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Record W1966245137 · doi:10.1037//1076-8998.5.4.428

Gender differences in job strain, social support at work, and psychological distress.

2000· article· en· W1966245137 on OpenAlexaff
Marian J. Vermeulen, Cameron Mustard

Bibliographic record

VenueJournal of Occupational Health Psychology · 2000
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsWomen's College HospitalInstitute for Work & HealthSunnybrook Health Science Centre
Fundersnot available
KeywordsJob strainPsychosocialPsychologySocial supportDistressPsychological distressJob controlOccupational stressClinical psychologyWork (physics)Social psychologyMental healthPsychiatry

Abstract

fetched live from OpenAlex

Using the demand-control-support model of job strain, the authors examined gender differences in the relationship between psychosocial work exposures and psychological distress in a cross-sectional sample of 7,484 employed Canadians. Compared with low-strain work, high-strain and active work were associated with a significantly higher level of distress in both men and women. Differences in psychological distress in relation to psychosocial work exposures were greater for men than for women. Low social support was associated with higher distress across all categories of job strain, and the combined effect of low social support and high job strain was associated with the greatest increase in distress. This pattern was similar in men and women. This study suggests that psychosocial work exposures may be a more significant determinant of psychological well-being in male workers compared with female workers.

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 score0.253
Threshold uncertainty score0.503

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.204
GPT teacher head0.519
Teacher spread0.315 · 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

Citations203
Published2000
Admission routes1
Has abstractyes

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