Pay equity and nursing in Ontario: ten years later
Bibliographic record
Abstract
'Nurses have never been compensated in accordance with their central role in health care' (Schreiber 1994), reflecting the generalized and well-documented under-valuing of the work of women (Schreiber 1993). Pay equity legislation, passed in Ontario, Canada in 1987, designed to correct gender wage discrimination, created great optimism that the under-valuing of nurses' work might be ending. Nonetheless, this has not been the case, as the social, political, and economic climate has not kept pace with the speed and enormity of social change necessary to enact the intent of the legislation. Indeed, gains in nurses' wages have been directly offset by significant lay-offs. In this paper, we examine the issues surrounding the implementation of pay equity legislation in Ontario, Canada, along with analysis and implications of these issues, drawn from 10 years of experience. In addition, we highlight lessons that can be learned from the Ontario experience.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".