No Right to be Safe: Justifying the Exclusion of Alberta Farm Workers from Health and Safety Legislations
Bibliographic record
Abstract
Alberta remains the only Canadian province to exclude agricultural workers from the ambit of its occupational health and safety laws. Consequently, farm workers have no right to know about workplace safety hazards and no right to refuse unsafe work, thereby increasing their risk of a workplace injury. This study uses qualitative content analysis to identify three narratives used by government members of the legislative assembly between 2000 and 2010 to justify the continued exclusion of agricultural workers from basic health and safety rights. These narratives are: (1) education is better than regulation, (2) farms cannot be regulated, and (3) farmers don’t want and can’t afford regulation. Analysis of these narratives reveals them to be largely invalid, raising the question of why government members rely upon these narratives. The electoral rewards associated with maintaining this exclusion may comprise part of the explanation.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.029 | 0.033 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| 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".