Arts and Social Sciences, Irving K. Barber Faculty of (Okanagan)
Psychology, Department of (Okanagan)
DSpace
UBCO
Winslow, Magpie Michael
Master of Arts - MA
University of British Columbia
Survivors of sexual assault are often pitted against their alleged attacker in a contest of credibility. However, there is little research on the relationship between the survivor’s credibility and the attacker’s. The present study in- vestigates this relationship using a model from quantum cognition called the QQ equality. This model predicts that the order of credibility judgements is important and that judgements about the survivor impact the alleged attacker’s credibility to the same degree that judgements about the alleged attacker impact the survivor’s credibility. A sample (n = 1493) of US adults were asked to judge the credibility of statements from both the survivor and attacker in hypothetical cases of sexual assault. Contrary to predictions, there was no effect of judgment order on the perceived credibility of either party. However, correlations between random subsamples did provide evi- dence of the QQ equality. These results suggest that the two judgements neither share a feature space nor exist in separate spaces; instead, they may exist in feature spaces with both unique and shared components. This study’s findings suggest that further research into modelling feature spaces may provide insight into factors impacting a survivor’s perceived credibility.
Quantum Equality in the CourtroombyMagpie Michael WinslowB.Sc., Montana State University, 2021A THESIS SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFMASTER OF ARTSinThe College of Graduate Studies(Psychology)THE UNIVERSITY OF BRITISH COLUMBIA(Okanagan)April 2024© Magpie Michael Winslow, 2024The following individuals certify that they have read, and recommendto the College of Graduate Studies for acceptance, a thesis/dissertation en-titled:Quantum Equality in the Courtroomsubmitted by Magpie Michael Winslow in partial fulfilment of the re-quirements of the degree of Master of ArtsDr. Leanne ten Brinke, Irving K. Barber School of Arts and SciencesSupervisorDr. Brian O’Connor, Irving K. Barber School of Arts and SciencesSupervisory Committee MemberDr. Douglas Scott, Department of Physics and Astronomy, UBC VancouverSupervisory Committee MemberDr. Elena Nicoladis, Irving K. Barber School of Arts and SciencesUniversity ExaminerDr. Madeleine Ransom, Simon Fraser UniversityExternal ExamineriiAbstractSurvivors of sexual assault are often pitted against their alleged attackerin a contest of credibility. However, there is little research on the relationshipbetween the survivor’s credibility and the attacker’s. The present study in-vestigates this relationship using a model from quantum cognition called theQQ equality. This model predicts that the order of credibility judgementsis important and that judgements about the survivor impact the allegedattacker’s credibility to the same degree that judgements about the allegedattacker impact the survivor’s credibility. A sample (n = 1493) of US adultswere asked to judge the credibility of statements from both the survivor andattacker in hypothetical cases of sexual assault. Contrary to predictions,there was no effect of judgment order on the perceived credibility of eitherparty. However, correlations between random subsamples did provide evi-dence of the QQ equality. These results suggest that the two judgementsneither share a feature space nor exist in separate spaces; instead, theymay exist in feature spaces with both unique and shared components. Thisstudy’s findings suggest that further research into modelling feature spacesmay provide insight into factors impacting a survivor’s perceived credibility.iiiLay SummaryWhile there is a fair amount of research on the perceived lack of credi-bility of sexual assault survivors, a majority of the studies look at survivorsin isolation, even though people are often asked to compare the credibilityof survivors against that of their attacker. To explore this relationship, thepresent study used a prediction from the field of quantum cognition calledthe QQ equality. Quantum cognition is a relatively new field that attemptsto describe decision-making using the tools of quantum physics, with theQQ equality being a prediction about the relationship between similar ques-tions. We found that changing the order in which people receive informationcan change who they think is credible. We proposed a new way for quantumcognition to describe the information people use in decision-making.ivPrefaceThis research was conducted at the University of British Columbia Okana-gan and was supervised by Dr. Leanne ten Brinke. For the present thesis,I was responsible for designing and developing the research paradigm, datapreparation and analysis, and the written thesis. I also provided an outlineof the statements presented to participants, and Dr. ten Brinke helped toflesh out the specifics. The Behavioural Research Ethics Board of the Uni-versity of British Columbia’s Okanagan Campus granted ethics approval forthis research. The certificate approval number for the project is H22-02650.To date, the results of this study have not been published.vTable of ContentsAbstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iiiLay Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ivPreface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vTable of Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . viList of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viiiList of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xAcknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . xiDedication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiiChapter 1: Introduction . . . . . . . . . . . . . . . . . . . . . . . 11.1 Sexual Assault in the Legal System . . . . . . . . . . . . . . . 11.1.1 Perceived Credibility of Sexual Assault Allegations . . 21.2 A New Perspective on Credibility Assessment . . . . . . . . . 31.2.1 Competing Narratives . . . . . . . . . . . . . . . . . . 41.2.2 Rational Choice Theory . . . . . . . . . . . . . . . . . 51.3 Quantum Cognition . . . . . . . . . . . . . . . . . . . . . . . 61.4 Current Study . . . . . . . . . . . . . . . . . . . . . . . . . . 9Chapter 2: Methods . . . . . . . . . . . . . . . . . . . . . . . . . 112.1 Participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112.1.1 Design & Materials . . . . . . . . . . . . . . . . . . . . 122.1.2 Procedure . . . . . . . . . . . . . . . . . . . . . . . . . 132.2 Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15Chapter 3: Results . . . . . . . . . . . . . . . . . . . . . . . . . . 18viTABLE OF CONTENTS3.1 Question Order . . . . . . . . . . . . . . . . . . . . . . . . . . 183.2 Statement Placement . . . . . . . . . . . . . . . . . . . . . . . 193.3 Subsampling . . . . . . . . . . . . . . . . . . . . . . . . . . . 21Chapter 4: Discussion . . . . . . . . . . . . . . . . . . . . . . . . 254.1 Quantum Cognition . . . . . . . . . . . . . . . . . . . . . . . 264.2 Limitations and Future Directions . . . . . . . . . . . . . . . 294.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31Appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38Appendix A: Vignette and Questions . . . . . . . . . . . . . . . . . 38A.1 Vignettes . . . . . . . . . . . . . . . . . . . . . . . . . . . 38A.2 Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . 40Appendix B: Task Instructions . . . . . . . . . . . . . . . . . . . . 42B.1 Conditions 1 & 2 instructions . . . . . . . . . . . . . . . . 42B.2 Conditions 3 instructions . . . . . . . . . . . . . . . . . . 42viiList of TablesTable 2.1 A table view of the different conditions in this study.“Survivor/Attacker Statement” here refers to the vari-ation of the Mary and Bill statements used in that partof the study. “Survivor/Attacker Credibility” meansthat participants will assess that party’s credibility.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15Table 2.2 Contingency table for the analysis of order effect. arepresents the number of people that gave the responsepattern for a given vignette in the first condition. brepresents the number of people that gave the responsepattern for a given vignette in the second condition.The subscripts give the response pattern with the re-sponse about the survivor first and the responses aboutthe attacker second. For instance, “YN ” is “Yes-No”and corresponds to thinking the survivor is credibleand the attacker isn’t. Each column has a responsepattern, while each row has a different question order.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16Table 2.3 Contigency table for the analysis of the QQ equality.a represents the proportion of people that gave a spe-cific response pattern in the first question order. brepresents the proportion of people that gave a spe-cific response pattern in the second question order.The subscripts represent the same response patternsin Table 2.2. “Major” refers to the total proportionof people who gave the same response to the first andsecond questions in that order (responded either yes-yes or no-no). “Minor” refers to the total proportionof people who responded differently to the first andsecond questions (either yes-no or no-yes).. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17viiiLIST OF TABLESTable 2.4 Contigency table for the analysis of the effect of in-formation on the QQ equality. In this table, the vari-able c represents the number of people who respondedwith that response pattern for a given vignette in thethird condition. “Mary - Bill” means that people de-termined Mary and Bill’s. “Mary - Statement - Bill”means that Bill’s statement was placed between cred-ibility judgments. All other notations follow the con-ventions established previously.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17Table 3.1 Response pattern frequencies for each vignette in Con-ditions 1 and 2. In the header, the first responseis whether the participants thought the survivor wascredible, and the second is whether they thought theattacker was credible (“Yes-No” corresponds to think-ing the survivor is credible and the attacker isn’t.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19Table 3.2 Response pattern frequencies for each vignette in Con-ditions 1 and 3. In the header, the first responseis whether the participants thought the survivor wascredible, and the second is whether they thought theattacker was credible (“Yes-No” corresponds to think-ing the survivor is credible and the attacker isn’t.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20Table 3.3 Correlations and means from subsamples of the data.Results significant for p ≤ 0.01 are bolded, and allcorrelations have a df = 98. The meaning of “Major,”“Minor,” and the subscripts for the means retain pre-viously established meanings.