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Record W4313857757 · doi:10.1037/pspi0000416

The disempowering implications for members of marginalized groups of imposing a focus on personal experiences in discussions of intergroup issues.

2023· article· en· W4313857757 on OpenAlexafffund
Jacquie D. Vorauer, Corey Petsnik

Bibliographic record

VenueJournal of Personality and Social Psychology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of Manitoba
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologySocial psychologyEmpathyFeelingPerspective-takingPsycINFOPerceptionPerspective (graphical)Competence (human resources)

Abstract

fetched live from OpenAlex

, whereby being prompted to talk about their personal experiences (vs. reasoning) in discussions of intergroup issues reduces racialized individuals' momentary feelings of power and power-relevant behaviors such as exerting social influence over White individuals' opinions. Perceptions of being viewed as less competent by others or seeing themselves as less competent in the moment were consistently implicated in this effect, which was not evident for White individuals or in discussions of general topics. Asking members of marginalized groups for their opinions in an open manner, or asking about their reasoning or personal firsthand knowledge, all appear to constitute means of learning about their perspective on intergroup issues in a more empowering way. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.003
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.001

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 head0.082
GPT teacher head0.443
Teacher spread0.360 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations8
Published2023
Admission routes2
Has abstractyes

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