Inference making and linking both require thinking: Spontaneous trait inference and spontaneous trait transference both rely on working memory capacity

Past research suggests that spontaneous trait inference (STI) and spontaneous trait transference (STT) may reflect different cognitive processes, the former being inferential and the latter associational. The present research was designed to explore whether either or both of these processes involve thinking that occupies cognitive capacity. Four studies suggest that reductions in available cognitive capacity reduce both STI and STT effects, both on measures of savings in relearning (which reflect the strength of trait associations with a person) and on trait ratings measures (which reflect the strength of trait inferences made about a person). Similar results were obtained using an individual difference measure of cognitive capacity. Although these results suggest that STI and STT are similar, in that both exhibit interference from reductions in cognitive capacity, other results, such as halo effects in trait ratings, support previous assertions that their underlying processes are distinct.     

Rewarding performance feedback alters reported time of action

Past studies have shown that the perceived time of actions is retrospectively influenced by post-action events. The current study examined whether rewarding performance feedback (even when false) altered the reported time of action. In Experiment 1, participants performed a speeded button press task and received monetary reward for a presumed “fast,” or a monetary punishment for a presumed “slow” response. Rewarded trials resulted in the false perception that the response action occurred earlier than punished trials. In Experiments 2 and 3, the need for a speeded response and reward were independently manipulated in order to decouple the cognitive and reward components in the feedback signal. When tested independently, neither variable affected the judged time of action. We conclude that meaningful feedback (fast or slow) is only used when made salient by reward, to modulate the judged time of an action.     

Personality and behavioral outcomes associated with risk-taking are accurately inferred from faces

Growing evidence suggests that people are able to accurately infer some personality traits and behavioral outcomes from facial photographs. However, little research has examined whether people are able to accurately infer personality traits or behavioral outcomes associated with risk-taking. In this study, we examined whether people were able to accurately infer, on average, others’ personality traits associated with risk-taking from facial photographs. We further examined whether such first impressions were associated with relevant and important behavioral outcomes—specifically, future discounting and gambling and problem gambling tendencies. Results suggest that people are able to accurately infer, on average, some personality traits and behavioral outcomes associated with risk-taking from faces.     

Speaker reliability guides children's inductive inferences about novel properties

Prior work shows that children can make inductive inferences about objects based on their labels rather than their appearance (Gelman, 2003). A separate line of research shows that children's trust in a speaker's label is selective. Children accept labels from a reliable speaker over an unreliable speaker (e.g., Koenig & Harris, 2005). In the current paper, we tested whether 3- and 5-year-old children attend to speaker reliability when they make inductive inferences about a non-obvious property of a novel artifact based on its label. Children were more likely to use a reliable speaker's label than an unreliable speaker's label when making inductive inferences. Thus, children not only prefer to learn from reliable speakers, they are also more likely to use information from reliable speakers as the basis for future inferences. The findings are discussed in light of the debate between a similarity-driven and a label-driven approach to inductive inferences.     

When promoting a charity can hurt charitable giving: A metacognitive analysis

Charities need to come to mind to enter a potential donor's consideration set. However, feeling familiar with a charity and its cause can facilitate or impair giving. In most cases, perceived good memory for details of the cause fosters the impression of personal importance, which increases giving (Studies 1 and 3). But when the charity aims to increase awareness of a cause, good memory for the cause suggests that awareness is already high, which impairs giving (Studies 2 and 3). Hence, promotions for awareness-raising charities can actually have negative consequences, confirming the predictions of a metacognitive analysis.     

How Chinese people infer helpers' ambiguous intentions: Helper effort and interpersonal relationships

Previous researchers have tried to understand in what situations people feel gratitude and indebtedness in response to other people helping them, and have found that benefit value, helper effort, helper obligation, and helper intention were all important. However, helper intentions are not always clear. We gave Chinese participants helping vignettes and tested how they inferred helpers' ambiguous intentions. Study 1 found that helper effort significantly influenced how they infer intentions, but benefit value and helper obligation did not. Study 2 replicated the effect of helper effort and found that more effort led participants to infer that the helper was more motivated by utilitarian interests. Study 3 focused on what type of relationship the helper had with the participants, and found that closeness led participants to infer more benevolent intentions and less utilitarian intentions.     

Rational Hypocrisy: A Bayesian Analysis Based on Informal Argumentation and Slippery Slopes

Moral hypocrisy is typically viewed as an ethical accusation: Someone is applying different moral standards to essentially identical cases, dishonestly claiming that one action is acceptable while otherwise equivalent actions are not. We suggest that in some instances the apparent logical inconsistency stems from different evaluations of a weak argument, rather than dishonesty per se. Extending Corner, Hahn, and Oaksford's (2006) analysis of slippery slope arguments, we develop a Bayesian framework in which accusations of hypocrisy depend on inferences of shared category membership between proposed actions and previous standards, based on prior probabilities that inform the strength of competing hypotheses. Across three experiments, we demonstrate that inferences of hypocrisy increase as perceptions of the likelihood of shared category membership between precedent cases and current cases increase, that these inferences follow established principles of category induction, and that the presence of self‐serving motives increases inferences of hypocrisy independent of changes in the actions themselves. Taken together, these results demonstrate that Bayesian analyses of weak arguments may have implications for assessing moral reasoning.     

A peculiar prevalence of p values just below .05

In null hypothesis significance testing (NHST), p values are judged relative to an arbitrary threshold for significance (.05). The present work examined whether that standard influences the distribution of p values reported in the psychology literature. We examined a large subset of papers from three highly regarded journals. Distributions of p were found to be similar across the different journals. Moreover, p values were much more common immediately below .05 than would be expected based on the number of p values occurring in other ranges. This prevalence of p values just below the arbitrary criterion for significance was observed in all three journals. We discuss potential sources of this pattern, including publication bias and researcher degrees of freedom.     

Learning about the internal structure of categories through classification and feature inference

Previous research on category learning has found that classification tasks produce representations that are skewed toward diagnostic feature dimensions, whereas feature inference tasks lead to richer representations of within-category structure. Yet, prior studies often measure category knowledge through tasks that involve identifying only the typical features of a category. This neglects an important aspect of a category's internal structure: how typical and atypical features are distributed within a category. The present experiments tested the hypothesis that inference learning results in richer knowledge of internal category structure than classification learning. We introduced several new measures to probe learners' representations of within-category structure. Experiment 1 found that participants in the inference condition learned and used a wider range of feature dimensions than classification learners. Classification learners, however, were more sensitive to the presence of atypical features within categories. Experiment 2 provided converging evidence that classification learners were more likely to incorporate atypical features into their representations. Inference learners were less likely to encode atypical category features, even in a “partial inference” condition that focused learners' attention on the feature dimensions relevant to classification. Overall, these results are contrary to the hypothesis that inference learning produces superior knowledge of within-category structure. Although inference learning promoted representations that included a broad range of category-typical features, classification learning promoted greater sensitivity to the distribution of typical and atypical features within categories.