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24ixList of FiguresFigure 3.1 Scatter plots of context effects for the subsampleddata of Conditions 1 and 2. The top row shows therelationship between the Yes-Yes response context ef-fects and the No-No context effects. The bottom rowshows the relationship between the Yes-No contexteffects and the No-Yes context effects. . . . . . . . . 22Figure 3.2 Scatter plots of context effects for the subsampleddata of Conditions 1 and 3. The top row shows therelationship between the Yes-Yes response context ef-fects and the No-No context effects. The bottom rowshows the relationship between the Yes-No contexteffects and the No-Yes context effects. . . . . . . . . 23xAcknowledgementsI can not begin to express how grateful I am to everyone who helpedme bring this project over the finish line. I am thankful to Dr. Leanne tenBrinke, who gave me a chance and gave me the ability to try this weird idea.I would genuinely be in a worse place without your support and patience. Ialso need to thank Dr. Brian O’Connor not only for agreeing to be on mycommittee but also for his help with ideas for data analysis. The findings,and especially the partial feature space hypothesis, would not exist withoutyour suggestions and advice. I am also so grateful to Dr. Douglas Scott foragreeing to try something new and supervise a psychology thesis. You’vehelped keep me honest about the implications of the work. Additionally,I want to thank Dr. Madeleine Ransom for agreeing to be my ExternalExaminer as you posed some of the most intriguing questions about thiswork and Dr. Elena Nicoladis for being my neutral chair.I could not have survived this thesis without the community I’ve metalong the way. I’m so grateful to my entire cohort, to whom I owe thesurvival of my first year. I could not think of a better group of peopleto help introduce me to Canada. I am so lucky to have had friends likeKirthana, Iana, Natashaa, Rebecca, and Amane´, who so often gave me theperspective and kind space I needed. I do not know what I would’ve donewithout you. I also need to thank my family for always being supportive ofmy weird theories. Finally, I need to thank Mx. Noble for so much, but alsofor teaching that math serves the theory, not the other way around.xiDedicationTo the hope for better days. May they come to my siblings and all whoneed them.We’re here because we’re here because we’re here...xiiChapter 1IntroductionSexual assault is a highly prevalent, rarely reported, and rarely triedcrime (Rotenberg, 2017). When reported, it is often met with skepti-cism (Rotenberg, 2017). When tried, there is rarely reliable physical ev-idence, and it becomes a credibility contest between the survivor and theattacker (Vandervort, 2005). Previous research has identified situational,behavioural, and appearance-related variables that contribute to percep-tions of the credibility of survivors and attackers (Bagby et al., 1994; Bakeret al., 2021; Berry-Caba´n et al., 2020; Golding et al., 2016; Lynch et al.,2020; Wasarhaley et al., 2012). However, what has not been considered iswhether making credibility judgements about one party may impact judge-ments about the other party, ultimately influencing case outcomes. Wedraw upon the burgeoning field of quantum cognition to test whether apredictable pattern of order effects exists in credibility judgements aroundsexual assault.1.1 Sexual Assault in the Legal SystemIt is estimated that only 6% of sexual assault cases are reported to thepolice (Cotter, 2021). In Canada, 34,242 cases of sexual assault were re-ported to the police in 2018 (Moreau, 2020), suggesting over half a million(570,700) cases of sexual assault occurred. Of the reported cases, 59% in-volved a person being accused, 43% of those resulted in charges, 49% ofthose went to trial, and 55% of those resulted in a conviction (Rotenberg,2017). In other words, approximately half of cases are dropped at each stepof the legal process, resulting in approximately 7% of accusations result-ing in a conviction. While some of this attrition is from survivors choosingalternate routes for justice, a perceived lack of evidence is another majorfactor. Before reaching court, if the police or The Crown think there is notenough evidence to prove the alleged attacker guilty beyond a reasonabledoubt, the charge will be changed to a less severe offence or be droppedaltogether (Rotenberg, 2017). Sexual assault legal cases often have littletangible evidence and a critical determinant in whether sexual assault cases11.1. SEXUAL ASSAULT IN THE LEGAL SYSTEMsee trial, much less conviction, is the survivor’s perceived credibility (Herlihy& Turner, 2015; Nitschke et al., 2019).1.1.1 Perceived Credibility of Sexual Assault AllegationsCurrent research suggests that false sexual assault claims are rare. Anestimated 5% of rape allegations in the United States are deemed unfounded(De Zutter et al., 2017). Less than 5% of rape cases brought before author-ities were considered fraudulent in over twenty European countries (Kelly,2010). In Canada, 8% of level one sexual assaults reported were classified asunfounded (Moreau, 2020). Despite such findings, McMillan (2018) foundthat police in the United Kingdom estimated 53% of rape allegations werefalse. The reasoning the police used for this estimate was often founded inassumptions of how “real” survivors of sexual assault ought to act (McMil-lan, 2018). The assumptions themselves were based on sexual assault mythsand included how injured a survivor should be, the amount of detail in theirstatement, and the sobriety and mental health of the survivor, amongst oth-ers (McMillan, 2018). The effects of these assumptions carry over to lawyerswho have also been found to use rape myths to determine the viability ofa case, no matter their level of experience (Krahe´ et al., 2008). Judges willalso rely on unfounded assumptions around the impact of traumatic mem-ories on behaviour to inform their rulings (Herlihy & Turner, 2015). At alllevels of the legal system, research suggests that survivors’ credibility is afunction of how those judging them think they should act.To understand the credibility of sexual assault survivors, previous re-search has attempted to unpack how a variety of behavioural and appearancecues can influence judgements. For survivors who are perceived as women,appearance cues such as being perceived as overweight (Clarke & Stermac,2011) or unattractive (Maeder et al., 2015) are related to being disbelieved.Behaviourally, a survivor’s credibility can be tied to whether they presenta distressed affect, whether their actions are congruent with expectationsaround sexual assault, and the degree to which they trigger other people’scompassion (Ask & Landstro¨m, 2010; Kaufmann et al., 2003; Nitschke et al.,2019; Winkel & Koppelaar, 1991). The use of affect to assess credibility isknown as the emotional survivor effect and is present regardless of profes-sional experience or presentation medium (Nitschke et al., 2019; Winkel &Koppelaar, 1991).Additionally, whether or not a survivor has a consistent narrative is oftenused to determine credibility. Consistency as a way to assess credibility as-sumes that, if a person’s story changes, they are not telling the truth and is21.2. A NEW PERSPECTIVE ON CREDIBILITY ASSESSMENToften used by both the police and judges to determine the credibility of sex-ual assault survivors (Herlihy & Turner, 2015; Kelly, 2010; McMillan, 2018).In reality, while traumatic memories tend to be more vivid than memoriesof other events, they are also highly susceptible to distortion (Strange &Takarangi, 2015). As a result, survivors have often been advised againstseeking therapy until after the trial (Herlihy & Turner, 2015).While these various biases are common, they do not lead to accurateassessments of a survivor’s credibility. In Peace et al. (2012), participantswere presented with two authentic and two false narratives about sexualassault. Not only were participants unable to accurately determine thecredibility of the statements, but they also performed significantly worsethan chance. Further, the more emotionally intense the narrative, the lesslikely participants were to judge the statement’s credibility correctly. If thebiases at play were simply inaccurate, then one would expect participantsto perform as well as chance; however, these results suggest that biases maybe in opposition to reality or that there may be further processes at play inbiasing participants’ responses.1.2 A New Perspective on CredibilityAssessmentThese previous studies assume that people take a set of discrete obser-vational cues to evaluate credibility through semi-rational processes. Forexample, Maeder et al. (2015) discusses multiple arguments participantscould use to determine the credibility of the survivor and attacker from theirrespective attractiveness and race. Clarke and Stermac (2011) suggest dif-ferent ways a survivor’s weight may factor into various sexual assault mythsby presenting potential ways participants could use the survivor’s weightin their reasoning process. Lynch et al. (2020) discusses how the perceivedgender of the survivor and attacker, as well as the cost of a date, influenceeach party’s credibility.This research is an attempt to step back and understand if these judge-ments can be influenced by something other than observational cues. Previ-ous research has used quantum cognition to describe and predict the waysthat the placement of information and the order of questions influence thecredibility of political candidates (Wang & Busemeyer, 2013; Wang et al.,2014). This prediction called the QQ equality (Wang & Busemeyer, 2013),concerns pairs of related questions, such as judgments about the credibilityof a survivor versus an attacker. This research will test if the QQ equality31.2. A NEW PERSPECTIVE ON CREDIBILITY ASSESSMENTholds for these credibility judgements.1.2.1 Competing NarrativesIn the literature reviewed thus far, most studies have focused on thesurvivor’s perceived credibility. Everything from the presentation medium(Nitschke et al., 2019) to the survivor’s appearance and description (Clarke& Stermac, 2011; Maeder et al., 2015) are considered and varied, but theattacker is rarely accounted for. This does not reflect the environmentalreality of sexual assault cases, because the attacker’s narrative is often pre-sented alongside the survivor’s in public discourse (Casselman & Tankersley,2019; Dale, 2022; Kessler, 2018; Peters, 2022; Urquhart, 2022). In Cana-dian law, once evidence has shown a lack of consent on the survivor’s part,the burden of evidence lies on the alleged attacker to show they made a“mistake of fact” and were unaware that consent had not been given or hadbeen withdrawn (Vandervort, 2005). This implies that the alleged attacker’scredibility is just as important as the survivor’s in deciding sexual assaultcases.The limited research that has presented both attacker and survivor nar-ratives has found that situational