi-nism, promoting the rights of women, and here was someone who publicly promotedit and practiced hypocrisy.2. ROBINSON#Yeah, and apparently there have been stories for years and years andyears, fordecades, about this guy Harvey Weinstein. For the record, there was not atime when what he did was acceptable, right?3. TODD#Let’s get that done, yes.4. ROBINSON#I mean, –(36) to know a person and knows who they are and how they tick and – and has a personalrelationship with them, it’s a totally diஸferent story.1971. GAYLE஡KING#Okay.2. NORAH஡O’DONNELL#Can I ask you about President George W. Bush spoke yes-terday and he said bigotry seems to be emboldened?3. REPRESENTATIVE஡PAU#Yeah. – well, I mean, I didn’t hear his speech but iden-titypolitics has gotten out of control in this country. And identity politics is beingplayed on the lefி and the right. it’s really dangerous for our country. And what iden-tity politics does is it seeks to(37) 1. …have done worst things and failed at Oxford, right as a Rhodes Scholar.2. KRISTEN஡HADEED- (09#44:32): Yeah.3. MEGYN஡KELLY- (09#44:33): Thank you both.4. RACHEL஡SIMMONS- (09#44:34): And I’ve done many, many things since.5. MEGYN஡KELLY- (09#44:36): Yeah, sure, including write this book.6. KRISTEN஡HADEED- (09#44:37): Yeah.7. MEGYN஡KELLY- (09#44:38): Thank you for coming on and talking about it openly.Ladies, thank you. (09:44:42): Coming up, we’ve got CMA Award winner and Grammy-nominated country star Lee Brice(38) 1. … has access to psychiatric help. But, that all of those people that saw that trauma won’t necessarily think that they need to seek out help. And he was hoping we could allspread the message that if you were one of those people, you should deஹ஭nitely do that.2. WATTERS#Yeah. Very traumatizing experience. All right. Our Democrats and Re-publicans close to anagreement on a new gun control measure following the massacre?An update next.3. PERINO#Democrats and Republicans in congress have long sparred on the subjectof gun regulation in America, but could they be nearing an agreement(39) 1. …had been before.2. UNIDENTIFIED஡WOMAN##Yeah. And so my perception of it, even though I doubtthat this is what went into it - but my perception was like, oh, this feels punitive justfor reporting something (laughter).1983. MELISSA஡BLOCK#Punitive to you, not to him.4. UNIDENTIFIED஡WOMAN##Yeah. And so that was a bummer because I was therefor the next yearand a half. And it changed the way that I trusted the system. And itchanged the way that - you know, if I saw him cleaning outside, I would just go all theway around(40) 1. GREG஡BAXTROM#Thanks.2. ALEX஡WAGNER#It tastes even better than the grape juice I remember.3. GREG஡BAXTROM#Yeah.4. ALEX஡WAGNER#Greg, I read – I read that that you got some culinary training.Well, obviously at some of the greatest restaurants in the world, but also in the BoyScouts.5. GREG஡BAXTROM#Yeah. I was in the Boy Scouts for – for really a long time.And,you know, in the beginning, you know, parents are doing a lot of the things for you.But as you get older, as you learn how to do things, you then are(41) 1. …going to behave that way, and to have accountability.2. SAVANNAH஡GUTHRIE- (#19:05): And it –3. TINA஡BROWN- (08#19:05): Well, the cool factor is important, that it’s just an uncoolthing to be this kind of a jerk.4. TED஡BUNCH- (08#19:09): Yeah. And it’s an invitation to men, not an indictmenton manhood.It’s an invitation to do things diஸferently.5. SAVANNAH஡GUTHRIE- (#19:14): And to change our culture.6. HODA஡KOTB- (08#19:15): Yeah.7. SAVANNAH஡GUTHRIE- (#19:15): And it really starts with(42) 1. …dollar. I’m totally getting that.2. STACEY஡VANEK஡SMITH#That is a good day.3. ROBERT஡SMITH#That’s a great day.4. STACEY஡VANEK஡SMITH#I mean, yeah.1995. ROBERT஡SMITH#But then you come back the next day.6. STACEY஡VANEK஡SMITH#And they’re, like, $3 apiece. Yes, all the time.7. ROBERT஡SMITH#Yeah. And who knows why, right? I would love some data thatwouldtell me how prices are going to change in the avocado market. Before we leaveGenscape, I give this pitch to Deirdre and her colleague Joseph Spelinka. I have theperfect name for our project. The(43) 1. …cheesesteaks - I’m not saying they’re better than Philadelphia - yeah, I am, actually,so there. This is great.2. ROBERT஡LUCAS#Glad you enjoyed it.3. DAVE஡DAVIES#That’s fun. That joint’s about ஹ஭ve miles from here. I’m going to getover there.4. ANTHONY஡BOURDAIN#Yeah, it’s good stuஸf.5. DAVE஡DAVIES#I’m going to get over there.Do you care about the reactions you getfrom the locals afிer the episodes appear?6. ANTHONY஡BOURDAIN#I care about the - yes. I - what I want to happen ideally- and it’s so weird. It(44) 1. LIANA HEDGE (09:04:47): Yeah. And –2. TAMARYN YODER (09:04:48): And then ten years afிer me, Adam came.3. LIANA HEDGE (09:04:50): Yeah. My –4. TAMARYN YODER (09:04:51): We adored him.5. LIANA HEDGE (09:04:52): Yeah. And he was ours. I mean, we –6. TAMARYN YODER (09:04:55): Mm-Hm.7. LIANA HEDGE (09:04:54): – he – we cuddled him, we held him. (Photo of Maryand Bill Yoder and kids)200(45) 1. …book. And my kids love it to this day. I read them that all the time.2. TERRY஡GROSS#My impression is you had a happy childhood. You’ve said you hada happy childhood.3. JIMMY஡FALLON#(Laughter) I really did. I know it’s odd for a comedian.4. TERRY஡GROSS#Yeah, that’s what I was going to say. It’s odd for acomedian. Somany comedians run on depression, anger...5. JIMMY஡FALLON#Yeah.6. TERRY஡GROSS#... Resentment and had, like, really diஸஹ஭cult childhoods. Do youthink that, like, your sense of humor was aஸfected by(46) 1. … at this construction site. It’s a few blocks from my apartment. They’re building anew part for the hospital. And she says you can go back in time and ஹ஭gure out howquickly the construction crews are moving.2. KATHERINE஡SCOTT#You can actually see that. That construction...3. ROBERT஡SMITH#Yeah. You see, like - you can see they - those used to bebuildingsthere, and they took it out.4. KATHERINE஡SCOTT#Yep.5. ROBERT஡SMITH#And, you know, I mean, if I did some analytics, you know, Icould use this data to ஹ஭gure out when they(47) 1. are grilled. I like to slice them down the middle to get a little more char on there –2. CARSON஡DALY- (08#49:14): I like that, too.3. CARRIE஡MASHANEY- (0#49:15): – because that’s my favorite part of the whole- -4. CARSON஡DALY- (08#49:16): Yeah. You double the surface area of the dog and youget a nice,crisp bite on twice as much meat.5. CARRIE஡MASHANEY- (0#49:20): Exactly. And the onions –6. CARSON஡DALY- (08#49:21): You got the onions going down.7. CARRIE஡MASHANEY- (0#49:22): Yep201(48) 1. and very problematic infection. And you’re also going to refer in the reading I’mabout to ask you to do to the microbiome, which is the collection of, you know, bac-teria and microorganisms in the gut. And so the goal is to always have a healthy mi-crobiome.2. JOHN஡GREEN#Yeah. I mean, one of the really weird things about being a personisthat about half of the cells inside of your body are not yours, they’re microbes. Andthat’s also something that is of some concern to Aza, and for that matter to me, to me.(49) 1. always raise, which is, you know, can you descend into this underground, describe itand not glamorize it? That...2. TERRY஡GROSS#But he kind of lived part-time in that underground.3. ANTHONY஡DECURTIS#He certainly did .4. TERRY஡GROSS#He used heroin, too.5. ANTHONY஡DECURTIS#He did use it.6. TERRY஡GROSS#Yeah, and he was the ஹ஭rst person to inject John Cale, his bandmatein The Velvets, with heroin.7. ANTHONY஡DECURTIS#That is true. Yeah, (laughter) I mean, all of that is true.They - I mean, it never really was his particular drug of choice(50) 1. actress. You like being other people.2. HODA KOTB (10:27:37): Yeah.3. IDINA MENZEL (10:27:38): Exactly.4. KATHIE LEE GIFFORD (10:27:38): And putting yourself out there is a whole otherthing, isn’t it? But this –5. IDINA MENZEL (10:27:41): Yeah. And it was a way to bond together. See, I’mtakingover. I’m going to let her speak.6. HODA KOTB (10:27:46): I know. It’s still happening.7. CARA MENTZEL (10:27:47): I remember – I remember saying – I remember saying202(51) 1. You like that?2. CARRIE஡MASHANEY- (0#49:53): Yeah.3. CARSON஡DALY- (08#49:53): Al, you cook a lot of dogs.4. AL ROKER (08:49:55): I do. I’ve never put cream cheese but this is great.5. CARRIE஡MASHANEY- (0#49:57): Yeah. And so with the jalapenos, too.6. HODA஡KOTB- (08#49:59):Wait. Is that Philadelphia cream cheese?7. SAVANNAH஡GUTHRIE- (#50:01): Oh.8. AL ROKER (08:50:02): Oh.9. CARRIE஡MASHANEY- (0#50:02): Deஹ஭nitely not, deஹ஭nitely not.10. BRIAN஡DUFFY- (08#50:04(52) 1. Stars, the one where it’s written from the point of view of a teenage girl who has - is itstage 4, cancer?2. JOHN஡GREEN#Yeah.3. TERRY஡GROSS#So my understanding is that’s based in part on one of your fans whoactually was dying of cancer.4. JOHN஡GREEN#Yeah. My friend, Esther Earl - she died of cancer in 2010 when she-was 16. And she was a really involved member of the community that grew up aroundthe videos that my brother and I made and was really involved in our charity projectsand became a friend of mine.(53) 1. the appeal of being nonbinary and also the attraction of traveling around in the camper.2. JAMIE஡SHUPE#But yeah, we went from the 3,000-square-foot house to the two-bedroom to the one-bedroom to the studio and - right? - which is almost to the puptent on the beach (laughter).3. SANDY஡SHUPE#Yeah, and I draw the line there. No, no - no pup tents on the beach.4. SHANKAR஡VEDANTAM#And that’s how we leave them - Jamie ஺ாowing like waterand Sandy the level ground nearby. Debates over gender quickly produce vitriol, angerand contempt. The folks who think biology203(54) 1. a pleasure to meet you.2. DANIELLE஡BRADBERY-#51:08): Thank you.3. MEGYN஡KELLY- (09#51:09): All right. So this is the one like you – you did this oneyourself. You’re in control. It sounds like you had something to say.4. DANIELLE஡BRADBERY-#51:15): Yeah. I was actually able to be a part of writingthis album because theஹ஭rst album, I wasn’t.5. MEGYN஡KELLY- (09#51:20): Yep.6. DANIELLE஡BRADBERY-#51:20): So there is a lot that I wanted to ஹ஭gure out just asan artist and as a person, being so young(55) 1. And he told everybody from the earliest possible age. This was not something that hecooked up when he became, you know, the Muhammad Ali. He always believed inhimself somehow.2. DAVE஡DAVIES#And Cadillacs and big houses were part of the dream, too.3. JONATHAN஡EIG#(Laughter) Yeah, he talked all the time about these mansions hewas going to build andhow many Cadillacs he was going to own. And he always talkedabout building housing projects and buying a house and living above the housingproject. He had these very speciஹ஭c dreams. And before certain ஹ஭ghts,B.1.2 COCA ‘yeah’ + disagree (37 examples)B.1.2.1 COCA ‘yeah’ + disagree, accept belief (15 examples)(1) 1. MAGGIE஡RODRIGUEZ: Welcome back to THE EARLY SHOW on this Tuesdaymorning. Weve got a fantastic crowd out here, including some kids and some folksfrom the Childrens Museum of Manhattan. My daughters favorite place on earth. Soimportant to support your citys local museums, especially kids museums because kidshave fun and learn a ton.2. HARRY஡SMITH: Thats a – its a great place. And as your daughter gets a little older,it will transfer to the Museum of Natural History.3. MAGGIE஡RODRIGUEZ: Yeah. She – shes kind of getting there already with thedinosaurs.2044. HARRY஡SMITH: Shes getting there already, right, right.5. MAGGIE஡RODRIGUEZ: Im Maggie Rodriguez with Harry Smith. And coming upin this hour, it captured the countrys attention when Facebook founder Mark Zucker-berg made an enormous donation – a hundred million dollars – to help turn aroundthe failing Newark, New Jersey, school system. Afிer all the hoopla about that dona-tion, it comes down now to this man – the mayor of Newark,(2) 1. I don’t even call myself a Mexican or a Latino. I usually call myself Zacatecano becausemy parents are from the state of Zacatecas. That’s my ethnic identity. But at the sametime, of course I’m American. I was born in this country. I’m speaking English, ofcourse I’m American. I don’t think there’s much of a question to it.2. CONAN: And Ruben, the language barrier, obviously not unique to Latinos but nev-ertheless diஸferent from a lot of Europeans who came here.3. Mr. NAVARRETTE: Yeah, and it’s similar to a lot of Europeans, as well. You look atthe German example. The ஹ஭rst group of people to be persecuted because of languagewere German-Americans. The ஹ஭rst victims, if you want to call them that, targets ofEnglish-only laws were Germans in the Midwest. And so, you know, that goes wayback. And I think the interesting thing there is there was once a time where peoplebelieved that Germans and Italians and Irish and Jews would never assimilate(3) 1. who’s given up guns because - like Sterling Hayden in Johnny Guitar and you’re ridinginto town. Like, you do n’t have a gun, but, like, you’re so tough and you’re so cool,you’re going to win no matter what anyways.2. JIMMY஡FALLON#Yeah. I probably was the sidekick to the cool guy where I still waskindof cool, but in my head, I saw myself getting shot oஸf a horse, which again, when Igo to therapy, something’s going to come from that.3. JIMMY஡FALLON#But I do n’t know(4) 1. we’re going to be the, you know, next big thing. And then shortly thereafிer, we startedgetting excited about this side project, Matchbox, which is what became Tinder. Butat the time , it was Matchbox.2. GUY஡RAZ#... Which was supposed to be a dating app.2053. WHITNEY஡WOLFE#Yeah, it was, like, a ஺ாirting app. It was, like,connecting peopleto ஺ாirt, right? And afிer we were really unable to get Cardify to gain signiஹ஭cant traction,we all - you know, the ஹ஭rst few of us were kind of like, maybe we need(5) 1. troubling to me because, you know, what comes afிer, if we do that?2. TERRY஡GROSS#And it’s hard to rebuild something. This whole, like, network oftreaties, and ambassadors and agreements, it’s hard to rebuild something like that if it’storn apart.3. DEXTER஡FILKINS#Yeah. I mean, you’re talking about - what you’re really talkingaboutis American leadership in the world. If you do n’t have American leadership,who’s it going to be? Is it going to be Russia? Is it going to be China? And I - you(6) 1. people who did similar drugs. And the people who were doing LSD and marijuanaand other drugs, those were the people I wanted to hang out with.2. DAVE஡DAVIES#You found a home in - among restaurant people , right? You droppedout of college, went to culinary school.3. ANTHONY஡BOURDAIN#Yeah. Well, I started working as a dishwasher one sum-mer. And it wasreally a big event for me because up to that point, I was lazy. This wasthe ஹ஭rst discipline, the ஹ஭rst organization because it is a very militaristic organization,the kitchen brigade, the ஹ஭rst people(7) 1. in the world, we’re all going to know about it.2. DEIRDRE஡ALPHENAAR#That’s right. Yeah. We’re all going to know about it. Andwe’re probably going to know within the day. And this is just one supply chain.3. ROBERT஡SMITH#It’s just oil.4. DEIRDRE஡ALPHENAAR#Yeah. It’s going to be the same for all commodities. Butit’salso going to be the same for how many new homes are being built, how much moretraஸஹ஭c are on the highways...5. ROBERT஡SMITH#Avocados. Soybeans.6. DEIRDRE஡ALPHENAAR#... How much more avocados are being grown. Yeah,206(8) 1. I make $50,000.2. DAVID஡BURKUS#So I believe that inside of a company everybody should know whateverybody gets paid.3. GUY஡RAZ#Which is crazy.4. DAVID஡BURKUS#(Laughter). You said it, not me.5. GUY஡RAZ#This is David Burkus. He’s a professor who writes about leadership andbusiness management.6. DAVID஡BURKUS#Yeah. But if you asked my 5-year-old son, I write books, I givetalks,and I take care of him.7. GUY஡RAZ#And David’s known for his ideas about salary transparency in the work-place.8. DAVID஡BURKUS#I mean, it’s sounds - you’re right. It sounds crazy,(9) 1. I go home. Its pork loin wrapped in prosciutto, you know, a lot of sage over the top ofit.2. ALEX஡WAGNER#Yum.3. ANTHONY஡MASON#And our beverage this morning?4. GREG஡BAXTROM#It’s a –5. ANTHONY஡MASON#With a lovely color, I must say.6. ALEX஡WAGNER#It’s beautiful.7. GREG஡BAXTROM#Yeah. It’s like a – it’s Concord grape. So, it sortof like a Welch’sGrape Juice. It’s like –8. ANTHONY஡MASON#Ah.9. GREG஡BAXTROM#It’s an heirloom –10. ALEX஡WAGNER#A real Concord grapes.11. GREG஡BAXTROM#Yeah. Real Concord grapes.12. ANTHONY஡MASON#You’re going back to207(10) 1. he does not represent the other 11 million individual who come to this country, theyplay by the rules. They work really hard. This guy is not one of them. And so to lumphim in as we’ve seen folks on the right do with them is unfortunate.2. CARLSON#Yeah. I don’t know if they’re living on the shadows. I have a lot of peo-ple here illegally on my show bragging about their status. I wonder if this is evidencethat the Democratic Party has changed. Hillary Clinton actually criticized the city ofSan Francisco two years ago for i don’t really get what’s going on here(11) have a model of it...1. STACEY஡VANEK஡SMITH#No.2. ROBERT஡SMITH#... Right here.3. STACEY஡VANEK஡SMITH#Oh, it’s so cute.4. ROBERT஡SMITH#Little Poddy (ph).5. STACEY஡VANEK஡SMITH#(Laughter).6. ROBERT஡SMITH#It’s about the size of a loaf of bread.7. STACEY஡VANEK஡SMITH#With, like, solar cell wings.8. ROBERT஡SMITH#Yeah, no. It’s got a little camera lens on it. So thatfeeling - thatfeeling you have right now, Stacey - that excitement about sending something you havetouched into orbit. It has a name. And it’s a name I heard over and over again when I(12) 1. don’t care what they do on their own time. But when they’re on the clock of theemployer, when they’re wearing the uniform of their team.2. MACCALLUM#They’re saying that the moment they can have the biggest impactbecause that’s when