Biases in Improvement Decisions: People Focus on the Relative Reduction in Bad Outcomes.

People often decide whether to invest scarce resources-such as time, money, or energy-to improve their chances of a positive outcome. For example, a doctor might decide whether to utilize scarce medicine to improve a patient's chances of recovery, or a student might decide whether to study a few additional hours to increase their chances of passing an exam. We conducted 11 studies (N = 5,342 adults) and found evidence that people behave as if they focus on the relative reduction in bad outcomes caused by such improvements. As a consequence, the same improvements (e.g., 10-percentage-point improvements) are valued very differently depending on whether one's initial chances of success are high or low. This focus on the relative reduction of bad outcomes drives risk preferences that violate normative standards (Studies 1a-1g and 2a), is amplified when decisions become more consequential (Study 2b), and leads even experienced professionals to make suboptimal decisions (Study 3).

Arbitrary fairness in reward and punishments.

People have a strong preference for fairness. For many, fairness means equal reward and punishments for equal efforts and offences. However, this belief does not specify the units in which equality should be expressed. We show that people generally fail to take the interchangeability of units into account when judging and assigning fair punishments and reward. Therefore, judgments about and distributions of resources are strongly influenced by arbitrary decisions about which unit to express them in. For example, if points represent different monetary values for different recipients, people attempt to distribute money equally if money is salient but attempt to distribute points equally if points are salient. Because beliefs about fairness are a fundamental principle in many domains, the implications of these findings are broad. Essentially any distribution of outcomes can be made to appear more or less fair by changing the units these outcomes are expressed in. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

On the role of similarity in mental accounting and hedonic editing.

The theory of mental accounting is often used to understand how people evaluate multiple outcomes or events. However, a model predicting which outcomes are associated with the same mental account and evaluated jointly, versus different accounts and evaluated separately, has remained elusive. We develop a framework that incorporates an online, bottom-up process of similarity and categorization into mental accounting operations. In this categorization-based model of mental accounting, outcomes that overlap on salient attributes are automatically categorized and assigned to the same mental account while outcomes that do not overlap on salient attributes are assigned to different accounts. We use this model to derive the hedonic accounting hypothesis, which generates testable behavioral predictions on people's preferences over the timing of outcomes given similarity-based constraints on mental accounting operations. Six studies provide support for the predictions: People prefer to experience similar losses close together in time and spread dissimilar losses apart; the reverse is true for gains, with a preference for dissimilar gains close together in time and similar gains spread apart across time. Importantly, our model is able to rationalize prior evidence that has found only limited support for the predictions of mental accounting and hedonic editing. Once the psychological process of similarity and categorization is explicitly incorporated into a formal model of mental accounting, its predictions are supported by the data. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Worse is bad: Divergent inferences from logically equivalent comparisons.

Comparisons can often be framed in different but equivalent ways. For example, "A is better than B," can also be expressed as "B is worse than A." In 7 studies (and 4 further studies in the Supplemental Materials available in the OSF) we find that logically equivalent comparison frames have divergent effects on judgments and choices for the items being compared as well as other members of the set from which those items were drawn. These effects are asymmetric, affecting inferior items more strongly than superior ones. We propose a "comparison framing" account that draws on theory in linguistics on the markedness of adjectives (Cruse, 1976; Lehrer, 1985) to explain these results. We show that this account fits the data better than 2 previous accounts of attribute framing: automatic valenced associations (Levin et al., 1998) and leakage of information (McKenzie & Nelson, 2003). (PsycInfo Database Record (c) 2022 APA, all rights reserved).

A pre-registered, multi-lab non-replication of the action-sentence compatibility effect (ACE).

The Action-sentence Compatibility Effect (ACE) is a well-known demonstration of the role of motor activity in the comprehension of language. Participants are asked to make sensibility judgments on sentences by producing movements toward the body or away from the body. The ACE is the finding that movements are faster when the direction of the movement (e.g., toward) matches the direction of the action in the to-be-judged sentence (e.g., Art gave you the pen describes action toward you). We report on a pre-registered, multi-lab replication of one version of the ACE. The results show that none of the 18 labs involved in the study observed a reliable ACE, and that the meta-analytic estimate of the size of the ACE was essentially zero.