context, attacker and survivor character-istics, and judge demographics are associated with perceived credibility. Forexample, in date-rape scenarios, attackers were perceived as more crediblein their denials when they were of higher status and paid for more expen-sive dates (Lynch et al., 2020). Men, in general, tend to be more lenienton male attackers, finding them more credible when compared to femaleparticipants’ judgements (Golding et al., 2016; Lynch et al., 2020; Wasarha-ley et al., 2012). Additionally, attackers described as obese were consideredmore credible than those who were described without referencing weight (Ya-mawaki et al., 2018). When looking at the dyad of survivor and attacker,cases of interracial rape are more likely to be believed than intraracial cases(George & Mart´ınez, 2002). In general, there is an understanding that sit-uational and behavioural factors impact attacker credibility; however, thereis little to no study of the relationship between the credibility of the attackerand the survivor.Most studies that consider both parties’ perceived credibility treat themas independent measures. That is, the attacker’s perceived credibility istreated as if it has no bearing on the perceived credibility of the survivor.This is not a trivial assumption as it implies that the alleged attacker’sverdict is independent of perceptions of the survivor’s statement and goesagainst the prevailing framework used by legal decision-makers: rational41.2. A NEW PERSPECTIVE ON CREDIBILITY ASSESSMENTchoice theory (Jaeger & Trueblood, 2018).1.2.2 Rational Choice TheoryRational choice theory assumes that humans will make entirely ratio-nal choices based on the available evidence. Specifically, when people areuncertain about a decision, they will collect information and apply the as-sumptions of classical probability theory to come to a decision (Becker, 1976;Jaeger & Trueblood, 2018). This theory, and its underlying logic, has beenthe basis for many policies and is often used when making legal decisions(Jaeger & Trueblood, 2018), despite research finding that it is not gener-ally applicable (Simon, 1955; Tversky & Kahneman, 1974, 1983). Theseinaccuracies have led legal scholars instead to develop behavioural law andeconomics (BLE: Jaeger & Trueblood, 2018) (Jaeger & Trueblood, 2018).BLE can be seen as an extension of rational choice theory since it uses re-search on heuristics and biases to describe specific instances where people donot follow the predictions of rational choice theory. However, BLE is severelylimited in its predictive capabilities because it does not specify a mechanismto explain why people act irrationally, instead saying that people can beirrational in the ways described by heuristics and bias research (Jaeger &Trueblood, 2018). Because of this limitation, rational choice theory is theprimary tool for making predictions in legal theory.While the typical assumption in statistical tests is that the survivor andattacker’s credibility are independent, applying rational choice theory pre-dicts the opposite. Assuming the survivor and the attacker contradict eachother, only one statement can be true, and the other must be false; thus, thetwo credibility scores should have a strong negative correlation. ApplyingBLE would predict the same negative correlation, with the addition thatfactors not directly related to the legal case, such as race, ethnicity, gender,affect, etc., may bias the credibility scores.The limitations of rational choice theory and BLE have recently led somescholars to propose the theory of quantum cognition. This theory is basedon the mathematical principles developed for quantum mechanics and canpredict multiple different heuristics and biases (Pothos & Busemeyer, 2022).When applied to legal cases around sexual assault, quantum cognition canprovide a unique perspective to understand credibility judgements.51.3. QUANTUM COGNITION1.3 Quantum CognitionThere is a fundamental difference between quantum cognition descrip-tions of uncertainty and measurement processes and the descriptions pro-vided by rational choice theory. In rational choice theory, people deal withuncertainty by following the rules and assumptions of classical probability,specifically Bayes’ theorem (Bruza et al., 2015). Bayes’ theorem broadlydescribes how new evidence should impact the likelihood of a given eventwhen reasoning using formal logic. Further, it assumes that the events arewell-defined and cannot occur concurrently. By modelling cognition withBayes’ theorem, rational choice assumes that people effectively use formallogic to update individual beliefs using specific pieces of evidence.While classical probability works with well-defined sets of distinct events,quantum mechanics is designed to work with more general, indeterminantsystems (Busemeyer et al., 2011). In quantum mechanics, phenomena suchas the position and momentum of an object only have specific values af-ter being measured, otherwise existing in multiple places and speeds atthe same time (Griffiths & Schroeter, 2018). Measurements then alter thephenomenon being measured and impact future measurements of relatedphenomena (Heisenberg, 1983). When applied to human cognition, one in-terpretation is that a person’s answer to a question only solidifies once theyrespond to that question. This interpretation suggests that before answer-ing, the person’s mental state is diffused over the possible responses, with apreference for certain options that make them more likely.A clear example of the differences between the classical perspective ofrational choice theory and quantum theory is the famous Linda problemfirst described in Kahneman et al. (1982). In this experiment, Linda is de-scribed as having been a philosophy student who was “deeply concernedwith issues of discrimination and social justice” and had “participated inanti-nuclear demonstrations.” Participants were then asked if she was morelikely to either be a bank teller or be a bank teller who is active in the fem-inist movement. If people use classical probability to reason, participantsshould say Linda is more likely to be just a bank teller. In classical prob-ability theory, the probability of two things occurring (being a bank tellerand an activist) will always be less than the probability of either occurringindividually (only being a bank teller or only being an activist). However,Kahneman et al. (1982) found that people primarily said Linda was morelikely to be both a bank teller and active in the feminist movement insteadof saying she was solely a bank teller. To explain this discrepancy, Buse-meyer et al. (2011) applied a quantum probability framework, which took61.3. QUANTUM COGNITIONinto account that Linda’s description was more similar to being both activein the feminist movement and a bank teller than just being a bank teller.The tools that come from quantum probability allowed for a more accuratedescription of how people use information to answer questions.Much of the experimental and theoretical support for quantum cognitionhas come from applying quantum models to situations where classical mod-els and rational choice are inaccurate. Li et al. (2020) compared quantumand classical models’ ability to predict people’s decision-making. Aerts andGabora (2005) used quantum principles to explain conceptual combinationsand related fallacies. Generally, quantum cognition has been used to de-scribe and quantitatively predict numerous heuristics and fallacies (Jaeger& Trueblood, 2018; Pothos & Busemeyer, 2022). The findings around theimpact of question order described in Wang and Busemeyer (2013) are ofparticular interest for this research.The impact of the order of measurements on results is one of the early ef-fects described by quantum mechanics (Griffiths & Schroeter, 2018; Heisen-berg, 1983). Wang and Busemeyer (2013) used what they referred to as the“law of reciprocity” in quantum mechanics. This law states that the proba-bility of transitioning from state x to state y is the same as the probabilityof transitioning from state y to state x. In terms of dichotomous questions,this means that the likelihood of someone who said Y es to question A willthen say Y es to question B is equal to the probability that of someone whosaid Y es to question B will then say Y es to question A. In other words,the impact of answering one question on responses to the other is indepen-dent of the order in which the questions are asked. Wang and Busemeyer(2013) used this law to model pairs of questions and arrived at the followingequations,p(AyBy) + p(AnBn) = p(ByAy) + p(BnAn), (1.1)p(AyBn) + p(AnBy) = p(ByAn) + p(BnAy). (1.2)In these equations, p(x) gives the probability of x, A and B are questionsA and B, subscript y indicates responding yes to a question, and subscript nmeans responding no. The two equations form the quantum question orderequality (the QQ equality). In plain language, the first equation states thatwhen you have two sequential, dichotomous questions on a similar topic, theprobability of saying yes to both questions plus the probability of saying noto both questions is constant regardless of question order. Classical prob-ability does not produce an equivalent prediction as it does not model the71.3. QUANTUM COGNITIONimpact of answering a question on mental states. To test this relationship,Wang et al. (2014) analyzed over 70 surveys and research papers, findingthe predicted relationship in all applicable surveys. This is one of the moststrongly supported a priori predictions in quantum psychology and supportsthe theory’s underlying principles.According to Wang and Busemeyer (2013), this relationship assumesno information is presented between the first and second questions. If in-formation comes after the first question, people’s responses to the secondquestion will be altered by the new information, not just their response tothe first question. As such, adding information between the two questionsmeans that the QQ equality is no longer expected to occur. To test this,Wang et al. (2014) tested the QQ equality for surveys where informationwas presented between the questions and did not find the equality present,as predicted.Returning to the sexual assault literature, the QQ equality may be ableto shed light on the relationship between the perceived credibility of thesurvivor and the attacker. If the survivor and attacker’s credibility arerelated, quantum cognition predicts that answering a question about thecredibility of one will impact the credibility of the other, producing an ordereffect. This order effect should follow the QQ equality such that the portionof participants who judge both parties as credible plus the portion who judgeboth as not credible will be the same whether they are judging the survivoror the attacker first. In other words, the order effect will be constrained bythe QQ equality. While previous research has focused on the factors relatingto