everybody is watching them.3. HUCKABEE#Yeah. But is that the proper place for politics? I mean, let’s face it,Martha, there’s a time and a place for everything. And if they really are that interestedin making political statements I’ve got a real good suggestion for them. Give up theirmultimillion208(13) 1. … coming said do you have an electric station at your home to charge my car? Is thatwhat it’s come to now?2. NICHOLAS஡THOMPSON#Well – so that’s – that’s, A, annoying, Gayle.3. CHARLIE஡ROSE#I have an electric car and I have a charging station.4. GAYLE஡KING#Yeah, but I mean, when you’re going to somebody’s house, I justsaw, wow, I never heard a questions like that.5. NICHOLAS஡THOMPSON#So that’s because we’re in a strange transition periodwhere things like that happen. A couple of years from now there will be(14) 1. And so then you feel like, you know - what? - I’m never allowed to have a rough day?I’m never allowed to be like, no, I do n’t want to take a picture with a fan? I just wanta coஸfee. Or...2. JASON஡MRAZ#Yeah, kind of. I mean, I learned early on that if I -let’s say - dis a fanor if I’m not in a good mood when I meet someone, they could be as proactive againstme as they are supporting me.3. OPHIRA஡EISENBERG#(Laughter) That’s true(15) 1. Four people killed in the United States, 1,500?2. BOOTHE#That’s also includes guns – that’s also includes gang violence.3. HARF#OK. (CROSSTALK)4. HARF#So it does n’t make it OK.5. GUTFELD#You’re using a speciஹ஭c term.6. HARF#Yes, and I just deஹ஭ned it for you.7. GUTFELD#Yeah. But it’s a miscalculation. You’re encompassing. You’re using aspeciஹ஭c term. And you’re talking all these others. A little bit dishonest.8. HARF#Whatever you want to call it, I do n’t think it’s acceptable that we’re the onlydeveloped country in the209B.1.2.2 COCA ‘yeah’ + disagree, accept QUD (22 examples)(1) 1. an elevator story for us, give us a call. 800-989-8255. Email us, talknpr.org You can alsojoin the conversation on our blog at npr.org/blogofிhenation. Nick Paumgarten is astaஸf writer for the New Yorker, and he joins us from our bureau in New York. Andthanks very much for coming in today.2. Mr-PAUMGARTEN-1St: Hi, Neal. Thanks for having me on.3. CONAN: And you said with your story about - your piece around the story of NicholasWhite, a man who was trapped in an elevator for 41 hours.4. Mr-PAUMGARTEN: Yeah. Poor Nicholas White went out for a cigarette break onenight while working at Business Week. He was a production manager there. He wentand had a cigarette, got back on the elevator and the thing stopped. And he spent thenext - yeah, 41 hours, a full weekend, in an elevator. By himself.5. CONAN: An event that we eventually ஹ஭nd out changed his life.6. Mr-PAUMGARTEN: It did. You know, Nick White holds that it wasn’t so much being(2) 1. going to ஹ஭nd out. And then later, bringing out the bright colors for spring. How toknow what you should be wearing when it’s time to shed those bulky coats. But ஹ஭rst,these messages.’ 40310602. HODA KOTB, co-host: We had a busy yesterday honoring a friend of ours.3. KATHIE஡LEE஡GIFFORD: Who didn’t even show up. Not by her own – not becauseshe didn’t want to show up.4. KOT5. B: Yeah, Ann Curry was honored as Mother of the Year by the American Cancer So-ciety. She and a really wonderful breast cancer surgeon as well, Dr. Heerdt.6. GIFFORD: Alexandra Heerdt.7. KOT8. B: Alexandra Heerdt. And...9. GIFFORD: By the American Cancer Society, by the way, yeah.10. KOT21011. B: Yes, what did I say?12. GIFFORD: Yeah, that’s who – that’s who honored.13. KOT14. B: Yeah, cancer. And Kathie Lee ended up being the emcee of the evening, or the(3) 1. I thought that was pretty remarkable that perhaps it is a lot more widespread. ChrisHayes who is a host at MSNBC said you have to wonder if Hollywood is staring atsomething that would be as big as the scandal that the Catholic Church went through15 years ago.2. GUILFOYLE#Yeah. And you had a good discussion about that today. The otherthing, Dana, just to follow very quickly is Steph McFarland had said that he had heardabout it or knew about it, was making jokes. At least there’s suggestion that there wassome knowledge and discussion about “i wonder about this problem” “Yeah it couldbe a problem” - not agreeing or disagreeing?(4) 1. Yes. And he could hear and feel my passion for this platform, and he said, you knowwhat? You need to build this, but you need to do it in dating. And I said ...2. GUY஡RAZ#(Laughter) Afிer you said I’m not doing dating.3. WHITNEY஡WOLFE#Yeah. And I said, I don’t think you understood me (laughter).I’m not going back into dating. Like, that’s not happening. And he said, no, no, no,this has to happen. What you’re trying to do needs to be(5) 1. world you hear a rising alarm in their voice about what we might potentially be facing.2. TERRY஡GROSS#You’ve been to Greenland, and you say you actually stood on landthat you might have been among the ஹ஭rst people to stand on because it wasn’t - it wasice before.3. JEFF஡GOODELL#Yeah, it was a very surreal experience. I was there with a scientistnamed Jason Box, and we were ஺ாying a helicopter over the Jakobshavn Glacier, whichis the fastest-moving glacier in the world. And he spotted this bare spot of ice, and hesaid, we have to land211(6) 1. to crack down on immigration to prevent threats like this from coming into the coun-try.2. ALEX஡EMSLIE#partially. But, you know, he also did n’t have any history of any kindof violent crime before Kathryn Steinle ’s death - some low-level drug convictions anddeportation - illegal re-entry-related crimes.3. RACHEL஡MARTIN#Yeah. So what’s been the reaction from the prosecution? Andjust more broadly, what’s the upshot of all of this now that a verdict has come in?4. ALEX஡EMSLIE#Well, I mean, the prosecution was disappointed in the outcome inthis case. They fought very hard and,(7) 1. there mostly doing data entry. But it - Booklist reviews like 400 books every two weeks.And, you know, all those books were written by somebody. So that’s when I started tofeel..2. TERRY஡GROSS#(Laughter) But were they read by anybody is the question.3. JOHN஡GREEN#Yeah. Not all of them, certainly. But that’s when I started tofeel like,OK, well, being - it’s not quite like being a professional athlete or being an astronaut.Like, this is something that regular people do. Lots of people write books. And(8) 1. TERRY஡GROSS#And it must be so - I do n’t have children, but it must be so inter-esting to have watched children who you did n’t expect to have become not only bornbut then, like, become full people and to see what that moment in your life led to.2. LOUDON஡WAINWRIGHT-#Yeah. Now I have four kids, and they’re all formidable.You know, three of them are singers and talented - and songwriters. And very talentedRufus and Martha and Lucy are in the business and doing well in their own particularand interesting ways. And Lexie is just out(9) 1. speech in the late 70s. He was always someone who was seen as – he was psychoana-lyzed by some of his critics. And so you can see a rapport as much as there’s a transac-tional play perhaps .2. TODD#And by the way, he still hasn’t forgiven the Clintons.3. COOPER#Yeah, I don’t know what to do with that. So, I...2124. TODD#There is a lot there. But it all comes down, he has not gotten over snubs fromthe Clintons. All right, guys, that’s all for today. Thanks for watching. We’ll(10) 1. odd for you to, like, come talk and, like, be in public and have to talk because - I don’t know. You’re just so used to - and you’re fantastic at your job. But, I mean, like it’sa diஸferent beast.2. TERRY஡GROSS#Yeah, I love the invisibility, yeah.3. JIMMY஡FALLON#It’s a diஸferent beast,but you did a bit with us. We played Pass-word, which is so fun.4. TERRY஡GROSS#I totally ஺ாunked out of Password.5. TERRY஡GROSS#Like, I’m ஺ாunking...6. JIMMY஡FALLON#But that’s the best.7. TERRY஡GROSS(11) 1. underestimate our viewer ever. we like to do smart stories. We like to do importantstories. And we – we always want them to get a better understanding of the worldbecause of what we’re reporting.2. CHARLIE஡ROSE#Talk about some of the correspondents you have worked with.3. JEFF஡FAGER#Yeah. Some of the greats, really. It’s amazing. I mean,beginning withDon Hewitt, actually, because he’s a big part of this book and he’s a huge part of ourstory. It would n’t have happened without him. Just a creative genius. And(12) 1. lot of money for some of this deadly equipment.2. CHARLIE஡ROSE#I’m wondering how well he covered up his tracks.3. BIANNA஡GOLODRYGA#Right.4. CHARLIE஡ROSE#He seemed so meticulously prepared.5. GAYLE஡KING#Yeah.6. BIANNA஡GOLODRYGA#Yeah.7. CHARLIE஡ROSE#And he also prepared so that people couldn’t ஹ஭nd things that helpedhim.2138. GAYLE஡KING#Yeah. A lot of questions still. The two biggest U.S. automakers aremaking ahuge bet on electric cars. Nicholas Thompson is here in our Toyota GreenRoom. Ahead – there he is, hello, Nicholas Thompson.9. NICHOLAS஡THOMPSON-#Good morning.10. GAYLE஡KING#How GM and Ford are racing to roll(13) 1. in the hospital, you know, trying to watch over their father and deal with the doctorsand the nurses and all the medical issues you have to deal with when someone’s in thehospital. Had you had a hospitalization experience with someone who you’re close toor yourself?2. NOAH஡BAUMBACH#Yeah. I mean, I’ve - that experience was, you know - insomeways came from my own experience being in the hospital - I mean, being with some-body who is in the hospital and, at the time, I mean, that just horribly vulnerablefeeling. But I(14) 1. if it all falls together. MICHELE஡KELEMEN#That’s right.2. RACHEL஡MARTIN#NPR’s Michele Kelemen - thanks so much, Michele.3. MICHELE஡KELEMEN#Thank you.4. RACHEL஡MARTIN#So we’ve got a verdict in a case that had become a focal pointin President Trump’s eஸforts to crack down on illegal immigration.5. DAVID஡GREENE#Yeah. So we’re talking here about a month-long trial that endedyesterday with anot-guilty verdict for an undocumented man in the death of KathrynSteinle in San Francisco. Here is defense attorney Francisco Ugarte speaking afிer theverdict.6. FRANCISCO஡UGARTE#From day one, this case was used as a means to(15) 1. editor of Bloomberg Businessweek who helped to compile the list. Bret, thanks forjoining us.2. BRET஡BEGUN- (Bloomb#Yes. You’re welcome.3. ALEX஡WAGNER#Let’s start with a man who is on many lists, but that does not di-minish his reason for being on this list, Jeஸf Bezos.2144. BRET஡BEGUN#Yeah, Jeஸf Bezos. It’s hard to argue that he didn’t have amassive year.On June sixteenth of this year, decides to drop 13.7 billion dollars on Whole Foods.Really, what he did in doing that is essentially signal to the world that he does n’t wantAmazon(16) 1. And there – thre she is, the Queen. (08:36:47): And some unexpected challenges forMatt Smith, who plays Prince Philip, the Duke of Edinburgh. (08:36:52): You have aspecial kind of walk that you do that is the Duke of Edinburgh –2. MATT஡SMITH- (08#36:55): Yeah. Well, he – he walked with his hands –3. KEIR஡SIMMONS- (08#36:59): Right.4. MATT஡SMITH- (08#36:59): – behind his backs. It’s like Danny from Grease, so.Yeah, I – I just love that he sort of lives by his own rules(17) 1. a lot of war, you know? I mean...2. TERRY஡GROSS#He’s seen a lot of war, right. So do you have any idea what kind ofwar he’s envisioning if we do go to war with North Korea? And I hate to even utterthose words.3. DEXTER஡FILKINS#Yeah, God forbid. there’s a lot of diஸferent options. And, Imean, I’ve had some discussions about what those options are. they’re all terrible.that the easy scenario to imagine - I mean, it’s a terrible scenario - is the moment theUnited States(18) 1. most afraid of contaminating you?2. JOHN஡GREEN#I mean there’s a - yeah, I’m being super intentional about not sayingthat (laughter).3. TERRY஡GROSS#Oh, OK, OK.4. JOHN஡GREEN#So yeah, that ’s the...5. TERRY஡GROSS#That’s ஹ஭ne. I don’t want to...6. JOHN஡GREEN#Yeah. That’s the only thing that I can’t. If I talk -I ca n’t talk directlyabout it because I get squirmy.7. TERRY஡GROSS#You get what, squirmy?2158. JOHN஡GREEN#Yeah.9. TERRY஡GROSS#Would it be awkward, too, for us all to know? Like, say we met(19) 1. We are back, eight forty. What a week of Steals& Deals and this is the grand ஹ஭naleof the gifி guide. TODAY contributor Jill Martin is back. And the best is last, gifிseverything we’re about see under twenty dollars.2. JILL஡MARTIN- (08#40:45): Yeah. I mean, I feel like everyone has so many peopleon their list and a budget. So we want it to be able that you can cross oஸf everyone onyour list. So twenty dollars and under and free shipping on all. So this is the price.3. SAVANNAH஡GUTHRIE- ((20) 1. Thomas Gunderson, later on the Facebook page, I will never lie down when the pres-ident of this great country comes to shake my hand. And he’s going to be on Hannitytonight, so hopefully everybody checks that out. Do you have something you wantto add?2. GUTFELD#Yeah. I just wanted to add, we’ve talked about the ஹ஭rst respondersandwe’ve talked about a lot of the brave citizens. The one thing we do n’t talk aboutare the dispatchers which are the police, ஹ஭re, and hospital dispatchers that are justinundated with information and misinformation(21) 1. that’s available. So this whole thing is kind of a diஸferent experience for me, and I- so every now and then, if someone brings it up or anything about kids books orsomething that, I can go, oh, yeah, I have a kids book.2. TERRY஡GROSS#Yeah, but you had - you were on Shaquille O’Neal’s lap while...3. TERRY஡GROSS#... He read your...4. JIMMY஡FALLON#With that...5. TERRY஡GROSS#How did you come up with that idea?6. JIMMY஡FALLON#I did n’t know he wanted me to have him on his lap. I...7. TERRY஡GROSS#You did n’t216(22) 1. And sometimes, that means working against the U.S. foreign policy best interests.Did you talk to Tillerson about that when you had a chance to talk with him? Anddid you get a sense that he’s trying to change his - the lens through which he sees theworld?2. DEXTER஡FILKINS#Yeah, a little bit. what’s amazing about Exxon - you know, it’sone of the world’s most successful corporations. It goes all the way back to StandardOil, you know, decades ago. It is an enormous company. its annual revenues are closeto $400 billionB.2 LDC ‘yeah’ (93 examples)This section includes 67 examples with agreeing followup content and 26 with disagreeing con-tent. Of these 26, ஹ஭fிeen were coded as accepting belief while rejecting at-issue content, and elevenwere coded as accepting the QUD.B.2.1 LDC ‘yeah’ + agree (67 examples)(1) 1. B: i used to use a lot of credit cards i guess for a while i would use you know a variety ofthe the Visa and the MasterCard and the stores but2. B: i think i i impulse buy too much with them or i buy things you know i see it on saleand i think oh it’s on sale i have to get it3. B: and i really don’t need it or i really haven’t budgeted for it so um the last couple ofyears i really have tried not to use them at all what about you4. A: Yeah5. A: well we have this philosophy we use it when we go oஸf somewhere6. A: but we pay for it as soon as we come back you know as soon as we get our bills wepay it oஸf and we only have one we tore all the rest of them up(2)1. B: i think that American manufacturers are getting a lot more2. B: um2173. B: pressure to compete in quality than maybe we saw you know ten or twelve ஹ஭fிeenyears ago4. A: um-hum5. B: that they’re they’re feeling the heat you know you see a lot of you know now uh youknow the ads that come out they’ll say you know ninety percent of our products youknow made in the USA6. B: you know that kind of thing we buy we buy American so you can too you knowkind of slogans7. A: um-hum8. A: yeah9. B: but uh so it must be a heightened you know awareness that way the uh10. B: um11. B: one thing i’ve uh well i jus-12. B: i don’t know how to say that cohesively so i’ll pass on that thought until it comesback in my head clearer13. A: Yeah i think probably they’re having to change some of their strategies due to sur-vival in a lot of situations uh i think the car industry is a good example of that(3) 1. B: we had more one-on-one since we seemed to know everyone on campus and we hada broad spectrum of languages and cultures and2. A: hum3. B: and backgrounds and so forth so i thought it was wonderful to be a bigger ஹ஭sh andnot so much a number um4. A: hm5. A: um-hum6. B: one of ஹ஭fிy thousand i was one of three thousand and and you know diஸferent per-spectives i uh but it sounds like we were both kind of looking at the same sort of sortof thing7. A: right8. A: um-hum yeah2189. A: y- Yeah i i could see i could see that point i could see how it would be i’m sure yourclasses were a lot smaller um because like we would have biology classes that did maincourses that everyone has to take i mean hundreds of students in this class so actuallyyes you were a number(4) 1. B: people aren’t tuned in to like saving for it and then buying it they just put it on acharge card put it on account and then pay oஸf the bill because they want it now it’salways have to have it now2. A: Yeah um well it didn’t hurt you did it to i mean you didn’t go out and charge awhole bunch and lose everything did you(5) 1. A: um yeah we had cat you know my family had cats when we were growing up thewhole time until my mom developed an allergies so i mean i’m used i’m used to havingcats around i like them2. B: Yeah i like having ca- cats around or pets around in general i- i favor dogs over catsactually but(6) 1. A: but um i could not charge to the limit and knowing that i was going to have to paythis thing out for ever and maybe suஸfer from having to pay out2. A: but that’s just the way i feel about it3. B: Yeah i think it’s it’s somewhat a um symptom of our4. B: me generation and that we think we need all these things(7) 1. B: you know