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Record W3156483075 · doi:10.1177/01461672211010038

Subjective Identity Concealability and the Consequences of Fearing Identity-Based Judgment

2021· article· en· W3156483075 on OpenAlexafffund
Joel M. Le Forestier, Elizabeth Page‐Gould, Calvin K. Lai, Alison L. Chasteen

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaOntario Ministry of Research, Innovation and ScienceCanada Research Chairs
KeywordsIdentity (music)PsychologySocial psychologyConstruct (python library)Set (abstract data type)Computer science

Abstract

fetched live from OpenAlex

In intergroup contexts, people may fear being judged negatively because of an identity they hold. For some, the prospect of concealment offers an opportunity to attenuate this fear. Therefore, believing an identity is concealable may minimize people's fears of identity-based judgment. Here, we explore the construct of subjective identity concealability: the belief that an identity one holds is concealable from others. Across four pre-registered studies and a set of internal meta-analyses, we develop and validate a scale to measure individual differences in subjective identity concealability and provide evidence that it is associated with lower levels of the psychological costs of fearing judgment in intergroup contexts. Open materials, data, and code for all studies, pre-registrations for Studies 1-4, and online supplementary materials can be found at the following link: https://osf.io/pzcf9/.

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)0.027
metaresearch head score (Gemma)0.100
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.100
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.053
GPT teacher head0.383
Teacher spread0.330 · 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

Citations23
Published2021
Admission routes2
Has abstractyes

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Same venuePersonality and Social Psychology BulletinSame topicSocial and Intergroup PsychologyFrench-language works237,207