Knowledge Activists on Health and Safety: Workmen-Inspectors in Metalliferous Mining in Australia 1901–25
Bibliographic record
Abstract
Worker campaigns for a more direct say in protecting their health and safety are a significant but under-researched subject in labour history. Largely overlooked are the attempts by coalminers in the UK, Australia and Canada to establish mechanisms for representation on health and safety in the 1870s. This push for a voice then spread to New Zealand, France, Belgium and other countries, with unions eventually securing legislative rights to inspect their workplaces a century before workers in other industries gained similar entitlements. In Australia metalliferous miners' unions followed coalminers in initiating a parallel campaign for the right to appoint their own mine-site and district inspectors (known as "check-inspectors") from the late nineteenth century. This article examines the struggle for and activities/impact of workmen-inspectors in Australian metalliferous mines, including adoption of the competing UK–Australian and Continental-European models. It finds the development conforms to a resistance rather than mutual-cooperation perspective with check-inspectors performing the role of "knowledge activists." The article argues this finding is not only relevant to understanding more recent experience of worker involvement in occupational health and safety but also demonstrates the relevance of historical research to contemporary regulatory policy debates and union strategies.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.015 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| 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".