Remapping Worker Citizenship in Contemporary Occupational Health and Safety Regimes
Bibliographic record
Abstract
The article draws on the rapidly growing field of citizenship studies to map and explore the dynamics of contemporary occupational health and safety (OHS) regulation. Using two key dimensions of OHS regulation (protection and participation), the author constructs four ideal types of worker citizenship (market, public, private industrial, and public industrial citizens). Historically, workers have been written into OHS regulatory regimes in each of these ways. Most recently lawmakers have created a new species of OHS regimes, best described as mandated partial self-regulation. Its distinguishing characteristic is its flexibility, such that worker citizenship can take on any of the forms previously described, often without changing the statutory framework. Using Ontario as an example, the study finds that in the late 20th century, workers made significant strides toward public industrial citizenship and, surprisingly, even under a neoconservative government, workers successfully defended their participatory rights and saw their right to protection modestly strengthened through increased enforcement. The conditions under which this regime operates, however, constantly threaten to undermine the efficacy of worker participation rights and to weaken the enforcement effort. Some suggestions are made about using a citizenship discourse to revitalize the worker OHS movement and strengthen OHS rights.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.059 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| 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 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".