@prefix vivo: . @prefix edm: . @prefix ns0: . @prefix dcterms: . @prefix skos: . vivo:departmentOrSchool "Arts, Faculty of"@en, "Psychology, Department of"@en ; edm:dataProvider "DSpace"@en ; ns0:degreeCampus "UBCV"@en ; dcterms:creator "Chudek, Matthew"@en ; dcterms:issued "2013-08-20T21:27:06Z"@en, "2013"@en ; vivo:relatedDegree "Doctor of Philosophy - PhD"@en ; ns0:degreeGrantor "University of British Columbia"@en ; dcterms:description """Explanations of humans' evolutionary origins that invoke the ratchet of cumulative cultural learning must confront the `cooperative dilemma of culture'. Adaptive cultural knowledge is a widely shared but easily degraded public goodle knowledge and to deceive and manipulate each other. How did our ancestors avoid the temptation to hoard valuab, before the advent of complex social institutions? I present one possible solution: negative indirect reciprocity (NIR). I use a series of mathematical models to reason about how our ancient ancestors' dispositions to gainfully exploit one another could have supported more complex forms of cooperation, providing a foundation for our rapidly evolving corpus of shared cultural know-how. Together these models show how reputation-based, opportunistic exploitation can play a pivotal role in sustaining cooperation in small scale societies, even before the advent of complex institutions. I also present two empirical tests of the assumptions made by these models. First, I measure contemporary reputational judgements in circumstances that the models predict are relevant. In the process I also map my participants' judgements to the full set of first and second-order reputation assessment rules described by indirect reciprocity theory. Second, I test whether a recently observed peculiarity of people's moral reasoning---our tendency to ascribe blame to those who profit from others suffering because of mere good fortune---is consistent with the constraints assumed by NIR. The results of both empirical studies support the assumptions made by NIR."""@en ; edm:aggregatedCHO "https://circle.library.ubc.ca/rest/handle/2429/44851?expand=metadata"@en ; skos:note "Negative Indirect ReciprocityTheory and EvidencebyMatthew ChudekB.A. University of Melbourne, 2003M.A. University of British Columbia, 2009a thesis submitted in partial fulfillmentof the requirements for the degree ofDoctor of Philosophyinthe faculty of graduate and postdoctoralstudies(Psychology)The University Of British Columbia(Vancouver)August 2013? Matthew Chudek, 2013AbstractExplanations of humans? evolutionary origins that invoke the ratchet of cu-mulative cultural learning must confront the ?cooperative dilemma of cul-ture?. Adaptive cultural knowledge is a widely shared but easily degradedpublic good. How did our ancestors avoid the temptation to hoard valuableknowledge and to deceive and manipulate each other, before the advent ofcomplex social institutions? I present one possible solution: negative in-direct reciprocity (NIR). I use a series of mathematical models to reasonabout how our ancient ancestors? dispositions to gainfully exploit one an-other could have supported more complex forms of cooperation, providinga foundation for our rapidly evolving corpus of shared cultural know-how.Together these models show how reputation-based, opportunistic exploita-tion can play a pivotal role in sustaining cooperation in small scale societies,even before the advent of complex institutions.I also present two empirical tests of the assumptions made by thesemodels. First, I measure contemporary reputational judgements in circum-stances that the models predict are relevant. In the process I also map myparticipants? judgements to the full set of first and second-order reputationassessment rules described by indirect reciprocity theory. Second, I testwhether a recently observed peculiarity of people?s moral reasoning?ourtendency to ascribe blame to those who profit from others suffering becauseof mere good fortune?is consistent with the constraints assumed by NIR.The results of both empirical studies support the assumptions made by NIR.iiPrefaceChapters three, four and five of this thesis are being prepared for publication.Chapters 3 and 4 are coauthored by Joseph Henrich.Chapter 3 is a theoretical model initially suggested by Joseph Henrich.I developed and refined numerous variants of this model. Henrich has pro-vided in depth conceptual feedback throughout and has also provided de-tailed feedback of many versions of this manuscript.The initial idea for the empirical study in chapter 4 emerged from dis-cussions between Henrich and myself. I designed the details of the study,built a web-survey system capable of administering it, gathered and analysedthe data, produced figures and prepared the manuscript. Henrich provideddetailed feedback on the manuscript.Henrich also provided all funding to pay participants in the studies de-scribed in chapters 4 and 5.The data for study one in chapter 5 were gathered by Erik Thulin.iiiTable of ContentsAbstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iiPreface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iiiTable of Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . ivList of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viiList of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viiiAcknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . ixDedication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 The cooperative dilemma of an emerging cultural species 92.1 The cooperative dilemma of culture (a.k.a. the evil teacherproblem) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142.1.1 Why does culture require cooperation? . . . . . . . . . 162.1.2 Why does (human-like) cooperation require culture? . 202.2 Three kinds of solutions . . . . . . . . . . . . . . . . . . . . . 222.2.1 Route 1: The big step . . . . . . . . . . . . . . . . . . 232.2.2 Route 2: The arms race . . . . . . . . . . . . . . . . . 242.2.3 Route 3: The ratchet . . . . . . . . . . . . . . . . . . . 26iv3 Negative indirect reciprocity . . . . . . . . . . . . . . . . . . 283.1 Mathematical model . . . . . . . . . . . . . . . . . . . . . . . 493.1.1 Context and overview . . . . . . . . . . . . . . . . . . 493.1.2 Model definition . . . . . . . . . . . . . . . . . . . . . 513.1.3 Reputational dynamics . . . . . . . . . . . . . . . . . . 543.1.4 Behavioural dynamics . . . . . . . . . . . . . . . . . . 583.1.5 Combining reputations and behaviour . . . . . . . . . 593.1.6 Discrete strategy approach . . . . . . . . . . . . . . . 623.1.7 Evolving continuous traits interpretation . . . . . . . . 773.2 Additional supplemental materials . . . . . . . . . . . . . . . 864 Surveying indirect reciprocity: how do people assign rep-utations? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 884.1 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1004.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1124.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1314.4 Supplemental . . . . . . . . . . . . . . . . . . . . . . . . . . . 1365 It is better to profiteer on the guilty: is moral condemna-tion sensitive to reputation? . . . . . . . . . . . . . . . . . . 1375.1 Methods, study one . . . . . . . . . . . . . . . . . . . . . . . 1415.2 Results, study one . . . . . . . . . . . . . . . . . . . . . . . . 1435.2.1 Do these questions index the same underlying construct?1435.2.2 Was condemnation of the lucky profiteer sensitive tothe victims? reputation? . . . . . . . . . . . . . . . . . 1445.3 Methods, study two . . . . . . . . . . . . . . . . . . . . . . . 1445.4 Results, study two . . . . . . . . . . . . . . . . . . . . . . . . 1505.4.1 Do these questions index the same underlying construct?1505.4.2 Was the manipulation effective? . . . . . . . . . . . . . 1505.4.3 Did participants condemn the profiteer less for profit-ing on the suffering of the wicked? . . . . . . . . . . . 1525.4.4 Did participants reward the trader for taking a loss inmiracle scenarios? . . . . . . . . . . . . . . . . . . . . 153v5.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1566 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1616.1 Near future directions . . . . . . . . . . . . . . . . . . . . . . 1676.2 Distant future directions . . . . . . . . . . . . . . . . . . . . . 169Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172viList of TablesTable 3.1 Summary of parameters . . . . . . . . . . . . . . . . . . . 54Table 4.1 Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92Table 4.2 The cues used to establish the Target?s reputation . . . . . 101Table 4.3 A map from dichotomous reputations reputation changesto their continuous interpretations . . . . . . . . . . . . . . 108Table 4.4 Correlations between our four measures of participants?reputational judgments . . . . . . . . . . . . . . . . . . . . 113Table 4.5 Summary of key results for Chapter 4 . . . . . . . . . . . . 118Table 4.6 Frequencies of discretely categorised judgements of Targets 124Table 4.7 Frequencies of discretely categorised judgements of Coop-erators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125Table 4.8 Frequencies of discretely categorised judgements of Defectors126Table 4.9 A discrete partition of participants? reputational judgements130Table 5.1 Likelihood-maximising linear regression parameters ? ofratings of the lucky profiteer . . . . . . . . . . . . . . . . . 146Table 5.2 Correlations among study two dependant variables . . . . 150Table 5.3 Participants? ratings of Floret residents in Study 2 . . . . . 152Table 5.4 Participants? ratings of the lucky profiteer in disaster sce-narios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154Table 5.5 Participants? ratings of the lucky profiteer in miracle sce-narios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156viiList of FiguresFigure 3.1 The NIR decision tree . . . . . . . . . . . . . . . . . . . . 35Figure 3.2 NIR-P basins of attraction and equilibrium reputations . 39Figure 3.3 NIR?s logic, testable assumptions and predictions . . . . . 48Figure 3.4 Simulations showing the accuracy of analytic predictionsabout Resident and Invader equilibrium reputations. . . . 61Figure 3.5 Simulations showing the accuracy of analytic predictionsabout equilibrium reputations of three discrete strategies. 64Figure 3.6 Invasability plots for the three discrete strategies in NIR . 69Figure 3.7 Meta-barycentric plots of NIR boundary equilibria . . . . 76Figure 3.8 Selection gradients for three version of NIR . . . . . . . . 84Figure 3.9 Relative volunteering rates for NIR-V and NIR-M . . . . 87Figure 4.1 American Participants? absolute judgements of Targetsand relative judgements of Actors . . . . . . . . . . . . . . 115Figure 4.2 Indian Participants? absolute judgements of Targets andrelative judgements of Actors . . . . . . . . . . . . . . . . 116Figure 5.1 Likelihood maximising estimates of the means of partici-pants? ratings . . . . . . . . . . . . . . . . . . . . . . . . . 145Figure 5.2 Means of participants? ratings of Floret residents . . . . . 151Figure 5.3 Means of participants? ratings of the profiteer . . . . . . . 