even young couples buying a home they’ve lived in apartments that2. B: provide those things so they just assume they’ll be in a home3. A: Yeah that’s true(8) 1. B: what kind of a dog is he2. A: he’s part golden lab and part uh let’s see Alaskan no not Alaskan i always forget uhAustralian shepherd3. B: Yeah oh boy he’s a big one then huh4. A: and yeah he’s pretty big that’s why i- it really surprises me you know that219(9) 1. B: well you know that animals are like that they like to roam and investigate and2. A: Yeah i guess that’s yeah i guess that’s probably true(10) 1. B: well the han- in the hands of the wrong person the car can be just as deadly as aweapon as a as a pistol2. A: Yeah well i’m a bicycler and that scares me too to tell you the truth because i’vebeen run oஸf the road and all sorts of things(11) 1. B: well now down here we’ve got you know collection bins in the parks and things butthere’s no2. B: you know there’s absolutely no3. A: Yeah there used to be uh a big uh trash bin several trash bins in front of the Wal-Mart in town here that uh you could put plastic jugs on one side and newspapers onanother and glass on the third(12) 1. B: well i i’ll i hope you’ll ஹ஭nd him you most likely will2. A: Yeah we keep you know they they told us like at the Humane Society and theadoption center you know don’t give up hope you know and then(13) 1. B: well for not summer crops summer crops it’s uh it’s really not time to plant okra notquite the ground isn’t warm enough but uh2. B: some of those3. A: yeah no i uh i put down black plastic4. B: um-hum5. B: um-hum6. A: to help heat it up you know put it on the radishes and spinach but spinach kind ofbolts quick on us so we put it Swiss chard instead yeah7. B: Yeah right get that out early um-hum um-hum8. A: so anyhow that’s what we’ve done for our house we’ve lefி it all natural so there’sno upkeep you know it’s white cedar shingle220(14) 1. B: well a lot of companies are are coming down in price and i think that the insurancecompanies are starting to give uh beneஹ஭ts2. B: you know re- reduction in in medical costs if you know they3. A: Yeah yeah it’s got to help them too4. B: yeah so i think everybody will will beneஹ஭t from the program5. A: yeah i do too that’s right(15) 1. B: well a lot of companies are are coming down in price and i think that the insurancecompanies are starting to give uh beneஹ஭ts2. B: you know re- reduction in in medical costs if you know they3. A: yeah yeah it’s got to help them too4. B: Yeah so i think everybody will will beneஹ஭t from the program5. A: yeah i do too that’s right(16) 1. B: well a lot of companies are are coming down in price and i think that the insurancecompanies are starting to give uh beneஹ஭ts2. B: you know re- reduction in in medical costs if you know they3. A: yeah yeah it’s got to help them too4. B: yeah so i think everybody will will beneஹ஭t from the program5. A: Yeah i do too that’s right(17) 1. B: uh you probably have seafood a lot also2. A: Yeah they do oddly enough even being ne- near the gulf uh they tend to advertisethe the main(18) 1. B: uh it’s a ba- i mean it’s the basic premise with you know drug testing2. A: Yeah3. A: that’s right221(19) 1. B: uh he’s really aஸfectionate he likes to lay next to you and have you scratch his headand2. A: huh3. B: and and snuggle up to you and but if he’s not in the mood you’d better stay awayfrom him so but dogs seem to be always in the mood they’re always you know rightthere and like like you to pet them and loving and so4. A: Yeah that’s true i i like the way they come up and they’ll(20) 1. B: they’re both females2. A: Yeah both females they’re both spayed or whatever it is neutered(21) 1. B: that’s true if if it’s on the credit card it doesn’t seem like it’s money out of your pocketand sometimes you may think well i don’t have the money so you use the credit cardit’s like fake money or something2. A:Yeah and it gives you a sense um a false sense of security or something it seems likebecause you say oh well i don’t have to pay for it now but you’re going to have to payfor it and it seems like(22) 1. B: right well we seem to agree on the jury thing and uh but uh we’ll need an unanimousverdict and maybe let the judge have a opportunity to make the sentence yeah2. A: Yeah3. A: i think we should try it like you say if it doesn’t work we can always come back buti think it would be a good idea to try it(23) 1. B: right well do you have crabs and lobster in that area that’s2. A: ye- Yeah yeah crab and lobster and and uh(24) 1. B: people i think probably prefer natural gas for for heating2. A: Yeah uh-huh i would too because me i like gas heat i love it222(25) 1. B: oh i’m i’m a dog person i had i guess it depends on what you had when he were akid right2. A: Yeah probably i was allergic to dogs when i was a kid in fact i may still be um we(26) 1. B: mandatory drug testing we’ll reduce your insurance costs by you know twenty percent and of course you know the company’s not going to reduce the employee’s costof insurance twenty per cent they’re going to reduce their own2. A: uh-huh3. A: no no but i- it’ll save in some areas yeah right4. B:Yeah and that’ll cover it and maybe some insurance companies might start oஸferingit as a uh5. B: as part of the package(27) 1. B: it’s uh you know it all starts to become similar there’s you know there’s beneஹ஭ts andthere’s things that weren’t as good but as an overall package i’d say i i’m pretty happyso far with the way it’s turned out2. A: Yeah3. A: good good well hasn’t been a long time TI or i i’m(28) 1. B: it’s the same principal when there’s a drought they ஹ஭ne you for using water youknow they just2. A: yeah3. B: you don’t do what they say and you4. B: not that i promote over government or anything but you know the the world’s ina bad enough state that5. B: you know i6. B: people being the way they are you kind of need some incentive7. A: Yeah it would deஹ஭nitely help you know even if they were to uh uh pay like forrecycling aluminum or223(29) 1. B: it was like a dead end on the other2. B: on the other end of the phone3. A: oh was that yesterday4. B: yeah uh-huh5. A: oh yesterday i wasn’t home my friend picked up6. B: oh yeah7. A: so i didn’t know what it was yeah yeah yeah8. A: but i like i what was it do you know what the day before it was9. B: no uh-huh i just started um10. B: actually yesterday11. A: Yeah oh you started yesterday12. B: yesterday is my ஹ஭rst day(30) 1. B: if you look at uh some countries you expect them to have problems Latin Americanow with cholera and and a bunch of other problems associated with2. A: um-hum3. B: waste management4. B: the United States you can expect more out of but we still have the same very deepproblem of how to take care of our waste we create a bunch now now what do we dowith it5. A: Yeah now that now that it’s getting harder to get permits for landஹ஭lls uh the theproblem’s pressing down harder than ever(31) 1. B: i thought this whole switchboard thing was shut down i was surprised to get thecall2. A: Yeah so did i but i thought i’d try one more time and sure enough it’s okay(32) 1. B: i think all around it it’s going to help out a lot course2. A: Yeah i do too224(33) 1. B: i imagine uh in in Texas there would be uh a lot of steak restaurants is that right2. A: Yeah there seem to be quite a few quite a few(34) 1. B: i have trouble with the chemical plants and things like that i just uh i think theyput oஸf so much and they’re not regulated enough2. A: Yeah that’s me too afிer um on channel thirteen uh they had some(35) 1. B: he said something about if you can win a million dollars would you not talk to yourbest friend anymore or something like that2. A: oh would i would you give up your friend for money is that what it was3. B: i think that’s the bas- what the basis of it was4. A: ah there isn’t enough money for in the world for that5. B: Yeah and i and i totally agree i don’t think i would give up i would give up myfriendships my best friend for that no ’cause once all the money’s gone then ah thenyou just have yourself your your friend will always be there for you yeah6. A: no not for money7. A: (( not for money ))(36) 1. B: and uh you know Texins is is not uh well i don’t think it’s2. B: really directly supported by TI i think it has it’s own kind of funding but somethinglike that that you know you would have to be a TI or a Texins kind of um does it3. A: Yeah i think that would take care of any questions about competency for peoplerunning the show(37) 1. B: and then she grew to be you know i had pictures of her when she would sit on myhand and then she grew to be pretty big you know like a pound or something i don’tknow how much and i had her for over two years and she was very aஸfectionate shewould you know2. A: uh-huh2253. B: crawl on me and she would sit like on my neck or my shoulder while i was workingand things like that yeah much more than you would think4. A: Yeah i mean you know if you get them young and everything before they go kindof nuts so yeah rats are not my favorite animals in the world but i could see gettingone from birth and everything5. B: yeah i sort of weird for me to have had one too but there it was a convenient littlepet to have because it stayed in it’s cage and you know it was easy easy to take care ofand but6. A: yeah i- i i have friends with hamsters and gerbils and they they tell me the samething i just again it gets into these aren’t much fun you know what i guess they can bei(38) 1. B: and then she grew to be you know i had pictures of her when she would sit on myhand and then she grew to be pretty big you know like a pound or something i don’tknow how much and i had her for over two years and she was very aஸfectionate shewould you know2. A: uh-huh3. B: crawl on me and she would sit like on my neck or my shoulder while i was workingand things like that yeah much more than you would think4. A: yeah i mean you know if you get them young and everything before they go kindof nuts so yeah rats are not my favorite animals in the world but i could see gettingone from birth and everything5. B: Yeah i sort of weird for me to have had one too but there it was a convenient littlepet to have because it stayed in it’s cage and you know it was easy easy to take care ofand but6. A: yeah i- i i have friends with hamsters and gerbils and they they tell me the samething i just again it gets into these aren’t much fun you know what i guess they can bei(39) 1. A: yeah pretty much so but other other than that i know some also who’s claim thatuh afிer they have their kids or started having kids they’re going to quit their job anduh dedicate their time to raising the kids right2262. A: according in in putting it in their words3. B: oh4. A: and staying at home so i don’t know i guess each way has it’s advantages5. B: Yeah well it’s whatever they feel comfortable with you know basically whateverthey feel best and there’s probably some women who6. B: may not do their child any good being there all the time because you know theythey they can’t uh quite see themselves you know dedicated that much(40) 1. A: yeah and there’s you know there’s people in our prisons that are not being rehabil-itated in any way shape or form and either they’re in there forever or when they getout they’re you know it’s a matter of a few months and they’re gonna be right backfor the same thing so the syst-2. B: Yeah we’re just not willing to as a society not willing to spend the time or themoney to3. B: do what it takes yeah(41) 1. A: yeah and i think outside you can just kind of kick back and and visit afிer dinnerbut is seems like when you’re inside the ஹ஭rst thing you know someone has turned ona TV and that kind of is the end of your party i think2. B: yeah3. B: that’s true yeah(42) 1. A: where i work there they have uh uh recycled paper2. A: thing so you just you have two trash cans in your oஸஹ஭ce one one is for the regular3. B: right4. A: non recyclable trash and is for paper yeah and you know i think it’s great i use it allthe time5. B: Yeah you’re TI right227(43) 1. A: well we’re way up the other end of the state we’re uh half way between Chicagoand Indianapolis on i sixty ஹ஭ve so and Terre Haute is you know it’s like three hourssouth2. B: Yeah well i know when we ஺ாew up there we ஺ாew into Indianapolis and then hadto drive down there so yeah3. A: yeah this is a little town of ஹ஭ve thousand just a perfect little town for us retiredpeople and for raising children and(44) 1. A: well we’re way up the other end of the state we’re uh half way between Chicagoand Indianapolis on i sixty ஹ஭ve so and Terre Haute is you know it’s like three hourssouth2. B: yeah well i know when we ஺ாew up there we ஺ாew into Indianapolis and then had todrive down there so yeah3. A: Yeah this is a little town of ஹ஭ve thousand just a perfect little town for us retiredpeople and for raising children and(45) 1. A: well tell me uh do your homes down there pretty much have garage disposals andthings like that2. B: Yeah they have everything(46) 1. A: well i personally don’t have any problem with uh drug testing employees or po-tential employees do you2. B: um3. A: i mean basically4. A: okay5. B: basically no6. B: um7. A: i don’t i really can’t disagree with it8. B: Yeah i i uh uh the policy that TI has i think is uh uh very fair228(47) 1. A: well i haven’t made the calls mostly i’ve just uh i answered them i live in a two storytype colonial here in Maryland2. B: Yeah that that i heard i know those words from the east when i was there but thatthey don’t use that word here3. A: yeah well most the homes here are two story because uh they stack them up sincethe property is so expensive at least in the Maryland area where i am(48) 1. A: well i haven’t made the calls mostly i’ve just uh i answered them i live in a two storytype colonial here in Maryland2. B: yeah that that i heard i know those words from the east when i was there but thatthey don’t use that word here3. A: Yeah well most the homes here are two story because uh they stack them up sincethe property is so expensive at least in the Maryland area where i am(49) 1. A: well i don’t mind electric heating and and the like it’s okay i mean i i like gas heatbecause it’s so nice and warm but when it comes to cooking i c- i just absolute think agas stove’s the best that money can buy2. B: yeah well i’ve heard peop-3. A: you just can’t beat cooking on gas4. B: Yeah i’ve heard people say that(50) 1. A: uh on about a quarter of an acre or less about ten thousand square feet2. B: Yeah the lots aren’t very big here either in the Dallas uh Fort Worth area(51) 1. A: that’s right that’s right oh gosh well it’s it’s a real problem i’m sure2. B: Yeah3. B: i have friends that work in other companies that are just now adopting the policyand and stuஸf and i uh uh i moved to a TI facility that um had never had uh randomdrug sampling before229(52) 1. A: that isn’t that funny how we do i mean we just really2. B: yes well you know they’re always there for you and they don’t talk back to you anduh it’s kind of pleasant yeah sure sure3. A: Yeah well they’re companions you know they’re really well do you have any p-4. B: yes we have a l- a dog a little white Lhasa5. B: and her name is Angel and we have a cat who a white cat he’s he’s just a Tabby justa and his name is Dominique we call him Neek but(53) 1. A: so the jury didn’t know about it so here they based their sentencing2. A: thinking that this was this guy’s ஹ஭rst oஸfense and so you know we’ll give him ஹ஭fிeenwhich’ll teach him a lesson but it’s not just3. B: sure4. A: you know horrible since it was ஹ஭rst oஸfense and he’d been convicted three timesbefore you know and and the jury was very upset and my husband came home at homevery upset i mean he felt like that that they had been tricked you know and so5. B: yeah6. B: yeah7. B: right8. B: that9. A: something i wonder if a judge didn’t have control of that if some of that wouldchange you know10. B: Yeah and the judge might know or at least it it wouldn’t hurt to switch over thereand see if it worked any better if it didn’t we can come back for something else or orwhat we’ve got so well so we deஹ஭nitely need a change in the system and uh(54) 1. A: or or to give their child the leeway to choose their school not so much choose theschool for them but you know kind of guide them along but let them more or lesschoose what they need and what they’re going to do2. B: Yeah2303. B: i think it helps uh uh now my grandfather was going to pay if i went to uh what’snow UT Arlington because it was there in my hometown i could live at home but ichose to go to another school(55) 1. A: oh it’s a uh long story but uh let’s discuss about our homes um what kind of homedo you live in2. B: uh i guess a typical home here is without a uh uh basement i guess that’s the classicaluh3. A: raised style4. B: Yeah uh we have something here we have something here you may not have upthere which is a well we we were phasing them out is the wood shingle roof i don’tknow if you had it when i ஹ஭rst got here(56) 1. A: now i thought that was just a sign of the times we’re all stressed out that’s whatthey’re trying to tell us that that we now get upset because we have to wait in line orwait in traஸஹ஭c but in in reality there’s so much more traஸஹ஭c and so many more lines and2. A: really like you say something needs to be done about that too3. B: Yeah it just seems to be a waste of time(57) 1. A: i wasn’t aware of that i thought they were more or less all the same2. B: Yeah so did i that’s that’s it was news to me too i thought it was kind of interestingthough(58) 1. A: i understand well uh you say you live in a ranch style house yourself2. B: Yeah it’s it’s multilevel yeah like my garage i have uh uh a bedroom over(59) 1. A: i guess you have to weigh the ஹ஭nancial beneஹ஭t of having somebody