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Record W3200191263 · doi:10.1002/jcop.22706

Feminist identification, social dominance orientation, and weight bias in men

2021· article· en· W3200191263 on OpenAlexaffabout
Émilie Bélanger, Marie‐Pierre Gagnon‐Girouard, Elisabeth Marquis, Benoît Brisson

Bibliographic record

VenueJournal of Community Psychology · 2021
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsSocial dominance orientationPrejudice (legal term)OppressionPsychologyDominance (genetics)Social psychologyIdentification (biology)FeminismSocial identity theoryOverweightSexual orientationGender studiesSocial groupObesitySociologyPolitical scienceMedicine

Abstract

fetched live from OpenAlex

Weight bias has deleterious consequences on individuals considered overweight and has similarities with forms of prejudice linked to social dominance orientation (SDO). Feminism can counter oppression that women are subject to notably through weight bias and SDO, but no studies have focused directly on these variables among men, as feminist identity is linked to less endorsement of certain beliefs in SDO and weight bias. The purpose of the present study is to explore the associations between feminist identification and beliefs, SDO, and weight bias among men from Quebec. Participants were divided into four feminist identification groups. Results indicate that feminist identification in men is linked to lower levels of SDO and less dislike toward people considered overweight. Also, feminism seems to predict prejudice toward others, but not toward oneself whereas SDO-D seems to be a good predictor of the belief that weight is controllable.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.206
Threshold uncertainty score0.410

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.197
GPT teacher head0.551
Teacher spread0.354 · 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

Citations2
Published2021
Admission routes2
Has abstractyes

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