155viiiAcknowledgmentsFirst and foremost I?d like to thank Joseph Henrich for support, adviceand stimulating discussion throughout my time at the University of BritishColumbia. This would not have been possible without him.I would also like to thank my committee members (Ara Norenzayan,Susan Birch and Michael Doebeli) and the amazingly bright and diversefaculty of the University of British Columbia?s psychology department foradvice, support, collaboration and feedback.I would like to acknowledge and thank the University of British Columbia,and especially the Faculty of Graduate Studies, for funding in the form ofgrants, fellowship and scholarships. I would like to thank the Departmentof Psychology for several travel grants and a terrific education.I would especially like to thank Faye d?Eon-Eggertson for all her care andsupport, and for her careful proofreading. Your reading experience wouldbe far less polished and far more jarring were it not for her heroic efforts.Finally, I would like to thank my friends, family and loved ones for theirsupport during these interesting times.ixDedicationI dedicate this work to my brother (Mark) and sister (Georgina). I?ve beenso far away from them and missed so much of their lives to undertake thisapprenticeship into the academy.They?re amazing people and I miss them.xChapter 1Introduction?What am I??Like ?why is the sky blue?? and ?why is my puppy sick??, it is an entirelyreasonable questions for a curious child to ask. But unlike those others, itis not a question we have a good answer to.Our understanding of modern humans lacks a central explanatory paradigm.We know of no simple set of laws or principles which integrates and makessense of the staggering range of things people do, make, say, think andbecome. Much of our understanding of humans is, by Thomas Khun?s1definition, pre-scientific.The explanations offered by sociologists?who focus on the institutionsthat emerge from our interactions?are entirely disconnected and often con-tradict those offered by social psychologists?who focus on how we, as in-dividuals, are influenced by our social institutions. Economists? consistentpreference optimising rational agents have little or nothing to do with his-torians? tension between Marxist or internalist interpretations of the causesof societal change. Anthropologists? relativism sits at stark odds with therobust universalism implied by psychologists? broad generalisations from un-dergraduate student samples. A psychologist studying crime who stumblesinto a criminology conference would be just as perplexed by symbolic interac-1a twentieth-century philosopher of science, who?s descriptions of scientific progress(Kuhn, 1996) still inform many scientists? understanding1tionism as a criminologist would be, were their situations reversed, by subtledistinctions between attitudes, attributions, appraisals, attachments, acti-vations, arousals, affects, automatic processes, beliefs, bias, construals, cog-nitions, dissonances, deindividuations, emotions, ego-threats, perceptions,representations, self-verbs, and the panoply other functionally-defined enti-ties psychologists suppose occupy human minds.It is rarer still for any of these disciplines? explanations to explicitlyconnect with the principles of biology. Even though we know that humansevolved by natural selection, most disciplines proceed as though humansplay by entirely different rules from other animals, without ever explicitlyaccounting for why or how this came to be.Even within psychology the theoretical picture is little more integrated.Cognitive psychologists, personality psychologists, developmentalists and so-cial psychologists are engaged in conversations that rarely overlap. Whenthey do it is by the idiosyncratic connections made by individual researchers,rather than due to the a priori, formally derived predictions of a shared cen-tral theory of psychology. Rather than systematically testing and buildinga shared paradigm, most psychological research consists of thorough butdisconnected local descriptions of particular phenomena and exciting noveleffects.Within social psychology in particular, the theoretical landscape is par-ticularly cacophonous. Many disconnected mini-theories cluster closely aroundthe empirical effects they describe and the methods used to investigatethem. Though individual researchers strive to make connections betweenthese mini-theories, these connections are typically ad hoc and rely on re-searchers? intuitive and common-sense understandings of their explanatoryconcepts rather than precise and formal definitions.When asked ?what am I??, we can offer many reasonable answers to littlequestions. Why do we sometimes help each other and sometimes not? Whyare we sometimes willing to spend more money than other times? Why dowe forget things when we?re old? Why did Rome fall? Why do people fromthat other country act so strangely?However we lack a shared set of central explanatory principles that could21. say how something like us can emerge from biology2. predict a priori what we would be like; individually, collectively andhistorically3. begin to integrate (and, sometimes, outright reject) the many verydifferent, sometimes contradictory explanations for different aspectsof our behaviour.This absence of core theoretical principles might be a malfunction of thesociology of our science, a consequence of how we incentivise and motivatesocial scientists. Walter Miscel, then president of the Association for Psy-chological Science, implied as much when he turned his peers? attention asthe ?toothbrush problem? (Mischel, 2009):Psychologists treat other peoples? theories like toothbrushes, noself-respecting person wants to use anyone elses.It is also possible that our scientific institutions (including those thatmotivate researchers to invest primarily in their own novel, distinct micro-theories) are merely shaping themselves to the contours of our object ofstudy. Central explanatory principles of the human phenotype may be per-versely difficult to discover, even with the full arsenal of modern empiricism,or worse, there may not be any principles to find.It is entirely conceivable that no such central explanatory principles ex-ist. Perhaps the best answer we will ever be able to give to ?What am I??is a scattering of local descriptions of disparate human-phenomena. Onefor cognitive dissonance. Another, that invokes very different theoreticalassumptions, for demographic transitions. A third for extraversion, andso on. In such a world, our current sociology of isolated, idiosyncraticallyconnected inquiry might be ideal.I believe that, difficult though they may be to untangle, such principlesdo exist and are worth searching for. The argument for their existence issimple and I find it persuasive. Our species evolved by natural selection.3It did so very recently (on evolutionary timescales) and in a sudden, un-precedented explosion of complex novel behaviour. What?s more, no otherspecies did the same. This suggests that, though some aspects of humanpsychology may have accreted independently over millennia, there were alsosome key recent ingredients that sparked an inferno of positive feedback andnew dynamics. If there were simple, discrete causes then chances are we canfind a simple explanatory principles that reconstruct them and predict theirmanifold consequences.The value of searching for these principles, let alone the means of doingit, are harder to argue for. One could make a good case that our cur-rent hodge-podge of cross-disciplinary inquiry is the best way of discoveringthem. By careful, if initially disconnected, empiricism we might graduallyestablish a solid foundation of accurate descriptions of human-phenomena.This would accumulate, bottom-up, until they converged on the central ex-planatory principles. The counter-point to this argument is that our domainof inquiry?human behaviour?may be complex enough that this process isnon-terminal. We could go on making empirical discoveries about humansforever. Or rather, like the proverbial blind men and their elephant2, wewould merely rediscover too-simple, low-dimensional redescriptions of thesame underlying higher-dimensional phenomena, cloaked in different, incom-patible theoretical jargon (for a philosophical explication of this possibilitysee Dennett, 1991).For instance, one regularity that will be relevant later in this disserta-tion is ?negativity bias?. People seem to have a robust tendency to respondmore strongly to subjectively bad or unpleasant events than good ones. In2001, Roy Baumeister and his colleagues documented a terrific diversity ofdomains and investigations in which this same pattern had been rediscov-ered (Baumeister et al., 2001). In each domain?from emotion research, tomorality, to the trajectory romantic relationships, to economic choices aboutpecuniary profit and loss?it was interpreted as a novel insight, a local anddistinct piece of evidence for a distinct theory, couched in distinct theoreti-2if you?re unfamiliar with the proverb, it can be readily found on the internet4cal terms and entailed by different assumptions. Identifying these seeminglydisconnected effects as facets of a single pattern was a great achievement.Even though negativity bias is a very simple pattern?a linear relation-ship between the valence of an event and its effect3?it was by no meanssimple or obvious to spot. If some or most of the real patterns that explainhuman behaviour are more complex than that?say non-linear relationships,or interactions between multiple factors, or patterns that spread across cul-tural timescales?then we may well be pessimistic about whether an industryof bottom-up empiricism will ever converge upon them.If such concerns have you worried, you may see the worth of simultane-ously pursuing a top-down strategy. That is, you might consider trying toderive the explanatory patterns a priori. To do so, you would start from ei-ther our understanding of the biological principles that launched our species,or another sufficiently abstract, theoretically rigorous description of humans.You would then postulate as few principles, and as simple principles as youcould and attempt to derive from them the gambit of human-phenomena(individual, collective, psychological, historical, etc.). Successful theorieswould be those that were simple, fit seamlessly with biology, and accuratelypredicted the greatest breadth of human-phenomena, especially previouslyundiscovered phenomena.Such top-down attempts are valuable because, if successful, they canintegrate disconnected empirical efforts and push our understanding forwardin leaps and bounds. But they are also risky. You can invent an almostlimitless diversity of such grand theories, but only a few are accurate oruseful. Decades of valuable researcher time could be squandered fruitlesslypursuing them, at the price of empirical phenomena that could have beenbetter documented in the meantime. This is, perhaps, why such ambitiousand unlikely speculation is often frowned upon by psychologists.However the difficulty of hitting upon an accurate top-down theory is also3Actually, given the null-hypothesis testing inferential framework in which most of thiswork is done, the relationship being formally tested is often magnitude-free and so simplerstill: a dichotomy. More bad means more strong, regardless of how much more of eitheror the specific functional relationship between them.5an asset: a low false-positive rate. Top-down theories are unlikely to broadlypredict novel contemporary empirical phenomena unless they are