Prototypes and same-gender bias in perceptions of hiring discrimination

The present study investigated the relative importance of two explanations behind perceptions of gender discrimination in hiring: prototypes and same-gender bias. According to the prototype explanation, people perceive an event as discrimination to the extent that it fits their preconceptions of typical discrimination. In contrast, the same-gender bias explanation asserts that people more readily detect discrimination toward members of their own gender. In four experiments (n = 797), women and men made considerably stronger discrimination attributions, and were moderately more discouraged from seeking work, when the victim was female rather than male. Further, a series of regressions analyses showed beliefs in discrimination of women to be moderately correlated with discrimination attributions of female victims, but little added explanatory value of participant gender, stigma consciousness, or feminist identification. The results offer strong support for the prototype explanation.     

Examining the visual processing patterns of lonely adults

Prior research has shown that loneliness is associated with hypervigilance to social threats, with eye‐tracking research showing lonely people display a specific attentional bias when viewing social rejection and social exclusion video footage (Bangee, Harris, Bridges, Rotenberg & Qualter, 2014; Qualter, Rotenberg, Barrett et al ., 2013). The current study uses eye‐tracker methodology to examine whether that attentional bias extends to negative emotional faces and negative social non‐rejecting stimuli, or whether it could be explained only as a specific bias to social rejection/exclusion. It is important to establish whether loneliness relates to a specific or general attention bias because it may explain the maintenance of loneliness. Participants (N = 43, F = 35, M age = 20 years and 2 months, SD = 3 months) took part in three tasks, where they viewed different social information: Task 1 – slides displaying four faces each with different emotions (anger, afraid, happy and neutral), Task 2 – slides displaying sixteen faces with varying ratios expressing happiness and anger, and Task 3 – slides displaying four visual scenes (socially rejecting, physically threatening, socially positive, neutral). For all three tasks, eye movements were recorded in real time with an eye‐tracker. Results showed no association between loneliness and viewing patterns of facial expressions, but an association between loneliness and hypervigilant viewing of social rejecting stimuli. The findings indicate that lonely adults do not have a generalised hypervigilance to social threat, but have, instead, a specific attentional bias to rejection information in social contexts. Implications of the findings for interventions are discussed.     

Effects of exposure to alcohol‐related cues on racial discrimination

Prior research has shown that exposure to alcohol‐related images exacerbates expression of implicit racial biases, and that brief exposure to alcohol‐related words increases aggressive responses. However, the potential for alcohol cue exposure to elicit differential aggression against a Black (outgroup) relative to a White (ingroup) target—that is, racial discrimination—has never been investigated. Here, we found that White participants (N = 92) exposed to alcohol‐related words made harsher judgments of a Black experimenter who had frustrated them than participants who were exposed to nonalcohol words. These findings suggest that exposure to alcohol cues increases discriminatory behaviors toward Blacks.     

情感预测的影响偏差——聚焦错觉还是适应忽视?

为了考察情感预测影响偏差中聚焦错觉和适应忽视的作用,本研究通过两个实验,先让大学生被试对考研(实验1a)、骨折手术(实验1b)、搬到新校区(实验2)进行情感预测,然后将其与情感体验进行比较,并比较了去焦点化训练、适应训练和控制组对影响偏差的干预效果。结果发现:去焦点化训练显著地降低了情感预测的影响偏差,而适应训练和控制组则没有显著降低影响偏差。因此,本研究认为,当情境线索清楚的时候,聚焦错觉是导致情感预测影响偏差的主要原因。     

Distinguished Lecture: Social structure,narrative and explanation

Recent work on social injustice has focused on implicit bias as an important factor in explaining persistent injustice in spite of achievements on civil rights. In this paper, I argue that because of its individualism, implicit bias explanation, taken alone, is inadequate to explain ongoing injustice; and, more importantly, it fails to call attention to what is morally at stake. An adequate account of how implicit bias functions must situate it within a broader theory of social structures and structural injustice; changing structures is often a precondition for changing patterns of thought and action and is certainly required for durable change.     

