Inaccurate group meta-perceptions drive negative out-group attributions in competitive contexts

Lees, Jeffrey Martin; Cikara, Mina

doi:10.1038/s41562-019-0766-4

Cited by 173 publications

(192 citation statements)

References 40 publications

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“…By highlighting an overarching identity, politicians, the media and opinion leaders could help reduce political division around the issue. Second, a growing body of work shows that misperceptions of the other side underlie polarization 96,97 . Therefore, it is likely important to combat misinformation that could generate partisan motivated reasoning and inaccurate beliefs (see "Fake news and misinformation" below).…”

Section: Culturementioning

confidence: 99%

Using social and behavioural science to support COVID-19 pandemic response

et al. 2020

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Section: Culturementioning

confidence: 99%

Using social and behavioural science to support COVID-19 pandemic response

et al. 2020

Self Cite

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“…On the other hand, a more positive bias exposes individuals to aversive outcomes (e.g., economic downturns, financial loss). Similarly, uncertainty may arise when judging another's trustworthiness 30 , or gauging the thoughts of others 31 , and the bias evident when resolving this uncertainty can facilitate or obstruct social affiliation and even enflame intergroup conflict (e.g., 32,33 ).…”

Section: Social Connectedness and Negative Affect Uniquely Explain Inmentioning

confidence: 99%

Social connectedness and negative affect uniquely explain individual differences in response to emotional ambiguity

Neta

Brock

2021

Sci Rep

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Negativity bias is not only central to mood and anxiety disorders, but can powerfully impact our decision-making across domains (e.g., financial, medical, social). This project builds on previous work examining negativity bias using dual-valence ambiguity. Specifically, although some facial expressions have a relatively clear negative (angry) or positive valence (happy), surprised expressions are interpreted negatively by some and positively by others, providing insight into one’s valence bias. Here, we examine putative sources of variability that distinguish individuals with a more negative versus positive valence bias using structural equation modeling. Our model reveals that one’s propensity toward negativity (operationalized as temperamental negative affect and internalizing symptomology) predicts valence bias particularly in older adulthood when a more positive bias is generally expected. Further, variability in social connectedness (a propensity to seek out social connections, use those connections to regulate one’s own emotions, and be empathic) emerges as a notable and unique predictor of valence bias, likely because these traits help to override an initial, default negativity. We argue that this task represents an important approach to examining variability in affective bias, and can be specifically useful across the lifespan and in populations with internalizing disorders or even subclinical symptomology.

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“…When it comes to gender, and potentially other demographic categories as well, the main lesson to be drawn from social psychological research into ingroup-outgroup biases might not be that people are biased in favour of their own groupsmost people know that alreadybut rather that people commonly overestimate the extent of these biases. If so, a more accurate view of the situation might help to foster more harmonious relationships among groups (Lees & Cikara, 2020;Stewart-Williams, 2002).…”

Section: Menmentioning

confidence: 99%

Reactions to male‐favouring versus female‐favouring sex differences: A pre‐registered experiment and Southeast Asian replication

Stewart‐Williams

Chang

Wong

et al. 2020

British J of Psychology

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Two studies investigated: (1) how people react to research describing a sex difference, depending on whether that difference favours males or females; and (2) how accurately people can predict how the average man and woman will react. In Study 1, Western participants (N = 492) viewed a fictional popular-science article describing either a malefavouring or a female-favouring sex difference (i.e., men/women draw better; women/men lie more). Both sexes reacted less positively to the male-favouring differences, judging the findings to be less important, less credible, and more offensive, harmful, and upsetting. Participants predicted that the average man and woman would react more positively to sex differences favouring their own sex. This was true of the average woman, although the level of own-sex favouritism was lower than participants predicted. It was not true, however, of the average man, wholike the average womanreacted more positively to the femalefavouring differences. Study 2 replicated these findings in a Southeast Asian sample (N = 336). Our results are consistent with the idea that both sexes are more protective of women than men, but that both exaggerate the level of same-sex favouritism within each sexa misconception that could potentially harm relations between the sexes.

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Inaccurate group meta-perceptions drive negative out-group attributions in competitive contexts

Cited by 173 publications

References 40 publications

Using social and behavioural science to support COVID-19 pandemic response

Using social and behavioural science to support COVID-19 pandemic response

Social connectedness and negative affect uniquely explain individual differences in response to emotional ambiguity

Reactions to male‐favouring versus female‐favouring sex differences: A pre‐registered experiment and Southeast Asian replication

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