accurate.By ?broadly?, ?novel? and ?predict? I mean that the theory is consistent with awide range of phenomena that it was not explicitly designed to explain. Themeasure of top-down theories is the breadth of their explanatory power, theirability to easily integrate phenomena that previously seemed disconnected.Relax. I will not propose a grand top-down theory in this dissertation.Instead, I hope to contribute to a broader paradigm of already successfultop-down explanation. I will refer to this paradigm, which I review below, as?culture-gene coevolution?, even though scholars from many disciplines haveconverged on this same theoretical space and called it by different names.Specifically, I hope to contribute by refining the theoretical terrain on whichculture-gene coevolutionary theories contend.In chapter 2, I spotlight a set of top-down explanations of human be-haviour that share these traits: 1) they are grounded in biology, and 2)they give a central role to ?culture??the social transmission of complex, en-coded, phenotype-shaping information. I argue that though these attemptsare already somewhat successful and very exciting, they are plagued by anunder-recognised theoretical challenge: the cooperative dilemma of culture.I review existing solutions to this dilemma.In the remainder of this dissertation I derive and test a novel solution tothe cooperative dilemma of culture.In chapter 3, I pick out one of the most plausible and commonly citedsocio-ecological dynamics that may have established the cooperative foun-dation on which ancestral culture thrived: reputation. I argue that exist-ing formal models of reputation do not address the cooperative dilemmaof culture and offer a new model that does. This new model, which I callNegative Indirect Reciprocity (NIR), shifts the theoretical focus from themutual-aid emphasised in most approaches to human cooperation (positivecooperation), to our countless unrealised opportunities to gainfully exploitone another (negative cooperation).Many scholars have assumed that positive and negative cooperation aretwo sides of the same coin, and are equally well represented by our existing6models of positive cooperation. In chapter 3 argue that they are not, detailsome of the important asymmetries between them and argue that negativecooperative dilemmas likely shaped our cultural species? early evolution morestrongly than positive ones did.Succinctly, NIR is a model of ?indirect reciprocity??reputation-basedcooperation. Unlike existing models, NIR minimises the cognitive prerequi-sites of reputation-based cooperation by assuming that cooperation or de-fection by ?inaction? (i.e., having an opportunity to act, but choosing not to)does not change reputations. That is, it does not assume that communitiesare able to coordinate their understanding of abstract opportunities, roles,responsibilities and so on. NIR show that, in the context of cooperation by?not exploiting?, such simple reputational systems can form the foundationof more complex societies.?Negative cooperation? and ?reputation without meaningful inaction? havea special synergy. Together they create selective pressure for individuals todo whatever it takes to improve their reputation?that is, to please theirpeers on average. This pressure to attend to one?s community?s behaviouralexpectations can help explain how more sophisticated forms of cooperationarose.NIR tells a specific, theoretically-rigorous story of how human reputa-tions may have first emerged and how they formed the substrate of otherforms of cooperation. It entails several clear empirical predictions aboutcontemporary humans psychology. In the remaining chapters I test some ofthese predictions.In chapter 4, I attempt to provide the first theoretically-informed cata-logue of people?s reputation-based intuitions by simply asking them. I findthat the valence of cooperation (whether it is helping or exploiting) mat-ters a lot (as predicted by NIR) and that negative non-cooperation causesparticularly strong reactions across cultures (as predicted by NIR).Chapter 5 documents a study that, while simple, is important because ittests NIR against a novel theoretical phenomenon that it was not designed toexplain. I find that this phenomenon, of people disliking those who inciden-tally profit while others suffer, fits quite nicely to the psychological biases7that NIR predicts we should have.8Chapter 2The cooperative dilemma ofan emerging cultural speciesSomewhere between our split from chimpanzees (circa 6-3 mya, Pattersonet al., 2006, but cf. Yamamichi et al., 2012) and the emergence of fullyanatomically modern humans (circa 200 kya, Day, 1969; McDougall et al.,2005) our ancestors began behaving very strangely. Their new ways of think-ing and behaving, and the social dynamics these engendered, were ultimatelyrooted in the same (relatively) well understood processes that shape the be-haviour of our many non-human relatives: evolution by natural section. Yetsomehow this species experience an unprecedented explosion of complex anddiverse behavioural forms like opera, foot-binding and hopscotch. On theface of it, it seems as though some new dynamics began interacting withnatural selection.Psychologists and other social scientists work to understand the stag-gering behavioural and cognitive diversity that has emerged in our species.For instance, cultural psychologists document deep cognitive differences be-tween humans raised among different communities (e.g., Nisbet, 2003), evo-lutionary psychologists try to identify behavioural similarities which can beexplained as adaptations to a shared ancestral environment (e.g., Barkowet al., 1992), while social psychologists tend to treat social environments asextrinsic and investigate how individuals respond to them, often implicitly9assuming that the breath of diversity is well represented by North Americanuniversity undergraduates (Henrich et al., 2010).Alongside this industry of bottom-up inquiry, some scholars also con-front the top-down challenge of disentangling the circumstances that firstlaunched this process and the core laws or principles that continue to driveit forward. Scholars from across disciplines have proposed mechanism anddynamics at the core of humans? distinct evolutionary trajectory, includingarchaeologists (Mithen, 1996), anthropologists (Boyd & Richerson, 2005;Deacon, 1998; Richerson & Boyd, 2004), primatologists (Tomasello, 1999)psychologists (Csibra & Gergely, 2009; Tomasello, 1999), biologists (La-land, 2004; Laland et al., 2001; Wilson, 2012), mathematicians (Nowak &Sigmund, 2005), linguists (Pinker, 2010) and philosophers (Sterelny, 2012),among others.Refining the glut of theory is not easy. Early human societies no longerexist so we cannot directly observe their behaviour, experiment on their cog-nition nor watch them change. We cannot directly measure the dynamicsthat gave rise to our species. However, we may have some chance of recon-structing them from the convergence of several indirect sources of evidence.Close inspection of our genome offers hints of ancestral speciation events(Garrigan & Hammer, 2006) and recent rates of genetic selection (Lalandet al., 2010). However much variability among contemporary humans seemsto be cultural, not genetic (Bell et al., 2009; Cavalli-Sforza & Cavalli-Sforza,2000). Archaeological remains help fill this gap, but are limited to materialsthat survive decomposition and more sparse the further into the past wewish to gaze. Cross-species comparisons with our nearest cousins (e.g., Deanet al., 2012; Herrmann et al., 2007, 2010) provide a source of direct and evenexperimental evidence about evolved behavioural and cognitive differences.But while contemporary primates share our ancestors, they are not ourancestors and have experienced several million years of distinct evolutionarypressures.Observation of contemporary forager societies can help here (e.g., Bellet al., 2009; Henrich et al., 2006), since their ecology, group size and residencepatterns may be more similar to our ancestors?. However the mere existence10of contemporary foragers is reason to suspect their societies are unlike ourearliest ancestors?. Contemporary foragers somehow escaped the explosivespread of agriculture (Gignoux et al., 2011), while typical foragers did not.A final empirical avenue for testing these theories is to carefully derivetheir implications for contemporary cognition, and compare these to howpeople think and behave today. This is the method I pursue in this disser-tation.We can also make purely theoretical progress by narrowing the windowof plausible theories. One way to do this is to reject willy-nilly post-hocexplanations of particular empirical phenomena (e.g., Frankenhuis, 2010;Navarrete & Fessler, 2005). Another way is to notice and define theoreticalpuzzles (e.g., Rogers, 1988) whose solutions (e.g., Boyd & Richerson, 2005;Enquist et al., 2008; Laland, 2004) push our theories towards assumptionsmore likely to be true. This dissertation highlights one such puzzle, thecooperative dilemma of culture, for a subset the of these hypotheses: culture-gene coevolutionary theories.Culture-gene coevolutionary theories explain humans by emphasising cu-mulative cultural learning. When they say ?culture? these theories are re-ferring to behaviour-shaping information that is transmitted across genera-tions socially, not genetically. While many species show evidence of somecultural transmission (Brown & Laland, 2003; Laland, 2004; Rendell et al.,2010; Whitehead et al., 2004; Whiten et al., 1999), only among ours did thiscultural information begin accumulating into ever more complex forms, thateventually included ?calculus?, ?maps? and ?dancing the Macarena?.The revolutionary importance of this transition is worth spending a fewparagraphs on. To give it some more intuitive, less jargony traction, I?llborrow a metaphor from cognitive psychology. Our minds, and other an-imals?, are information processing systems; software instantiated upon thehardware of our brains. They are computers designed to take sensory input,interpret it, make some sense of the world outside, and make decisions abouthow to behave. To do this, they must make assumptions about that world.For instance we can, in a sense, directly perceive some of the assump-tions our visual system makes when we look at a visual illusion and see11something we know is not really there. Developmental scientists have at-tempted to identify other, more conceptual assumptions that children useto make sense of the world. Proposed assumptions range from intuitionsabout the existence and properties of objects, the geometry of space, the ex-istence and behaviour of goal-directed agents and even mathematical princi-ples (see Spelke & Kinzler, 2006, for a review). They even include complexintuitions about the relative importance different kinds of information (e.g.,Barrett & Broesch, 2012), the existence of ?minds? that are distinct frombodies (Chudek et al., forthcoming) and something functionally equivalentto Bayesian priors about the nature of causality (Griffiths et al., 2011; Kalishet al., 2007; Yeung & Griffiths, 2011).Many of the assumptions we use to make sense of the world, like thosethat process vision, are encoded genetically. Our minds also seem to be ableto infer other assumptions as they develop. For instance, rats rapidly makestrong