else take careof your kids if uh the working wife can uh make uh more than enough to handle thatexpense i guess it’s worthwhile2. B: Yeah it gets to be kind of expensive and i think you know some of the woman douh weigh that um231(60) 1. A: i forget how she got it but it was um it was the same kind of a deal i think she gotit i think she was a psych major and she got it from the psych department2. B: Yeah mine had been a a a3. B: how did this work a male rat had been bought and the people in the lab one daycalled in my friend and said you know this rat is acting really strange i think he’s sickand she said i don’t think he’s sick i think she’s pregnant(61) 1. A: dogs are real high maintenances you got to take them for walks and you’ve got topay a lot you know you need to pay attention to cats and everything but it’s not quitethe same thing um and um2. B: Yeah that’s true(62) 1. A: Defense Electronic Division when i retired i know it was a you know it was a realhot hot item there i think i want to think maybe they you know really got some nudg-ing from you know D O D to do this sort of thing2. B: yeah i used to be in DSEG myself3. B: um A P D as a matter of fact4. A: Yeah so you knew you know the atmosphere then(63) 1. A: but a lot of people i think afிer they thought about it for awhile and you knowweighed the pros and cons decided you know it’s really not a bad idea unless you’redoing drugs of course2. B: Yeah3. B: i mean uh you should have no objection to it it’s like uh going down to get yourlicense and checking your eyes i mean you know why do i need my eyes checked wellwe want to make sure you can see(64) 1. A: before i retired so i was not uh ever called upon to do a drug test i certainly wouldn’tobject to it and i think random is probably you know the only really fair way to do it2. B:Yeahum i like it because um you know i i i grew up in the sixties i mean i graduatedhigh school in sixty eight and232(65) 1. A: and take them down and throw it in there i mean i think that would be great i i’dsupport that entirely because2. A: you know as a country we produce way too much garbage it’s it’s it’s phenomenal3. B: Yeah way too much well i know just as an individual you know i know how manytimes i haul out a bag of trash and it’s like incredible if you multiply that times every-body(66) 1. A: and my husband’s sister is the world’s worst at oh well i’ll just use the credit cardsand she has all of her credit cards up to the limit2. B: um3. A: you know and i’m i’m thinking woman wake up and smell the roses before theycome and get you but4. B: right besides the fact that how much interest you pay and then this5. A: right and people don’t see that either6. B: Yeah this thing that you thought you got on sale by the time you get done payingwith that with all the ஹ஭nance charges because you pay it oஸf over a long period of timeyou’ve spent a heck of a lot of money on that thing(67) 1. A: and get your money back or at least exchange it for another bottle that’s full youknow2. B: that’s true3. A: um i haven’t seen that done for a long time either4. B: Yeah no deposit no return5. A: yeah everything’s no deposit no return or else it’s all plastic jugs that you just pitchyou know uhB.2.2 LDC ‘yeah’ + disagree (26 examples)B.2.2.1 LDC ‘yeah’ + disagree, accept belief (15 examples)233(1) 1. B: oஸfered that our forefathers wouldn’t have even crossed their brains to have expectedyou know a dishwasher or a disposal or uh uh2. B: track lighting or garage door opener you know those ki- the fancy bathrooms andstuஸf and yet the sturdiness of them3. B: doesn’t a- al- doesn’t always44. B: measure up5. A: Yeah i think they’re they’re trying to lower costs by cheapening in a lot of areasdisagree slightly, in that it’s not a wholesale acceptance(2) 1. B: and then she grew to be you know i had pictures of her when she would sit on myhand and then she grew to be pretty big you know like a pound or something i don’tknow how much and i had her for over two years and she was very aஸfectionate shewould you know2. A: uh-huh3. B: crawl on me and she would sit like on my neck or my shoulder while i was workingand things like that yeah much more than you would think4. A: yeah i mean you know if you get them young and everything before they go kind ofnuts so yeah rats are not my favorite animals in the world but i could see getting onefrom birth and everything5. B: Yeah i sort of weird for me to have had one too but there it was a convenient littlepet to have because it stayed in it’s cage and you know it was easy easy to take care ofand but6. A: yeah i- i i have friends with hamsters and gerbils and they they tell me the same thingi just again it gets into these aren’t much fun you know what i guess they can be i(3) 1. A: yeah well if they went AWOL what are you going to do shoot them put them in jail2. B: Yeah i don’t know send them over to Iraq have a vacation in Iraq for a year234(4) 1. A: i would think you know he might i mean he might could get hurt by a car or some-thing i don’t know that he could really get killed that easily because he is so big youknow but i don’t know2. B: Yeah oh well i i hope he comes back that’s too bad how long have you had himwhere is the ‘yeah’??(5) 1. B: very good uh uh the uh planning for college tuition and all the associated costs is atough tough decision at2. A: Yeah i think it’s it’s when you’re looking for a college that you want to go i thinkyou really should know exactly what you want to be so you can pick the best quality(6) 1. B: i wouldn’t have thought that Pillsbury could would the i mean or even had chem-you know well2. A: Yeah they have chemicals that they use to reஹ஭ne their ஺ாours with and stuஸf youknow to to break the ஺ாours down and then they they also do testing there and i don’tyou know wh- when you consider you know it’s probably not radioactive but toxic canbe referencing the QUD - chemicals @ pillsbury - not really agreeing or disagreeing?(7) 1. B: do you have a basement2. A: yeah3. B: oh yeah that’s typical up there to you know4. A:Yeahwell like i say the land here and depending on where you are and how crowdedit is the land bays go up and here a little old measly quarter of an acre goes from any-where from four to ஹ஭ve thousand to a hundred and some odd thousand depending onwhere it is “yeah well(8) 1. B: and i think well what if somebody’s dumped something back there in the and noone knows about it and you know it sinked in through the ground and all that2. A: Yeah well i know out in some i’m not sure referring back to the QUD but notagreeing?3. A: well i would imagine all you need is just air-conditioning2354. B: yeah we we have heat uh some have air-conditioning units i i i have an all electrichouse but uh it’s ஹ஭fிy ஹ஭fிy there’s a lot of gas houses here uh because it’s so popular“yeah, well we do have heat as well as air conditioning”(9) 1. A: um they generally go abroad and and uh serve but they don’t get a salary and theygive up uh X number of years of their lives to do this2. B: Yeah but they must get some compensation somewhere(10) 1. A: that’s uh that’s a good thought now see i hadn’t thought about it that way myஹ஭rst uh thought was when they mentioned that was to people who go abroad and doservice abroad2. A: and perhaps there might be as you say more of an eஸfort here needed3. B: Yeah4. B: and we’ve done5. B: we’ve sent6. B: people abroad and the people that do go abroad are are usually7. B: um8. B: college educated talking about people abroad - doesn’t really agree than an eஸfort isneeded but talks about college educated individuals.(11) 1. A: so there could be a lot of things that they could put you know that chemicalwisethat they use to uh that they are testing with2. B: right you know like in3. A: that they’re dumping4. A: yeah5. B: in packaging and uh you know just goodness6. A: Yeah i don’t think they do the packaging at this plant but they do they do a lotof research and they do um they do do a lot of the reஹ஭ning up there or i’m not reallywhat’s it called when you do ஺ாour i’m not yeah, I don’t think they do the packaging..236(12) 1. A: so i’m not sure how anybody checks up on that but um i think there’s a maximumnumber of kids that they can take care of at any one time2. B: Yeah there’s been a few people that have kind of used the same person kind of likeword of mouth one person in the department had them and(13) 1. A: okay so they do go garage because i lived down south for a long time carports werereal popular in certain areas where i2. B: Yeah not Dallas uh Fort Worth is you know the two car garage and certainly allair-conditioned uh(14) 1. A: i agree it doesn’t always work that way the way it was intended and then the peoplechange in this country too and not and are not able to see it through our administra-tion changes also2. B: yeah3. A: so4. B: Yeah i’m kind of uh a dreamer i guess i st- i still believe in5. B: we could put this country back to work we could bring the steel mills back in wecould we could build our own rails we could we could create all kinds of jobs doesn’treally agree or disagree?(15) 1. A: but i do ஹ஭nd that i- in order to have your party last beyond2. A: the dinner table there h- there does have to be something to go on to or you justkind of sit around and everybody goes to sleep and gets bored you know there’s got tobe a a silly game or a3. A: something fun to do afிerwards4. B: Yeah um-hum5. B: i would say our dinners are probably more casual than that with um having kids andthat kind of stuஸf it may be inviting you know neighbors over for dinner or somethinglike that but not really we haven’t really tried a dinner party i guess237(16) 1. A: and supposedly we’re uh reeducating them and putting them back out in the publicso give them some public service2. B: Yeah but are we really doing that educating i- i suppose someB.2.2.2 LDC ‘yeah’ + disagree, accept QUD (11 examples)(1) 1. B: you know now the question is would you again go buy that same brand would yourecommend that brand2. B: to somebody or because of the experience would you just say uh don’t fool with thatbrand it3. A:Yeah pr- yeah i think you’re right it’s probably hurting hurting that brand not to dothat uh(2) 1. B: wow how about that yeah that’s what it did report was a hundred and thirty relocat-ing down to McKinney2. A: Yeah that’s possible “yeah that’s possible not agreeing or disagreeing(3) 1. B: to do you know if you were building a house and you were going to spend you knowஹ஭fிy thousand versus twenty thousand on materials because your2. A: yeah3. B: you’re going to you’re going to pay for uh technology that’s not mature yet4. A: Yeah that that’s a problem also not accepting or denying(4) 1. B: maybe they want to work a little bit whatever it is maybe they should think aboutdo you really want a child or not2. A: uh-huh3. A: Yeah good question238(5) 1. B: and you know i’m actually all for that i don’t i’m probably not the b-2. B: best person for recycling but i’ll be damned if you know if they they didn’t uh3. B: charge me an extra ten bucks for garbage collection every month i’d be sure and re-cycle4. A: Yeah how how how do they monitor that though i wonder not necessarily agree-ment(6) 1. A: um i think it should all be voluntary as it is now but um i do agree that i think it isa good thing because i don’t know how else a lot of these um things could happen ifthey didn’t have the volunteers to do it2. B: Yeah they uh3. B: um the example they gave was like the Peace Corps not agreeing or disagreeing?(7) 1. A: so i i think i’m developing a new handicrafி i think it’ll become resume writing2. B: oh yeah3. B: oh well let’s hope that you you you aren’t e- employed by that crafி for too long4. A: uh Yeah i i hate to think about it and and i’m getting rather good at reading wantads yeah it it not agreement - just kind of accepting the QUD as a thing(8) 1. A: Defense Electronic Division when i retired i know it was a you know it was a real hothot item there i think i want to think maybe they you know really got some nudgingfrom you know D O D to do this sort of thing2. B: yeah i used to be in DSEG myself3. B: um A P D as a matter of fact4. A: Yeah so you knew you know the atmosphere then same as previous(9) 1. A: well of course down there you probably don’t have land as quite as much a premiumso you can sprawl a big rancher out2. B: Yeah i guess it’s the style i really don’t have an answer here because of the tornadoi always thought tornados uh i thought people would build a lot of storm cellars you239know or shelters you know but even that is not uh popular at all i don’t know i don’tknow of anyone doing that uh(10) 1. B: well and i guess you know you always have to think about things like your gasmileage and stuஸf like that you know you2. A: oh it’s easy to get gas mileage in this car it gets excellent gas mileage3. B: Yeah that’s one of the big throwing cards for some of the foreign ones(11) 1. B: i i couldn’t see having ஹ஭sh like that i could see sort of having maybe some of thetropical ஹ஭sh that are really really pretty but2. A: Yeah like i remember a friend of mine at work telling me that at his frat in collegethat they had a tank of piranha didn’t agree really??!B.3 COCA ‘no’ (95 examples)This section includes 29 examples with agreeing followup content which agreed with negationin the triggering utterance, and 59 with disagreeing content which rejected the at-issue content.The remaining seven were coded as rejecting the QUD.B.3.1 COCA ‘no’ + agree (negative concord) (29 examples)(1) 1. since they’re both going to be playing on the same ஹ஭eld.2. CARSON஡DALY- (08#53:44): Unbelievable. Look at that.3. SAVANNAH஡GUTHRIE- (#53:47): That looks so good. Do n’t take a bite becauseyou have to do the birthdays.4. AL ROKER (08:53:49): No, because I got to do the birthdays. That’s right. Washitdown with a big old jar of Smucker’s. All right, birthday time. We got some great folksto celebrate with help from our friends at Smucker’s. First up, happy one hundred andஹ஭fிh240(2) 1. Well, they’re about 25 megs each. So it’s about - yeah, it’s about 800,000 images everyday.2. ROBERT஡SMITH#Eight hundred thousand photos a day. So no one can look throughthem. There’s not a human being here, watching the photos come down.3. KATHERINE஡SCOTT#No. Everything is automatic.4. ROBERT஡SMITH#Planet has computers that stitch together all of thephotos of theEarth every day. So you can essentially do that thing you always see in spy movies, youknow, pick a spot on the Earth and then zoom in.5. STACEY஡VANEK஡SMITH#Oh, enhance. Enhance(3) 1. thinks it’s not – the Russia investigation is not a real thing. I mean I believe he said thatrepeatedly, no?2. MARTIN#Well, he says what most of us say, which is it’s a prosecutor in search of aproblem. The election was not changed –3. COOPER#No, he says it’s a hoax, it’s fake news. I meanthat’s what he said. Anyway,we’ve got to leave it there. We’ll continue – obviously, we’re going to be talking aboutthis for days to come. Ed Martin, thank you(4) 1. There’s a lot of, you know, this thing is real. We employ a lot of people. We are growingreally rapidly. Those are, you know, real...2. GUY஡RAZ#But you are not , like, swimming in money and throwing it up in the air.3. SUSAN஡TYNAN#No. That is a funny thing. We still have, you know, cash-strappedconversations.4. GUY஡RAZ#Do friends of yours just assume that you’re, like, rolling in cash?5. SUSAN஡TYNAN#Yeah. I laughed’ cause I started to get a lot of things from, like, allthe(5) 1. the story.2. BOSSIE#I understand, but that’s not – I do n’t believe it’s a change.3. TODD#Is it his voice? Was that him in the Access Hollywood tape?4. BOSSIE#Oh, it ’s clear that’s it is.2415. TODD#So there is no disputing this.6. BOSSIE#No, and I don’t think he does either.7. TODD#Well then, Corey, explain this. You’ve been with him frankly longer thanDavid did. Why does he have this penchant to try to change his story – a bad story.He’ll own up - when he does(6) 1. that was - that was a tragic choice. It helped him win a few ஹ஭ghts, but it cost him in thelong run.2. DAVE஡DAVIES#Right, right. You do n’t - you do n’t build up calluses in the brain.That’s not the way the science works.3. JONATHAN஡EIG#No. You know, I worked with CompuBox, which is the boxingstats company, to count how many times Ali was punched over the course of his ca-reer. And I calculate that if you include the sparring sessions and his amateur years andeverything else, it’s probably about 200,000 shots(7) 1. should be covered simply because there are other major –2. WILLIAMS#Right. Let me just say. Another distinction to be made, in the Conyerscase, the allegation – it is more of an allegation now. You could correct me if I’m wrong.He used taxpayer dollars –3. KURTZ#No, that’s a fact.4. WILLIAMS#that is oஸஹ஭ce funds to buy oஸf orsilence –5. KURTZ#Yes.6. WILLIAMS#– this woman.7. KURTZ#This was just a couple of years ago and it was done in secret.8. WILLIAMS#Right. That is the case, that is diஸferent than what we(8) 1. on how you want to read into them. But he was obviously critical of the Democraticcongresswoman. Some of his comments could have been interpreted as being critical242of the president of the United States, though he certainly did not, you know, name thepresident in any way.2. MURRAY#No, he didn’t name the president. He said the president sort of delivered-his condolences in his own way. But he was very forthcoming about the fact in thatsound bite you just played, that he kind of explained to the president, this is what Iwas told when my(9) 1. my own vision, my own brand, but we would have access to his resources beyond justmoney. And that was something that was never going to happen twice.2. GUY஡RAZ#And you did n’t know - at this point, you didn’t know what that was goingto be.3. WHITNEY஡WOLFE#No. And so