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Sexual Orientation and Gender-Typed Work: Combining Implicit Inversion and Role Congruity Theories

2013· article· en· W2313520954 on OpenAlexaff
Heather M. Clarke, Kara A. Arnold

Bibliographic record

VenueAcademy of Management Proceedings · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSexual orientationPsychologySocial psychologyPrejudice (legal term)BacklashGender schema theory

Abstract

fetched live from OpenAlex

Research on gender-inconsistent employment calls attention to backlash and discrimination experienced by individuals engaged in such work. These phenomena, according to role congruity theory, occur, at least in part, through the operation of gender stereotypes. Further, research on sexual orientation has shown that when given information about an individual's sexual orientation, combined with their sex, people make assumptions about the individual's gender. In fact, gender stereotypes of homosexual individuals tend to be in the opposite direction of those about heterosexual individuals. Gender stereotypes are not only descriptive, however, but also prescriptive. Significant research has examined the interaction of prescriptive stereotypes with assumptions about sexual orientation. Little research, however, has investigated the practical or behavioural implications of these stereotypes. In this paper, we examine, conceptually, gender stereotypes within the context of gender-typed work, suggesting how they contribute to prejudice and discrimination against homosexual individuals in the workplace. We do this through integrating the theories of role congruity and implicit inversion. This paper contributes to the sexual orientation literature as well as the gender stereotypes literature by examining, theoretically, how homosexual stereotypes are related to gender stereotypes. It also contributes to work on gender-typed occupations by being the first to explore the impact of sexual orientation on evaluations of individuals engaged in gender-typed jobs.

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)0.005
metaresearch head score (Gemma)0.012
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 score0.005
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.008
Scholarly communication0.0050.006
Open science0.0010.005
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 head0.066
GPT teacher head0.299
Teacher spread0.232 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

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