assumptions about which olfactory cues signal toxic food merely byobserving other rats? reactions (Galef & Whiskin, 2008). Though we don?tknow whether rats explicitly represent this information in the same wayhumans do, we can observe their minds translating sensory information intobehaviour as though they were assuming this of the outside world.Though our minds (and rats?) can make some sense of the world beyondthat encoded in our genes, the accuracy and complexity of these represen-tations is limited by the scant sensory experience we are exposed to duringour short lives. The advent of cumulative cultural learning was a revolutionin the potential complexity of these representations. It let our minds alsotap into the experiences of our conspecifics. In addition to learning aboutthe world from our own experience and by observing others, we began totap into the accumulated wisdom of minds long dead.Imagine all the different assumptions our minds could make about theoutside world as a vast space that stretches off in as many directions asyou can conceive. Before the revolution of cumulative culture our individualjourneys through this space were like sparks flying off of the slow-burningfuse of genetic evolution. Even today this fuse continues to endlessly wend itsway through the space of possible external realities, guided by the selective12retention of more successful variants. Like other animals, our brains wereconstrained to perceive the world in whichever ways had led their ancestorsto be more robust, fecund or in other ways fitter.With the advent of cumulative culture something entirely new happened.Our ancestors detached from the fuse. They began incorporating others?representations of the outside world into their own, building on others? as-sumptions, sparking into the unknown from a new position far from theirgenetically imbued starting point. We are still on this journey together.We each aggregate the experiences, knowledge and assumptions of our peersand each new generation inherits this amalgam. To continue the metaphor,our cultures are like great fireballs travelling through the space of ?possi-ble assumptions our minds could make about the world outside?. We blazemost brightly around an evolving core of shared assumptions, practices andunderstandings. From there our individual sparks still fly in all directions,innovating their own unique sense of the world outside.Culture-gene coevolutionists work to understand this phenomenon ofcumulative cultural learning; to theoretically and empirically describe itand discover any laws or principles that govern it. The questions they askinclude:? How did this process start, and why did it seemingly happen only inour phylogenetic line (e.g., Boyd & Richerson, 1988, 1996; Richerson& Boyd, 2004)?? What cognitive adaptations and behavioural traits make it possible,and what new cognitive adaptations does it favour (e.g., Boyd & Rich-erson, 2005; Henrich, 2009; Henrich & Gil-White, 2001; Laland, 2004;Nakahashi et al., 2012)?? Are there rules or principles that govern the trajectories such confla-grations of cultural learning will take through the space of all possibleculture (e.g., Boyd & Richerson, 1988; Cavalli-Sforza & Feldman, 1981;Laland et al., 2001; Richerson & Boyd, 2004)?? Can our evolving cultural corpus cause us to fracture into distinct,13symbolically marked ethnicities or social classes (e.g., Henrich & Boyd,2008; McElreath et al., 2003)?? How and why does this process produce cross-generational institutions,like religion (e.g., Gervais et al., 2011; Norenzayan & Shariff, 2008) ormarriage (e.g., Henrich et al., 2012), and how do these evolve?? How does cultural evolution redirect genetic evolution (e.g., Lalandet al., 2010); how does it reshape our ecology and adaptive landscape(e.g., O?Brien & Laland, 2012; Rendell et al., 2011)?? Does this process ever break down, how and why (e.g., Henrich, 2004)?? How does this our evolving culture interface with our capacity forcooperation (e.g., Boyd et al., 2011a; Chudek & Henrich, 2011, andthis dissertation)?This culture-gene coevolutionary explanatory story is rapidly maturing,and has already had considerable success predicting many emergent featuresof contemporary society and psychology. However there is something trou-bling about it. Why did it make sense?from the perspective of our genes?for our genome to give up so much control over our adult phenotype, andlet cultural information shape us instead?2.1 The cooperative dilemma of culture (a.k.a.the evil teacher problem)The cooperative dilemma of culture, which I also like to call the ?evil teacherproblem?, is pervasive. One need not agree with any of the specifics of anyparticular CGC theory to be trouble by it. It should concern you whateveryour stance in controversies over group selection (e.g., Abbot et al., 2011;Nowak et al., 2010; West et al., 2011) and other evolutionary processes. Tomeet it, you merely need to accept the following premises:1. Humans are cultural To understand us you need to explain the corpusof technology, ideas and knowledge that we have accumulated overgenerations, non-genetically.142. Humans are strangely cooperative To understand us you need toexplain how we became so cooperative. We regularly make choices thatentail a relative cost (or forfeiture of a possible benefit) for us and rela-tive benefit for others. Those others regularly include non-kin, peoplewe know distantly or only by reputation, and even complete strangerswho we are unlikely to meet again. The ways we cooperate are oftenunique to particular societies, and in any case vary dramatically acrossshort stretches of time and space. No other species cooperates like wedo (for detailed arguments for the peculiarity of human cooperationsee Chudek et al., 2013b). Though many species cooperate in theirown unique ways, human cooperation is distinct in its variety and rateof change. Humans in some places build houses together, in othersthey queue, and in others they construct and police far flung tradenetworks whose purpose is taking other humans as slaves. They alsocooperate on vastly different scales. In some regions, villages are per-manently at war with each other. In others, huge empires maintainrelative internal harmony. Furthermore the rates at which the scaleand form of human cooperation changes?some regions have movedfrom villages to nations within a single lifetime?is unprecedented andcannot be explained by genetic mutation and natural selection alone.3. Culture requires cooperation For a species to accumulate a corpusof complex cultural knowledge, its members must accurately sharevaluable, fitness-relevant, phenotype-shaping information. Each indi-viduals acquires this information from the minds of others, who couldeasily distort it to their advantage or keep it to themselves but, typi-cally, do not. When we share cultural knowledge, we cooperate. Thisis especially true for the complex, hard-to-observe ecological masterythat allows small scale foragers to thrive in some of the worlds harshestecologies.4. Explanations of human cooperation invoke culture Culture typ-ically changes far more quickly than genomes do. Any mechanismthat could keep us cooperatively sharing valuable cultural knowledge,15across its staggering breadth of domains, would need to keep up withculture. For example, a set of genetically adapted intuitions that man-aged to keep us honestly sharing food would do us little good whenwe began culturally transmitting warfare techniques, inheritance sys-tems, queuing etiquette or intellectual property laws. Models of pow-erful, domain-general, human-specific cooperation-sustaining mecha-nisms do exist; I discuss some below and in Chapter 3. However thesemechanisms typically presuppose that social groups are able to rapidlyconverge on and even enforce behavioural norms. That is, they pre-suppose that we are already a fairly cultural species.5. There is an explanatory regress Accounts of human emergence facethe challenge of explaining the origins of human culture and coopera-tion simultaneously, without assuming each to explain the other.I will assume you agree with the first two claims, and will try to convinceyou of the others.2.1.1 Why does culture require cooperation?I am aware of three interrelated cooperative challenges posed by the emer-gence of human culture.The first challenge: for complex culture (e.g., behavioural patterns no a-cultural individual could plausibly devise alone, like ?trebuchets? and ?opera?)to accumulate, some individuals must share valuable information with otherswhen they could do nothing. The second: those same individuals must notdistort the cultural information to their own benefit, even though othersmust (to some degree) trust them. The third, language makes lying cheap.For a clearer sense of these three arguments, lets imagine two individuals:a learner and a teacher. They are unrelated and the teacher has someinformation that would be useful to the learner. Each of us plays both theseroles in our lives, sometimes both simultaneously.At very early stages of the emergence of culture, when only simple be-haviours are transmitted, it is plausible that the teacher has no choice but16to transmit their information. For example, imagine the information is aforaging technique. Unless the teacher is willing to not forage at all, theymight have no choice but to demonstrate their technique to the onlookinglearner. As long as cultural information is simple enough to be transmittedby mere looking-on, learners are in a position of power. However as soon asculture becomes complex enough that it requires any deliberate demonstra-tion of a technique (e.g., stone-tool making), or a process must be performedprecisely and rarely (e.g., making tools for making tools, house building), orcan be done out of view of other (e.g., food processing) or requires specialisedknowledge (e.g., tracking, foraging, medicinal plant use), the power changeshands. As soon as culture gets really interesting, interesting enough thatsome specialised teaching is required, teachers must cooperatively transmitvaluable information to unrelated others.I have heard two counter-arguments to this first thesis.The first is that perhaps such teaching could begin within the family,piggy-backing on kin-recognition mechanisms for cooperation. I have seenno formal models of such a process, and whether it could allow enoughhorizontal transmission for cultural accumulation to ever get off the ground.I do not think such models are necessary for two reasons:? Humans don?t just behave that way. We do not show a widespreadproclivity for limiting our cultural transmission to family members(e.g., Henrich & Broesch, 2011) and certain eye- and body-cues seemto put children into a ?pedagogical stance? where they are highly cred-ulous to information transmitted by any adult, even stranger-scientistsstudying them (Csibra & Gergely, 2009).? Even if cultural transmission started within families, the cooperativedilemma is merely pushed back (or forward in time) to whenever hu-mans started sharing enough of this information with non-kin for ourcomplex societies to begin developing (Chudek et al., 2013b).The second counter-argument is usually voiced after people reflect onwhy they themselves are not evil teachers. A selfish teacher would soon17find that others refused to teach them