Past Seminars

Abstract.
Behavioral economists have proposed that incentive contracts result in higher productivity when bonuses are “loss framed”—prepaid then clawed back if targets are unmet. We test this claim in a large-scale field experiment. Holding financial incentives fixed, we randomized the pre- or postpayment of sales bonuses at 294 car dealerships. Prepayment was estimated to reduce sales by 5%, generating a revenue loss of $45 million over 4 months. We document, both empirically and theoretically, that negative effects of loss framing can arise due to an increase in incentives for “gaming” behaviors. Based on these claims, we reassess the common wisdom regarding the desirability of loss framing.

Abstract.
Five studies (N=3,526) reveal that willingness-to-pay (WTP) reflects perceived market price rather than personal valuation. Moreover, people tend to indicate WTP for the goods as if they were in the market for those goods, even when those goods are personally irrelevant (e.g., steak for vegetarians). We demonstrate that these market related characteristics of WTP explain some of the well documented anomalies such as preference reversals. Furthermore, merely highlighting that a WTP of $0 indicates not wanting to buy attenuates these anomalies. This research offers a novel interpretation for research using WTP anda simple intervention that shifts WTP closer to personal valuation.

Abstract.
Are two heads better than one, or do too many cooks spoil the broth? Although researchers have generated a large number of nuanced answers to this question, they have had little success specifying the range of conditions for which a given answer applies. I argue that one of the keys to solving the puzzle is to better understand the underlying nature of the tasks being performed. Because no clear language exists to describe tasks in a way that allows for straightforward comparisons across studies, the role of task characteristics remains poorly understood. I will present an idea for developing a comprehensive, empirically grounded theory of group tasks using high-throughput, adaptive experiment design.

Abstract.
An influential research tradition argues that the US media’s effects on voter preferences either are minimized by selective exposure or operate through subtle mechanisms. Using behavioral data from a media company on household-level television viewership, we recruited heavy consumers of Fox News to a field experiment in late 2020. We first document that heavy Fox News viewers are homogeneously conservative Republicans. During September 2020, we incentivized a randomized treatment group to instead watch CNN. At the end of the incentivized period, we find that changing the slant of participants’ media consumption had profound effects on: 1) factual beliefs. The treatment group was less likely to harbor misperceptions about COVID-19, vote-by-mail, and protests and policing, and more informed about Trump and Biden’s positions on them. 2) personal views and policy preferences. 3) issue importance. The treatment group saw COVID-19 as more important and efforts to quell protests as less important. 4) overall political views. The treatment group was much less approving of Donald Trump and Republicans generally. 5) attitudes towards the media. The treatment group evaluated Fox News more negatively and was more likely to state that it conceals negative information about Trump. However, many of these results decayed after the experiment ended and participants returned to their previous media diet. Our results are consistent with partisan coverage filtering impacting viewers’ opinions: partisan media filters which information it presents to an audience that cannot readily infer the contents of filtered information, resulting in changes in their factual beliefs, issue preferences, and evaluations of elected officials.

 

Abstract.
We propose that decisions under risk often generate a consequential outcome that has been overlooked in the literature – error. Specifically, when prospects are tied to future states of the world (e.g., win $5 if horse #6 wins the race), risky decisions necessitate selecting a future state of the world. As a result, choosing among prospects generates error – the difference between the chosen and realized future state of the world. In 7 studies (N = 5,187), we find that people systematically value error and that they take more risk when their decisions generate error. These results suggest that error is a missing component in current theories of decision making under risk and that failing to account for error can result in biases in these theories. We believe people’s sensitivity to error has especially important implications for our understanding of real-world risk preferences because prospects in real-world decisions under risk are almost always tied to future states of the world.

