The Gender Composition and Wages: Why is Canada Different from the United States?
Bibliographic record
Abstract
The correlation of occupational gender composition and wages is the basis of pay equity/comparable worth legislation. A number of previous studies have examined this correlation in US data, identifying some of the determinants of low wages in "female jobs", as well as important limitations of public policy in this area. There is little evidence, however, from other jurisdictions. This omission is particularly disturbing in the case of Canada, which now has some of the most extensive pay equity legislation in the world. In this paper, we provide a comprehensive picture, circa the late 1980's, of the occupational gender segregation in Canada and its consequences for wages. We also draw explicit comparisons of our findings to evidence for the United States. We find that the link between female wages and gender composition is much stronger in the United States than in Canada, where it is generally small and not statistically significant. The relatively more advantageous position of women in female jobs in Canada is found to be linked to higher unionization rates and the industry-wage effects of "public goods" sectors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".