Group heterogeneity and tolerance: The moderating role of conservation values

Does diversity promote tolerance? We propose that reactions to group heterogeneity depend on individual value priorities. In three studies we investigate how values moderate the effect of raising the salience of group heterogeneity (versus homogeneity) on tolerance. As hypothesized, the findings indicate that conservation values moderate the effects of the saliency of the group's heterogeneity. People high on conservation values were more tolerant when the group's homogeneity was made salient than when its heterogeneity was made salient. People low on conservation were either insensitive to information on the group's heterogeneity (Studies 1 and 2), or were more tolerant when the group's heterogeneity was made salient than when its homogeneity was made salient (Study 3). Values are also directly associated with tolerance: conservation values (as well as SDO and RWA in Study 3) were negatively associated whereas openness-to-change and self-transcendence values were positively associated with tolerance. These findings indicate the importance of integrating individual and contextual variables in theories of group processes.     

Violent, nonviolent, and substance-related offending over the life course in a cohort of males and females treated for substance misuse as youths

Most studies on adolescent offending heterogeneity are based on general population samples, and few include individuals with substance misuse or look specifically at substance-related offending. It is also unclear how offender subtypes develop after young adulthood or how offending heterogeneity varies between genders. This study aimed to identify subgroups of offending among adolescents with misuse problems and to examine associations with offending in adulthood. The study included 1,992 females and males that consulted a clinic for adolescents with misuse problems between 1968 and 1971. Latent Class Analyses were conducted to identify subgroups based on violent and nonviolent offending before age 20. Participants were then followed until age 50 and reexamined regarding violent, nonviolent, and substance-related crimes. Associations between subgroups before age 20 and subgroups age 21-50 were examined. Before age 20, three subgroups were identified among the females and six among the males. Males were more specialized in their offending and demonstrated higher levels of offending. Results pointed to both stability and decrease of violent and nonviolent offending, and to the emergence of substance-related offending in adulthood in both genders. The connection between substance-related crimes and general delinquency in adulthood among individuals treated for substance misuse suggests that interventions should also address substance misuse for reducing the overall volume of crime. This study also highlights the importance of including females in research on offending heterogeneity.     

Just world beliefs, causal beliefs, and acquaintance: Associations with stigma toward eating disorders and obesity

The current study investigated the relationship between just world beliefs and stigmatizing attitudes toward eating disorders and obesity. Further, the associations between stigma and causal beliefs, and between stigma and acquaintance with these conditions, were examined. Participants (n = 447) read four vignettes describing an individual with anorexia nervosa, bulimia nervosa, binge eating disorder, or obesity. After each vignette, participants completed questionnaires assessing stigmatizing attitudes, just world beliefs, causal beliefs, and acquaintance with the condition depicted in the vignette. Stronger just world beliefs were associated with greater stigma toward all three eating disorders, as well as obesity (rs ranging from −.11 to −.18). More stigmatizing attitudes were associated with greater attribution of individual responsibility for the development of the disorder. However, participants with personal experience or who knew someone with the depicted problem did not have lower stigma scores than those who did not. The current study suggests that justification ideologies such as just world beliefs and controllability beliefs may underlie the stigmatization of eating disorders and obesity. These findings provide support for stigma reduction efforts aimed at targeting justification ideologies and altering causal beliefs.     

Transfer effects between moral dilemmas: A causal model theory

Evaluations of analogous situations are an important source for our moral intuitions. A puzzling recent set of findings in experiments exploring transfer effects between intuitions about moral dilemmas has demonstrated a striking asymmetry. Transfer often occurred with a specific ordering of moral dilemmas, but not when the sequence was reversed. In this article we present a new theory of transfer between moral intuitions that focuses on two components of moral dilemmas, namely their causal structure and their default evaluations. According to this theory, transfer effects are expected when the causal models underlying the considered dilemmas allow for a mapping of the highlighted aspect of the first scenario onto the causal structure of the second dilemma, and when the default evaluations of the two dilemmas substantially differ. The theory’s key predictions for the occurrence and the direction of transfer effects between two moral dilemmas are tested in five experiments with various variants of moral dilemmas from different domains. A sixth experiment tests the predictions of the theory for how the target action in the moral dilemmas is represented.     

Inference and coherence in causal-based artifact categorization

In four experiments, we tested conditions under which artifact concepts support inference and coherence in causal categorization. In all four experiments, participants categorized scenarios in which we systematically varied information about artifacts’ associated design history, physical structure, user intention, user action and functional outcome, and where each property could be specified as intact, compromised or not observed. Consistently across experiments, when participants received complete information (i.e., when all properties were observed), they categorized based on individual properties and did not show evidence of using coherence to categorize. In contrast, when the state of some property was not observed, participants gave evidence of using available information to infer the state of the unobserved property, which increased the value of the available information for categorization. Our data offers answers to longstanding questions regarding artifact categorization, such as whether there are underlying causal models for artifacts, which properties are part of them, whether design history is an artifact’s causal essence, and whether physical appearance or functional outcome is the most central artifact property.     