the survivor and attacker credibility separately, to our knowledge, this isthe first study to test if these judgements are connected and to use quantumcognition to make predictions about the nature of this relationship.If the QQ equality holds in this context, then quantum cognition couldbe used more broadly in legal theory and challenge rational choice and BLE.If quantum cognition applies to legal decision-making, it could change ourunderstanding of sequential line-ups, factfinder’s final judgements, and theuse of biases in legal knowledge as a whole (Jaeger & Trueblood, 2018). Ifthe QQ equality does not hold, that could suggest previously unpredictedconstraints on the QQ equality, which would challenge our current under-standing of quantum cognition.81.4. CURRENT STUDY1.4 Current StudyThis study will attempt to determine whether the relationship betweenthe credibility of the survivor and attacker follows the relationship predictedby the QQ equality. As such, there are three main hypotheses:H1: Successive judgements of the survivor’s and attacker’s credibilitywill produce an order effect.H2: This order effect will follow the QQ equality.H3: The QQ equality will not hold when new information is presentedbetween questions.H1 is a prerequisite for meaningful results because the QQ equality istrivially true if there is no significant order effect. At a high level, if there isno order effect, then the order the questions are in does not matter. Thus,the probability of a given response pattern will not be impacted by the orderof questions, and the QQ equality will always be true. As such, support forH1 is necessary to meaningfully test for the QQ equality. Support for H2would suggest that credibility assessments follow a similar pattern as theQQ equality. Support for H3 would indicate that the pattern in H2 requiresthe same conditions as the QQ equality. Support for all three hypotheseswould suggest that these credibility judgements follow the QQ equality.The tests for the QQ equality used for H2 and H3 was the χ2 test usedin Wang et al. (2014) and described in that paper’s supplemental material.This χ2 test is specifically designed to test if the QQ equality is not presentin the data, meaning that a significant χ2 value indicates that the data doesnot follow the QQ equality. A common practice in quantum cognition wherethe lack of significance when testing if a model does not apply to data isinterpreted to mean that data follows the model. In the case of Wang et al.(2014), they interpreted a χ2 with p > 0.05 to mean that the QQ equalitydid not apply to the data. However, this can not be concluded from a p-valuesignificance test and requires the calculation of a Bayes factor instead.The p-value is defined to be the probability of an experiment producinga test statistic value equal to or greater than the observed value, assumingthe null hypothesis is true (mathematically, the p-value represents p(D|H0)where D represents the observed data and H0 is the null hypothesis). Thiscan not be turned into a statement about the probability of the null hy-pothesis because it assumes that the null hypothesis is true (Connor2017;Pollard1987). A non-significant χ2 value in the χ2 test for the absence ofthe QQ equality is not equivalent to a significant value in a hypotheticaltest for the presence of the QQ equality. To test for the presence of the QQequality using the χ2 from Wang et al. (2014), a Bayes factor needs to be91.4. CURRENT STUDYcalculated. The Bayes factor originates in Bayesian statistics and allows forthe comparison of two hypotheses. It is interpreted as the odds ratio of thelikelihood of finding a result given one hypothesis versus the likelihood offinding the same result given a different hypothesis (Connor2017). In thecase of this study, the likelihood under the null hypothesis is over the like-lihood under the alternative hypothesis. Since the Bayes factor compareshow likely a result is under two different assumed hypotheses, it allows usto perform null hypothesis testing.In this study, most p-values are accompanied by the Bayes factor forthat test statistic presented as BF01 = x. The subscript of the variable tellsyou how to interpret the Bayes factor where BF01 is the null hypothesis forthe statistic over the alternative hypothesis, while BF10 is the alternativehypothesis over the null. Each Bayes factor is calculated such that a largervalue indicates more substantial support for the experimental hypothesis.If it is a test for the QQ equality, for instance, then a larger Bayes factormeans more robust support for the presence of the QQ equality in the data.Finally, a loose rule of thumb for interpreting a Bayes factor is that 1 <BF10 ≤ 3 is weak support for the hypothesis, 3 < BF10 < 10 is moderatesupport for the hypothesis, 10 ≤ BF10 is strong support the hypothesis,and 0 < BF10 < 1 is evidence against the hypothesis with small valuessuggesting strong evidence(Van2021).10Chapter 2Methods2.1 ParticipantsWe recruited 1493 participants aged 14 to 79 (mean = 40.4) from theUnited States using the online platform Prolific in exchange for monetarycompensation. There were moderately more men (n = 792) than women(n = 621). The sample was predominately cisgender (n = 1378), witha minority of people identifying as trans or nonbinary (n = 81). Mostparticipants were White (n = 1101), with people identifying as the followingin descending order: Black/African American (n = 175), Hispanic (n =144), Asian (n = 139), Native American/Alaskan Native (n = 18), NativeHawaiian/Pacific Islander (n = 12).This sample size was estimated beforehand using previous studies. Thestudies used in Wang et al. (2014) were primarily studies with an averageof ≈1,000 participants with an average of ≈ 500 participants in each condi-tion. Since this study used three conditions, we needed approximately 1500participants to have an equivalent number of participants in each condition.Since the analysis consists primarily of the novel statistical test developedin Wang et al. (2014), a full power analysis to determine the sample sizewas not in the scope of this study. However, as the novel test achieves thesame effect as a χ2 test of independence, a power analysis of that statisticcan also provide an estimate for the sample size.Similar to Wang et al. (2014), support for H1 requires a significant ordereffect with DF = 3 and support for H2 requires a non-significant resultfor the QQ equality with DF = 1. The reduction in degrees of freedombetween testing for an order effect and testing for the QQ equality is becauseEquation 1.1 and 1.2 each function as separate constraints on the data,reducing the degrees of freedom. A significant test result for H2 suggeststhat the two sides of the equality are significantly different, supporting theidea that the QQ equality was not present. We tested if the QQ equalitydid not apply to the data by testing for a small difference in the two sidesof the equation, which required powering the study for a small effect sizefor the QQ equality. However, since the test of the order effect has more112.1. PARTICIPANTSdegrees of freedom, a study that can find a small order effect can also finda small difference in the QQ equality. According to G∗Power v3.1, to findan order effect of effect size w = 0.1 with a power of 0.8, the study neededa sample of 1091 participants, or approximately 500 participants in eachcondition (Faul et al., 2007). This generally aligns with the studies used inWang et al. (2014) and confirms that we needed around 1500 participantsin this study.2.1.1 Design & MaterialsWe used a between-subject design with two phases. The first phase hadtwo conditions that changed the credibility assessment order. The secondphase consisted of one condition where new information was presented be-tween the questions. Credibility was evaluated as a dichotomous measurewith two levels: the person is either credible or not.Participants were presented with three vignettes describing three differ-ent assaults. Each vignette consisted of a written statement from a survivorand a written statement from the attacker. The first vignette was adaptedfrom Messman-Moore and Brown (2006) where the survivor was namedMary and the attacker was named Bill. The second and third vignetteswere written for this study, with Dakota and Bill being the survivors andAlex and Alice being the attackers, respectively. To ensure each vignettewas different, we varied four factors present in the Mary-Bill vignette, whichare known to impact bias in sexual assault cases. To ensure each vignettehad similar levels of ambiguity and bias, when one factor was changed to in-crease participant bias, others were changed to decrease bias. The strengthof each factor’s relationship to participant bias was approximated from theresults of the studies and the number of studies that did not find an effectfrom the variable. The four variables were implied gender identity (Davieset al., 2009; George & Mart´ınez, 2002; Pica et al., 2020, 2021; Sommer etal., 2016), prior relationship (D. J. Angelone et al., 2012; Bouffard, 2000;Campbell et al., 2009; Morabito et al., 2019; O’Neal, 2019; Sommer et al.,2016), intoxication (Schuller & Stewart, 2000; Wall & Schuller, 2000), andwhether or not the survivor attempted to resist the attacker (D. Angeloneet al., 2018; Davies et al., 2009; George & Mart´ınez, 2002; Rogers et al.,2014). The text of all three vignettes and the corresponding questions canbe found in Appendix A.The initial vignette from Messman-Moore and Brown (2006) can be de-scribed as follows: the survivor (Mary) was implied to be a woman, andthe attacker (Bill) was implied to be a man, they had just met, Mary was122.1. PARTICIPANTSintoxicated, Bill was sober, and Mary did not describe resisting. In thiscase, previous research suggests that the fact that Mary was a woman likelybiased participants in her favour (Sommer et al., 2016) while the fact thatshe did not resist biased participants against her (Davies et al., 2009; Rogerset al., 2014; Schuller & Stewart, 2000). Previous research suggests that thefact that Bill was male likely produced some participant bias for him (Picaet al., 2020; Sommer et al., 2016). The fact that Mary was sober but Bill wasintoxicated likely produced some bias against Bill (Wall & Schuller, 2000).The second vignette featured a survivor named Dakota and an attackernamed Alex. It was described as a third date where neither was significantlyintoxicated. Neither had an implied gender, and the survivor describedattempting to resist the attack. Previous research suggests that the lengthof the relationship, the resistance, and the lack of alcohol would produce aneffect in the survivor’s favour (Bouffard, 2000; Campbell et al., 2009; Davieset al., 2009; Morabito et al., 2019; Rogers et al., 2014; Wall & Schuller,2000).The third vignette described a male survivor (Frank) and a female at-tacker (Alice). They were described as previously