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Record W31297602 · doi:10.1007/s00394-019-02048-8

The effect of perceived gender role congruence and perceived sexual orientation on the selection interview process.

2000· article· en· W31297602 on OpenAlexaff
Charles Fehr

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsUniversity of Windsor
FundersNatural Science Foundation of Zhejiang ProvinceNational Natural Science Foundation of China
KeywordsCongruence (geometry)PsychologySexual orientationSocial psychologyProcess (computing)Computer science

Abstract

fetched live from OpenAlex

This study sought to determine whether stereotypical gender role behaviour and perceived sexual orientation of a male employment candidate would influence merit-based ratings of the candidate's employment potential. The study consisted of three phases: (1) a simulated interview phase, (2) a resume phase, and (3) an assessment of attitudes toward gays and lesbians. In the interview phase, participants observed either a stereotypically masculine candidate, or a stereotypically feminine candidate on videotape in a simulated interview situation in order to determine whether this behaviour was stereotypically gender congruent, or gender incongruent. In the resume phase, information designed to influence the participant's perception of the candidate's sexual orientation was included in the "volunteer experience" section of the resume. Participants examined the resume of either a candidate who was presented as gay or a candidate who was not presented as gay. Participants in the study consisted of 44 male and 72 female University of Windsor undergraduate psychology students who provided ratings of the employment candidate immediately following both the interview and resume components of the study. (Abstract shortened by UMI.)Dept. of Psychology. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis1999 .F44. Source: Masters Abstracts International, Volume: 39-02, page: 0603. Adviser: Durhane Wong-Rieger. Thesis (M.A.)--University of Windsor (Canada), 2000.

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)0.083
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 score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.083
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.051
GPT teacher head0.306
Teacher spread0.256 · 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

Citations0
Published2000
Admission routes1
Has abstractyes

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