Abstract.
Across twelve studies using archival data, surveys, and experiments, we identify a novel factor that predicts gender differences in time stress and burnout. Across academic and professional settings, women are less likely to ask for more time when working under adjustable deadlines (Studies 1-4a). Women’s discomfort in asking for more time on adjustable deadlines uniquely predicts time stress and burnout, controlling for marital status, industry, tenure, and delegation preferences (Study 1). Women are less likely to ask for more time to complete their tasks because they hold stronger beliefs that they will be penalized for these requests and worry more about burdening others (Studies 1-2d). We find no evidence that women are judged more harshly than men (Studies 3-5). We also document a simple organizational intervention: formal processes for requesting deadline extensions reduce gender differences in asking for more time (Studies 6a-7).

Abstract.
Hypotheses involving interactions, where one variable modifies the association between another two, are common in experimental and observational social science. Interactions are typically tested relying on models that assume effects are linear, e.g., with a regression like y=ax+bz+cxz. In the real world few effects are linear, invalidating inferences about interactions. For instance, in realistic situations, the false-positive rate for an interaction can be 100%. The sign of the interaction can be wrong with certainty. And results from probing the interaction estimates, where one computes the effect of interest for different levels of the moderator, can be entirely disconnected from reality. This paper proposes a revised toolbox for studying interactions which is curvilinear-robust, giving correct answers 'even' when effects aren't linear. It's applicable to most study designs, while introducing minor modifications to current analytical and reporting practices. The presentation combines statistical intuition, examples of published results, and simulations.

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Abstract.
In several countries, individuals have multiple opportunities to join the organ donor registry. In Ontario, Canada, for example, one can register when visiting a branch of ServiceOntario, the agency of the Ministry of Government and Consumer Services, which provides a single point of contact for most government services in the province such as driver’s license or health card issuance and renewal. However, registration rates are still below the desired level in Ontario. In collaboration with ServiceOntario, the organ and tissue donation agency of Ontario (TGLN), and the Behavioral Insight Unit at the provincial Treasury Ministry, we conducted a natural field experiment to study the effects of providing absolute and relative performance feedback to customer service representatives (CSRs). We ran the experiment in three waves over two years (2017-2019) with all government-owned 80 branches in the Province to either a baseline condition consisting of an email sent to CSRs to encourage them to ask clients if they would like to join the organ donor registry, or to one of two performance feedback interventions. The first intervention treatment added to the baseline e-mail information about the number of new registry members (per hundred transactions) that the CSR had signed up in the previous six months. The second treatment included, in addition to the CSR’s individual signup performance, the average signup rate in the region the branch belonged to and the performance at the 80th percentile in the region. Overall, providing performance feedback (no matter if only individual signup performance or also average and 80th percentile reference performances) resulted in a significant increase in daily signups compared to encouragement alone. The effects were particularly strong in the few weeks immediately following receipt of a treatment email, but a substantial effect persisted for several months.

Abstract.

Behavioral science and experimentation have the potential to inform policy, but discrepancies in intervention effectiveness across evaluations could make policymakers question the scalability of empirical findings. In this talk, I will offer insights that contribute to explain some of these discrepancies by leveraging data from two pre-registered randomized controlled trials (RCTs) testing the impact of nudges on COVID-19 vaccine uptake. In February-April, 2021, we delivered interventions via text to people one day (first RCT; N=187,134) and eight days (second RCT; N=149,720) after they received notification of vaccine eligibility from their healthcare provider. I will share key lessons gleaned from this research focusing on three questions. First, how do our interventions affect vaccinations across different outcome measures? Second, how does the efficacy of our interventions vary with people’ baseline motivation to act? Third, do hypothetical responses match behavior in the field? Altogether, this work advances our understanding of nudges’ impact and limits, helps reconcile divergent effects documented across evaluations, and provides implications for evaluating the scalability of RCT results.