A Below‐Average Effect with Respect to American Political Stereotypes on Warmth and Competence

The “above‐average effect” is the phenomenon that people tend to judge themselves above average on desirable traits. Based on social identity theory, we propose that a “below‐average effect” may arise when individuals rate themselves and the average ingroup member on traits stereotypically associated with the ingroup. In two studies, Republican and Democrat participants rated themselves and the average political ingroup member on possession of desirable traits related to warmth and competence. Current political stereotypes in America associate the former dimension with Democrats and the latter with Republicans. Consistent with our hypothesis, the above‐average effect was moderated by political group and dimension in interaction. In particular, Democrats rated themselves below the average Democrat on warmth and Republicans rated themselves below the average Republican on competence.     

A Single Counterexample Leads to Moral Belief Revision

What kind of evidence will lead people to revise their moral beliefs? Moral beliefs are often strongly held convictions, and existing research has shown that morality is rooted in emotion and socialization rather than deliberative reasoning. In addition, more general issues—such as confirmation bias—further impede coherent belief revision. Here, we explored a unique means for inducing belief revision. In two experiments, participants considered a moral dilemma in which an overwhelming majority of people judged that it was inappropriate to take action to maximize utility. Their judgments contradicted a utilitarian principle they otherwise strongly endorsed. Exposure to this scenario led participants to revise their belief in the utilitarian principle, and this revision persisted over several hours. This method provides a new avenue for inducing belief revision.     

Learning to Manipulate and Categorize in Human and Artificial Agents

This study investigates the acquisition of integrated object manipulation and categorization abilities through a series of experiments in which human adults and artificial agents were asked to learn to manipulate two‐dimensional objects that varied in shape, color, weight, and color intensity. The analysis of the obtained results and the comparison of the behavior displayed by human and artificial agents allowed us to identify the key role played by features affecting the agent/environment interaction, the relation between category and action development, and the role of cognitive biases originating from previous knowledge.     

Reducing the risk of bias in health behaviour change trials: Improving trial design,reporting or bias assessment criteria? A review and case study

Objective: It has been suggested that randomised controlled trials (RCTs) of health behaviour change (HBC) interventions are less rigorously designed than – for example– drug trials. This study presents an approach to clarifying whether this is due to poor trial design, incomplete trial reporting and/or the inappropriateness of commonly applied risk of bias assessment criteria.

Design: First, a framework of key sources of bias and common strategies for reducing bias risk is developed based on a literature review. Second, we describe the design of a multi-site RCT evaluating the cost-effectiveness of an HIV-treatment adherence intervention (case study). The choices made by the multidisciplinary team trying to minimise the risk of bias are compared against the risk of bias framework.

Main outcome measures: Implementation of common strategies for reducing the risk of bias in the case study; alternative or additional strategies applied; a justification for each deviation from the risk of bias framework.

Results: Most of the common strategies for reducing the risk of bias could be implemented. Alternative strategies were developed for minimising the risk of performance bias and contamination. Several additional, domain-specific risk of bias strategies were implemented.

Conclusions: The literature provides useful guidance for reducing the risk of bias in HBC trials. Yet, the case study suggests that HBC trial designers may face specific challenges that require alternative/additional measures for reducing the risk of bias. Using the risk of bias justification table (RATIONALE) could lead to better-designed HBC trials, more comprehensive trial reports and the data necessary for evaluating the appropriateness of commonly applied risk of bias assessment criteria to HBC trials.     

What Goes Up Apparently Needn't Come Down: Asymmetric Predictions of Ascent and Descent in Rankings

In eight studies, we document an upward mobility bias, or a tendency to predict that a rise in rankings is more likely than a decline. This asymmetry was observed in predictions of classroom performance, NBA and NFL standings, business school rankings, and employee performance rankings. The bias was found for entities people care about and want to see improve their standing, as well as entities in which people are not invested. It appears to result from people's tendency to give considerable weight to a focal agent's intentions and motivation, but to give less weight to the intentions of competitors and other factors that would thwart the focal agent's improvement. We show that this bias is most pronounced for implicit incremental theorists, who believe that performance is malleable (and hence assign more weight to intentions and effort). We discuss implications of this asymmetry for decision making and for an understanding of the underdog bias. Copyright © 2015 John Wiley & Sons, Ltd.