The Bias of Individuals (in Crowds): Why Implicit Bias Is Probably a Noisily Measured Individual-Level Construct.

Payne, Vuletich, and Lundberg's bias-of-crowds model proposes that a number of empirical puzzles can be resolved by conceptualizing implicit bias as a feature of situations rather than a feature of individuals. In the present article we argue against this model and propose that, given the existing evidence, implicit bias is best understood as an individual-level construct measured with substantial error. First, using real and simulated data, we show how each of Payne and colleagues' proposed puzzles can be explained as being the result of measurement error and its reduction via aggregation. Second, we discuss why the authors' counterarguments against this explanation have been unconvincing. Finally, we test a hypothesis derived from the bias-of-crowds model about the effect of an individually targeted "implicit-bias-based expulsion program" within universities and show the model to lack empirical support. We conclude by considering the implications of conceptualizing implicit bias as a noisily measured individual-level construct for ongoing implicit-bias research. All data and code are available at https://osf.io/tj8u6/.

Intermediate-term emotional bookkeeping is necessary for long-term reciprocal grooming partner preferences in an agent-based model of macaque groups.

Whether and how primates are able to maintain long-term affiliative relationships is still under debate. Emotional bookkeeping (EB), the partner-specific accumulation of emotional responses to earlier interactions, is a candidate mechanism that does not require high cognitive abilities. EB is difficult to study in real animals, due to the complexity of primate social life. Therefore, we developed an agent-based model based on macaque behavior, the EMO-model, that implements arousal and two emotional dimensions, anxiety-FEAR and satisfaction-LIKE, which regulate social behavior. To implement EB, model individuals assign dynamic LIKE attitudes towards their group members, integrating partner-specific emotional responses to earlier received grooming episodes. Two key parameters in the model were varied to explore their effects on long-term affiliative relationships: (1) the timeframe over which earlier affiliation is accumulated into the LIKE attitudes; and (2) the degree of partner selectivity. EB over short and long timeframes gave rise to low variation in LIKE attitudes, and grooming partner preferences were only maintained over one to two months. Only EB over intermediate-term timeframes resulted in enough variation in LIKE attitudes, which, in combination with high partner selectivity, enables individuals to differentiate between regular and incidental grooming partners. These specific settings resulted in a strong feedback between differentiated LIKE attitudes and the distribution of grooming, giving rise to strongly reciprocated partner preferences that could be maintained for longer periods, occasionally up to one or two years. Moreover, at these settings the individual's internal, socio-emotional memory of earlier affiliative episodes (LIKE attitudes) corresponded best to observable behavior (grooming partner preferences). In sum, our model suggests that intermediate-term LIKE dynamics and high partner selectivity seem most plausible for primates relying on emotional bookkeeping to maintain their social bonds.

Emotional bookkeeping and high partner selectivity are necessary for the emergence of partner-specific reciprocal affiliation in an agent-based model of primate groups.

Primate affiliative relationships are differentiated, individual-specific and often reciprocal. However, the required cognitive abilities are still under debate. Recently, we introduced the EMO-model, in which two emotional dimensions regulate social behaviour: anxiety-FEAR and satisfaction-LIKE. Emotional bookkeeping is modelled by providing each individual with partner-specific LIKE attitudes in which the emotional experiences of earlier affiliations with others are accumulated. Individuals also possess fixed partner-specific FEAR attitudes, reflecting the stable dominance hierarchy. In this paper, we focus on one key parameter of the model, namely the degree of partner selectivity, i.e. the extent to which individuals rely on their LIKE attitudes when choosing affiliation partners. Studying the effect of partner selectivity on the emergent affiliative relationships, we found that at high selectivity, individuals restricted their affiliative behaviours more to similar-ranking individuals and that reciprocity of affiliation was enhanced. We compared the emotional bookkeeping model with a control model, in which individuals had fixed LIKE attitudes simply based on the (fixed) rank-distance, instead of dynamic LIKE attitudes based on earlier events. Results from the control model were very similar to the emotional bookkeeping model: high selectivity resulted in preference of similar-ranking partners and enhanced reciprocity. However, only in the emotional bookkeeping model did high selectivity result in the emergence of reciprocal affiliative relationships that were highly partner-specific. Moreover, in the emotional bookkeeping model, LIKE attitude predicted affiliative behaviour better than rank-distance, especially at high selectivity. Our model suggests that emotional bookkeeping is a likely candidate mechanism to underlie partner-specific reciprocal affiliation.