Dispersion knowledge—the beliefs that consumers have about the minimum, the maximum, and the overall variability of values in a distribution—is a key antecedent of many judgments and decisions. In this talk, I will present the results of multiple studies examining people’s ability to form accurate dispersion knowledge. I will first describe a phenomenon we call dispersion spillover: Seeing more (vs. less) dispersed prices in one category inflates people’s perception of price dispersion in another category. I will then highlight marketplace implications of this dispersion spillover, and present evidence that it can influence judgments of price attractiveness, the likelihood that people will search for (and find) better options, and how much people bid in auctions. Finally, I will discuss what this bias reveals about the mental representations underpinning dispersion knowledge.

In theory, when employees voice suggestions for organizational improvement, they should not only contribute to organizational success but also gain status. In practice, however, voicers can go unrecognized and underutilized. Previous research has largely looked to voicer-supervisor relationships to explain and rectify this issue. We investigate how employees can help peers get a status boost from voicing, while also raising their own status, by introducing the concept of amplification—public endorsement of another person’s contribution, with attribution to that person. In two experiments and one field study, we find that amplification enhances status both for voicers and for those who amplify voice. Being amplified was equally beneficial for voicers who framed their ideas promotively (improvement-focused) and prohibitively (problem-focused; Study 1), and for men and women (Study 2). Furthermore, amplified ideas were rated as higher quality than nonamplified ideas. Amplification also helped amplifiers: participants reading experimentally manipulated meeting transcripts rated amplifiers as higher status than those who self-promoted, stayed quiet, or contributed additional ideas (Studies 1 and 2). Finally, in an intervention in a nonprofit organization, select employees trained to use amplification attained higher status in their work groups (Study 3). In all, these results increase our understanding of how social actors can capitalize on instances of voice to give a status boost to voicers who might otherwise be overlooked, and help organizations realize the potential of employees’ diverse perspectives.

Mistrust of scientific evidence and government-issued guidelines is increasingly correlated with political affiliation. Survey evidence has documented skepticism in a diverse set of issues including climate change, vaccine hesitancy, and, most recently, COVID-19 risks. Less well understood is whether these beliefs alter high-stakes behavior. Combining GPS data for 2.7 million smartphone users in Florida and Texas with 2016 U.S. presidential election precinct-level results, we examine how conservative-media dismissals of hurricane advisories in 2017 influenced evacuation decisions. Likely Trump-voting Florida residents were 10 to 11 percentage points less likely to evacuate Hurricane Irma than Clinton voters (34% versus 45%), a gap not present in prior hurricanes. Results are robust to fine-grain geographic controls, which compare likely Clinton and Trump voters living within 150m of each other. The rapid surge in media-led suspicion of hurricane forecasts—and the resulting divide in self-protective measures—illustrates a large behavioral consequence of science denialism.

 In the past decade, behavioral science has seen the introduction of beneficial reforms to reduce false positive results. Serving as the motivational backdrop for the present research, we wondered whether these reforms might have unintended negative consequences on researchers’ behavior and emotional experiences. In an experiment simulating the research process, Study 1 (N=449 researchers) suggested that engaging in a pre-registration task impeded the discovery of an interesting but non-hypothesized result. Study 2 (N=404 researchers) indicated that relative to confirmatory research, researchers found exploratory research more enjoyable, motivating, and interesting; and less anxiety-inducing, frustrating, boring, and scientific. These studies raise the possibility that emphasizing confirmation can shift researchers away from exploration, and that such a shift could degrade the subjective experience of conducting research. Study 3 (N=314 researchers) introduced a scale to measure “prediction preoccupation”—the feeling of heightened concern over, and fixation with, confirming predictions.

Self-correction is commonly praised as a strength of the scientific method: Over time, errors will be detected, corrected, and replaced by more accurate results. Attractive in principle, the practical reality of trying to correct the scientific literature leaves much to be desired. In this talk, I discuss some techniques for identifying erroneous claims. I describe the responses from authors, universities, and journal editors, both helpful and unhelpful. I conclude with suggestions to help science live up to its promises of self-correction.