being friends, with bothbeing moderately drunk and Frank attempting to resist Alice verbally. Theliterature generally describes male survivors as having low credibility (Davieset al., 2009; Sommer et al., 2016) and female attackers being perceived asmore credible than male attackers (Sommer et al., 2016). Finally, the litera-ture suggests that both parties being moderately intoxicated likely producedsome bias towards the survivor (Wall & Schuller, 2000).Finally, a personality assessment based on the five-factor model of per-sonality was used as a distractor task between vignettes. Specifically, weused a shortened version of the International Personality Item Pool—Five-Factor Model measure (mini-IPIP) (Donnellan et al., 2006) because it pro-vided a substantial number of questions on unrelated topics to distract par-ticipants.2.1.2 ProcedureIn phase one, participants were directed to a Qualtrics survey, where theyprovided fully informed consent before receiving instructions for the task(See Appendix B for all instructions provided to participants). Next, theywere randomly assigned to one of two order conditions and moved into thefirst credibility assessment procedure. Both conditions started by readingboth statements in the Mary-Bill vignette. After reading both statements,participants in the first condition (n = 500) were shown a new screen asking132.1. PARTICIPANTSabout Mary’s credibility. Upon answering, they were shown a new screenthat asked about Bill’s credibility. Participants in the second condition (n =496) were presented with the same vignettes in the same order. However,Condition 2 answered the questions in reverse order, judging Bill’s credibilitybefore Mary’s. After judging Mary and Bill, both conditions were presentedwith the first ten questions of the mini-IPIP as a distractor task.Participants then repeated this credibility assessment procedure for theDakota-Alex vignette; however, participants in Condition 1 rated the at-tacker’s (Alex’s) credibility before the survivor’s (Dakota’s) credibility, withCondition 2 making their ratings in the opposite order, starting with Dakota.After both ratings, participants were presented with another distractor taskconsisting of the last ten questions of the mini-IPIP before moving on to thefinal credibility assessment procedure on the Frank-Alice vignette. In thisfinal procedure, participants in Condition 1 were asked about the credibil-ity of the survivor (Frank) before the credibility of the attacker (Alice). Incontrast, participants in Condition 2 started with Alice’s credibility beforemoving on to Frank’s.Finally, participants provided demographic information, were debriefed,and thanked for their time. The entire procedure for this study is depictedin Table 2.1. The counterbalancing of question orders between vignettes andthe distractor tasks was to reduce carryover effects from previous vignettesand judgements.Phase 2 tested if breaking the assumptions of the QQ equality impactedparticipants’ response patterns. This phase involved Condition 3 (n = 497),which followed the same structure as Condition 1. However, instead ofreading both vignettes and then making credibility judgements, partici-pants made credibility judgements directly after reading the correspondingvignettes. For instance, participants read Mary’s vignette, gave their credi-bility assessment of Mary, and then read Bill’s statement and assessed him.Refer to Table 2.1 to see the entire procedure for this condition.142.2. ANALYSISTable 2.1: A table view of the different conditions in this study. “Sur-vivor/Attacker Statement” here refers to the variation of the Mary and Billstatements used in that part of the study. “Survivor/Attacker Credibility”means that participants will assess that party’s credibility.Condition 1 Condition 2 Condition 3Survivor Statement 1 Survivor Statement 1 Survivor Statement 1Attacker Statement 1 Attacker Statement 1 Survivor 1 CredibilitySurvivor 1 Credibility Attacker 1 Credibility Attacker Statement 1Attacker 1 Credibility Survivor 1 Credibility Attacker 1 Credibilitymini-IPIP 1-10 mini-IPIP 1-10 mini-IPIP 1-10Survivor Statement 2 Survivor Statement 2 Attacker Statement 2Attacker Statement 2 Attacker Statement 2 Attacker 2 CredibilityAttacker 2 Credibility Survivor 2 Credibility Survivor Statement 2Survivor 2 Credibility Attacker 2 Credibility Survivor 2 Credibilitymini-IPIP 11-20 mini-IPIP 11-20 mini-IPIP 11-20Survivor Statement 3 Survivor Statement 3 Survivor Statement 3Attacker Statement 3 Attacker Statement 3 Survivor 3 CredibilitySurvivor 3 Credibility Attacker 3 Credibility Attacker Statement 3Attacker 3 Credibility Survivor 3 Credibility Attacker 3 Credibility2.2 AnalysisTo test for an order effect (H1), we used the χ2 independence test fromWang and Busemeyer (2013) on contingency Table 2.2. This test was appliedto the answers for each pair of credibility assessments. To determine if H1is meaningfully supported, we calculated both a p-value and a Bayes factorfor our χ2 value. To calculate the Bayes factor, we applied the piecewiseapproximation of the Bayes factor described by Wagenmakers (2022).152.2. ANALYSISTable 2.2: Contingency table for the analysis of order effect. a representsthe number of people that gave the response pattern for a given vignette inthe first condition. b represents the number of people that gave the responsepattern for a given vignette in the second condition. The subscripts givethe response pattern with the response about the survivor first and theresponses about the attacker second. For instance, “YN ” is “Yes-No” andcorresponds to thinking the survivor is credible and the attacker isn’t. Eachcolumn has a response pattern, while each row has a different question order.Credibility Order Yes - Yes Yes - No No - Yes No - NoSurvivor - Attacker ayy ayn any annAttacker - Survivor byy byn bny bnnThe test for the QQ equality (H2) used Table 2.3 with the data fromConditions 1 and 2. The “Major” column refers to the “major diagonal” orthe proportion of people who said yes to both questions plus the proportionof people who said no to both questions (see equation 1.1). “Minor” refersto the “minor diagonal” or the proportion of people who said yes to the firstquestion and no to the second plus the proportion of people who said no tothe first question and then yes to the second (see equation 1.2). The QQequality predicts that the major and minor sum will stay constant regardlessof order (Wang et al., 2014), which aligns with the null hypothesis of theindependence test. Because we tested for the null hypotheses, we calculatedthe Bayes factor and conducted a p-value significance test. Support for theQQ equality occurs when the Bayes factor supports the null hypothesis andthere is a non-significant p-value. This analysis was performed for eachvignette.162.2. ANALYSISTable 2.3: Contigency table for the analysis of the QQ equality. a representsthe proportion of people that gave a specific response pattern in the firstquestion order. b represents the proportion of people that gave a specificresponse pattern in the second question order. The subscripts represent thesame response patterns in Table 2.2. “Major” refers to the total proportionof people who gave the same response to the first and second questionsin that order (responded either yes-yes or no-no). “Minor” refers to thetotal proportion of people who responded differently to the first and secondquestions (either yes-no or no-yes).Credibility judgement Order Major MinorSurvivor - Attacker ayy + ann ayn + anyAttacker - Survivor byy + bnn byn + bnyFinally, to determine if new information breaks the QQ equality and testH3, we performed the same χ2 but on Conditions 1 and 3 as depicted in Table2.4. Since Condition 3 breaks the assumption that the questions directlyfollow each other, we would not expect the QQ equality to hold. Thus, H3is supported if the Bayes factor supports the alternate hypothesis and thereis a significant p-value. This analysis was also performed independently foreach vignette.Table 2.4: Contigency table for the analysis of the effect of informationon the QQ equality. In this table, the variable c represents the number ofpeople who responded with that response pattern for a given vignette inthe third condition. “Mary - Bill” means that people determined Mary andBill’s. “Mary - Statement - Bill” means that Bill’s statement was placedbetween credibility judgments. All other notations follow the conventionsestablished previously.Statement Placement Major MinorStatements - Survivor - Attacker ayy + ann ayn + anyStatement - Survivor - Statement - Attacker cyy + cnn cyn + cny17Chapter 3ResultsAcross all vignettes, 75.5% of people thought the survivor was credible,and 56.4% thought the attacker was credible. When judging Mary andBill in the first vignette, 74.5% of participants overall said that Mary (thesurvivor) was credible, and 60.7% thought Bill (the attacker) was credible.In the second vignette about Dakota and Alex, 81.6% said Dakota (thesurvivor) was credible, and 55.0% said Alex (the attacker) was. In the finalvignette on Frank and Alice, 70.2% said Frank (the survivor) was credible,and 53.5% said Alice (the attacker) was.When participants judged the credibility of the survivor first after read-ing both statements (Condition 1), 76.0% of participants thought at leastone survivor was credible, and 50.0% thought at least one attacker wascredible. When the judgment order flipped (Condition 2), the percentagesbecame 76.5% and 51.0%, respectively. Across all judgements that weremade immediately following their corresponding statement (Condition 3),73.9% thought the survivor was credible, and 68.3% thought the attackerwas. The breakdown of response frequencies by condition and vignette canbe found in Tables 3.1 and 3.2.3.1 Question OrderUsing the data in Table 3.1, the test described in Wang and Busemeyer(2013) was used to test if an order effect was present in successive credibilityjudgements as predicted by H1. In all three vignettes, there was substantialevidence that changing the question order from baseline did not impactcredibility judgements, χ2 = 2.44 (p = 0.49, BF10 = 0.0384) for the Mary-Bill vignette, χ2 = 2.26 (p = 0.54, BF10 = 0.037) for the Dakota-Alexvignette, and χ2 = 1.24 (p = 0.74, BF10 = 0.0341) for the Frank-Alicevignette. As such, we did not find support for H1.To test H2 and determine if the data followed the QQ equality, the χ2test was performed on the same data but structured according to Table 2.3.The test found that the major and minor sums did not vary with questionorder in any vignette, χ2 = 0.67 (p = 0.41, BF01 = 23.33) for the Mary-Bill183.2. STATEMENT PLACEMENTTable 3.1: Response pattern frequencies for each vignette in Conditions 1and 2. In the header, the first response is whether the participants thoughtthe survivor was credible, and the second is whether they thought theattacker was credible (“Yes-No” corresponds to