Contemporary theories of associative learning are increasingly complex, which necessitates the use of computational methods to reveal predictions of these models. We argue that comparisons across multiple models in terms of goodness of fit to empirical data from experiments often reveal more about the actual mechanisms of learning and behavior than do simulations of only a single model. Such comparisons are best made when the values of free parameters are discovered through some optimization procedure based on the specific data being fit (e.g., hill climbing), so that the comparisons hinge on the psychological mechanisms assumed by each model rather than being biased by using parameters that differ in quality across models with respect to the data being fit. Statistics like the Bayesian information criterion facilitate comparisons among models that have different numbers of free parameters. These issues are examined using retrospective revaluation data.

Intergroup biases shape most aspects of person construal, including lower-level visual representations of group members' faces. Specifically, ingroup members' faces tend to be represented more positively than outgroup members' faces. Here, we used a reverse-correlation paradigm to test whether engaging in perspective taking (i. e., actively imagining another person's mental states) can reduce these biased visual representations. In an initial image-generation experiment, participants were randomly assigned to a minimal group and then composed a narrative essay about an ingroup or an outgroup target person, either while adopting the person's perspective or while following control instructions. Afterward, they generated an image of the person's face in a reversecorrelation image-classification task. Subsequent image-assessment experiments using an explicit rating task, a sequential priming task, and an economic trust game with separate samples of participants revealed that ingroup faces elicited more likability and trustworthiness than did outgroup faces. Importantly, this pattern of intergroup bias was consistently weaker in faces created by perspective takers. Additional image-assessment experiments identified the mouth (i.e., smiling cues) as a critical facial region wherein the interactive effects of group membership and perspective taking emerged. These findings provide initial evidence that perspective taking may be an effective strategy for attenuating, though not for eliminating, intergroup biases in visual representations of what group members look like.

Initial evaluations generalise to new contexts, whereas counter-attitudinal evaluations are context-specific. Counter-attitudinal information may not change evaluations in new contexts because perceivers fail to retrieve counter-attitudinal cue-evaluation associations from memory outside the counter-attitudinal learning context. The current work examines whether an additional, counter-attitudinal retrieval cue can enhance the generalizability of counter-attitudinal evaluations. In four experiments, participants learned positive information about a target person, Bob, in one context, and then learned negative information about Bob in a different context. While learning the negative information, participants wore a wristband as a retrieval cue for counter-attitudinal Bob-negative associations. Participants then made speeded as well as deliberate evaluations of Bob while wearing or not wearing the wristband. Internal meta-analysis failed to find a reliable effect of the counterattitudinal retrieval cue on speeded or deliberate evaluations, whereas the context cues influenced speeded and deliberate evaluations. Counter to predictions, counter-attitudinal retrieval cues did not disrupt the generalisation of first-learned evaluations or the context-specificity of second-learned evaluations (Experiments 2-4), but the counter-attitudinal retrieval cue did influence evaluations in the absence of context cues (Experiment 1). The current work provides initial evidence that additional counter-attitudinal retrieval cues fail to disrupt the renewal and generalizability of first-learned evaluations.

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The authors investigated the role of perceived discrimination in the association between adverse childhood experiences and psychological distress in adulthood in a sample of individuals (n ¼ 125) at a university-based couple and family therapy clinic. Results showed that a majority had experienced four or more adverse experiences, indicating a high risk of negative health outcomes. A significant indirect effect of adverse experiences through perceived discrimination on psychological distress, even with gender, race/ethnicity, and household income as covariates, was noted. Findings underscore the importance of incorporating assessment of perceived discrimination in therapy with clients presenting with childhood adversity and psychological distress.

The gravest public health challenge in a century has disrupted and transformed our civil justice system. In the span of weeks, courts across the country were forced to make countless, rapid, and difficult decisions. Many courts suspended in-person hearings and moved proceedings to online platforms, such as Zoom. While a shift to virtual courts has been lauded by technological enthusiasts and reformers for decades, little research has examined how this technological change may affect vulnerable unrepresented persons and low-income people in the United States on the "have-not" side of the digital divide.In this chapter, we seek to cast light on how virtual proceedings unfold for these low-income unrepresented persons in the everyday. It is important to do so. To date, much of the conversation has lauded Zoom court proceedings as the future of civil justice, centering this praise on idealized forms of online proceedings and their conveniences, without interrogating the impact of the precarity that low-income people contend with or persistent digital divides.In marked departure, we examine how these new technologies affect the experiences of low-income unrepresented persons who encounter, and contend with, adversities within virtual court proceedings. We examine how these new technologies reconfigure the features, affordances, and barriers present within the civil justice system, and the impact of these new technologies on the psychology of judges, lawyers, and unrepresented persons, as well as the impact of these new technologies on the meaning of the judicial role and on a person's unrepresented status. As political theorist of science and technology Langdon Winner observes, "[i]f the We are incredibly grateful to Nora Al Haider and Rachel Wang for their help designing and administering this study, and to the research assistants who helped by observing the virtual hearings involved in this preliminary study, including

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