too. The long-term costs of others?exclusion would be too great. More formally, this intuition suggests thatdirect, pairwise reciprocity might have solved the cooperative dilemma ofculture. Below I argue that it cannot (section 2.1.2).The dilemma runs deeper. Imagine that the learner and teacher passthe first hurdle and the teacher begins sharing valuable information withthe learner. This puts the learner in a very vulnerable position. While cul-tural information is simple enough that the learner can readily apprehendthe causal logic of what they are doing, they need not ?trust? the teacherin any fitness-relevant sense. However as soon as the corpus accumulatesinformation complex enough that it is causally opaque to us (which, I sus-pect, need not be very complex at all), the learner must trust. That is,adaptations must enter their genome which cause it to give up some controlover its adult phenotype. Instead, their behaviour starts to be shaped byinformation that has passed through others? minds. This information mustbe, on average, adaptive for the learner or such adaptations would not befavoured.The second challenge: complex cultural accumulation implies that somecontrol over the learner?s behaviour is in the hands of the teacher. Thisshould select for exploitative adaptations in the teacher. Teachers who findways to mutate and distort cultural information to their own advantageshould be favoured by selection.Such evil teachers could, for instance, teach foraging techniques or di-etary prohibitions that result in the teacher eating some of the learner?sfood. While I have occasionally seen older children teaching younger chil-dren rules unabashedly biased in their interests, the endless possibilities forsuch Machiavellian manipulation of cultural information do not even occurto most adults. The more the first challenge is overcome, the more this sec-ond challenge is exacerbated. The more valuable information we share, themore culture-dependent learners come trust this causally-opaque informa-tion, the more opportunities there are for evil teachers to distort it to theirbenefit. The importance of this second challenge is underscored by just howtrusting contemporary children are of non-kin adults (Harris, 2012).18The most common answers I have heard to this challenge are that ma-nipulative teaching would result in a) retaliation and b) the teacher beingignored in the future. These are ways of restating the dilemma rather thansolutions. How do learners know when to retaliate? Say I teach you a medic-inal remedy but omit a scarce ingredient so I can gather more myself. Howare you to know that your slower recovery times are not a consequence ofsome other aspect of your lifestyle, your poorer skill at preparing medicinesor the ill will you earned of a sorcerer? How can I infer that you snare thebig game more often than me because you deliberately taught me inferiortechniques, and not due to the countless other differences between us?If retaliation is error-prone (sometimes you weren?t deceiving me) howis it not more costly for the learner than blind trust or walking away? Whydo the benefits of exploitation for the evil teacher not exceed the costs ofpotential retaliation or being ignored? Answering these questions requiresspecific hypotheses about ancestral socio-ecological dynamics and how theretaliation or ignoring affected them. It requires detailed models of howthese ecologies interacted with genetic and cultural evolution. It requires asolution to the cooperative dilemma of culture.The third challenge of the cooperative dilemma of culture: languagemakes lying cheap. One plausible way to meet the first two challenges is toargue that it is more costly for the teacher to withhold information, or figureout how to distort it exploitatively, than the benefits they could obtain bydoing so. This argument fails, and the first two challenges are exacerbated,when language enters the picture. At some point in the history of ourcultural corpus, it became encoded it in a semantically rich, combinatoriallanguage.I find persuasive the argument that given what a complex, specialisedadaptation language is, there must have existed a strong need for it (i.e., acomplex cultural corpus worth transmitting) before it was selected for. Re-gardless of your stance on this issue when language entered the picture, itbecame possible to transmit far more complex, subtle cultural information,but also to engage in subtler, more complex deceptions. There are mathe-matical models demonstrating that language makes lying powerful and easy19(Lachmann & Bergstrom, 2004), but I suspect that this evolutionary argu-ment is intuitive, simple and uncontroversial enough that it does not requirethem. When you have language, it is easy to lie.Hopefully these arguments convince you that only a cooperative speciescould be cultural. But how do we know that the cooperative chicken didnot preceded the cultural egg?2.1.2 Why does (human-like) cooperation require culture?Many animals cooperate. For instance, some eusocial insects act as a singlesuper organism by sequestering their reproductive line, just like the cellsin our bodies do (Smith & Szathm?ry, 1997). On a smaller scale, somesocial mammals provision one another with public goods, such as makingself-endangering alarm-calls upon sighting a predator (Seyfarth et al., 1980).However human culture could not have piggy-backed on these simplerforms of cooperation. First, humans are not eusocial, we are distantly re-lated and each reproduce individually. Second, specific genetic adaptationsfor specific cooperative behaviours in specific domains could not sustain cul-ture. Culture changes much faster than genes do. As culture accumulates,cooperative dilemmas arise rapidly in many different domains. Who shouldtake the risks when hunting? How should we divide the spoils? Who shoulddo the hard-labour and who should pray for rain? Who marries whom, whoreproduces when and who contributes which resource to which resource-hungry child, during their long, unproductive juvenile period (Gurven et al.,2006; Kaplan & Robson, 2002; Lancaster et al., 2000; Walker et al., 2006,2002)? By the time our slowly mutating genome develops a mechanism (e.g.,a signal; Boyd et al., 2010) for solving one of these dilemmas, our rapidlychanging cultural corpus has generated countless others.If ancestral humans had genetic adaptations for sustaining cooperationthat supported their cultural accumulation, they must have been domain-general adaptations that could rapidly stabilise arbitrary, new forms of co-operation whenever they arose. I am aware of no purely-genetic mechanismsfor sustaining culture (e.g., kin-selection, limited dispersal, genetic group-20selection, etc.) that can satisfy this criterion.A second class of mechanisms posit institutions for sustaining culture.That is, highly coordinated, sometimes socially enforced, behaviours thatensure that it is in individuals? interest to cooperate in arbitrary domains.A simple example is a police force or ?punishment pool? (Sigmund et al.,2010). Individuals first put resources towards sustaining the existence of animpartial punisher (e.g., paying the sheriff) and then the punisher spendsthose resources on making defectors pay. These institutional mechanismscan ?keep up with culture?. They can sustain arbitrary forms of cooperationwithout requiring slow, specific genetic adaptations. However most insti-tutional mechanisms presuppose a species that is able to dynamically andrapidly coordinate such institutions. For instance, how do people establishpunishment pools? How do they ensure the pool?s resources do effectivelypunish? How do they coordinate what specific behaviours the pool shouldpunish. How do all these moving parts keep up with our rapidly evolvingculture?Even if such institutional mechanisms did not require language and so-phisticated, culturally transmitted concepts, they would at a minimum re-quire that we carefully attended to and trustingly imitated one-another?sbehaviour. While institutional mechanisms undoubtedly played and con-tinue to play a role in sustaining and managing the latter forms of humansociality, they cannot be invoked to explain the emergence of culture withoutstumbling into an explanatory regress.A third class of models posits genetically-selected, individual-level be-havioural strategies that, in aggregate when common-enough, sustain coop-eration in arbitrary domains. The flagship of such promising solutions isreciprocity.?Direct reciprocity? explores how individuals? can benefit by conditioningtheir behaviour towards someone on how that someone treated them in thepast. If enough individuals act this way, pairwise cooperation can thrive(Axelrod & Hamilton, 1981; Boyd & Lorberbaum, 1987; Doebeli & Hauert,2005; Trivers, 1971; van Veelen et al., 2012). However direct reciprocitystruggles to explain cooperation among many individuals simultaneously,21such as provisioning non-excludable goods to an entire group (e.g., sharingvaluable cultural information).?Indirect reciprocity? (Leimar & Hammerstein, 2001; Ohtsuki et al., 2006;Panchanathan & Boyd, 2004; Panchanathan et al., 2003; Sigmund, 2012) orreputation-based cooperation is a better candidate for catalysing the emer-gence of human culture. Models of indirect reciprocity (discussed furtherin chapter 3) explore how individuals can benefit by conditioning their be-haviour towards someone on how that someone treated a third person inthe past. Though most models of indirect reciprocity only consider pairwisecooperation, it is easy to see how they can be extended. Once individualshave reputations, and once those reputations coordinate how others treatthem, selection will favour individuals who do whatever it takes (as longas it is not too costly) to improve their reputation. If provisioning pub-lic goods (e.g., freely sharing knowledge) improves one?s reputation, thenindirect reciprocity can sustain that too.However for indirect reciprocity to hold water as a solution to the coop-erative dilemma of culture, one would need to demonstrate that it can getoff the ground without presupposing the existence of a cultural species. Inchapter three I argue that existing models do make this supposition and sofall prey to the explanatory regress we are trying to avoid. I then go on toprovide an alternative that does not.In short, I am not aware of any existing theories (or formal, evolution-ary models) that show how the kind of domain-arbitrary, rapidly adaptingcooperation necessary for culture could emerge with assuming sophisticatedcultural pre-adaptations.If the cooperative dilemma of culture is a real puzzle of CGC theories,then how can we solve it?2.2 Three kinds of solutionsI am aware of three broad approaches to untangling the cooperative dilemmaof culture.222.2.1 Route 1: The big stepThe first approach supposes that human culture was a fortuitous accident,the convergence of several other mature preadaptations. My impressionis that this is many non-experts? default model, though it has also beenproposed by careful thinkers (e.g., Pinker, 2010).Humans became bipedal, began using tools, developed language includ-ing specialised, localised cognitive adaptations, became quite intelligent anddeveloped many of the specialised cognitive adaptations psychologists aredocumenting today. All this happened, without any