thinking the survivor iscredible and the attacker isn’t.Condtion Yes-Yes Yes-No No-Yes No-NoVignette 1Condition 1 167 185 136 12Condition 2 176 114 192 14Vignette 2Condition 1 152 264 70 14Condition 2 136 276 64 19Vignette 3Condition 1 130 241 113 15Condition 2 131 227 118 20vignette, χ2 = 0.40 (p = 0.52, BF01 = 26.84) for the Dakota-Alex vignette,and χ2 = 0.23 (p = 0.63, BF01 = 28.13) for the Frank-Alice vignette.These results can equally be explained by the lack of an order effect and thepresence of the QQ equality, and thus, they do not provide evidence for oragainst H2.3.2 Statement PlacementUsing the data in Table 3.2, the χ2 test found that participants’ re-sponses were significantly different when judgements were made immediatelyafter their corresponding statement (Condition 3) instead of responding af-ter reading both statements (Condition 1). Specifically, more participantssaid both parties were credible when judging Mary and Bill and when judg-ing Dakota and Alex, compared to the initial condition, which had thesame question order but presented both statements first, with χ2 = 13.58(p < 0.01, BF10 = 2.98) and χ2 = 154.4 (p < 0.001, BF10 > 100) re-193.2. STATEMENT PLACEMENTTable 3.2: Response pattern frequencies for each vignette in Conditions 1and 3. In the header, the first response is whether the participants thoughtthe survivor was credible, and the second is whether they thought theattacker was credible (“Yes-No” corresponds to thinking the survivor iscredible and the attacker isn’t.)Condtion Yes-Yes Yes-No No-Yes No-NoVignette 1Condition 1 167 185 136 12Condition 3 215 177 97 8Vignette 2Condition 1 152 264 70 14Condition 3 304 83 94 13Vignette 3Condition 1 130 241 113 15Condition 3 157 161 148 29spectively. For Frank and Alice, more participants said that only Frank’sstatement was credible in the initial condition when they had read bothstatements before making a judgement as opposed to having questions in-terspersed between statements with χ2 = 27.80 (p < 0.001, BF10 > 100).The χ2 test was then used on Table 2.4 to test if placing a vignette inbetween the questions resulted in data which did not follow the QQ equality,in accordance with H3. This test found strong evidence that the majorand minor sums changed if a statement was placed inbetween questionsas opposed to presenting both statements before the questions, χ2 = 8.53(p < 0.01, BF01 = 0.03) for the Mary-Bill vignette, χ2 = 97.00 (p < 0.001,BF01 < 0.003) for the Dakota-Alex vignette, and χ2 = 8.13 (p < 0.01,BF01 = 0.04) for the Frank-Alice vignette. These results suggest that theQQ equality did not apply to our data when new information was presentedbetween questions, supporting H3.203.3. SUBSAMPLING3.3 SubsamplingSince question order did not impact participants’ responses, a supple-mental analysis based on Wang et al. (2014) was performed to test for thepresence of the QQ equality in the data (H2). By comparing multiple stud-ies, Wang et al. (2014) showed that the QQ equality impacts the change inresponse pattern frequencies that result from different question orders (re-ferred to as a context effect). Specifically, they found that the context effectfor responding “Yes” to both questions (Yes-Yes context effects) had a verylarge, negative correlation with the context effect for responding “No” toboth questions (No-No context effects) when the QQ equality was presentin the data. The same was found for the correlation between the contexteffect for responding “Yes” and then “No” (Yes-No context effects) and thecontext effect for responding “No” and then “Yes” (No-Yes context effects).Wang et al. (2014) also found that the above correlations were centred at ornear zero. If the QQ equality is present in this study, then similar resultsshould be found for the impact of question order on response frequenciesbut not for the effect of the arrangement of statements and questions.To determine if similar correlations appear in the present study, 100samples of 200 participants were created for each experimental conditionusing random sampling. The relationships between context effects resultingfrom question order and the arrangement of questions and statements areshown in Figures 3.1 and 3.2, respectively, with the correlations and meansdisplayed in Table 3.3.For subsamples of the first two conditions, there were no significantcorrelations between Yes-Yes and No-No context effects (major context ef-fects) produced by changing the question order, r(98) = 0.062 (p = 0.5398,BF10 = 0.117) for subsamples from the Mary-Bill vignette, r(98) = −0.003(p = 0.9789, BF10 = 0.1) for subsamples of the Dakota-Alex vignette, andr(98) = −0.237 (p = 0.01778, BF10 = 1.87) for subsamples of the Frank-Alice vignette. The small correlations between Yes-Yes and No-No contexteffects (major context effects) are likely due to the low frequency of No-No responses in the original data, as this resulted in limited variance in theNo-No context effects and thus small correlations. However, there were mod-erate to large correlations between the Yes-No and No-Yes context effects(minor context effects), r(98) = −0.432 (p < 0.01, BF10 > 100) for subsam-ples from the Mary-Bill vignette, r(98) = −0.362 (p < 0.01, BF10 > 100)for subsamples of the Dakota-Alex vignette, and r(98) = −0.565 (p < 0.01,BF10 > 100) for subsamples of the Frank-Alice vignette. While these resultsare not as large as the QQ equality predicts, they do suggest a significant,213.3. SUBSAMPLINGFigure 3.1: Scatter plots of context effects for the subsampled data of Con-ditions 1 and 2. The top row shows the relationship between the Yes-Yesresponse context effects and the No-No context effects. The bottom rowshows the relationship between the Yes-No context effects and the No-Yescontext effects.negative relationship between context effects produced by changing the ques-tion order.To determine if the subsamples are centred near zero, we calculated themean context effect for all major and minor pairs to approximate the centerpoint for the correlated data (see Table 3.3 for each pair of means). If thedata was centred at the origin, then the origin is expected to be closer to theapproximate center than 95% of subsamples. Quantitatively, this means thedistance between the origin and the pair of mean subsample context effectsshould be less than the distance between the paired mean context effects and95% of the subsample context effects. Since only the minor context effectshad significant correlations, the test was only performed on those data. Forthe Mary-Bill vignette, the distance between the center and the origin wasDm = 9.426 and was closer than 64% of subsamples, which had an averagedistance of Md = 12.413 (SDd = 7.057). For the Dakota-Alex vignette,the distance from the origin was Dm = 7.754, which was closer than 63% of223.3. SUBSAMPLINGFigure 3.2: Scatter plots of context effects for the subsampled data of Con-ditions 1 and 3. The top row shows the relationship between the Yes-Yesresponse context effects and the No-No context effects. The bottom rowshows the relationship between the Yes-No context effects and the No-Yescontext effects.samples at an average distance ofMd = 10.83616 (SDd = 10.83616). Finally,for the Frank-Alice vignette, the distance from the origin was Dm = 6.935,closer than 76% of samples whose average distance from the center wasMd = 11.348 (SDd = 6.102). These results suggest that the correlationswere not significantly centred at zero; however, they also suggest that theyare not significantly different than zero. Instead, it indicates that the centersof the correlations were within range of the origin, providing partial supportfor H2, that QQ equality applies to the first and second conditions.The context effects produced by interspersing the statements with credi-bility judgements (Condition 3) compared to making both judgements afterreading all statements (Condition 1) have a similar pattern of correlationsto the previous set of context effects. Similar to the context effects fromchanging the order of questions, the correlations between major contextseffects were either small or non-significant, r(98) = 0.062 (p = 0.5324,BF10 = 0.117) for subsamples from the Mary-Bill vignette, r(98) = −0.0328233.3. SUBSAMPLINGTable 3.3: Correlations and means from subsamples of the data. Resultssignificant for p ≤ 0.01 are bolded, and all correlations have a df = 98.The meaning of “Major,” “Minor,” and the subscripts for the means retainpreviously established meanings.Vignette Major MinorQuestion OrderMary-Bill 0.062 (Myy = 20.34, Mnn = −1.53) -0.432 (Myn = −4.07, Mny = −14.74)Dakota-Alex -0.003 (Myy = 62.24, Mnn = −0.42) -0.362 (Myn = 9.96, Mny = −71.78)Frank-Alice -0.237 (Myy = 11.42, Mnn = 6.22) -0.565 (Myn = −32.63, Mny = 14.99)Statement PlacementMary-Bill -0.0632 (Myy = 16.24, Mnn = −2.27) -0.484 (Myn = −6.11, Mny = −7.86)Dakota-Alex -0.0328 (Myy = 69.08, Mnn = −2.09) -0.359 (Myn = −79.20, Mny = 12.21)Frank-Alice -0.259 (Myy = 11.22, Mnn = 3.62) -0.540 (Myn = 11.69, Mny = −26.53)(p = 0.746, BF10 = 0.108) for subsamples of the Dakota-Alex vignette, andr(98) = −0.259 (p < 0.01, BF10 = 3.66) for subsamples of the Frank-Alice vignette. Following the results from the previous set of context ef-fects, the correlations between minor context effects were moderate to large,r(98) = −0.484 (p < 0.01, BF10 > 100) for subsamples from the Mary-Bill vignette, r(98) = −0.359 (p < 0.01, BF10 > 100) for subsamples ofthe Dakota-Alex vignette, and r(98) = −0.540 (p < 0.01, BF10 > 100) forsubsamples of the Frank-Alice vignette.Comparing these data to the origin, we find that the distance fromthe center for the Mary-Bill vignette is Dm = 15.29158 which is closerthan 23% of subsamples which had an average distance of Md = 11.28911(SDd = 6.430167). For the Dakota-Alex vignette, the distance between thecenter and origin was Dm = 72.46772, which is larger than any other sub-sample with a mean distance of Md = 10.30154 (SDd = 5.414926). Finally,for the Frank-Alice vignette, distance from the origin was Dm = 35.90845,which was farther than any other subsample considering the mean distancewas Md = 9.927761 (SDd = 6.448127). These results suggest that the originis farther from the center than a majority of subsamples and significantlydifferent for all but the Mary-Bill vignette. This thus provides further sup-port for the QQ equality not applying to the first and third vignettes, whichis in line with H3.24Chapter 4DiscussionThis study tested if a prediction from quantum cognition, the QQ equal-ity, applies to credibility judgements of attackers and survivors in threecases of sexual assault. Contrary to previous studies and H1, question orderdid not impact participant’s credibility judgements. Although this makestesting the QQ equality challenging, a novel subsampling procedure wasused to show that the correlations between question orders were consistentwith the QQ equality (H2). Additionally, altering the