it really wasn’t until a couple of weeks later whenwebrought on - you know, I called Chris Gulczynski and Sarah Mick, who I’d workedwith that Tinder. They’re really, really talented designers, and, you know, in order tobuild a(10) 1. led to make that decision. But HBO has become a place of zero tolerance. There area lot of women in power. And we would have been angry had it gone ahead.2. JUDY஡WOODRUFF#You said, I saw in one interview, that there weren’t human re-sources departments.3. SHEILA஡NEVINS#No, there was no one to go to. There was no – I don’t know theword sexual harassment. I do n’t think I knew it until about 25 years ago.4. JUDY஡WOODRUFF#But there are human resources departments now, and yet womenare saying they do n’t feel safe necessarily(11) 1. just being able to open up. And like I said, just understand that it’s okay to not be okay.Like none of us are perfect in this world. None of us are.2. MEGYN KELLY (09:34:18): Not even Michael Phelps.3. MICHAEL PHELPS (09:34:19): No. Hell no. But just those little things that I’vebeen able tolearn and just to talk to people like you feel better. You know, like you feelbetter.2434. MEGYN KELLY (09:34:30): Yeah.5. MICHAEL PHELPS (09:34:30): You know, like for me(12) 1. it accurately? the question is no. the answer to that is no. The media is biased againstTrump. And even if they were talking about tax cuts, they would only be saying, well,this is just a break for the richest Americans, the most wealthy Americans.2. CAVUTO#No, no, you’re dead on. The media is not going to givehim a fair shake.And it does n’t help matters any, no matter how the president tries to structure thistax cut or to say that the rich, the very rich, certainly are going to be(13) 1. issue is the power outages. And, you know, that’s going to be a big issue. And therewill be folks who will be inconvenienced for a couple of days, which, as you know inTampa in the middle of September, is not a pleasant thing.2. JUDY஡WOODRUFF#No, it’s not. I do want to ask you about – we knowthere’s someanalysis that has been pointed out to us, analysis going back several years, experts sayingthat Tampa is one of the most unprepared cities in the country to deal with a majorhurricane, in(14) 1. is what I’ve been looking for – for you know, all my albums and so. It’s me.2. MEGYN஡KELLY- (09#51:09): You did n’t lay down a bunch of vocals. It’s going tobe us and you when you sing.3. LEE஡BRICE- (09#51:11): No. Like what you hear today is what you’re going to hearon therecord.4. MEGYN஡KELLY- (09#51:13): Yes, because he’s going to sing for us right afிer thisbreak. Standby because we’re going to have Lee Brice live right here next. (AN-NOUNCEMENTS)5. MEGYN஡KELLY- (244(15) 1. in this story at all.2. BANFIELD#So, Miss Ashley, wearing the lovely silver bracelet in this picture, appar-ently had that $34,000 deposited into her own checking account and then spent it.Listen. You ca n’t do that if you think your pal Taylor is somewhere out there.3. JACKSON#No. The further problem there, of course, is the issue of motive,right?Why would she want her to disappear? Why would she want to exact harm upon her?Well, because I have money that I do n’t want to return. And we always talk about this(16) 1. gay afிer that. You know, he had very complicated feelings about his homosexual life.And even as he was as out there as anybody could be, he also turned on it and ofிennot with that , you know, that much bitterness but still would never discuss it.2. TERRY஡GROSS#No. So I want to play a diஸferent excerpt of ” Street Hassle, ”notthe slipway part that you referred to...3. ANTHONY஡DECURTIS#Sure.4. TERRY஡GROSS#... But the part that’s about somebody overdosing. And the personnarrating the story is, like, so cold, just so indiஸferent about(17) 1. being like, mom, he’s so cute. Like, as a twelve-year-old, like, that was awesome.2. DENNIS஡MURPHY- (09#06:53): But it was n’t as that she – she was bedridden oranything at that point, so she could –3. LYNDSAY஡LOVELACE- (#06:57): No. She would –4. DENNIS஡MURPHY- (09#06:58): She was just feeling crummy, huh?5. LYNDSAY஡LOVELACE- (#06:59): She was feeling sick. And even for my mom thatwas not common, because she – even if she was sick, she did what was like – like(18) 1. alive or out of prison. I mean, at least if I can get just in the prison, then maybe some-one have to visit me or something.2. JENNA஡BUSH஡HAGER- (#37:06): And you’re not – you’re not playing a police of-ஹ஭cer.3. BROOKE஡SHIELDS- (10#37:08): No, I didn’t get a badge.4. JENNA஡BUSH஡HAGER- (#37:09): Talkabout your role.2455. BROOKE஡SHIELDS- (10#37:09): I begged for a badge. I begged for one.6. JENNA஡BUSH஡HAGER- (#37:12): Who are you?7. BROOKE஡SHIELDS- (10#37:13): I ca n’t(19) 1. ’s talk about the cost to the government. I mean, on its face, you would think, oh,well, they’re stopping the subsidies; that means the government is going to save a lotof money. But you were telling us it’s not that simple.2. JULIE஡ROVNER#No. What’s ironic is that this will cost the federal governmentmore money,according to the Congressional Budget Oஸஹ஭ce, because what happensis that insurers will raise their premiums. When they raise premiums, remember, thepremium subsidy comes in. Those premium subsidies will go up to match the(20) 1. ’s and 60’s. He loved technology. He loved the ability to communicate his message –2. INGRAHAM#Absolutely.3. UPDEGROVE#– to as wide as audience as possible. Reagan was alive today he wouldbe using Facebook and Twitter.4. INGRAHAM#Maybe it wouldn’t be just like Trump’s tweets.5. SHIRLEY#No, it wouldn’t be.6. INGRAHAM#It would be. He would tweet andwe would all love the tweets. Let’sface it great to have you both on. Thank you so much. I wish you were here at thelibrary with me, though. Directly ahead, what(21) 1. He has been in Moria for eight months, and he says the pressure of the camp causedhim to attempt suicide.2. FRANK#I was like, let me just hang myself and forget about life, instead of trying tokill somebody.3. MALCOLM஡BRABANT#But you didn’t do it.4. FRANK#No, I didn’t.5. MALCOLM஡BRABANT#Did you try?2466. FRANK#Yes, I tried. Igot the rope. I went to the bush. At this stage, I have a thoughtcome inside me. Are you stupid? Do you want to kill yourself? Are you crazy? Whatis wrong(22) 1. GUY஡RAZ#So I mean, the diஸference between your company and so many companieswe’ve featured on the show is that you’re still in the thick of it.2. SUSAN஡TYNAN#Yeah.3. GUY஡RAZ#You are not, like, able to just sit back and say, let me just...4. SUSAN஡TYNAN#No, we’re in the throes.5. GUY஡RAZ#Yeah.6. SUSAN஡TYNAN#Like, what’sgoing to happen with our major competitors? Like,are they going to try and launch stuஸf we’re doing? Probably. You know, will we getto be a sustainably, you know, healthy business(23) 1. All right. First question: this is from John K. I’m going to you, Tucker.2. CARLSON#All right.3. GUTFELD# If you were on’ Who Wants to Be a Millionaire,’ which is a game show,if you’re not familiar with it.4. CARLSON#No. I’m so high-toned.5. GUTFELD#All right. Then you might not know whatI’m asking. Who would beyour lifeline, Tucker?6. CARLSON#I do n’t know what that means.7. GUTFELD#All right.8. CARLSON#That’s cool (ph).9. GUTFELD#What?10. CARLSON#Oh247(24) 1. Oh, I ca n’t –2. KATHIE LEE GIFFORD (10:10:18): And to your mother’s life and your sister, yourbrother. Everybody. Mine.3. HODA KOTB (10:10:22): You ca n’t really quantify. I know how much.4. KATHIE LEE GIFFORD (10:10:24): No, you can not. It’s exponentially – it goes tothe whole world.5. HODA KOTB (10:10:26): Yes.6. KATHIE LEE GIFFORD (10:10:28): I should n’t do that. I have to work on my armsa little bit more.7. HODA KOTB (10:10:31):(25) 1. I’m sure he – if he could cast a vote – and he was born in Alabama, actually – MitchMcConnell would not be voting for Roy Moore because this is – for one thing, RoyMoore is not a Mitch McConnell Republican. I mean he’s running –2. DICKERSON#No, as David was saying. Yes.3. PAGE#Running on a campaign to ejectMitch McConnell from the – from the lead-ership. So in no way is this – is this good for Mitch McConnell, even if it costs himone of those crucial Republican Senate seats. it’s hard to(26) 1. he was working with at least one grand jury already, but now there’s another one, anewer one that has been set up here in Washington, which spells, according to all theexperts, a really serious investigation that isn’t going to end any time soon.2. MARK஡SHIELDS#No, it suggests that we’re in for some duration, that don’t plan-Thanksgiving or Christmas, that it’s going to be of long standing. I would say this,that, Judy, ஹ஭rst of all, a grand jury just is impaneled. Its purpose is to hear evidence(27) 1. a lot of it was because of being hurt, because what she had been telling me was thatwhatever she had, as far as a relationship with Brad, she had been telling me for a weekto ten days or so that that was over.2. KEITH஡MORRISON#Apparently it wasn’t.2483. MARTY஡LARSON#No. And somewhere in my head I suspected that and that’s whyI sentthe e-mails. There was a lot of confusion. (Car on highway at night; exterior ofapartment at night)4. KEITH஡MORRISON- (vo#Confusion or something else that made him decided todrive three hours to(28) 1. up a lot of really interesting legal issues. Like, you have an expectation of privacy inyour house, but if Amazon is now installing a camera there to watch these deliveryguys...2. CAVUTO#No, it ’s pre-approved. They are not going to do this without your say-so.3. KUNZIG#No, but now do you have expectation, the way we had problems withtheEcho Dot and Amazon Echo?4. MELCHIOR#And that’s scary. That’s deஹ஭nitely all being stored up in the cloud.5. (CROSSTALK)6. CAVUTO#Let’s say you live in a city or an area where things could be This depends onwhich “no” - either rejecting the QUD (the ஹ஭rst one) or accepting belief (the secondone)B.3.2 COCA ‘no’ + disagree, rejecting the at-issue content (59 examples)(1) 1. up a lot of really interesting legal issues. Like, you have an expectation of privacy in yourhouse, but if Amazon is now installing a camera there to watch these delivery guys...2. CAVUTO#No, it ’s pre-approved. They are not going to do this without your say-so.3. KUNZIG#No, but now do you have expectation, the way we had problems with theE-cho Dot and Amazon Echo?4. MELCHIOR#And that’s scary. That’s deஹ஭nitely all being stored up in the cloud.5. (CROSSTALK)6. CAVUTO#Let’s say you live in a city or an area where things could be This depends onwhich “no” - either rejecting the QUD (the ஹ஭rst one) or accepting belief (the secondone)249(2) 1. up a lot of really interesting legal issues. Like, you have an expectation of privacy inyour house, but if Amazon is now installing a camera there to watch these deliveryguys...2. CAVUTO#No, it ’s pre-approved. They are not going to do this without your say-so.3. KUNZIG#No, but now do you have expectation, the way we had problems with theE-cho Dot and Amazon Echo?4. MELCHIOR#And that’s scary. That’s deஹ஭nitely all being stored up in the cloud.5. (CROSSTALK)6. CAVUTO#Let’s say you live in a city or an area where things could be This depends onwhich “no” - either rejecting the QUD (the ஹ஭rst one) or accepting belief (the secondone)(3) 1. video) (10:08:45): You would n’t hurt Mary?2. KATHY CONLEY (interrogation video) (10:08:46): No.3. ANDREA CANNING (10:08:47): I know killers come in all shapes and sizes. ButKatie does not look like a killer.4. ROBERT NELSON (10:08:52): No. But again, it – it’s poison. And she had madeacomment earlier that it’s a lady’s weapon. (Police interview video of Katie Conley)5. ANDREA CANNING (voiceover) (10:08:58): The detectives kept at it. They ques-tioned her for more than six(4) 1. this happened or that happened because he’s an admitted liar at this point.2. WALLACE#Do you by that?3. WILLIAMS#No, it’s part of a deal, Congressman. that’s why it was –4. CHAFFETZ#If they wanted to charge them with something greater, they would have.5. WILLIAMS#No, but they didn’t want to, that’s my point.6. CHAFFETZ#Andthey did n’t get anything. They did n’t –7. WILLIAMS#But they would – if they – if they are making a deal, they are using it aspressure. In fact, you notice no sentencing component250(5) 1. 08#41:32): – at the stocking stuஸfer.2. SAVANNAH஡GUTHRIE- (#41:33): Oh, the kids. Darn, I was thinking for adults.Okay.3. JILL஡MARTIN- (08#41:36): You actually –4. SAVANNAH஡GUTHRIE- (#41:36): Or the kids.5. JILL஡MARTIN- (08#41:37): No. But you wear that purple tinsel in your hair.6. SAVANNAH஡GUTHRIE- (#41:39): Yeah. That pink glitter in your hair.7. JILL஡MARTIN- (08#41:40): There you go. Okay. So over twenty collections again ontoday.com. The retail, forty-ஹ஭ve to ஹ஭fிy. The deal(6) 1. we would never have been talking about him. That is what made him –2. LEWIS#But there was a –3. POWERS#So we live in a cultural that demeans women to the point that you, Matt,do n’t understand what’s –4. CARDONA#Yes.5. POWERS#– the problem here.6. LEWIS#No, you’re being hard on Matt.7. (CROSSTALK)8. LEWIS#I want to make a pointabout the liberal bias.9. COOPER#Matt, you can respond. We’ll take a quick break. Again, with two big starsGwyneth Paltrow, Angelina Jolie speaking out, claiming Weinstein sexually harassedthem. A(7) 1. the major potential Democratic candidates for president who have come out againstObamacare and for single payer. Obamacare is being attacked on the...2. GEORGE஡STEPHANOPOU#(Oஸf-camera) They’re not against Obamacare.3. MATT஡SCHLAPP#Well, but they’re trying to expand, they’re trying to... They’re try-ing to improve it.4. MATT஡SCHLAPP#No, no, they’re undermining the central part premise of Oba-macare, which youall decided... Sounds good, sounds good, go ahead.2515. MATT஡SCHLAPP#You all decided to not have single payer. The lefி is ஹ஭ghting Oba-macare. The right is ஹ஭ghting Obamacare. And Americans have told Republicans,(8) 1. grieving, you know...2. PAULA஡FARIS#And at the end of the day, like, why is she getting all this attention?Why is she a rock star?3. –Because... Because she called the President out on his insensitivity. It’s that simple.It’s not that complicated.4. PAULA஡FARIS#No, but the genesis, no, but the genesis of it is because asoldier waskilled.5. –Yes, and he made an inappropriate phone call two weeks too late.6. PAULA஡FARIS#And that is the genesis of it, exactly, exactly, but it still feels a littleinsensitive. And(9) 1. What’s all that about? And he kind of looked up at me in the hospital bed and saidyou can have the name when I die. So...2. TERRY஡GROSS#Which is an interesting thing to say. But you didn’t change it. Like,on your book cover...3. LOUDON஡WAINWRIGHT-#No. I use the third. I...4. TERRY஡GROSS#... You’re Loudon Wainwright III.5. LOUDON஡WAINWRIGHT-#Yeah. Sometimes when I use - when I get work as anactor, I lop oஸf the Roman numeral. But I’m comfortable with being the third. (Laugh-ter) My ஹ஭rst album was(10) 1. wanted something along those lines. So I do n’t - I hardly ever do it, but today isspecial.2. TERRY஡GROSS#Well, today’s autobiography day. And you do talk about the songin your book , so I thought it would be a good idea to include it.3. LOUDON஡WAINWRIGHT-#No, it will be in my obituary. The ” Dead Skunk ”thing willbe there.2524. TERRY஡GROSS#It will be. It will be. So another really life-changing thing - you metthe singer Kate McGarrigle. And she was a backup singer when you met her when shestarted writing her(11) 1. very prestigious award in London. We saw Jeremy Irons introducing you. C2. HARLIE஡ROSE#Oh, yeah.3. GAYLE஡KING#It was great. Congratulations.4. NORAH஡O’DONNELL#Yes, congratulation.5. CHARLIE஡ROSE#Thank you. Well, I was humbled because the people there whowere also being honored were much more renowned and accomplished.6. GAYLE஡KING#No, they weren’t. No, they weren’t. No, they weren’t. But it was avery August group and we’re so glad you’re back. So we do not have to call you SirCharles, I just want to be clear.7. CHARLIE஡ROSE#No, no(12) 1. to balance the budget? The stimulus money that every conservative in this countrywas against. A lot of it. So let’s not – let’s not give him all the credit.2. HANNITY: With all due respect, so you expect him to not take the money.3. HAHN: No, I expect – that’s what it’s there for.4. HANNITY: Andthen the citizens of his state have to pay the money. He’s just gettingsome back.5. PISCOPO: When are we going to draw on the resources of the United States of Amer-ica? When are we(13) 1. the opportunity and what do we do? This oatmeal. This bland, pale oatmeal.2. CAMPOS஡DUFFY#But you ca n’t – you ca n’t do...3. FOWLER#Touchdown, America!4. CAMPOS஡DUFFY#Greg, you can not do the bold reform that you and me and all ofus here want.5. FOWLER#No, not me. Count me out. I don’t want the bold reform.2536. CAMPOS஡DUFFY#OK, ஹ஭ne. But you can not do that without the Senate changingthe rules.7. (CROSSTALK)8. FOWLER#That’s not true. You’ve just got to come to the table. Thank you. If(14) 1. that we all stand together on it.2. JUDY஡WOODRUFF#Well...3. MATT஡SCHLAPP#Think about this. We actually ca n’t stand together even on re-placing Obamacare. That’s quite a stunning statement.4. JUDY஡WOODRUFF#So, is the answer , Tom Davis, to elect more Roy Moores to theSenate?5. (CROSSTALK)6. TOM஡DAVIS#No, look, the answer is – the wakeup call for Republicans is they needtowork together as a team to get these passed. If not, they are going to have to work withDemocrats. And that’s going to make some Republicans very unhappy.7. JUDY஡WOODRUFF#But Roy Moore coming(15) 1. T-shirt and the political junkie no-prize button in exchange for your promise of a dig-ital picture of yourself wearing same to be posted on our wall of shame.2. TERRY#Will do.3. NEAL஡CONAN#Congratulations.4. TERRY#Thank you.5. NEAL஡CONAN#And let’s go to...6. KEN஡RUDIN#She didn’t sound happy.7. NEAL஡CONAN#No, she’s