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Occupational Gender Segregation in Canada, 1981–1996: Overall, Vertical and Horizontal Segregation*

2003· article· fr· W2001566452 on OpenAlexaffabout
Bradley Brooks, Jennifer Jarman, Robert M. Blackburn

Bibliographic record

VenueCanadian Review of Sociology/Revue canadienne de sociologie · 2003
Typearticle
Languagefr
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsHumanitiesPolitical scienceSociologyArt

Abstract

fetched live from OpenAlex

Cet article examine les changements survenus entre 1981 et 1996 dans la ségrégation hommes‐femmes. Le niveau de ségrégation dans son ensemble a faiblement baissé, suivant en cela la tendance observée depuis les années soixante. La diminution se traduit par une décroissance de 41% de la ségrégation verticale (équité salariale) mais par une augmentation de la ségrégation horizontale (différences autres que cette équité). Les femmes ont renforcé leur point d'ancrage dans la main‐d'œuvre à plein temps et élargi L'étendue de leur participation alors que celle des hommes dans des secteurs à temps partiel et moins prisés a augmenté, et que les emplois traditionnellement occupés par des hommes ont connu un déclin et ont vu L'arrivée des femmes. This article examines changes in gender segregation in Canada between 1981 and 1996. Overall segregation declined slightly. This is a continuation of a trend occurring since the 1960s. The decline comprises a 41% decrease in vertical segregation, representing inequality associated with occupational earnings, and increases in horizontal segregation, difference without such inequality. Women strengthened their footholds in the full‐time work force and diversified their breadth of participation, just as men's participation in part‐time and less desirable enclaves began to increase, and as traditionally male occupations experienced both decline and some influx of 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.065
GPT teacher head0.283
Teacher spread0.218 · 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 teacher head, not a consensus.

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

Citations26
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Review of Sociology/Revue canadienne de sociologieSame topicUrban, Neighborhood, and Segregation StudiesFrench-language works237,207