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Record W4405798266 · doi:10.1111/cag.12971

Conceptualizing discrimination against LGBTQ+ workers in the unbounded workplace

2024· article· en· W4405798266 on OpenAlexafffundvenue
Benjamin Owens, Suzanne Mills

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2024
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsMcMaster University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsStressorMental healthDistressMental distressPsychologyPerceptionMinority stressCoping (psychology)Social psychologyPsychological distressSexual orientationClinical psychologySexual minorityPsychotherapist

Abstract

fetched live from OpenAlex

Abstract The workplace is a key space where LGBTQ+ people face discrimination leading to mental health distress. This paper shows how spatial attributes of work shape experiences and perceptions of discrimination and mental health distress . Building on minority stress theory, we demonstrate how spatial attributes of work can cause, amplify, or mitigate mental health distress among LGBTQ+ people through direct and indirect mechanisms, such as anticipated discrimination, perceived discrimination, and the availability of coping devices. Our findings suggest that understanding the connection between workplace discrimination and poor mental health requires a more nuanced understanding of the workplace, highlighting how workplace stressors are simultaneously emplaced in and exceed the spatiotemporal bounds of the workplace .

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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.708

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0090.027
Scholarly communication0.0070.003
Open science0.0010.007
Research integrity0.0020.002
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 head0.023
GPT teacher head0.286
Teacher spread0.263 · 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 designTheoretical or conceptual
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
Published2024
Admission routes3
Has abstractyes

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