"Mercy killing” is an unproblematic concept when used to justify the active killing (euthanasia) of animals in extreme pain that would die anyway.  It seems humane because it alleviates suffering and is therefore in the animals’ best interests.  Do people similarly believe that actively killing humans in intractable, terminal pain is morally preferable to passively allowing them to die?  In this research, we document a pattern of perverse judgments in which active (vs. passive) killing is judged to be in the best interests of both human and animal sufferers, yet morally preferable only for animals.  Paradoxically, it seems that precisely because humans are judged to have especially high moral status, they are subject to moral decisions that violate their best interests.

We identify a consumer preference for information disclosure that is ultimately costly to consumers (a preference for costly disclosures). We examine the impact of additional (but in fact irrelevant) information in price disclosures, operationalized as price disaggregation (i.e., separating charges into multiple line items). Across a variety of products, we find: (1) most consumers prefer disaggregated, rather than consolidated, price disclosures; (2) disaggregated price disclosure can be harmful to consumers, as consumers are more likely to choose financially dominated options (higher priced but not higher quality) when presented with disaggregated price disclosures; and (3) these results are not artifacts of mismatched preferences, as consumers’ preferences for disclosure type are uncorrelated with the likelihood they choose financially dominated options. Furthermore, while consumers perceive disaggregated prices as more complex, they also tend to believe that disaggregation facilitates the selection of lower-price options and signals firm transparency. These results suggest that consumers perceive benefits from disaggregated price disclosures but also commit computational errors while believing they will not. In addition, these results identify consumer preferences as a novel factor enabling price shrouding, suggesting that firms could use disaggregation to shroud prices while signaling transparency and trustworthiness.

People’s estimates of unknown quantities tend to be higher after previously considering a high value (or “anchor”) than after considering a low value. Researchers attempting to explain this “anchoring effect” have emphasized how anchors often prompt people to engage in “insufficient adjustment,” whereby people adjust downwards (but insufficiently) from high anchors and upwards (but insufficiently) from low anchors. In our research, we find that people engage not only in insufficient adjustment, but often in wrong-way adjustments as well. The mere act of considering a high anchor leads people to entertain the possibility that the correct answer might be even higher, and the mere act of considering a low anchor leads people to entertain the possibility that the right answer might be even lower. As a consequence, anchors can lead people to adjust higher from high anchors and lower from low anchors, which, of course, increases the size of anchoring effects. In Study 1, we elicit both anchored and unanchored estimates of the same quantities from the same people, and we find that a sizable proportion of them – roughly 20% – adjust the “wrong way” from anchor values. In Studies 2 and 3, we find that this tendency is predictable. People are more likely to adjust upwards from high anchors for quantities that are intuitively large (e.g., the weight of an elephant) and to adjust downwards for small anchors for quantities that are intuitively small (e.g., the weight of a mouse). In Study 3, we further show that this effect has implications for consumer purchase decisions.

A primary goal of behavioral science is to collect true facts about people. If our experimental claims are true, then we should be able to make predictions about how people will behave. The easiest prediction to make is that people will behave similarly in a replication experiment as they did in the original. In this regard, replicability is our best proxy for the truth of a claim. I report two large projects designed to turn the lens of replication onto the subject of consumer research. In one (N = 17,481), replication experiments give a window into multiple potential threats to the validity of claims in consumer research, including that of non-replication. In another, we conduct many replications to develop and empirical audit of research on the psychological consequences of scarcity (N = 12,366). We identify which elements of that active literature are replicable, and which are not. We forward this empirical approach as an alternative to qualitative review or meta-analysis. Replications are a valuable and necessary tool for advancing behavioral and consumer sciences.