substantial accumula-tion of a cultural corpus (certainly not enough to warrant worrying aboutthe cooperative dilemma), during the five million years or so since we splitfrom other primates. Finally, during the last fifty thousand years or so, amature version of human culture emerged all at once, a consequence of theseother adaptations.In this scenario, there is no cooperative dilemma because culture doesn?tcoevolve slowly with genetics. It comes into existence full-blown after hu-mans are, more or less, anatomically and cognitively modern. We need notpuzzle over how selection favoured genes that promoted reliance on culturesimultaneously to selecting cooperative cultural content, because the geneticadaptations happened first and then culture came second. By the time cul-ture was on the table, humans were intelligent enough to reason their waypast the fitness trough of mutual exploitation to the distant fitness peakof mutual cooperation. This route out of the dilemma relies on us beingtoo smart to culturally exploit one another, smart enough to share culturefreely.I can understand why this is most people?s default argument, and whyit seems intuitive. Emerging evidence suggests that humans are intuitivedualists (Chudek et al., forthcoming), we think about our intentional, ra-tional human minds and our animalistic bodies as different (and potentiallyseparable) kinds of things. We intuitively imagine minds as inhabiting bod-ies. This makes it particularly easy to imagine that our gene-built brainsand bodies came first, and then our culture-shaped minds began inhabiting23them, fully-formed, afterwards.While I believe these accounts do not hold up to close inspection, thisdissertation is not the place for that argument (see Boyd et al., 2011b, for re-cent arguments to this end). Notice only that for such big-step explanationsto be plausible, they must specify a suite of adaptive benefits that carvedout a ?cognitive niche? (e.g., Pinker, 2010) and drove our metabolically costlybrain expansion (Aiello & Wheeler, 1995; Kotrschal et al., 2013), but didnot do so for other species in our planet?s long history. They must also ex-plain what favoured our fantastic penchant for language, which children notexposed to a language-community seemingly develop spontaneously (Sen-ghas et al., 2004), without invoking its advantages for the transmission ofcomplex, encoded information.Explanations that put culture first can do this parsimoniously?the adap-tive value of our accumulated cultural knowledge selects for brains ever bet-ter at accessing and using it. If we prefer this parsimony, we must pay forit by confronting the evil teacher problem.2.2.2 Route 2: The arms raceAn alternative is that, though teachers have always been incentivised to ex-ploit, learners have evolved cognitive counter-measures, ways of sifting thecultural wheat from the deceptive chaff. On this account, there is an evolu-tionary arms race between evil-teachers, whom evolution is shaping to sendbiased information, and sceptical learners. Learners may avoid exploitativecultural information by, for instance, preferring information that is backedby action (Henrich, 2009), averaging information between models (Boyd &Richerson, 1988) or imitating others? model choices (Henrich & Gil-White,2001).I find this solution more plausible but have several concerns. First, evenif learners are not manipulable, it is not obvious why teachers would trans-mit cultural information at all (though plausible solutions do exist, such asthe possibility that valued teachers accrue social benefits, termed deference;Henrich & Gil-White, 2001). Solving the second challenge merely exacer-24bates the first. It may be possible that a run-away evolutionary processcould navigate this trade-off. Learners have an advantage, then teachersdo, then learners, and so on. Cognitive adaptations for culturally exploitingand avoiding exploitation escalate quickly enough that it is always worthtransmitting ever more valuable cultural information. However I have notyet seen (or developed) any clear models of whether and how such a processcould work.On the empirical front, if our were species were situated at the cuttingend of such an arms-race, we ought to be suspicious learners and shrewdlymanipulative teachers. Instead, when it comes to sharing cultural informa-tion, we are both credulous and honest. We happily send our children toschools where they diligently learn from often under-paid, selfless strangers.Children (Lyons et al., 2007; Whiten et al., 2009) and even adults (McGuiganet al., 2011) dutifully follow the strange and seemingly pointless instruc-tions of strangers, even strangers who are patently from exotic out-groups(Nielsen & Tomaselli, 2010). Children even go out of their way to enforcerules learned from strangers on others (Rakoczy et al., 2009). Infants delib-erately make patently incorrect choices when strangers suggest them witheven very subtle pedagogical cues (Top?l et al., 2008). We even find it hardto distinguish strangers? subtle suggestions from our own memories (Loftus& Palmer, 1974), and infants trust knowledgeable strangers over their ownmothers (Stenberg, 2009).These high levels of trust contrast starkly with children?s impressiveselectivity in choosing between potential social models. They prefer, forinstance, to learn from their more confident (Birch et al., 2009), previouslyknowledgeable (Birch et al., 2008), self-similar (Buttelmann et al., 2012)and prestigious (Chudek et al., 2012) peers (see Chudek et al., 2013a, for arecent review). This suite of learning behaviour is more likely a product of aselective environment where communities shared knowledge freely, honestlyand cooperatively children?s dilemma was distinguishing the higher qualitymodel, than an arms race between Machiavellian deception and lie-detecting.252.2.3 Route 3: The ratchetA third possibility is that some co-evolutionary process ratcheted up humancooperation and culture simultaneously. This ratchet would start from smallamounts of culture, little and simple enough that its transmission wouldnot generate a cooperative dilemma. This early culture would generateevolutionary dynamics that sustained cooperation in the ways required tosustain more complex culture, which would sustain more cooperation andso on.There are many possible ways that such culture-cooperation ratchetscould have worked. For instance, one could posit that teaching began pri-marily among kin (Fogarty et al., 2011), allowing enough cultural sophistica-tion to accumulate that complex cooperation sustaining mechanisms couldcome into play and allow broader information sharing. Or perhaps earlyteaching was promoted by its utility in improving the return of mutualisticendeavours like hunting (see Sterelny, 2012, for one such account).Alternatively, culture could have given rise to new strategic niches (e.g.,prestigious leaders Henrich & Gil-White, 2001) or new learning strategiessuch as conformism (Boyd & Richerson, 1988; Henrich & Boyd, 2001) and?credibility enhancing displays? (Henrich, 2009) which changed the nature ofthe cooperative dilemmas faced by our ancestors.I am keen to promote a clearer understanding of the cooperative dilemmaof culture, and to see the many plausible solutions proposed, formalised,debated and evaluated. To help drive this process forward, here I will presenta novel proposal which uses reputation to kick off the ratchet by solvingthe cooperative dilemma in a way that selects for conformity to arbitrary,culturally evolving norms.Contemporary interactions between cooperation and cultural learning,especially non-concious behavioural imitation, give prima facie grounds tosuspect that they have a long and intertwined evolutionary history. Peoplewho are imitated by others tend to act more prosocially afterwards, bothadults (for reviews of this extensive literature, see Chartrand & Bargh, 1999;Chartrand & van Baaren, 2009; Lakin et al., 2003) and children (Carpenter26et al., 2013). Also, children are more likely to trust information learnedfrom individuals who have imitated them (Over et al., 2013). Reciprocally,people who are motivated to affiliate with others?for instance, those whohave been ostracised (that is, excluded from the benefits of their peers?sociality)?respond by imitating others more. Again, this is true of bothadults (Chartrand & van Baaren, 2009; Lakin et al., 2008, 2003; Leightonet al., 2010) and children (Over & Carpenter, 2009).In chapter 3, I argue for the plausibility of a previously unconsideredratchet: Negative Indirect Reciprocity (NIR). NIR explains how, if smallamounts of cultural learning brought proto-reputations into existence, com-munities could have coordinated their opportunities to exploit others in away that enforced their shared social norms. The existence of such community-enforced norms, in turn, could support more sophisticated, institution-basedforms of cooperation, facilitating the emergence of a complex, cooperativecultural corpus.In the next chapter I present the mathematical theory that articulatesNIR in a way that is accessible to psychologists. I focus on deriving clear,testable predictions about contemporary psychology. In the subsequentchapters, provide empirical tests of these predictions. In chapter 4, I surveypeople?s actual reputational intuitions and compare them to the predictionsmade by indirect reciprocity theory, including NIR. In chapter 5, I present agenuinely novel test of NIR. I test its fit to a recently observed psychologicalphenomenon that it was not designed to explain.27Chapter 3Negative indirect reciprocityThe puzzling origins of both human cooperation and cultural learning arelikely intertwined. Some aspects of human cooperation are shared with otherspecies and were likely shaped by the same kinds of distal pressures (e.g.,kin-based sociality; Daly & Wilson, 1988; Hamilton, 1964; Park et al., 2008;Smith, 1964; Stewart-Williams, 2007). Other aspects seem peculiar to hu-mans, such as queuing, paying taxes, and sacrificing to all-powerful deities(Norenzayan & Shariff, 2008). Formal models of how such cooperation-sustaining institutions emerge and persist typically presuppose that we area highly cultural species. For instance, important models assume that in-dividuals can readily coordinate their cognitive representations related toidentifying who is a deserving ?recipient? and a responsible ?donor? (Boydet al., 2010; Leimar & Hammerstein, 2001; Panchanathan & Boyd, 2004),that people establish abstract institutions (Sigmund et al., 2010) and knowhow to interpret one-another?s signals of cooperative intention (Boyd et al.,2010).These assumptions imply a deeper puzzle, since cognitive capacities forsophisticated cultural learning themselves pose a cooperative dilemma. Theyimply that natural selection favoured mutations that relaxed our genome?scontrol over its phenotype, and allowed fitness-relevant behaviour to beshaped by cultural information (Richerson & Boyd, 2004) acquired fromunrelated conspecifics. For this to be plausible, something must ensure that28the information acquired from others is, on average, fitness-enhancing, espe-cially if large, metabolically expensive brains are required to access it (Aiello& Wheeler, 1995).But the more influence culturally-learned information has on one individ-ual?s behaviour, the greater the selection