happy.8. KEN஡RUDIN#OK, you never can tell, really,on the phone.9. NEAL஡CONAN#From Jersey, yeah. South Carolina, Tim Scott’s seat is up.10. KEN஡RUDIN#It is, and we talked last week about Mark Sanford, the former gover-nor, who is trying254(16) 1. saying is it –2. KATHIE஡LEE஡GIFFORD#35:40): Are selஹ஭es out of style now?3. HODA஡KOTB- (10#35:42): And right now we should let everyone know where thewine bot is.4. KATHIE஡LEE஡GIFFORD#35:44): You’re probably killing it. You’re killing it.5. HODA஡KOTB- (10#35:45): No, actually we’re not killing it.6. KATHIE஡LEE஡GIFFORD#35:46): Really?7. HODA஡KOTB-(10#35:47): I’m winning that selஹ஭es are not out of style but not bymuch. Actually it does n’t seem like people care.8. KATHIE஡LEE஡GIFFORD#35:54): People do n’t give a royal rip(17) 1. say that for the procedure of American –2. KING#What do you want to say to Miss Kelley, sir?3. UNIDENTIFIED஡MALE#Miss Kelley, Frank Sinatra’s children are, any of them arein marriage age? 21:50:034. KING: They both well married and Nacy and Tina are both successful –5. KELLEY#No, they’re not.6. KING#What Tina is not married now, right?7. KELLEY#No, Nancy is widowed and –8. KING#Nancy is widow now.9. KELLEY#– and Frank Sinatra, Jr. has never married.10. KING#He’s never married, so all three are not married the ஹ஭rst(18) 1. rewrite history.2. LEWANDOWSKI#Chuck, you know, what’s amazing is we have n’t talked aboutonce yet is the signiஹ஭cant tax reform that the U.S. Senate just talked about. We’retalking about a story that ’s been litigated last year...3. TODD#We’re talking about your book.2554. LEWANDOWSKI#No, but look – I know, but look, let’s talk about theAccess Hol-lywood tape. The American people had a month before election day when the AccessHollywood tape came out and you know what they said? We have a choice between acandidate who wants to change the direction complete rejection of what he wants tosay(19) 1. really gone wrong. So I remember that drama.2. GUY஡RAZ#Did you grow up thinking entrepreneurially, like, I’m going to be an en-trepreneur because, I mean, we’re around the same age and I don’t remember thatbeing a big part of our culture as kids.3. SUSAN஡TYNAN#No, I looked at my dad and I thought I was going to be theboss.But I did n’t - that was n’t, like, I’m going to be the boss and great things come withbeing the boss, it was, like, and all the responsibility that comes(20) 1. rate could be 22 percent. Well, that was not in either the Senate or the House bill.2. WALLACE#Might I just suggest that I have saved that to ask Senator Barrasso in thenext segment.3. (CROSSTALK)4. GRIFFIN#Preemptive. But you could lose the freedom caucus Mark Meadows - -5. WALLACE#No, because they want to see that down to 20 percent.6. GRIFFIN#They wantit down to 15 percent, but 20 percent was the bare minimum.So, the razor-thin margin that they pass it by in the Senate, they could lose that if theymake –7. WALLACE#Karl, we(21) 1. pretty great eஸfect on the continent. I mean, they turned it into America, which to thisday is a beacon of hope for the world, that’s what everyone wants to come here. So,you are trying to delegitimize that and let’s be honest about that.2. NICHOLS#No. Again I disagree. First of all, we are talking about the mainlandofthe United States. Columbus never made it here. So, we’re talking about people whocame, the Europeans who came to Ellis Island and other places, that in஺ாuence we cansay for the most256(22) 1. place to Ted Cruz who has a very strong organization on the ground in Iowa. Yes, hehas a ஹ஭ght with FOX News and Megyn Kelly. This is sort of like the 3rd grader ofMegyn Kelly . He keeps telling her, he hates her.2. BORGER#Seventh grade.3. KING#No, it is the third grade. He keeps telling her he hates her.And there’s some-thing else to it. But it is more than that. He knows now that Ted Cruz is going to takea lot of harpoons because Ted Cruz is going to be there. And Cruz(23) 1. out to be a not true assumption, and so we adjusted, and I completely disagree withthe take eye oஸf the ball. I found that to be empty political rhetoric.2. KING: Empty political rhetoric. It was a NATO shortcoming, not a U.S. shortcomingin Afghanistan?3. ZAKARIA:No I think that’s simply not true and I think if you look at thestatementsof the time, Secretary Rumsfeld believed very, very strongly in a very light foot. Hewanted to get in and get out as quickly as possible. He did n’t want to have troops onthe(24) 1. of my tour.2. (CROSSTALK)3. KING#OK. Well I do n’t want to believe with this, just –4. WOODFILL-(ph)#No, you do n’t believe, I’m not telling you that I’m –5. (CROSSTALK)6. WOODFILL-(ph)#– I want to tell anybody else that everything that she said is wrong.7. KING#No, give me one example.8. WOODFILL-(ph)#The idea of me asking Frank Sinatra afிerknowing him or, oh 10years, what the maஹ஭a, was n’t ever said. The question was asked to a man they didPochi and she knows that with that Pochi (ph), he put257(25) 1. of Coke is Coke reform. This is not – this is not an overhaul. It’s not reform.2. CARLSON#You’re stealing that (ph).3. GUTFELD#Whoever wrote sweeping reform needs their head examined. This is –this is more liberal than it is conservative.4. FOWLER#No, I disagree.5. GUTFELD#The top 1 percent provides 40 percent of the federalincome tax revenue.Is this helping them or hurting them? It’s hurting them. the corporate part is ஹ஭ne.I’m for that. The individual thing is a mess. It’s a mess.(26) 1. meeting between the intelligence people and President-elect was a private meeting. Itwas a national security meeting.2. RIVERA#You’re a news man. You know that’s not so.3. O’REILLY#Sure, it is. There was no press conference.4. RIVERA#Well, the substance may be frivolous –5. O’REILLY#No, there was a leak by the U.S. Intel Community to a news organiza-tion.6. RIVERA#You can not deny that the intelligence community brieஹ஭ng Donald Trumpon the salacious, horrifying activities –7. O’REILLY#That is between Trump and the people in the Intel community.8. RIVERA#Oh, absolutely not.9. O’REILLY#No(27) 1. means we need to, with partners to destroy them, in whatever time it takes it takes,and most people are not ready for that, but I am.2. TODD#Are we going to need a new war authorization? You’re – it sounds like you’rearguing –3. (CROSSTALK)4. TODD#– No. But, by the way, you’re going to be in the minority, are n’t you?5. GRAHAM#I do n’t know. I’m arguing that the current authorization, as long as itrelated to radical Islam, is enough. But here’s – the military determines who the258(28) 1. maybe it says he’s a Muslim. I do n’t know. Maybe he does n’t want that or he maynot have one.2. ANDERSON஡COOPER, -C#On Bill O’Reilly’s show, you said maybe he does n’twant to release it because it might say he’s a Muslim.3. TRUMP#No, I didn’t say that. I said there may be something on itand they askedme like what? I said, well, perhaps because he’s a Muslim, perhaps something. Whoknows what’s on it? I do n’t know. He did n’t want to release(29) 1. know of anything like that. I do n’t know that anybody else does, either. What theoஸஹ஭cial protocol was in that point. But does he have a point? There might be peoplelooking at this going, well, yes, that’s a good question to ask.2. LOUIS#No, I’d say he doesn’t have a point because what we have seenfor over a yearis when ever anyone asks candidate and then president- elect, now President DonaldTrump, about his actions, about what he has done, he goes to personal insults, he goesback to(30) 1. HODA஡KOTB- (10#29:03): Come on, Athena. How do you feel?2. ATHENA- (10#29:05): I feel amazing.3. KATHIE஡LEE஡GIFFORD#29:06): How many dress sizes is that?4. ATHENA- (10#29:08): That’s about like four dress sizes.5. KATHIE஡LEE஡GIFFORD#29:10): No, you were four last week. So you might –6. ATHENA- (10#29:11): Maybe a little bit more. Yeah.7. HODA஡KOTB- (10#29:12): How about ஹ஭ve or six?8. ATHENA- (10#29:13): Maybe ஹ஭ve or six.9. HODA஡KOTB- (10#29:15): What(31) 1. him win would be people like, guess what? You know, Condoleezza Rice would helphim win. Marco Rubio, I do n’t know, people are going to say, he’s kind of young.Pawlenty is being underestimated and Portman.2. GUILFOYLE#You are trying to sabotage.3. WILLIAMS#No, I’m not, no, no.2594. PERINO#You don’t talk about thebig rumor this week which was General Petraeus.5. WILLIAMS#That was a total, total rabbit.6. PERINO#I know, I know. All right. Coming up, drama on the track today as BladeRunner(32) 1. hear us?2. KATHIE LEE GIFFORD (10:18:51): She just keep –3. HODA KOTB (10:18:53): Oh, my god. She’s right there. She’s crying.4. KATHIE LEE GIFFORD (10:18:56) : Oh, don’t cry, Susan.5. HODA KOTB (10:18:57): No, she said she’s not crying. I’m lip reading. I’mveryhappy.6. LAUREN MINGER (10:19:02): Why is the volume not working.7. HODA KOTB (10:19:03): We do n’t know. But we love you, mom.8. KATHIE LEE GIFFORD (10:19:04)(33) 1. has said during the campaign, he would go to jail if he2. (INAUDIBLE) of what Hillary Clinton did. And that looks like it might be true.That speaks the FBI credibility.3. KURTZ#OK. Robert Mueller did the right thing by taking this agent oஸf the investi-gation.4. HEMINGWAY#No, he did not do the right thing because actually congressional in-vestigators have been askingfor months what happened there.5. (CROSSTALK)6. HEMINGWAY#They stonewalled and obstructed what actually happened there. Theywere n’t telling House investigators.7. KURTZ#Right.8. HEMINGWAY#And in fact, they leaked this to the media, which260(34) 1. had, nuclear, you know, we talk about being a peanut farmer, but nuclear engineer,not a great president. So, yes, there’s no correlation. But, look, Donald Trump seesthe world through uncertain pecking order and intelligence is certainly part of that.2. COOPER#No, he commented that the shooter in Las Vegas was probably smart.I’mnot sure that’s a great compliment.3. LEWIS#He also complimented the leader of North Korea for being resilient and smart–4. POWERS#And several others –5. LEWIS#Yes, but the height thing, I want to go(35) 1. get up every day and think I think what do I have to try to do to advance my campaign?2. CYNTHIA஡MCFADDEN-#(Oஸf-camera) Can you really let go of yesterday?3. SENATOR஡HILLARY஡CL#Absolutely.4. CYNTHIA஡MCFADDEN-#(Oஸf-camera) So if you feel you blew it at a moment inthe debate, you don’t... S5. ENATOR஡HILLARY஡CL#No, I am so tired by the time I ஹ஭nally get to bed. Bythetime my head hits the pillow it’s lights out.6. CYNTHIA஡MCFADDEN-#(Oஸf-camera) I want to tell you, I’ve talked to womenaround the country, many who are ardent supporters of yours, some who are(36) 1. for the stars to becoming one of them. Again, that’s on Sunday TODAY with WillieGeist.2. SAVANNAH஡GUTHRIE- (#55:34): Love it.3. CRAIG஡MELVIN- (08#55:35): Meanwhile, while we’re chatting , you almost set thestudio on ஹ஭re.4. SAVANNAH஡GUTHRIE- (#55:37): No, I didn’t.5. AL ROKER (08:55:37): No, no.The burner was lefி on.6. SAVANNAH஡GUTHRIE- (#55:39): It was setting itself on ஹ஭re.7. HODA஡KOTB- (08#55:41): Yes, it was.8. SAVANNAH஡GUTHRIE- (#55:41): And we put out261(37) 1. do you think Ronald Reagan would tweet if he was alive during Twitter, do you thinkhe would tweet.2. SHIRLEY#Yes, he would.3. UPDEGROVE#No, I do n’t. I disagree.4. SHIRLEY#May I jump in here. I will make my point. Go ahead, Mark.5. UPDEGROVE#No, I don’t think he would. Reagan was about civility. When hewentto Washington. He campaigned against a big government. Government actually gotbigger during the Reagan administration. There were three platforms he campaignedon. One was ending the cold war by a clear American victory,(38) 1. do something in North Korea because it is a sort of wag the dog or kill the messengerand they’re kind of trying to force ஹ஭t it. And, John, is there any evidence out there todisprove what this report, what this State Department insider is –2. (CROSSTALK)3. THOMAS#No, not necessarily, other than Trump’s rhetoric on the campaign trail,whichwas he does n’t think we should be involved in all these foreign entanglements.He thought the Iraq war was a mistake. So I do n’t think – you know, he said we don’t need to(39) 1. communication.2. SESSIONS#I did not conஹ஭rm or deny the existence of any communication betweenthe president that I consider to be conஹ஭dential.3. UNIDENTIFIED஡MALE#Were you requested, been interviewed or you’ve been re-quested to be interviewed by the special counsel?4. SESSIONS#You’ll have to ask the special counsel.5. UNIDENTIFIED஡MALE#No, I’m asking you. Have you been interviewed by thespecial counsel inany shape or matter?6. SESSIONS#The answer is no. No. Mr. Chairman I do n’t have to sit here and listento his...7. (CROSSTALK)8. UNIDENTIFIED஡MALE#You’re the one who testiஹ஭ed...2629. SESSIONS#... without having(40) 1. come from the president himself, that it was actually written by his top personal at-torney John Dowd and Dowd is trying to mimic something that Ty Cobb, anotherattorney for the president, wrote on Friday. Is that customary? Do we see his attor-neys writing tweets for him ofிen?2. KAREM#No. Actually, the Twitter is spread by the president himself. He gets upinthe morning and tweets his, you know, to his little heart’s content, including stuஸf,fake video from anti-Muslim extremists. And the things he tweets ofிen come straightfrom him, come straight from(41) 1. clear and they have to be changed. And it’s an opportunity that President Trump hascreated for them to ஹ஭x this very bad deal, which is dangerous for them, no less than itis for others .2. DICKERSON#But they believe that changing the deal basically breaks the deal.3. NETANYAHU#No. In fact – in fact, if you don’t change it, youbreak it. That’s whatthe president told them, that if they do n’t change it, if they do n’t ஹ஭x it, if they do n’tprevent Iran from automatically getting in a decade to a(42) 1. certain ideas and beliefs, and we just want to be really sure that you are aware of them.2. GAYLE஡KING#Julia Roberts – Julia Fiona Roberts is turning ஹ஭fிy this year. I like it.3. JULIA஡ROBERTS#Gayle.4. GAYLE஡KING#I like it.5. JULIA஡ROBERTS#Gosh, you’re breaking the girl code.6. GAYLE஡KING#No. Look, it’s – it’s published everywhere, Julia. Listen,I’m sixty-two, and it’s great. And I wonder, do you have those kind of hang-ups that, youknow, when you reach a milestone birthday?7. JULIA஡ROBERTS#Well, there’s nothing to be263(43) 1. CARLSON#However, Democrats have made no meaningful eஸfort to win them over.Instead, they have made a clear and conscious decision to import new voters to replacethem. And that is why that party moved has radically to the lefி to the no-borderposition. You can’t ஹ஭nd...2. FOWLER#No. We don’t...3. CARLSON#What do you mean? I do this every– I do this every night.4. FOWLER#Tucker, I hear you. I hear you!5. (CROSSTALK)6. CARLSON#You can say that all you want, but the truth is...7. FOWLER#I hear you, but when(44)1. never do another thing to you. Five minutes. Do n’t ruin your friendship with mefor ஹ஭ve minutes.2. AMBRA஡GUTIERREZ#I know, but it’s kind of like, it’s too much for me. I can’t.3. HARVEY஡WEINSTEIN#Please, you’re making a big scene here, please.4. AMBRA஡GUTIERREZ#No, but I want to leave.5. HARVEY஡WEINSTEIN#Okay, bye. Thank you.6. ELIZABETH஡VARGAS#(Voiceover) Police have heard enough. They confront We-instein and bring him into the station for questioning. News of the incident quicklybecomes public, but curiously lurid articles about his accuser soon begin popping upin the(45) 1. big case with a man named Brendan Eich at Mozilla who was ஹ஭red because he hadgiven money to an anti- same-sex marriage initiative and he lost his job. And Mozillasaid that’s not who are we. And conservatives went insane.2. LEWIS#They have the right to do that.3. POWERS#No. The conservatives said that that wasn’t OK, that was an infringe-ment, he should be able to express that. So I do n’t know why he was able to expressthat but then these players should –4. COOPER#We have to take a break because we’re out of time.264(46) 1. at Fort Hood, Texas, they had a daughter.2. SANDY஡SHUPE#She’s an awesome kid.3. SHANKAR஡VEDANTAM#And when Jamie talks about getting grief from colleaguesin the military, did you hear about that? I’m wondering if these issues of gender andsexuality came up in your conversations.4. SANDY஡SHUPE#No. Jamie really didn’t, you know, discuss that kind of stuஸf.Yeah,Jamie would grumble about, you know, the things - the, like, you know, work issuesand stuஸf like that. But I really do n’t remember Jamie, you know, talking about(47) 1. And it’s the same...2. (CROSSTALK)3. TAMMERO#Oh, stop, Neil.4. CAVUTO#It’s the same stupid...5. TAMMERO#You’re hating on Star Wars now. Yes, there are a few lightsabers.6. CAVUTO#Stop it . Really? Is there – it gets old afிer a while.7. (CROSSTALK)8. TAMMERO#No, it never gets old for Star Wars fans.9. CAVUTO#What is this,Episode VIII, looking backwards, or....10. TAMMERO#This is Episode IX, or VIII. No, Episode VIII, Yes.11. CAVUTO#So, enough. That’s going to keep going on for decades.(48) 1. aired out publicly and should be part of this discussion.2. SCHIEFFER#Let me ask you this: Mayor David Bing said this morning on ABC,that no decision has yet been made on asking for a federal bailout . Do you thinkthere is a federal bailout in Detroit’s future?3. SNYDER#No, and I don’t expect one. I’ve said before the state cannot bail out thecity of Detroit. And part of the context I would say that to you in is it’s not about justputting more money in a situation; it’s about better services to citizens265(49) 1. a reset button that actually made kind of sense, which we may or may not have hap-pened, I do n’t know. But that’s what this was about in my opinion. Tucker, you’regiving me that weird look you give people on your show.2. (LAUGHTER)3. TUCKER஡CARLSON, -TH#No, I’m actually agreeing with everything you say.4. GUTFELD#You say that tothat people you’re about to yell at. You say I agree com-pletely.5. CARLSON#But in this case it’s heart felt.6. GUTFELD#OK.7. CARLSON#No, I actually think that General Flynn did do something wrong(50) 1. a larger problem is that Donald Trump is destroying norms.2. CARDONA#Yes.3. LEWIS#That could impact democracy and this country like ongoing. Are you con-cerned about those?4. JENNINGS#Well, number one, you’re being a little dramatic. Number two –5. LEWIS#I don’t think so.6. CARDONA#No, I don’t think he is.7. JENNINGS#– I want Donald Trump to passhis agenda because it’s the agenda thatnot only he ran on but virtually the entire Republican Party ran on and failure topass repealing health care and now tax reform, people do n’t understand the politicalimplications(51) 1. 