Due to the power of social influence, donors could amplify their impact by sharing about their donations. However, when deciding whether to tell others about their generosity, donors often overlook the social impact of sharing and instead focus on possible risks to their reputation (e.g., of seeming braggy, inauthentic). In a large pre-registered field experiment, we tested a brief post-donation intervention designed to encourage word-of-mouth by re-orienting donors to the social impact case for sharing. After donating, 80,679 donors to an education non-profit received either a control or a treatment message asking them to share a link to the cause via social media, text, or email. Compared to the organization’s standard solicitation (‘Please share your donation…’), our intervention emphasized the consequences of sharing for the cause (‘Your donation can start a chain reaction…’). This message increased click-through by 4.8%, likelihood of recruiting at least one later donation by 11.6%, and funds raised via social influence by 15.2% per donor treated. While many field experiments aim to increase donation rates or magnitudes, we show that thoughtful marketing can also exogenously influence word-of-mouth, and we discuss approaches for encouraging sharing in the domain of charity and beyond.

Rituals are ubiquitous in our personal lives – enacted before performances or during family holidays – and in our interactions with firms – from sports fans doing the “wave” to customers being served wine after an elaborate uncorking. Our research has documented the benefits of rituals in domains ranging from grief recovery to chocolate consumption to team performance to singing Journey’s “Don’t Stop Believing.” And, we have identified the psychological underpinnings of rituals, demonstrating how they can lead to increased immersion in experiences, greater feelings of control, reduced anxiety, and increased liking for teammates.

The Cognitive Reflection Test (CRT) allegedly measures the tendency to override the prepotent incorrect answers to some special problems, and to engage in further reflection. A growing literature suggests that the CRT is a powerful predictor of performance in a wide range of tasks. This research has mostly glossed over the fact that the CRT is composed of math problems. The purpose of this paper is to investigate whether numerical CRT items do indeed call upon more than is required by standard math problems, and whether the latter predict performancein other tasks as well as the CRT. In Study 1 we selected from a bank of standard math problems items that, like CRT items, have a fast lure, as well as others which do not. A 1-factormodel was the best supported measurement model for the underlying abilities required by all three item types. Moreover, the quality of all these items – CRT and math problems alike – as predictors of performance on a set of choice and reasoning tasks did not depend on whether or not they had a fast lure, but rather only on their quality as math items. In other words, CRT items seem not to be a “special” category of math problems, although they are quite excellent ones. Study 2 replicated these results with a different population and a different set of math problems.

In 2008, we proposed a simple 2-dimensional model, according to which faces are evaluated on perceived valence and power (Oosterhof & Todorov, 2008). A recent large cross-cultural replication (N = 11,481; 11 world regions; Jones et al., 2020) tested whether this 2D model generalizes to world regions. When the original analysis – principal components analysis (PCA) – was implemented, the model generalized across world regions. However, when an alternative analysis – exploratory factor analysis (EFA) – was implemented, it appeared that the model didn’t generalize. One disconcerting implication of this discrepancy is that whether one observers cross-cultural universality or not is a function of arbitrary analytic choices. However, an inspection of the input data (the pairwise correlations of judgments) to both PCA and EFA shows striking consistency across cultures. How is it that the same highly convergent input data lead to divergent analytic solutions? I discuss differences between PCA and EFA and well-known indeterminacies in EFA solutions. A principled approach that minimizes the role of statistical noise is to decide a priori on testing a 2D model and to align the data using a Procrustes rotation. When these procedures are implemented, the 2D model generalizes across cultures irrespective of analytic choices. Bootstrapping simulations show that this generalization is extremely unlikely to be an artifact of the rotation procedure. I argue that when analytic choices are properly specified, different analyses should converge in terms of broad claims about differences, similarity, and universality.

Does shame serve a moral function? Past work has addressed this question by looking at the intra-individual effects of shame. In the face of weak evidence that shame effectively regulates behavior in line with normative standards, pessimistic conclusions have been drawn about shame’s moral function. Rather than focusing on how shame affects the person who experiences it, we take a social learning perspective on shame. By focusing on the consequences of a person’s shame for other people who witness it, our findings suggest a more affirmative answer to the opening question. In a series of experiments, we show that people infer stronger injunctive norms against a workplace behavior, and report greater behavioral intentions to avoid the behavior, when they see someone feel ashamed in response to the behavior compared to a neutral emotion or anger. We further find that a target’s expression of shame in response to a novel behavior motivates other people to avoid this behavior, even when this avoidance carries a personal financial cost.  Finally, we find that expressing shame about a behavior can convey similar information about group norms as does being shamed by a third-party. Overall, these findings suggest that shame communicates information about a group’s values, thereby serving a critical role in socialization, norm acquisition, and behavior regulation.

