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An Examination of Lesbian and Gay Employees’ Intention to Change Workplace Heterosexism in China

2023· article· en· W4385224357 on OpenAlexaff
Wenjun Zhang, You‐Ta Chuang, Jing Wang, Robin Church

Bibliographic record

VenueAcademy of Management Proceedings · 2023
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsToronto Metropolitan UniversityWilfrid Laurier University
Fundersnot available
KeywordsHeterosexismLesbianPsychologySocial psychologyContinuanceConstraint (computer-aided design)PerceptionChinaPolitical scienceEngineering

Abstract

fetched live from OpenAlex

This study focused on the condition under which lesbian and gay (LG) employees intend to change workplace heterosexism. I theorized that the experience of institutional contradictions derived from the misalignment between LG employees’ interests of advocating equal treatment and workplace heterosexism triggers their intention to change. In a sample of 840 LG employees in organizations in China, as hypothesized, LG employees’ experience of institutional contradictions related to direct and indirect heterosexism positively associated with their intention to change. In addition, the study also shows that LG employees’ intention to change is constrained by their continuance commitment to their organization. However, such constraint is contingent on their perception of the likelihood that workplace heterosexism could be changed in such a way that 1) high perceived changeability lifted the constraint of continuance commitment, and 2) the constraint of continuance commitment becomes stronger when perceived changeability is low.

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 score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.077
GPT teacher head0.388
Teacher spread0.311 · 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
Published2023
Admission routes1
Has abstractyes

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