10#17:33): See, they –2. JENNA஡BUSH஡HAGER- (#17:33): Okay, look. And then this one –3. HODA஡KOTB- (10#17:33): Is n’t that cute?4. JENNA஡BUSH஡HAGER- (#17:34): – likes it when I go like this.5. HODA஡KOTB- (10#17:35): No, he doesn’t like it. You’re giving him a headache. No.Look, mine says no.2666. JENNA஡BUSH஡HAGER- (#17:39): They told me. Mine said oh.7. HODA஡KOTB- (10#17:41): It responds to touch or sound and motion. So thanks toWowWe,(52) 1. ): It did n’t entirely make sense to detectives either. (09:50:20): You let Adam go.2. ROBERT NELSON (09:50:22): Yes.3. ANDREA CANNING (09:50:22): But I would imagine you ’re not crossing Adamoஸf your list yet.4. ROBERT NELSON (09:50:28): No. We are comfortable enough to let him go, butwe didn’t sayhe absolutely had nothing to do with it. (Detectives; David King; photoof Adam Yoder)5. ANDREA CANNING (voiceover) (09:50:33): The investigation led them to talk toAdam’s cousin and(53) 1. ’re ஹ஭nished if you do the job.2. KING#Do you want a break because of what you do, I know, is that you’re saying toNew York and other places, I’ll come in and do this, please give me what you will notgive someone else.3. TRUMP#No, I’m not looking for breaks. I probably would have a harder timeget-ting breaks. I mean, you talk about Ed Koch. The man tried to ஹ஭ght me in so manydiஸferent things and he’s failed. In each case, he has failed and that’s nice.(54) 1. . Okay.2. KATHIE஡LEE஡GIFFORD#Okay.3. HODA஡KOTB#Okay. I am moving on from Robert Duvall–4. KATHIE஡LEE஡GIFFORD#He’s a very good dancer.5. HODA஡KOTB#I’m going to make out with Eddie and I’m going to marry Birdman. What are you doing?6. KATHIE஡LEE஡GIFFORD#I would– none of the above with–7. HODA஡KOTB#No, you have to. You have to play.2678. KATHIE஡LEE஡GIFFORD#All right. Makeout Mary– I would make out with EddieRedmayne because his lips are unbelievable. HODA஡KOTB#Next.9. KATHIE஡LEE஡GIFFORD#I would move on from Michael Keaton, although I hearhe is a lovely guy. Marry Robert Duvall,(55) 1. . I had 73 men answering that they’ve came out, and they got ஹ஭red. So, this is a per-vasive problem in this country and the way we’re dealing with it by dragging it intothese political environments and calling people out. It’s damaging to the victims.2. HELDMAN#No, that’s where it exists. It exists in political environment –3. DATIG#Weshould –4. HELDMAN#We’re not dragged. No one is dragging it in there.5. DATIG#We should create policies – we should create policies that deal with theseproblems immediately. Sexual harassment, something happens in the(56) 1. . But now the sauce thing you were talking about.2. SANDRA஡LEE-1’SEMI#You’re going to make the herb mayonnaise, are you goodwith that?3. ROBIN஡ROBERTS-1-A#(Oஸf-camera) I am, I’m great.4. SANDRA஡LEE-1’SEMI#Okay.5. ROBIN஡ROBERTS-1-A#(Oஸf-camera) But I want to take this oஸf because I’m worriedabout...6. SANDRA஡LEE-1’SEMI#No it’s good, it needs some time.7. ROBIN஡ROBERTS-1-A#(Oஸf-camera) Okay. All right.8. SANDRA஡LEE-1’SEMI#You’re so cute. Okay in the, in this bowl, we have mayon-naise.9. ROBIN஡ROBERTS-1-A#(Oஸf-camera) The store-bought mayonnaise.10. SANDRA஡LEE-1’SEMI#Yes, some spicy, brown mustard. We did not make the mus-tard from scratch268(57) 1. , you have to get the store on board, and then once the store is on board, you have tohope that the customer has the app, right?2. GUY஡RAZ#Yeah. Were the stores interested when you came in? Were they like - Imean, was it...3. WHITNEY஡WOLFE#No. To be honest, very few people were interested. it was re-ally howyou positioned it. And I learned a lot through that experience because, youknow, one pitch would go one way, and you’d say something a little diஸferent the nexttime, and it’d go(58) 1. , it was a matter of normal practice and whenever we use a dynamic entry.2. WOMAN-##Sheriஸf, was there anything else in that hotel room that – that made youthink aside from the number of weapons that made you think he had been there fora while or – or –3. JOSEPH஡LOMBARDO#No, we have information he’s been there since the 28th ofSeptember. SoI have no idea whether he prevented the housekeepers from enteringthe room or not, that’s just a matter of continued investigation. All right, thank youvery much. We’ll provide you an update probably(59) 1. , I’ve listened to you on the radio, and your evolution from a so-called free marketcapitalist to a nationalist protectionist is baஸ஺ாing.2. INGRAHAM#Really?3. ARAMESH#It’s funny that conservatives like you keep talking about who – at leastused to talk about the open market and anti-socialism –4. INGRAHAM#No, I never did. I don’t know what you’re listening to.I never talkabout the open market.5. ARAMESH#I listened to you for ஹ஭ve years.6. INGRAHAM#No, no, no, no.7. ARAMESH#You’re a nationalist protectionist.8. INGRAHAM#No. Arash, Arash, I269(60) 1. in terms of the Trump campaign. But remember that when you talk about Paul Man-afort or Rick Gates, who have already been indicted, these people have been chargedwith conspiracy, not collusion speciஹ஭cally. And when we talk about –2. WALLACE#But it had nothing to do with Russia.3. WILLIAMS#No, conspiracy potentially that could say that there was a conspiracyto bring Russia intocooperation with the Trump campaign.4. (CROSSTALK)5. WALLACE#No, no, no. But, look, the Manafort charges had altered it with his ஹ஭-nancial dealings and it nothing to do with interference in the campaign.B.3.3 COCA ‘no’ + agree, reject QUD (7 examples)(1) 1. a rock, so steady that I wake up to a text message from him every single morning at thesame exact time.2. JENNA஡BUSH஡HAGER#Which, by the way, I do n’t. I’m like, does that say some-thing about me? Just kidding. It’s so sweet.3. BARBARA஡BUSH#No, it just says that he’s a steady little rock, and he started becauseI was brokenhearted once, and he would call me every day to check on me, and then hejust never stopped reaching out every day. So, that’s the sweetest.4. JENNA஡BUSH஡HAGER#It’s the(2) 1. – CARLSON#What should they do about it? He had background checks already.2. CALLOWAY#The government – we can know, we can know how many –3. (CROSSTALK)4. CALLOWAY#Tucker, stop. This is just – this is not productive. So, let’s go to the nextquestion.5. CARLSON#No, but you are not answering my question. Which is what should thegovernmentneeds to do?6. CALLOWAY#This is not being productive, Tucker. What we know at this point thatwe have allowed ourselves to end the gun control debate in this country.2707. CARLSON#This is just propaganda.(3) 1. : I... MATTHEWS: Character?2. Mr-WHITAKER: I think it’s a – well, I think it’s going to be two campaigns. I thinkthey’re going to continue to pursue a lot of that but I think you’re not necessarily goingto see it from McCain.3. Ms-KAY: No, but you’re going to – it’s going to be there on people’s doorsteps.4. MATTHEWS: Kathleen, character? Is that going to it, the endgame?5. Ms-PARKER: Yeah, absolutely. And I agree with Andrew that McCain surrenderedthe experience argument. But that’s really all(4) 1. Come on.2. KATHIE஡LEE஡GIFFORD#21:10): All right.3. HODA஡KOTB- (10#21:11): All right. Anyway, it’s Valentine’s Day. All right. So –4. KATHIE஡LEE஡GIFFORD#21:15): If you want to talk about it more I’m happy to.5. HODA஡KOTB- (10#21:18): No, you’re done. Fine. All right.6. KATHIE஡LEE஡GIFFORD#21:22): Allright. There was an article in the New York Post.There was a piece on how everybody in life needs a work wife or I suppose they alsomean work husband –7. HODA஡KOTB- (10#21:30):(5) 1. n’t commit other crimes or that necessarily that his cooperation is going to be not allthat helpful.2. SMERCONISH#So put your Holland and Knight hat on and not your hat as a formerU.S. Attorney, you’d have a ஹ஭eld day with someone who admitted to the felony of lying.3. BROWNLEY#No, that’s right. that if you look at General Flynn, this issomeone whoboth President Obama and Attorney General Yates had warned folks not to trust. Thisis an individual who was terminated from his job as National Security Advisor becausehe was untruthful to the Vice President and now271(6) 1. it’s all going to be public. And if it’s illegitimate, to which you and the president willsay so. But let’s see what he ஹ஭nds. I would n’t exactly characterize Bob Mueller and theattorneys working for him at the federal bureau as being on a witch-hunt.2. MARTIN#No, I’m trying to narrow the description by the media of what they’redoing.If it’s an investigation into Russia collusion, that seems narrow in focus.3. KRISTOL#What about obstruction of justice? Is that OK with you?4. MARTIN#It depends what it is. If it’s(7) 1. is evil, that’s what you said in your piece.2. YANKAH#I did n’t at all say that in piece, and if you can cite that I would be veryhappy to see it. What I did say –3. CARLSON#Well, you say you can’t thrust them.4. YANKAH#No, I did say that.5. CARLSON#I don’t know if we are making headway. I asked you a question, can youanswer it?6. YANKAH#No. Forgive me, you ask me a question and I returned the question, so Iwanted to conclude on that.7. (LAUGHTER)8. CARLSONB.4 LDC ‘no’ (98 examples)This section includes 37 examples with agreeing followup content which agreed with negationin the triggering utterance, and 33 with disagreeing content which rejected the at-issue content.The remaining 28 were coded as rejecting the QUD.B.4.1 LDC ‘no’ + agree (negative concord) (37 examples)272(1) 1. B: yeah uh uh2. A: it to whi- oh3. B: oh i’m sorry go ahead4. A: No that’s okay(2) 1. B: well you are not from that area originally i can tell2. A: No originally i’m from New Mexico i was born in New Mexico and we lived in uhSouthbend for eighty eight years and uh then moved to uh Tennessee actually(3) 1. B: and just sit and watch the game and a have a pizza and a beer that i would enjoy2. A: uh-huh at a3. A: at a restaurant or at home4. B: No no at home just have it delivered yeah we we have number of our pizza placesdeliver and i assume that you have that there also5. A: at home oh yeah(4) 1. B: and my son o- my son only ஹ஭ve so he’s not old enough yet to send out to to the dothe yard work2. A: No but he will be(5) 1. B: yeah so we’ve got you know we’ve got some investment in it but you really don’t getanything out of it2. A:No you really don’t were you said you were out of state for a while was that a smallertown than than Dallas area(6) 1. B: the big ten didn’t fair too well in the tournament2. A: No they sure didn’t sure didn’t(7) 1. B: of course you could annex Cuba but they wouldn’t like that a bit2. A: No i don’t think they would273(8) 1. B: not too many of the situation comedies do i care for2. A: No i don’t care for tho-3. B: and i’m deஹ஭nitely not a soap fan4. A: too much5. A: the only crazy comedy i really like is Saturday Night Live(9) 1. B: like if you are land up in a such a situation where you can’t escape without takingthat money then deஹ஭nitely one may go for it the diஸference unlike the situation wherein which you are2. B: but like practically thinking like you should not take that money it won’t be a sen-sible decision to take that money3. A: No not at all4. A: in fact it would be probably really harmful to you(10) 1. B: i’m not sure that there is a solution to that as far as uh th- d- there you know every-body has in their mind the kind of day care that they want but2. B: it seems you know that there’s not really the perfect one out there3. A: No there’s not nobody can take care of your kids better than you(11) 1. B: he said something about if you can win a million dollars would you not talk to yourbest friend anymore or something like that2. A: oh would i would you give up your friend for money is that what it was3. B: i think that’s the bas- what the basis of it was4. A: ah there isn’t enough money for in the world for that5. B: yeah and i and i totally agree i don’t think i would give up i would give up my friend-ships my best friend for that no ’cause once all the money’s gone then ah then you justhave yourself your your friend will always be there for you yeah6. A: No not for money7. A: (( not for money ))274(12) 1. A: yeah there’s a lot of crazies out there that can just go in and buy a gun because theydon’t really ask a lot of questions when you walk into those stores2. B: No they don’t they don’t ask anything except how old you are i don’t think that’skind of scary(13) 1. A: yeah see the winter season’s just not that long to to invest a whole lot of money inin uh2. B: and3. A: in the the heavier heavier materials4. B: No and you don’t um you know if you usually can wear pretty close to the sametypes of things just with a jacket or sweater(14) 1. A: yeah my daughter had one i wouldn’t have one ஺ாying around my house2. B: No i know uh(15) 1. A: well they’re showing uh Live and Let Die at this moment and it is the ஹ஭rst appear-ance of Roger Moore as 0072. B: uh-huh yeah3. B: yeah4. A: so it it5. B: oh he could never cut it6. A: No no that’s true i was just thinking that today he well in some of the later movieshe looks very eஸfeminate in the early movies whereas uh Sean Connery has maintainedthe(16) 1. A: well i guess it wasn’t a situa- i mean i guess the mother wasn’t really asked to to lieanyway i guess it was you know2. B: No she wasn’t asked to lie mhm she just was asked um what they were just say-ing you know um what how did she feel about it and she said that her daughter theywere not going to put up any bail and her daughter would just have to um suஸfer theconsequences275(17) 1. A: uh you had to have your car checked for pollution every year you had to have thatlittle sticker in the window i know Texas does2. B: uh yeah um-hum3. A: and there are about three places in Georgia that does4. A: and i think Louisiana does i’m not sure but i there’s not very many of them aroundanymore5. B: well6. B: uh they used to do it down in Florida now i lived down there for ten years7. A: yeah they don’t do it anymore8. B: No they did away with it because they found out that uh9. A: yeah10. B: the people that were doing it it was just a racket to them(18) 1. A: they just grabbed but boy they sure hit pay dirt with that one ring luckily my in-surance you know reimbursed me but i can’t replace those diamonds2. B: No and and and yeah how to put a value on a ring that you’d made(19) 1. A: the fall is what i really miss from Pennsylvania2. B: it just everything just kind of gives up and dies here3. A: yeah it just turns brown and makes a mess4. A: nothing pretty about it5. B:No it j- the the trees just go to about the ஹ஭rst of December and then just oh well it’stime to die so it just it’s just an ugly mess(20) 1. A: the companies felt they had to hire a minority2. A: and ah im- you know i’m like you i really don’t think that that’s right3. B: No not at all you know if someone is4. B: qualiஹ஭ed no matter5. B: what the color of their skin or where they’re from276(21) 1. A: one of my other daughters got a uh gerbil and they came to me for a name and isaid well name him Libreg2. A: and they said well how did you get that name i said well that’s gerbil spelled back-wards3. B: now that’s a good idea4. A: well they wouldn’t let me name the dog5. B: No that one would might get you in trouble(22) 1. A: oh they don’t last that long unfortunately yeah2. B: No they don’t mm mm(23) 1. A: oh i see so so there’s nobody that asks questions2. B: so3. B:Nono there’s no one that asks questions we sit and talk about i guess the the subjectof the day which is they said uh current aஸfairs was today(24) 1. A: money money is not the answer2. B: No there’s plenty of money in the system it’s just(25) 1. A: i mean that’s all you need for like for like bullet charts and stuஸf you don’t needthem in four colors2. B:Nouh-huh if it was a customer presentation then that would be diஸferent we wouldwant to to razzle-dazzle uh but uh(26) 1. A: i i’m more worried about the ozone than i am anything else i i i think we’re gettinga handle on sulfur dioxides and2. A: all that kind of stuஸf uh cooperating with the Canadians on the acid rain problem3. A: but the ozone i mean you know we can’t replace that4. B: No that’s true277(27) 1. A: but just you know to receive a letter in the mail that says you know you need toreport somewhere by next Monday you know i’m not sure that would be a terriஹ஭callygood idea2. B:No i don’t think so either because a lot of people um depending on how the publicservice programs are set up and i’m not -at that familiar with them to know(28) 1. A: but i thought you had to call on three diஸferent days but you don’t2. B: No there is nothing like(29) 1. A: and millwood i mean millwood uh they lose them and they and they still they don’tskip a beat right2. B: No they don’t skip a beat they they have the pitching uh(30)1. B: yeah i think you’re right too but then i don’t i don’t really you know i don’t knowi it’s a terrorist attack and you never really i guess you never know how you’ll respondto a situation until you’re put in it2. A: No you you cannot tell until i think it’s really actually happening(31)1. B: but you know putting them in prison my God that doesn’t work2. A: No apparently not because look how many years