We document a tendency to demean others’ needs: believing that psychological needs—those requiring mental capacity, and hence more uniquely human (e.g., need for meaning and autonomy)—are relatively less important to others compared with physical needs—those shared with other biological agents, and hence more animalistic (e.g., need for food and sleep). Because valuing psychological needs requires a sophisticated humanlike mind, agents presumed to have relatively weaker mental capacities should also be presumed to value psychological needs less compared with biological needs. Supporting this, our studies found that people demeaned the needs of nonhuman animals (e.g., chimpanzees) and historically dehumanized groups (e.g., drug addicts) more than the needs of close friends or oneself (Studies 1 and 3). Because mental capacities are more readily recognized through introspection than by external observation, people also demean peers’ needs more than their own, inferring that one’s own behavior is guided more strongly by psychological needs than identical behavior in others (Study 4). Two additional experiments suggest that demeaning could be a systematic error (Studies 5 and 6), as charity donors and students underestimated the importance of homeless people’s psychological (vs. physical) needs compared with self-reports and choices from homeless people. Underestimating the importance of others’ psychological needs could impair the ability to help others. These experiments indicate that demeaning is a unique facet of dehumanization reflecting a reliable, consequential, and potentially mistaken understanding of others’ minds.

New technologies in agriculture, reproduction, medicine, and elsewhere can provide significant social benefits, but may also pose significant risks. Consequently, it is important to understand which technologies will be adopted or rejected by the public and why. I first examine opposition to genetic engineering (GE) technology in the food domain. In surveys of Americans and Europeans representative of the population on gender, age, and income, pluralities or majorities were “absolutely” opposed—that is, they claimed that GE food should be prohibited no matter the risks and benefits. I discuss how these “absolutist” opponents differ from other opponents and supporters, and what kind of persuasion attempts they might respond to. I then discuss new research in which I examine underlying regularities in laypeople’s technology evaluations. I provide evidence for underlying regularities in technology evaluations, such that evaluations of superficially quite different technologies tend to cohere across individuals. Dimension reduction of people’s ratings of a wide range of technologies recovers three groups, which I label Contaminating, Playing God, and Mainstream. Attitudes towards these groups of technologies seem to result from different underlying intuitions that are associated with distinct individual differences.

The replication crisis in behavioral research concerns not only false-positives but also effects that turn out to be smaller than commonly understood. Why might scientists' perceptions of effect sizes be inflated? Much justified attention has been paid to p-hacking and file drawer effects. We test whether a third mechanism plays a role: the manner in which behavioral results are visually displayed. We present a series of studies about how people perceive treatment effectiveness when scientific results are summarized in various ways. We first show that a prevalent form of summarizing scientific results—presenting mean differences between conditions—can lead to significant overestimation of treatment effectiveness, and that including confidence intervals can in some cases exacerbate the problem. We next attempt to remedy these misperceptions by displaying information about variability in individual outcomes in different formats: explicit statements about variance, a quantitative measure of standardized effect size, and analogies that compare the treatment with more familiar effects (e.g.,differences in height by age). We find that all of these formats can substantially reduce initial misperceptions, and that effect size analogies can be as helpful as more precise quantitative statements of standardized effect size. Besides Jake and Dan, co-authors on this work

People obviously consume more of products they enjoy than products they dislike. However, when two products are both enjoyable, to what extent does people's relative preference for each product still drive their consumption amount? Across several studies of food and entertainment consumption, we find that, although people expect that their consumption amount will increase with increased liking of a product, actual consumption is surprisingly insensitive to their preferences. We propose that, because consumers' liking of a product is known, salient, and normative (“I should consume more of items I like more”), their predictions tend to focus on liking at the expense of other drivers of consumption, such as boredom, habit, and consumption opportunities.