relative placementof statements and questions affected response patterns without producingthe QQ equality, as predicted by H3. This sub-sampling procedure also il-lustrated that the subsample correlations between different arrangements ofstatements and questions were inconsistent with the QQ equality, providingmore support for H3.Our finding that 75.5% of participants found the survivor credible seemsto contradict previous findings that show survivors not typically believed.However, across all vignettes, an average of approximately 40% of respon-dents thought the survivor’s narrative was the sole credible account. This ismore in line with the results of Rotenberg (2017) where approximately 50%of cases were consistently dropped at each step of the legal process. Ourfindings suggest that cases were not necessarily settled because the survivorlacked credibility, but that the combination of the survivor’s and alleged at-tacker’s statements produced reasonable doubt if a mistake of fact occurred.This idea would follow from the reasoning presented in Rotenberg (2017).While changing the order of questions had little impact, responses afterreading both perspectives differed from responses produced when readingonly one perspective at a time. According to Table 3.2, most participantswho read both statements before making any credibility judgments reportedthat the survivor was credible and the attacker was not. However, partici-pants who evaluated the survivor based only on their statement and subse-quently read about and judged the attacker tended to assess both parties ascredible. While the mechanism behind this change is beyond the scope ofthis study, it may be that breaking up the statements and questions worksto decouple the people’s credibility judgements, in line with the predictions254.1. QUANTUM COGNITIONfrom quantum cognition (Wang & Busemeyer, 2013). Specifically, quantumcognition predicts that putting information between questions means that aperson’s mental state for the second question is based on the new informa-tion presented, not the previous question. As such, judgements about theattacker would primarily be based on the attacker’s statement and conclu-sions about the survivor could only be influenced by the survivor’s state-ment. On a practical level, this implies that the survivor’s experience wouldnot contextualize the attacker’s statement, thus potentially resulting in moreperceived uncertainty about who to believe.4.1 Quantum CognitionOutside of their application, these findings also have significant implica-tions for the field of quantum cognition. In opposition to previous results,this study did not find an effect of order on response rates. Prior researchsuggests that questions that draw on the same pool of information producean order effect that follows the QQ equality (Pothos & Busemeyer, 2022;Wang & Busemeyer, 2013; Wang et al., 2014). If there is no order effect,then quantum cognition predicts that the questions are unrelated. However,the primary source of information for both credibility judgements was apair of statements concerning the same incident, which contained a notableamount of redundant information. If the judgements were unrelated, wewould not expect correlations between subsamples to follow the QQ equal-ity. To explain these results, we suggest that the size of the order effect wasdiminished because the feature spaces for each credibility judgement hadshared and unique components.In quantum cognition, all the information and environmental featuresused in a decision form a feature space (an interpretation of a Hilbert space),which forms the basis for all descriptions of the decision moving forward(Busemeyer et al., 2011; Wang & Busemeyer, 2013). The outcomes of thedecision are seen as different mutually exclusive combinations of some subsetof features described mathematically as orthogonal subspaces (Bruza et al.,2015; Busemeyer et al., 2011; Pothos & Busemeyer, 2022; Wang & Buse-meyer, 2013). After making the decision, a person’s mental state moves tothe subspace corresponding to that outcome. In this study, Mary’s credibil-ity is defined as a feature space based on information from both her and Bill’sstatements. Within this feature space, there are two subspaces: one corre-sponding to deciding Mary’s statement was credible and one correspondingto deciding her statement was not credible. The features that compose these264.1. QUANTUM COGNITIONsubspaces correspond to the information that supports the conclusion, suchas the parts of Mary’s statement that make her appear truthful or the partsof Bill’s statement that make the participant suspicious of his narrative.When coming to a conclusion, the participant’s mental state changes froman arbitrary combination of features to a combination of features which fallwithin the subspace for their conclusion.When two questions share a feature space, the change in mental stateresulting from answering a question produces an order effect. When partici-pants decide that Bill is credible after their decision about Mary, their men-tal states move from the subspace corresponding to thinking that Mary iscredible to the subspace for thinking that Bill is credible with a specific prob-ability. However, if participants say Bill is credible before being asked aboutMary, they will instead move from a random mental state to the correspond-ing subspace with a different probability, producing an order effect. Sincethis study did not find an order effect, quantum cognition would typicallydescribe these questions as existing in different feature spaces. However,subsamples of this study’s data showed some evidence of the QQ equalityand the response rates changed if participants read both statements firstinstead of in sequence, suggesting that information from both vignettes isused in the question feature spaces. These results cannot thus be wholly de-scribed as the credibility judgments having entirely separate feature spacesnor as fully sharing feature spaces.Conceptually, two main experimental factors differentiate this studyfrom previous ones similar to Wang et al. (2014): the relationships beingevaluated and the amount of information available. With respect to the firstfactor, a survivor’s credibility is likely influenced by some features that donot impact the attacker’s credibility, while the question pairs in Wang et al.(2014) are likely influenced by most of the same features. The pairs of ques-tions analyzed in Wang et al. (2014) often focused on either two connectedgroups (i.e. president/vice president, democrats/republicans, etc.), a pairof related beliefs (i.e. affirmative action for minorities/women, abortion indifferent contexts, etc.), or a pair of inverse opinions (i.e. was political can-didate A unfair towards candidate B versus was B unfair to A). In each case,the two questions are likely to be evaluated on similar features using simi-lar criteria and biases, making them good candidates for sharing a featurespace. Alternatively, survivors and attackers are conflicting parties evalu-ated on different grounds using different biases while still influencing eachother (Clarke & Stermac, 2011; Maeder et al., 2015; Pica et al., 2020, 2021;Vandervort, 2005; Wall & Schuller, 2000). For example, survivors are seenas more credible in cases of interracial sexual assault, while alleged attackers274.1. QUANTUM COGNITIONare seen as less credible (George & Mart´ınez, 2002). This suggests that thefeature spaces for Mary and Bill’s credibility will likely be far more distinctthan those analyzed in previous research while still sharing some features.As for the second factor, participants’ responses in this study likely hadfar less to draw on than those analyzed in Wang et al. (2014). The questionsin Wang et al. (2014) focused on prominent political figures and the mainpolitical issues of the time. This means that the answers would likely bebased on a large well of knowledge, opinion, and personal experience uponwhich to build an ample feature space to answer the question. Conversely,this study asked participants about specific examples of sexual assault andprovided vignettes with a limited set of features. While participants mayhave drawn from their pre-existing notions of sexual assault, there were qual-itative differences in each vignette’s response pattern, suggesting that thefeature spaces contained at least some of the information from the vignettes.This would indicate that participants had a smaller feature space to use indecision-making, potentially impacting their responses.Traditionally, quantum cognition has assumed that decisions influenceeach other when they exist wholly in the same feature spaces. QuestionA only impacts Question B when the answers are based on different ar-rangements of the same information. This is based on quantum mechanicsin which Hilbert spaces describe components of our physical space, mak-ing this assumption trivial. However, this assumption becomes non-trivialin psychology because information is more fluid than physical dimensionsand thus can be arranged in different manners. For example, when buyinga smartphone and a desktop computer, a person may consider the storagesize and processing speed for both items but will not likely think about thecomputer’s battery life since that is not applicable to desktop computers.These judgements are not independent of each other, and it would not makesense to describe them using wholly unique feature spaces because there aremany related features. However, you could not describe them as sharing afeature space either, since there are features that apply to the phone thatare not related to the desktop computer. As such, the simplest solution isfor the two to share some components of the feature space but not others.While the credibility of survivors and attackers appear to be related(Clarke & Stermac, 2011; Lynch et al., 2020; Maeder et al., 2015; Pica et al.,2020; Vandervort, 2005; Wall & Schuller, 2000), these findings suggest thatjudgments may depend on both shared and unique features. This means theQQ equality would only apply to the components that use features sharedby both judgements. Judgements about Mary would change part of theparticipant’s understanding of Bill’s credibility, but not all of it. In general,284.2. LIMITATIONS AND FUTURE DIRECTIONSthe size of the order effect would now depend on the number of features usedin both judgements relative to the number used in a single decision. Thus,order effects are then more likely to be obscured in a small feature spacesince each feature represents a more significant percentage of the total, andfewer unique features are required to obscure the order effect.These unique factors mean that each judgement, and thus each responseoption, has a degree of unique variance, which would diminish the correla-tions between context effects, as seen in this study. On the level of responseoptions, this hypothesis allows the