Revisiting Tversky's diagnosticity principle.

Similarity is a fundamental concept in cognition. In 1977, Amos Tversky published a highly influential feature-based model of how people judge the similarity between objects. The model highlights the context-dependence of similarity judgments, and challenged geometric models of similarity. One of the context-dependent effects Tversky describes is the diagnosticity principle. The diagnosticity principle determines which features are used to cluster multiple objects into subgroups. Perceived similarity between items within clusters is expected to increase, while similarity between items in different clusters decreases. Here, we present two pre-registered replications of the studies on the diagnosticity effect reported in Tversky (1977). Additionally, one alternative mechanism that has been proposed to play a role in the original studies, an increase in the choice for distractor items (a substitution effect, see Medin et al., 1995), is examined. Our results replicate those found by Tversky (1977), revealing an average diagnosticity-effect of 4.75%. However, when we eliminate the possibility of substitution effects confounding the results, a meta-analysis of the data provides no indication of any remaining effect of diagnosticity.

The EMO-model: an agent-based model of primate social behavior regulated by two emotional dimensions, anxiety-FEAR and satisfaction-LIKE.

Agent-based models provide a promising tool to investigate the relationship between individuals' behavior and emerging group-level patterns. An individual's behavior may be regulated by its emotional state and its interaction history with specific individuals. Emotional bookkeeping is a candidate mechanism to keep track of received benefits from specific individuals without requiring high cognitive abilities. However, how this mechanism may work is difficult to study in real animals, due to the complexity of primate social life. To explore this theoretically, we introduce an agent-based model, dubbed EMO-model, in which we implemented emotional bookkeeping. In this model the social behaviors of primate-like individuals are regulated by emotional processes along two dimensions. An individual's emotional state is described by an aversive and a pleasant dimension (anxiety and satisfaction) and by its activating quality (arousal). Social behaviors affect the individuals' emotional state. To implement emotional bookkeeping, the receiver of grooming assigns an accumulated affiliative attitude (LIKE) to the groomer. Fixed partner-specific agonistic attitudes (FEAR) reflect the stable dominance relations between group members. While the emotional state affects an individual's general probability of executing certain behaviors, LIKE and FEAR affect the individual's partner-specific behavioral probabilities. In this way, emotional processes regulate both spontaneous behaviors and appropriate responses to received behaviors, while emotional bookkeeping via LIKE attitudes regulates the development and maintenance of affiliative relations. Using an array of empirical data, the model processes were substantiated and the emerging model patterns were partially validated. The EMO-model offers a framework to investigate the emotional bookkeeping hypothesis theoretically and pinpoints gaps that need to be investigated empirically.

Set-fit effects in choice.

In 4 experiments, we investigate how the "fit" of an item with a set of similar items affects choice. We find that people have a notion of a set that "fits" together--one where all items are the same, or all items differ, on salient attributes. One consequence of this notion is that in addition to preferences over the set's individual items, choice reflects set-fit. This leads to predictable shifts in preferences, sometimes even resulting in people choosing normatively inferior options over superior ones.

Sailing From the Seas of Chaos Into the Corridor of Stability: Practical Recommendations to Increase the Informational Value of Studies.