People obviously consume more of products they enjoy than products they dislike. However, when two products are both enjoyable, to what extent does people's relative preference for each product still drive their consumption amount? Across several studies of food and entertainment consumption, we find that, although people expect that their consumption amount will increase with increased liking of a product, actual consumption is surprisingly insensitive to their preferences. We propose that, because consumers' liking of a product is known, salient, and normative (“I should consume more of items I like more”), their predictions tend to focus on liking at the expense of other drivers of consumption, such as boredom, habit, and consumption opportunities.

We explore how self-assessments respond to feedback about own ability across a range of tasks, with a particular focus on how gender stereotypes impact belief updating. Participants in our experiments take tests of their ability across different domains. Absent feedback, beliefs of own ability are strongly influenced by gender stereotypes: holding own ability fixed, individuals are more confident in gender congruent domains (i.e., male-typed domains for men, female-typed domains for women). We then provide noisy feedback about own absolute performance to participants and elicit posterior beliefs. Gender stereotypes have significant predictive power for posterior beliefs, both through their influence on prior beliefs, as predicted by the Bayesian model, but also through their influence on updating, a non-Bayesian channel. Both men and women’s beliefs are more responsive to information in gender congruent domains than gender incongruent domains. This is primarily driven by differential reactions to exogenously-received good news about own ability: both men and women react more to good news when it arrives in a gender congruent domain than when it arrives in a gender incongruent domain. Our results have important implications for understanding how feedback shapes, and perpetuates, gender gaps in self-assessments.

We explore how self-assessments respond to feedback about own ability across a range of tasks, with a particular focus on how gender stereotypes impact belief updating. Participants in our experiments take tests of their ability across different domains. Absent feedback, beliefs of own ability are strongly influenced by gender stereotypes: holding own ability fixed, individuals are more confident in gender congruent domains (i.e., male-typed domains for men, female-typed domains for women). We then provide noisy feedback about own absolute performance to participants and elicit posterior beliefs. Gender stereotypes have significant predictive power for posterior beliefs, both through their influence on prior beliefs, as predicted by the Bayesian model, but also through their influence on updating, a non-Bayesian channel. Both men and women’s beliefs are more responsive to information in gender congruent domains than gender incongruent domains. This is primarily driven by differential reactions to exogenously-received good news about own ability: both men and women react more to good news when it arrives in a gender congruent domain than when it arrives in a gender incongruent domain. Our results have important implications for understanding how feedback shapes, and perpetuates, gender gaps in self-assessments.

Borrowing can help consumers facing liquidity constraints, but unnecessary borrowing can pose problems for consumer and societal welfare. This work establishes the concept of psychological ownership of borrowed money, the extent to which consumers see borrowed money as their own money. We demonstrate that both individual-level and contextual-level variation in the degree to which consumers feel psychological ownership of borrowed money explains people's willingness to borrow. Moreover, we show that psychological ownership of borrowed money is malleable and can be used to discourage suboptimal borrowing. Finally, this talk discusses new research investigating the consequences of psychological ownership of other types of monetary resources and a discussion of how and when these perceptions may be malleable.

Science builds upon science. Even after peer-review and publication, science papers could still contain images or other data of concern. If not addressed post-publication, papers containing incorrect or even falsified data could lead to wasted time and money spent by other researchers trying to reproduce those results. Several high-profile science misconduct cases have been described, but many cases are yet undetected. Elisabeth Bik is an image forensics detective who left her paid job in industry to search for and report duplicated and manipulated images in biomedical articles. She has done a systematic scan of 20,000 papers in 40 journals and found that about 4% of these contained inappropriately duplicated images. In her talk she will present her work and show several types of inappropriately duplicated images. In addition, she will show how to report scientific papers of concern, and how journals and institutions handle such allegations.