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Record W3027567544 · doi:10.1111/pops.12667

Social Cure Processes Help Lower Intergroup Anxiety Among Neighborhood Residents

2020· article· en· W3027567544 on OpenAlexfundno aff
Clifford Stevenson, Sebastiano Costa, Matthew J. Easterbrook, Niamh McNamara, Blerina Këllezi

Bibliographic record

VenuePolitical Psychology · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsnot available
FundersTrent UniversityNottingham Trent University
KeywordsIngroups and outgroupsOutgroupPsychologyFeelingSocial psychologyGroup cohesivenessAnxietyCohesion (chemistry)Social anxietyGroup conflictSocial group

Abstract

fetched live from OpenAlex

Research in the social cure tradition shows that groups can reduce members' stress by providing support to cope with challenges, but it has yet to consider how this applies to the anxiety occasioned by outgroups. Research on intergroup contact has extensively examined how reducing intergroup anxiety improves attitudes towards outgroups, but it has yet to examine the role of intragroup support processes in facilitating this. The present article takes the case of residential contact, in which the impact of diversification upon neighborhood cohesion is hotly debated, but the role of neighborhood identification and social support from neighbors in facilitating residential mixing has been largely ignored. Our surveys of two geographically bounded communities in England ( n = 310; n = 94) and one in Northern Ireland ( n = 206) show that neighborhood identification predicts both well‐being and more positive feelings towards outgroups, with both effects occurring via increased intragroup support. In studies 2 and 3, we show that this positive effect on feelings towards the outgroup occurs independently of that of intergroup contact and is further explained by the effect of neighborhood support in reducing intergroup anxiety. This suggests that social cure processes can improve intergroup attitudes by supporting group members to deal with the stress of intergroup interactions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.746
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.057
GPT teacher head0.403
Teacher spread0.346 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations37
Published2020
Admission routes1
Has abstractyes

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