subspace for agreeing with the survivor,for instance, to be composed of a different number of unique factors thanthe subspace for agreeing with the attacker. This unequal variance wouldthen suggest different amounts of unique variance in the context effects forthe various pairs of responses, thus suggesting that the correlations woulddeviate from zero, as again seen in this study. In general, if this hypothesisis valid, it could indicate that feature spaces and quantum cognition mod-els can contain more nuance and produce more variable predictions thanpreviously thought.4.2 Limitations and Future DirectionsOne of the most significant problems in quantum cognition is predictingwhen one question will impact the next (Pothos & Busemeyer, 2022). Whilewe can make predictions assuming that two questions will interact, it isdifficult to know when those situations occur. This study suggests that itis not a question of whether two decisions interact but how much. If thepartial feature space hypothesis is true, then quantum interactions dependon the amount of information used in a decision and what proportion ofit is used in the next. This could be tested using a similar experimentaldesign to this study using a fully between-subject design where, instead ofhaving three different vignettes, participants are presented with the samevignette with differing amounts of information and overlap. Even if it is notsupported, the methodology of this study may offer insight into the spacesand subspaces involved in decision-making by using vignettes to control theamount of available information.Outside of quantum cognition, the small scope of this study limited ourconclusions about credibility judgements in sexual assault cases. Futurestudies can systematically vary the biases present in each vignette to testif the placement of information relative to the questions has a significantimpact. Because we presented participants with written statements isolated294.3. CONCLUSIONfrom their broader context and allowed only dichotomous judgements, par-ticipants had a limited data set to work with and could not provide a detailedresponse. Further studies can test if these results hold when participantshave more realistic information for their judgement (i.e. police statements,photographs or videos of both parties, witness statements, etc.) and whenparticipants are not limited to a dichotomous decision. Finally, while previ-ous research has shown that decision-making biases for sexual assault casesdo not vary with a person’s level of expertise, it is unclear whether these re-sults generalize to those communities because the study only sampled fromthe general population.4.3 ConclusionIn exploring credibility judgements around sexual assault, this studyfound initial support for applying the ideas of quantum cognition to thejudgements of the survivor and the alleged attacker. While participants’responses were not impacted by question order, there was evidence for theQQ equality in correlations between subsamples of the data. Additionally,there was an effect of statement order on participants’ responses, whichsuggested that hearing both perspectives of the assault before making ajudgement could reduce the use of biases. In general, this study functionsas a proof of concept of using the tools of quantum cognition to understandthe ways sexual assault survivors are perceived. Future research is requiredfor a more robust exploration of this approach and may provide new avenuesto test and grow both quantum cognition and credibility research.30BibliographyAerts, D., & Gabora, L. (2005). A theory of concepts and their combinationsi: The structure of the sets of contexts and properties. Kybernetes.Angelone, D. J., Mitchell, D., & Lucente, L. (2012). Predicting perceptions ofdate rape: An examination of perpetrator motivation, relationshiplength, and gender role beliefs. Journal of interpersonal violence,27 (13), 2582–2602.Angelone, D., Mitchell, D., & Smith, D. (2018). 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I told Bill I did not want to have sex but wasenjoying making out with him. Later I felt Bill’s penis penetrate my vagina.I told him to stop, but he did not. The next day I went to the hospital andreported the event.”Bill’s Account“I met Mary at a friend’s party on Friday night. This was the first timewe met, but we really hit it off and spent a lot of time flirting. I noticedthat Mary had been drinking so I thought it would be safe and courteousto offer her a ride home. She accepted. When we got to Mary’s apartmentbuilding, I walked her up to her apartment and kissed her goodnight. Maryinvited me in and I accepted. Then Mary put on a movie for us to watch.Instead of watching the movie we were making out. We were both reallyinto it and so we undressed each other and continued making out. Maryeven said aloud she was really enjoying hooking up. We ended up havingsex. She never said anything to suggest she didn’t enjoy it. I didn’t evensuspect anything was wrong until the next day when the police came to myapartment.”37BIBLIOGRAPHYDakota’s Account“Jordyn and I attended met up for a third date on Saturday night. Wehad met up for a coffee date and dinner over the past few weeks. Thistime we went bowling down the street from my house and we were hungryafterward, so we picked up a couple slices of pizza and I invited them up tomy apartment to eat since we were nearby. We were chatting on the couchwhen they kissed me. We were having a good time – I was ok with the kiss,but then Jordyn put their hand on my inner thigh. I pushed their handaway a couple times but they kept doing it. Then they put their hand downmy pants and started touching me. They were rough. I didn’t like it andI tried to push them off but they held me down. Eventually I gave up andjust hoped that it would be over quickly. I kinda pretended I was tired andwas falling asleep. After about 20 minutes Jordyn got a phone call fromtheir roommate and had to go because there was some sort of emergency.I was so grateful that the call distracted them. I told my roommate aboutit when she got home and she told me that I should report it to police, sothat’s when we came here to give my statement.”Jordyn’s Account”I met Dakota on a dating app about a month ago and we went outon a few dates and had a good time. On Saturday we decided to meet upat a bowling alley and we were having fun. We were both pretty terribleat bowling so it was funny. After a couple hours we were getting hungryso we grabbed a slice of pizza at Mario’s Pizzeria and took it to Dakota’sapartment to eat since it was just a block or two away. We were hanging outon the couch and started making out. Dakota seemed into it. They weredefinitely kissing me back. I thought we really liked each other. We werekinda getting into it. Like, we hadn’t taken any clothes off yet, but we wereboth feeling each other up if you know what I mean. I thought we mightgo further but then my phone rang and wouldn’t stop ringing. It turns outit was my roommate. He was calling to tell me that a pipe burst at myapartment and he really needed my help to try to clean up this huge mess.Anyway, I had to leave. I’m just totally shocked that I’m here because Ithought Dakota was really cool and into me so I really don’t know whathappened.”38BIBLIOGRAPHYFrank’s Account“Alice and I went to a comedy club – The Laugh Track – on Wednesdaynight with a bunch of our mutual friends. There were, like 8 of us there,but most people had upcoming exams and stuff so everyone went homeearly except for Alice and I who went to a dive bar next door. We werethere a long time and had both drunk quite a bit. We were feeling prettytipsy—laughing, having fun. Probably around midnight, I said that weshould leave. But I had to go to the bathroom first. I had drank a fewbeers, you know. I walked to the bathroom at the back of the bar andturned around to find that Alice had followed me in there. I asked her whatthe hell she was doing—I have a girlfriend and she knows that. I told her toget out of there and that I just liked her as a friend. I kept saying ‘no’ and‘this isn’t a good idea’. But, she didn’t leave. She kinda cornered me andstarted grabbing at my zipper. Next thing I knew she was going down onme. I didn’t want to push her off—I don’t hit girls, but I told her no andshe didn’t listen. I didn’t really know what else to do.”Alice’s Account”Frank and I and a bunch of friends went to a comedy show on Wednes-day. It started at, like, 8pm and was over by 10pm. I was hoping that morepeople would come out for drinks afterward but a bunch of people had testsand assignments to work on so they didn’t want to be out late. It was justFrank and I that went out afterward. We had a few beers, probably threeor so each, and were chatting. It was fun, easy. Frank is really funny. We’vealways had a good time together but this time he seemed kinda flirty. Heand his girlfriend had a fight last week and I think that’s basically over now.He kinda looked back at me on his way to the bathroom and it seemed likean invitation. I was drunk and feeling pretty bold so I followed him backthere. I gave him head and he seemed to like it. He definitely acted thatway. I’m a little embarrassed about it now, but it wasn’t like a big deal. Weboth just kinda got carried away.”QuestionsDo you believe Mary’s Statement?Y es or No39BIBLIOGRAPHYDo you believe Bill’s Statement?Y es or No40BIBLIOGRAPHYAppendix B: Task InstructionsInstructions provided to participants before starting the taskConditions 1 & 2 instructionsOn the next page you will find the account of the incident provided fromthe alleged victim (Mary) and alleged perpetrator (Bill).Please read each account carefully. You will not be able to proceed tothe following page for 60 seconds. On the following page, you will be askedto answer questions about the individuals involved and yourself.This sequence of events (reading accounts and answering questions) willrepeat two more times afterwards, meaning you will read about three inci-dents in total.Condition 3 instructionsOn the next page you will find the account of the incident provided fromthe alleged victim (Mary).Please read each account carefully. You will not be able to proceed tothe following page for 30 seconds. On the following page, you will be askedto answer questions about the individual.You will then be presented with the account of the same incident pro-vided from the alleged attacker (Bill) followed by questions about that in-dividual. Finally you will be presented with questions about yourself.This sequence of events (reading accounts and answering questions) willrepeat two more times afterwards, meaning you will read about three inci-41BIBLIOGRAPHYdents in total.42
Thesis/Dissertation
eng
Psychology
Vancouver : University of British Columbia Library
Attribution-NonCommercial-ShareAlike 4.0 International
Graduate
Ten Brinke, Leanne Marie
Quantum equality in the courtroom
Text