pressure for others to exploit thatdependence by distorting the information they transmit to their own ben-efit. At first, many learnable phenotypes (e.g., stone tools use techniques)may have been hard to conceal or distort. However as soon as culturalknow-how became complex enough that it required language or pedagogy(Csibra & Gergely, 2009) for transmission, lying to exploit trusting othersbecame cheap and almost limitless in its potential for lucrative deceptions(Henrich, 2009; Lachmann & Bergstrom, 2004). This ?cooperative dilemmaof culture? is exacerbated by the fact that cultural information changes farmore quickly than genetic information, making it unlikely that genetically-evolved intuitions alone could distinguish useful from exploitative culturalknowledge. Before language and the cognitive capacities for coordinatingcomplex cultural institutions could have emerged, some mechanisms oper-ating on the same timescale as cultural change must have reliably sustainedthe quality of the public good that is our shared corpus of adaptive culturalknow-how.To tackle this puzzle, I ask how mechanisms that rapidly ensure co-operation in arbitrary domains (e.g., hunting, sharing information, trade)can get off the ground without pre-existing capacities for socially coordi-nating complex institutions and cognitive representations. One promisingpossibility are models of ?indirect reciprocity? (IR). Prima facie most IRmodels merely assume that (a) individuals have opinions of one another,(b) that these opinions influence how they treat each other and (c) thatcommunities somehow synchronise these opinions. These synchronised opin-ions are called ?reputations?. Once reputations exist they can catalyse theemergence of more complex forms of cooperation (Chudek & Henrich, 2011;Panchanathan & Boyd, 2004).Since many primates form coalitions with non-kin (Higham & Maestrip-ieri, 2010; Langergraber et al., 2007; Perry & Manson, 2008; Silk, 2002;29Watts, 2002), the first two assumptions typical of IR models are plausiblypreadaptations in our phylogenetic lineage. The third assumption impliessome social coordination and suggests a cooperative dilemma of culture. Onecould accrue many fitness benefits by strategically manipulating reputations.However it is also plausible that early, pre-verbal reputations were trans-mitted by observing others interactions (i.e., rather than gossip) and couldnot be easily distorted. Cognitive biases initially evolved to increase thequality of general social learning (e.g., Boyd & Richerson, 2005; Henrich,2009; Henrich & Gil-White, 2001; Laland, 2004; Nakahashi et al., 2012),may have incidentally also caused the transmission of social opinions (whichare, after all, just another type of cultural information) bringing reputationsinto existence. If early cultural learners closely monitored one-another?s di-etary, foraging or tool-use preferences, they may have picked up preferencesconcerning community members too.However, even if we grant the plausibility of the third assumption, ex-isting IR models implicitly assume an even stronger form of cultural coordi-nation. Framed in the context of reciprocal helping, these models supposethat sometimes someone has an opportunity to help but does not, and thattheir reputation worsens due to their inaction. This seemingly innocuous as-sumption implies that their peers somehow coordinate their representationsof both the abstract opportunity to act, and the significance of inaction.This is a sophisticated cognitive feat. It is especially impressive if we as-sume it emerged early enough to sustain the diverse, cooperative culturalcorpus that allowed an African primate species to spread across the globe.Noting this issue, Leimer and Hammerstein write that IR models assume?a reasonably fair and efficient mechanism of assigning donors and recipi-ents?a well-organised society, with a fair amount of agreement between itsmembers as to which circumstances define the roles of donor and recipi-ent.?(Leimar & Hammerstein, 2001). Subsequent IR models have mirroredthese assumptions without concern for their limitations.Here I fill the gap between the emergence of human culture, cooper-ation and reputations by showing how IR can get off the ground withoutassuming coordinated reactions to ?inaction?. Our model assumes that inac-30tion never changes reputations and demonstrates that even so IR can formthe substrate of more complex forms of cooperation. In fact, our modelis grounded in a relatively modest assumption about early cognition: thatindividuals disliked (i.e., worsen their reputational representation of) thosewho actively and observably exploited someone they liked (i.e., those witha good reputation).For several reason I focus on ?negative cooperative dilemmas? where ?de-fecting? means gainfully exploiting someone and ?cooperating? means seeingsuch an opportunity to exploit someone but passing it up (?doing nothing?).Substantial positive cooperation presupposes negative cooperation:Before more complex forms of mutual aid, defence and helping emerge,the ubiquitous opportunities to exploit each other (particularly, theold, weak and injured) must be brought under control. Otherwise, ex-ploitation and cycles of revenge will undermine positive cooperation.Positive cooperation exacerbates the negative dilemma(but not the reverse):The mutual aid of positive cooperation can create an abundance ofexploitable resources, both tangible (e.g., food caches) and intangible(e.g., trust). If cooperation has not first been stabilized in negativedilemmas, exploitation can quickly sap these benefits, sabotaging theviability of positive cooperation.Escalating returns: Prior to the emergence of complex institutions likemoney and debt, if an individual with a good reputation is helpedmultiple times (i.e., by multiple peers) they typically experience dimin-ishing marginal returns. A little food when you are starving providesa huge benefit; a lot of food when you are full provides only a smallone. On the other hand, repeated exploitation (e.g., stealing someone?sresources) can put victims in an ever more desperate situation withballooning fitness consequences. This suggests negative dilemmas mayhave generated steeper selection gradients earlier in our evolutionaryhistory, and so had more influence on the direction of evolution.31Built-in individual-level motivation: In a positive cooperative dilemmawith unobservable inaction (or lack of sufficient agreement about whatconstitutes ?inaction?), an individual?s reputation can endogenouslyrise (by observably helping) but not fall. Though an individual?s rep-utation might fall accidentally, selection will never favour individualswho take deliberate costly actions to worsen their reputation. Recip-rocally, negative dilemmas generate selective pressure for individualsto take deliberate, costly actions to improve their reputation. Positivedilemmas can?t accomplish this until sufficiently complex cultural in-stitutions or cognitive abilities establish agreement about what consti-tutes ?inaction?. This creates a chicken and egg situation for positivedilemmas, since substantial cooperation is required before sophisti-cated cultural-cognitive abilities can emerge.Relevance to culture: The cooperative dilemma of cultural learning, themain hurdle to more sophisticated institutional forms of cooperation,is a fundamentally negative dilemma. Individuals must pass up op-portunities to gainfully deceive their credulous conspecifics.Preadaptations are more plausible: Negative dilemmas are not sym-metric with positive cooperative dilemmas because they require thatindividuals notice, cognitively represent and respond to opportunitiesto profit by exploiting others, while positive cooperation requires theyrepresent opportunities to pay costs to help others. The former abili-ties were likely better, earlier in the culture-cooperation coevolutionaryprocess, since they yield direct, self-interested gains.Contemporary humans are more sensitive to harm than helping:Harmful or aversive actions, events or stimuli are more likely to haveeffects, and typically have stronger effects on contemporary humansthan their positive or beneficial counterparts (for extensive and influ-ential reviews, see Baumeister et al., 2001; Cacioppo & Berntson, 1994;Rozin & Royzman, 2001). This pattern recurs across the gambit of hu-man cognition, from sensation, to the experience of emotions and their32effect on cognitive processing, to trajectories of learning, to memory,impression formation, and the effect of feedback on self-perception. Ofparticular relevance is that negative information (i.e., about other?sharmful acts) seems to have a far more potent effect on diminish-ing someone?s reputation than positive information has on restoring it(Fiske, 1980; Rozin & Royzman, 2001; Skowronski & Carlston, 1987).Early antecedents of this negativity bias may even be apparent amongthree-month-old infants (Hamlin et al., 2010). In fact, people are morelikely to judge that someone caused, and intended to cause, a negativeoutcome than a corresponding positive one, even if their actual actionwas identical (Knobe, 2003, 2010). The ubiquity of negativity biases incontemporary cognitions suggests they run deep and may have ancientevolutionary roots. If our ancestors were as negativity-biased as weare, the impact of negative cooperative dilemmas may dwarfed positiveones in determining the long-run distribution of their reputations.Contemporary humans are more sensitive to harm by commissionthan harm by omission:Contemporary humans tend to condemn others moral transgressionmore severely (Baron & Ritov, 2004; Cushman et al., 2006; Sprancaet al., 1991) when they are the result of deliberate actions (commis-sions, which play a central role in NIR), than if they are the conse-quence of an equally intentional inactions (omission, which are absentfrom NIR). Correspondingly, people seem less-disposed to transgressby commission than omission (Ritov & Baron, 1999), especially if theymight be punished by others (DeScioli et al., 2011). These effects,which seem peculiar to negative commissions (Spranca et al., 1991)not positive ones, support NIR?s emphasis on negativity cooperationby commission alone.3334.Opportunityto actOpportunityto exploitVictim hasgood rep-utationExploit(Inflict d-amage, earn t-akings,reputation worsens)sDo nothing(Nothing changes)1? sVictim hasbad reputation Exploit(Inflict d-amage, earn t-akings)1??Opportunityto improvereputationCostly chanceto improvereputationvDo nothingPeers disappointed(Reputation worsens)?Peers apathetic(Nothing changes)1??1? v1??Costless exogenous reputation improvement(Reputation improves)??Pay for reputation improvement (volunteering)(Pay costs (k), reputation improves)NIR-P: ? = 1; NIR-V: ? = 0;NIR-M: ? = 1Evolving variables: v,sParameters: ? ,? ,?Consequences: d, t,k35Figure 3.1 (preceding page): The NIR decision tree. The probability of each branch is described byblue parameters and green variables (v: evolving disposition to pay reputationimprovement costs; s: evolving disposition to exploit victims with good and badreputations). Red text at terminal nodes describes the consequences of eachoutcome.ModelsTo help resolve the puzzle of early human cooperation I unpack three stagesof complexity that emerge from a more general model of Negative IndirectReciprocity (NIR). These insights follow from two convergent thought exper-iments. One possibility is a ?discrete strategy? perspective, where we imagineinteractions between very different kinds of individuals such as those whoalways cooperate with well reputed individuals (reputation-conditional coop-erators; RepCoop) and obligate defectors (Exploiter). An alternative isa ?continuous disposition? perspective (based on the successive invasions as-sumptions of Adaptive Dynamics (Geritz et al., 1997; Waxman & Gavrilets,2005)), where we imagine communities of individuals who share very similar,perhaps genetically endowed, dispositions to cooperate. In either case, wecan reason formally about what kinds of individuals would be favoured byselection, and both perspectives lead to similar general conclusions.Here I summarise these key qualitative insights and feature the succinctbut informative discrete strategy invasion criteria: the conditions underwhich obligate defectors (Exploiter) cannot invade a population of obli-gate cooperators (RepCoop). Figure 3.1 depicts the logic of these models.The Mathematical Model section below contains full details.Imagine a single, large population of individuals who each have a ?reputation??a community-wide opinion that influences others? behaviour?which can beeither ?good? or ?bad?. I represent this reputation as a stochastic variablewhose stationary distribution is the probability of being ?good? on average.During their lifetimes these individuals encounter two kinds of oppor-tunities. Sometimes (with frequency 1??) they notice a way to exploit aconspecific, yielding some takings (t) to the exploiter while damaging (d > t)their target. This situation is error-prone: sometimes well-meaning individu-als accidentally exploit (probability ?), and sometimes exploitation attemptsfail (probability ?). By assuming accidental exploitation is vanishingly rare(? ? 0), I present simplified expressions that preserve the model?s essentialinsights as long as ? remain small(? ? 120). The mathematical model sectionbelow provides the full expressions and robustness analyses.36I assume that individuals tend to dislike those who exploit someonethey like. That is, exploiting someone with a good reputation causes one?sown reputation to worsen. However I assume that forgoing opportunitiesto exploit (i.e., cooperating by inaction) carries no consequences. Assumingotherwise would imply that individuals were recognizing that opportunitiesto exploit existed, assessing that another individual noticed them as well,coordinating their reactions to these counterfactuals as a community, andso on.Consequently, not-exploiting badly-reputed individuals only ever yieldscosts and that poorly reputed individuals are always exploited. In this simplemodel, which focuses on active exploitation, unconditional cooperators neverprosper.Individuals also have opportunities to improve their reputation (withprobability ?). My first model?Pure Negative Indirect Reciprocity (NIR-P)?assumes that such improvement is costless and exogenous. Our earliestreputation-using ancestors had no awareness of their own reputation norhow to improve it. However their reputations may still have improved atrandom after some time, perhaps because their peers had limited memoriesand eventually forgot their old gripes or because they stumbled upon a non-excludable food resource that their peers gratefully shared.All the models presented here, including NIR-P, are bistable. They havean uncooperative equilibrium?where selection favours exploiting anyonewhenever the chance arises?and a cooperative equilibrium?where selectiondisfavours exploiting well-reputed individuals. At NIR-P?s cooperative equi-librium, a population of individuals who never exploit well-reputed peers(RepCoop) have, on average, higher fitness than rare individuals who al-ways exploit everyone, so long asExploitation inefficiency????td 0)makes this inequality harder to satisfy by making cooperators? reputationsslightly worse on average, but does not change these qualitative insights(the details of this possibility are spelled out in the ?Mathematical Model?section, below).Figure 3.2 shows the population frequency of reputation-respecting RepCoopneeded before selection favours more cooperation. When opportunities forexploitation are far more common that opportunities for reputation improve-ment (? is small) and exploitation is inefficient ( td is small), a few cooper-ators are enough to trigger a cascade of ecological interactions that lead toa world where only poorly reputed individuals are exploited. A convergentresult under a ?continuous disposition? perspective implies that, under thesecircumstances, selection will mould a population only slightly ill-disposed toexploit their better-reputed peers, into highly reputation-sensitive individu-als loathe to exploit those with good reputations.A key challenge for models of cooperation is explaining how a speciesinitially composed of uncooperative individuals could arrive at the cooper-ative equilibrium?s basin of attraction. Here NIR has an easier time thanmost other approaches. It is plausible that preadaptations for friendship,coalition-formation and direct reciprocity gave early reputation-users someproclivity to dislike those who harmed their allies before social learning be-came strong enough to coordinate individual opinions into community-widereputations. That is, this evolving system may have started within its coop-erative basin of attraction, particular if inefficient exploitation opportunities(low td ) were plentiful (low ?).Assume that the reputation-sensitive communities described by NIR-P did emerge. As reputations came to carry great fitness consequences,38.0.0 0.4 0.80.00.20.40.60.81.0?Locationofunstableinternalequilibrium0.0 0.4 0.80.00.20.40.60.81.0?ProbabilityofhavingagoodreputationFigure 3.2: NIR-P basins of attraction and equilibrium reputations.The location of the internal unstable equilibrium that dividesNIR-P?s cooperative (above the lines) and uncooperative basinsof attraction (left panel); and the equilibrium reputations (rightpanel) of cooperative RepCoop and Miser (higher, red lines)and uncooperative Exploiter (lower, blue lines) for td = 0.1(darkest lines), 0.5 and .0.8 (lightest lines). All errors (?,? ,?)set to 120 . When the proportion of non-exploiters is above thethreshold demarked in the left panel, selection, on average,favours even less exploitation (i.e., more cooperation).39selection could begin to favour individuals who noticed costly opportunitiesto improve their reputation and were disposed to act on them. For instance,they might chose to share a resource they could have kept to themselves tomake their peers? sentiments towards view them more favourable. To modelthis I assume that if an opportunity to improve one?s reputation occurs(?), it is sometimes costless and exogenous (probability ?), and sometimes(1??) requires the individual to pay a deliberate cost (k). For brevity, I callthis ?volunteering?, since the most interesting cases are those in which thesecosts raised reputations by contributing to others? fitness. These error pronevolunteering attempts sometimes fail (probability ?), but are still costly. Icontinue to assume that these early reputation-users could not coordinatereactions to inaction, and so ?not volunteering? carries no consequences forreputations. NIR-P is a special case of this broader model (i.e., where ? = 1).My next model?Voluntary NIR (NIR-V)?extends NIR-P by askingjust how much costly volunteering the threat of reputation-based exploita-tion can sustain. I consider two distinct cooperative strategies; both neverexploit well-reputed peers, but one always volunteers (RepCoop) and theother never does (Miser). In the formal model below I show that RepCoophave an advantage over Miser when exploitation is inefficient ( td small), op-portunities for reputation improvement are relatively rare (? small), costlyopportunities relatively plentiful compared to costless exogenous improve-ment (? small) and these costs are not too great ( kd small). Here I show thecondition for a cooperative, volunteering population (RepCoop) to do bet-ter than a rare, uncooperative, un-volunteering mutant (Exploiter). Thisis easiest to express in terms of the long-run probability that each strategywill be well-reputed (pi):pinirvRepCoop = 1pinirvExploiter =2??2??+(1??)(1??)td < (pinirvRepCoop?nirvExploiter)?kd?1??2(1??)(1??)40The first term on the right again represents the difference between co-operators? and defectors? equilibrium reputations. Now a second term ex-presses the additional burden of costly reputation improvement. In general,this condition can be satisfied so long as the costs of contributing are not toogreat ( kd is small) and opportunities to improve reputations are infrequent(? ,? is small).Continuous disposition perspectives on NIR-V models (see mathematicalmodel, below) suggest that, if intermediate dispositions to contribute arepossible they will be favoured by selection under NIR-V. Selection favourscontribution rates that balance the costs of reputation improvement againstthe benefits of sometimes gainfully exploiting others.To see why NIR-V is important, consider what ?volunteering? represents.Among a reputation-using community, selection favours doing whatever ittakes to improve your reputation, up to a certain cost (k). This could includeresource sharing, grooming, or chasing pests away from shared resources, butalso includes conformity to others? preferred behavioural standards and imi-tation of the best-reputed individuals. This selective pressure for conformityto whatever pleases one?s community could help sustain more sophisticatedforms of socially coordinated cooperation. NIR-V provides a plausible cog-nitive foundation for the emergence of ?social norms? (Chudek & Henrich,2011). Under NIR-V adhering to norms is rewarded, with a higher reputa-tion, but failing to is not punished.NIR-V also describes plausible cognitive and socioecological precondi-tions for the emerge of coordinated responses to inaction.In societies at NIR-V?s cooperative equilibrium?where individuals aredisposed to perform costly to please their peers?as individuals becomes evermore attentive to their own opportunities to volunteer they might also noticeand respond to others? volunteering opportunities. If volunteering typicallypleases peers, these more reputation-savvy communities may (with proba-bility ? ) be disappointed when someone pass up a volunteering opportunity,causing their reputation to worsen.Such reputation loss is not a deliberate attempt to punish deviance, it isan emergent consequence of prior selection for cognitive systems that attend41to volunteering opportunities. Nevertheless, since low reputations lead toexploitation by many peers, this disappointment coordinates community-wide sanctioning of failures to perform commonly expected behaviours.My final model?Mandatory NIR (NIR-M)?asks how interactions changeas volunteering gradually becomes a norm sanctioned by reputation loss(? ? 1). Now NIR-V is a special case (i.e., where ? = 0). At NIR-M?scooperative equilibrium, obligate cooperator-volunteers (RepCoop) resistinvasions by obligate defector-nonvolunteers (Exploiter) whenpinirmRepCoop =1??(1??)1??(1?? )(1??)pinirmExploiter =2??2??+2??(1??)+ (1??(1??))(1??)(1??)1??(1?? )(1??)td