Children Use Temporal Cues to Learn Causal Directionality

The ability to learn the direction of causal relations is critical for understanding and acting in the world. We investigated how children learn causal directionality in situations in which the states of variables are temporally dependent (i.e., autocorrelated). In Experiment 1, children learned about causal direction by comparing the states of one variable before versus after an intervention on another variable. In Experiment 2, children reliably inferred causal directionality merely from observing how two variables change over time; they interpreted Y changing without a change in X as evidence that Y does not influence X. Both of these strategies make sense if one believes the variables to be temporally dependent. We discuss the implications of these results for interpreting previous findings. More broadly, given that many real‐world environments are characterized by temporal dependency, these results suggest strategies that children may use to learn the causal structure of their environments.     

Singular Clues to Causality and Their Use in Human Causal Judgment

It is argued that causal understanding originates in experiences of acting on objects. Such experiences have consistent features that can be used as clues to causal identification and judgment. These are singular clues, meaning that they can be detected in single instances. A catalog of 14 singular clues is proposed. The clues function as heuristics for generating causal judgments under uncertainty and are a pervasive source of bias in causal judgment. More sophisticated clues such as mechanism clues and repeated interventions are derived from the 14. Research on the use of empirical information and conditional probabilities to identify causes has used scenarios in which several of the clues are present, and the use of empirical association information for causal judgment depends on the presence of singular clues. It is the singular clues and their origin that are basic to causal understanding, not multiple instance clues such as empirical association, contingency, and conditional probabilities.     

Causal Networks or Causal Islands? The Representation of Mechanisms and the Transitivity of Causal Judgment

Knowledge of mechanisms is critical for causal reasoning. We contrasted two possible organizations of causal knowledge—an interconnected causal network, where events are causally connected without any boundaries delineating discrete mechanisms; or a set of disparate mechanisms—causal islands—such that events in different mechanisms are not thought to be related even when they belong to the same causal chain. To distinguish these possibilities, we tested whether people make transitive judgments about causal chains by inferring, given A causes B and B causes C, that A causes C. Specifically, causal chains schematized as one chunk or mechanism in semantic memory (e.g., exercising, becoming thirsty, drinking water) led to transitive causal judgments. On the other hand, chains schematized as multiple chunks (e.g., having sex, becoming pregnant, becoming nauseous) led to intransitive judgments despite strong intermediate links ((Experiments 1–3). Normative accounts of causal intransitivity could not explain these intransitive judgments (Experiments 4 and 5).     

Investing Even in Uneven Contests: Effects of Asymmetry on Investment in Contests

Many competitions, such as political campaigns, innovative endeavors, sports, or courting rituals, require investment of nonrefundable resources: One contestant wins the prize for the invested amount, whereas all others lose their investments without receiving compensation. Frequently, contests are asymmetric, because of differing resources or prize valuations. Does asymmetry discourage the weaker contestants from investing? Do stronger contestants take this into account and also invest less? Or does the desire to win abolish these differences? Two experiments explored the effects of asymmetry between the contestants—arising from their resources or prizes—on nonrefundable investments. Subjects repeatedly competed in both symmetric and asymmetric contests, enabling within‐subject comparisons. We observed an effect of asymmetry only when it concerned resources: Subjects overall invested less when their resources were unequal, whereas inequality in the prizes did not influence investments. This pattern suggests that winning itself is motivating. The changes between consecutive investments can be explained by reactions to the previous outcome (win or loss): Across all contests, investment decreased following a win and increased following a loss. Copyright © 2015 John Wiley & Sons, Ltd.     

Identifying expectations about the strength of causal relationships

When we try to identify causal relationships, how strong do we expect that relationship to be? Bayesian models of causal induction rely on assumptions regarding people’s a priori beliefs about causal systems, with recent research focusing on people’s expectations about the strength of causes. These expectations are expressed in terms of prior probability distributions. While proposals about the form of such prior distributions have been made previously, many different distributions are possible, making it difficult to test such proposals exhaustively. In Experiment 1 we used iterated learning—a method in which participants make inferences about data generated based on their own responses in previous trials—to estimate participants’ prior beliefs about the strengths of causes. This method produced estimated prior distributions that were quite different from those previously proposed in the literature. Experiment 2 collected a large set of human judgments on the strength of causal relationships to be used as a benchmark for evaluating different models, using stimuli that cover a wider and more systematic set of contingencies than previous research. Using these judgments, we evaluated the predictions of various Bayesian models. The Bayesian model with priors estimated via iterated learning compared favorably against the others. Experiment 3 estimated participants’ prior beliefs concerning different causal systems, revealing key similarities in their expectations across diverse scenarios.