Comparable Worth Comes to the Private Sector: The Case of Ontario
Bibliographic record
Abstract
We investigate the effect of pro-active comparable worth legislation, covering both the public and private sectors, on wages, employment and the gender gap. Our focus is the pay equity initiative adopted by the Canadian province of Ontario in the early 1990s. Our preliminary finding is that the law fell short of its goal of reducing gender based wage differentials.Firm surveys indicate that the effect of the legislation was blunted by lack of compliance in small private firms, the low incidence of undervalued female work in larger firms, and more generally the lack of male comparators for female jobs. These sorts of problems would appear endemic to any attempt to extend comparable worth to the private sector of a decentralized labor market. Our analysis of individual level data, which uses difference--in--difference models, kernel regressions and kernel density estimations, suggests that even in those sectors where the legislation had ``bite'' (among non-unionized workers in larger establishments), any positive effects on the wages of females in female jobs were very modest. Our most consistently estimated effects of the law on wages are negative: slower wage growth for females in male jobs and for males in female jobs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".