Recent events have led psychologists to acknowledge that the inherent uncertainty encapsulated in an inductive science is amplified by problematic research practices. In this article, we provide a practical introduction to recently developed statistical tools that can be used to deal with these uncertainties when performing and evaluating research. In Part 1, we discuss the importance of accurate and stable effect size estimates as well as how to design studies to reach a corridor of stability around effect size estimates. In Part 2, we explain how, given uncertain effect size estimates, well-powered studies can be designed with sequential analyses. In Part 3, we (a) explain what p values convey about the likelihood that an effect is true, (b) illustrate how the v statistic can be used to evaluate the accuracy of individual studies, and (c) show how the evidential value of multiple studies can be examined with a p-curve analysis. We end by discussing the consequences of incorporating our recommendations in terms of a reduced quantity, but increased quality, of the research output. We hope that the practical recommendations discussed in this article will provide researchers with the tools to make important steps toward a psychological science that allows researchers to differentiate among all possible truths on the basis of their likelihood.

Look before you leap - individual variation in social vigilance shapes socio-spatial group properties in an agent-based model.

Next to predator detection, primate vigilance also serves to keep track of relevant conspecifics. The degree of vigilance towards group members often reflects the dominance rank of an individual: subordinates pay attention to dominants. Although it has been suggested that subordinates' vigilance may result in spatial centrality of dominants, this has not been addressed in either empirical or modeling studies. Using agent-based models, we determined how social vigilance affects socio-spatial properties of primate groups. A basic model without social vigilance, where individuals avoid potential aggressors (avoidance model), was contrasted with two models that each additionally included a different type of social vigilance: a) monitoring a specific potential aggressor to remain informed on its whereabouts (monitoring model) or b) scanning the whole group to detect potential aggressors (scanning model). Adding monitoring or scanning behavior to the avoidance model reinforced spatial centrality of dominants, a pattern often observed in primates, and resulted in more spread out groups. Moreover, variation in scanning tendency alone was already sufficient to generate spatial centrality of dominants: frequently scanning subordinates could move further away from the group center than dominants, before losing sight of group members. In the monitoring model, two mechanisms caused decreased encounter frequencies among subordinates: a) increased inter-individual distances, and b) frequent monitoring of central dominants. In the scanning model, encounters among subordinates decreased due to increased inter-individual distances. This agent-based model study provides a clear indication that individual variation in social vigilance may be an important structuring feature of primate social groups.

Better safe than sorry--socio-spatial group structure emerges from individual variation in fleeing, avoidance or velocity in an agent-based model.

In group-living animals, such as primates, the average spatial group structure often reflects the dominance hierarchy, with central dominants and peripheral subordinates. This central-peripheral group structure can arise by self-organization as a result of subordinates fleeing from dominants after losing a fight. However, in real primates, subordinates often avoid interactions with potentially aggressive group members, thereby preventing aggression and subsequent fleeing. Using agent-based modeling, we investigated which spatial and encounter structures emerge when subordinates also avoid known potential aggressors at a distance as compared with the model which only included fleeing after losing a fight (fleeing model). A central-peripheral group structure emerged in most conditions. When avoidance was employed at small or intermediate distances, centrality of dominants emerged similar to the fleeing model, but in a more pronounced way. This result was also found when fleeing after a fight was made independent of dominance rank, i.e. occurred randomly. Employing avoidance at larger distances yielded more spread out groups. This provides a possible explanation of larger group spread in more aggressive species. With avoidance at very large distances, spatially and socially distinct subgroups emerged. We also investigated how encounters were distributed amongst group members. In the fleeing model all individuals encountered all group members equally often, whereas in the avoidance model encounters occurred mostly among similar-ranking individuals. Finally, we also identified a very general and simple mechanism causing a central-peripheral group structure: when individuals merely differed in velocity, faster individuals automatically ended up at the periphery. In summary, a central-peripheral group pattern can easily emerge from individual variation in different movement properties in general, such as fleeing, avoidance or velocity. Moreover, avoidance behavior also affects the encounter structure and can lead to subgroup formation.