they’ve been doing that and looki mean yeah(32) 1. A: because i ஹ஭gured when i got old and retire i don’t want to be working i don’t be aslave to the home2. B: no no you don’t want to be on ladders do you(33) 1. A: you don’t do what they say and you2. B: no not that i promote over government or anything but you know the the world’sin a bad enough state that278(34) 1. B: yeah and the the ground will ஹ஭lter some of it but not all of it2. A:no not when you ஹ஭gure i didn’t realize a cow one cow produces that much manureand they were talking like(35) 1. A: oh so you didn’t even get the severance package2. B: no i should have taken the the the you know uh option when that was there but itwas just i missed it by a couple months(36) 1. A: well don’t you all have mosquitoes down there2. B: no not like not like you have up there no(37) 1. A: yeah um well it didn’t hurt you did it to i mean you didn’t go out and charge awhole bunch and lose everything did you2. B:no no but i have had some times when i’ve had some pretty good balances on thereand uh you know i ஹ஭nallyB.4.2 LDC ‘no’ + disagree, rejecting the at-issue content (33 examples)(1) 1. B: yeah and then they give give you just the local O bits and that’s it and well hell youdon’t know know those people that died or or what from2. A: No the older you get the more you know though(2) 1. B: depending on what industry you get into or whatever like uh you know TI beingelectronics uh you never get out of school so you know2. A: um-hum3. A: No well actually i graduated4. A: with a BS in double E in in eighty eight and i’ve been in school ever since then279(3) 1. B: and of course they’re not going to tell the other side of the story and they’re notgoing to tell it accurately2. A: No3. A: but i do enjoy we are here temporarily i enjoyed having CNN so that i could tune inthe news any time i wanted to and not wait for network broadcasting(4) 1. A: you would never think of having to replace the clutch in a Mercedes2. B: no but then um3. A: especially not afிer two years4. B:No but on the other hand i guess too uh whenever you do have to have some majorwork done on one of those it costs a fortune(5) 1. A: he was really funny2. A: both of the ones i met have been really funny guys i don’t know if that’s uh3. A: if that’s true about all Puerto Ricans or not4. A: ones i met have been pretty pretty funny5. B: No i have no idea but uh so you think that mostly they’re they’re pretty much satis-ஹ஭ed with things the way they are(6) 1. B: and then the spackling had to dry a day and then the painting took another day2. A: you didn’t try we rewallpapering you just uh3. B: No i i just painted(7) 1. B: i’ve i’ve i’ve also thought thought ballese would be an interesting choice because it’suh you have english speakers i mean i speak spanish but the english would help um youhave the the galapagos which are close by i believe2. A: oh yeah3. A: oh deஹ஭nitely4. A: oh yeah2805. B: so there there’s a lot of beauty there too6. A: oh i yeah actually that’s one place i really would like to go7. B: ballese8. A: No galapagos9. B: yeah the galapagos it’s it’s supposed to be something else(8) 1. B: yeah see my husband’s one of these that will switch from game to game to catch alittle bit of every one you know2. A: No i like to stick to one game(9) 1. B: you seen the movie2. A: No i that looked just horrible to me(10) 1. B: yeah well i mean if if you didn’t have to2. B: you know take the oஸfer ah genuinely w- would you ah would you accept it no3. A: No i wouldn’t of course not nah money’s not worth that(11) 1. B: yeah california is really weird about smoking2. A: that’s you said that’s where you’re from3. B: No no no no i’m from michigan(12) 1. B: yeah2. A: and that’s true um3. A: (( and they pay me through right ))4. B: No they send a check to you281(13) 1. B: would you rather go out to eat or not i think2. B: that’s the only question i heard3. A: No i4. A: i think there was another one i thought there was another question(14) 1. B: well do you think that we do it because we want it to deter crime or it’s not becausewe don’t want to pay for inmates to stay in prison2. A: No i don’t think it’s a monetary thing i think we hope that it will be you know3. B: um-hum4. A: some sort of deterrent deterrent or you know an eye for an eye type thing or some-thing like that(15) 1. B: well are you uh you said you’re not in a in a rich neighborhood but are there arethere obviously um2. B: drug people in the area3. A: No not right here i i have never even seen like uh what they call a crack house oranything i wouldn’t(16) 1. B: so well i guess i’ll let you get back to feeding your little one there2. A: No uh he’s all done yeah yeah i set him down(17) 1. B: oh your up in Memphis2. A: No i used to be i’m in Texas(18) 1. B: it was like a dead end on the other2. B: on the other end of the phone3. A: oh was that yesterday4. B: yeah uh-huh5. A: oh yesterday i wasn’t home my friend picked up2826. B: oh yeah7. A: so i didn’t know what it was yeah yeah yeah8. A: but i like i what was it do you know what the day before it was9. B: No uh-huh i just started um10. B: actually yesterday11. A: yeah oh you started yesterday12. B: yesterday is my ஹ஭rst day(19) 1. B: i’m surprised that a bird uh i guess they can ஹ஭nd their way back but i wonder exactlywhere a tame bird would go2. A: did she ever get it back3. B: No no she never got it back i’ve heard stories like this before with parrots and allthis uh because people let them out out in their house you know and ஺ாy around(20) 1. B: i was there a couple of years ago actually2. A: oh you lived here3. B: No i had a conference down there(21) 1. A: you’re way too young to remember the original castle wolfenstein2. B: No i remember that i actually have it on i have it a- actually on ஺ாoppy [laughter]uh my uncle gave it to me like i don’t know i don’t know six years ago or eight yearsago or something like that and i still have it somewhere in a box on a on a ஺ாoppy(22) 1. A: yeah you watching uh the sixer game2. B: No i’m i’m i ha- i have on the channel that we get our sixer g- games on but uh i’mwatching um uh enterprise283(23) 1. A: yeah it’s always economic and it’s economic there too2. B: and like what the germans probably have the upper hand or the germanic3. A:No i think the french do actually yeah the french traditionally have had all the youknow manufacturing jobs and the good agricultural jobs(24) 1. A: yeah ah yeah i ah i defended this country in a military uniform yeah yeah2. B: really i mean you are you in the armed forces3. A: No not now(25) 1. A: we raise orchids2. B: oh my3. A: which is a little bit tough to do up here in the north but it’s a solar greenhouse weput up you know like the walls are six inches thick4. B: yeah yeah well do you not have shade cloths and so forth and5. B: uh-huh well6. A: No no we we we used uh ஹ஭berglass uh we’re face- the the greenhouse faces solarsouth(26) 1. A: once i get this last one into school then we’ll see about me going to work2. B: right that that’s true now you you d- you d- just need to treasure all them days thatyou’re home with them little ones ’cause3. B: it they it’s going so quick it’s going so quick4. A: oh i’ll be glad when they’re gone [laughter] oh yes i will5. B: No you won’t you won’t [laughter] you’ll look back and say oh i did i i just didn’tenjoy them enough [laughter]284(27) 1. A: okay so we’ve got to talk about music and um do you like classic rock or modernrock or which kind2. B: okay3. B: oh i guess the stuஸf that was done more in the seventies because that’s4. A: No not a seventies baby(28) 1. A: okay he did where’d he decide to go2. B: um to Williams College in Massachusetts3. A: uh-huh sure i’m familiar with it4. B: and that he was he was uh trying to decide between University of Pennsylvania andWilliams and it was a very diஸஹ஭cult choice and uh5. A: and he well he must know is he interested in law or medicine he must have a deஹ஭niteprofession in mind6. B:No but that’s one of the reasons why he chose Williams that it has solid liberal arts7. A: oh okay(29) 1. A: oh i didn’t know how that ’cause i was waiting for them to call me i didn’t knowyou could call the system up2. B: but you received the call right now3. A: No i re- i called into the system but i i last night the system called me(30) 1. A: oh dear well i don’t have any my big solutions all go back to elect politicians thatare more sensitive because i think we can’t do it ourselves2. B: No i i n- no i don’t think we will because you nee- you need some kind of organi-zation for it and3. A: you need clout(31) 1. A: now i’ve got a portable cordless is that what you’re using2. B: No i’m using a regular phone now uh285(32) 1. A: i thought you were saying can you hold on oh okay2. B: No no i was talking my little girl wanted her shoes oஸf(33) 1. A: hello2. B: hi this is frank3. A: hi frank i’m mark how are you4. B: okay5. A: um where are ya6. B: where am i7. A: yeah8. B: ah new jersey9. A: new jersey oh okay you’re not too far i’m in phili10. B: (( oh okay ))11. A: ah so um this ah question sounds [laughter] sounds a little ludicrous if you ask me12. B: [laughter] you’re right13. B: ah personally speaking ah14. B: i feel it’d be a tough thing to to accept15. A: you would accept it16. B: No i don’t think i i don’t think i could17. A: oh you wouldn’t accept it no iB.4.3 LDC ‘no’ + agree, reject QUD (28 examples)(1) 1. B: you don’t even want to know what it cost to keep a horse you know and i2. A: cost yeah3. A: i think i’ll just go rent a horse if i want to ride one4. B: right i think the best thing in the world is to rent them i think that uh5. A: yeah i do too2866. B: tha- that and boats are probably the same way i’d love to have a boat too but i thinkuh i’m not too sure i i would get that much use out of it you know7. A: yeah8. A: No i mean well i do enjoy my dog uh she’s such a9. A: oh she’s my best friend and when when i lived in Orlando she uh got paralyzed fromher waist down and uh waist(2) 1. B: you could never get use to that kind of weather2. A: No it’s true(3) 1. B: yeah you wouldn’t know what to say ’cause you’re just you’re mind would be2. A: No what am i going to call my mother and i’m telling her i’m about to die(4) 1. B: yeah in fact i think you can even uh order a magazine that keeps you up to date everyday of what happened on every particular soap in case you miss it2. A: uh-huh3. B: but uh4. B: that that’s not real life to me so5. A: No i think it’d be an awful waste of time(5) 1. B: well we place a real high priority on education in our family2. A: No and i agree i mean my husband and i in fact i’m taking my LSATs um i’m thirtysomething and taking my LSATs on June tenth(6) 1. B: well that doesn’t sound very expensive to me2. A: No i liked it i had fun with it but uh you know uh i’m a little shaky when it comesto detail work so i couldn’t get the ஹ஭ne pieces so you know i had to287(7) 1. B: so we have to keep talking right2. A: i don’t know i don’t know what the heck to do3. A: i don’t think i’ve ever gotten one of these before4. B: No5. B: well how many times have you done this6. A: well i mean i’ve never gotten a phone call(8) 1. B: so but you haven’t seen any money2. A:No i talked to someone they said something about how it takes eight weeks er whichmakes sense(9) 1. B: pretty hard to go back2. B: to pennsylvania where i was born and raised it’s got ah3. B: it’s got fake mexican food4. A: No fake fake mexi- like taco bell(10) 1. B: okay well i just didn’t know that much about music and i wasn’t sure what kind ofmusic you know2. A:No it’s very hard because see well i mean in the whole spectrum i’d rather listen youknow t- what- i listen to heavy metal or or classic rock(11) 1. B: i don’t know how people stay at home and watch soaps and get involved in thembut2. A: No i don’t either i just don’t have any interest(12) 1. B: but still i would hate to be on the jury that sentenced someone2. A: so would i- i fortunately never been in that circumstance i hope i never am like likeeverybody else3. B: nNoo i know when um we just we moved here um i from the4. B: i got a summons jury summons just288(13) 1. A: yeah we’re not from Texas either um2. A: we’re i grew up in Pennsylvania so3. B: oh so you’re really4. A: yeah it it’s not like this in Pennsylvania5. B: No i like the winters but i don’t like the summers down here it6. A: it’s awfully hot(14) 1. A: well i guess our ten minutes aren’t quite up yet [laughter]2. B: No i don’t know it’s getting close this is h- how how many of these have you done(15) 1. A: well i guess it wasn’t a situa- i mean i guess the mother wasn’t really asked to to lieanyway i guess it was you know2. B: No she wasn’t asked to lie mhm she just was asked um what they were just say-ing you know um what how did she feel about it and she said that her daughter theywere not going to put up any bail and her daughter would just have to um suஸfer theconsequences3. A: (( hm ))4. A: no i i i’m that’s interesting because i hadn’t heard any more about that story(16) 1. A: that’s pretty interesting too but like you’re right it was over too quick [laughter]2. B: yeah but certainly if you can try and see if you can sign up3. A: sign sign up for what for more4. B: No no for more see if you could get more(17) 1. A: she is she’s the most intelligent dog i’ve ever seen2. A: course i’m3. A: little prejudice of course4. B: well that’s understandable yeah that’s uh5. A: No the ஹ஭rst time i brought her home she was only uh was it six weeks old289(18) 1. A: other than those jobs i c- i’m i’m not crafிy at all so i don’t think i could come upwith any kind of a crafி business [laughter]2. B: No i like cross stitch and i like latch hook and needlepoint but i don’t you know itseems like crafி stores are like populated everywhere though(19) 1. A: imagine terrorists attack when you are on the airplane here i would freak out forsure2. B: No3. B: oh you would freak out on an airplane(20) 1. A: i’ve never been there my dad used to work for DuPont and they built a chemicalplant down there i almost moved there when i was in high school2. B: really3. A: yeah4. B: No i’ve never been there either i’ve not known but just a few people from there(21) 1. A: i’ve never been past Ohio2. B: you’ve never seen the great American desert3. A: No huh-uh i’ve never seen anything out i never seen the great i’ve seen(22) 1. A: hello2. B: hi it’s ah roy3. A: oh i’m ben4. B: he5. B: had a little bit of time to think about it kind of put you on the spot6. B: throws you right in7. A: that’s true you all go ஹ஭rst or i’ll go ஹ஭rst8. B: No sure ah9. B: i’m ah i’m thinking i’m staying290(23) 1. A: he really was going to was going to do surgery for ஹ஭fிeen hundred dollars or put herto sleep and i was going to have to opt to have to put her to sleep even as mu- much asi loved her i wasn’t going to spend ஹ஭fிeen hundred dollars on an experiment2. B: oh yeah3. B: yeah plus i’m not too sure yeah i think they are experiments too and they don’tknow that much uh4. A: No but it was just uh that spot that they put on the back of a dog uh they used touse it on cattle and uh so i started using it on her and i’d take to her to the vet once amonth and get that spot put on her(24) 1. A: but they don’t look you know like uh she had complained about it one time andthe girl said she was sorry she picked up these utensils and and when back and grabbedsome new ones and then put the new ones back down and the new ones looked worsethan the ones that she took away so she is not even looking you know and2. B: oh3. B: No no and actually you know those are the kind of things that should get takenback to the management(25) 1. A: yeah that is too much and i mean i um i can only say it’s strange your son pickedthose kinds of college because i spent a year at Bennington in Vermont um and thatwas this was twenty years ago showing my age um2. B: oh it’s so you3. B: uh-huh4. B: and did you ever eat at the Blue Bin Diner5. A: yes oh my God where are you from well let’s not talk about that6. B: No but we’ve been there when i’m up at Williams we’ve gone up there(26) 1. B: that’s not going to help anybody get over the problem i believe it is a a a medicalproblem2. A: no ab-3. A: that’s right291(27) 1. A: i don’t know i- i suppose to somebody’s way of thinking we are but um i know thatwhen they do get out the majority of them aren’t able to ஹ஭nd jobs are they or get backinto society because they have that stigmatism2. B: no3. B: that’s right and as much as you say yes you know i’ve paid my debt to society andall that it’s still there(28) 1. B: well we place a real high priority on education in our family2. A: no and i agree i mean my husband and i in fact i’m taking my LSATs um i’m thirtysomething and taking my LSATs on June tenth292Appendix CExperimental dataThe following table presents the number of responses for each rating and under each experimen-tal condition.293Table C.1: Count of acceptability ratings under experimental conditionsStimuli ResponsesPRP FollowupCondi-tionVeryacceptableAcceptable Unaccept-ableVery Unac-ceptable‘Yeah’8>>>>>>>>>>>>>>>><>>>>>>>>>>>>>>>>:Agreeing8>>><>>>:CS 77 54 25 8CN 88 45 20 11DS 7 10 28 119DN 2 9 38 115Disgreeing8>>><>>>:CS 1 19 63 81CN 15 53 60 36DS 44 61 34 25DN 49 62 37 16‘No’8>>>>>>>>>>>>>>>><>>>>>>>>>>>>>>>>:Agreeing8>>><>>>:CS 107 36 17 4CN 93 50 12 9DS 9 45 55 55DN 17 17 82 48Disgreeing8>>><>>>:CS 3 8 28 125CN 17 53 50 44DS 135 12 8 9DN 49 63 32 20“Condition” refers to the experimental conditions of convergence/divergence and scalar/nonscalar:CS = Convergent Scalar, CN = Convergent Nonscalar, DS = Divergent Scalar, DN = Divergent Nonscalar.294
Thesis/Dissertation
eng
Linguistics
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
'Yeah, I doubt it.' 'No, it's true.' How paradoxical responses impact the common ground
Text