Masculinity, Medicine and Mechanization. The Construction of Occupational Health in Northern Ontario
Bibliographic record
Abstract
This dissertation examines workplace issues and events that shaped men’s health, and the healthcare services in support of them, in northern Ontario’s resource extraction industries. Between 1890 and 1925 there were important transformations in the hardrock mining sector including: technological innovations and refinements of the materials and devices used to extract ores; the healthcare mandated and legislatively prescribed but challenging to deliver to frontier workspaces; and how the complex interactions of the men, their work, their communities, wartime demands and collective bargaining combined to construct new definitions of masculinity. \nUsing quantitative data from the Ontario Bureau of Mines on the numbers of annual accidents and fatalities, a clearer understanding emerges that reveals how workingmen’s bodies were understood over time. Together with newspaper accounts, the reports of coroners’ juries, personal papers, doctors’ memoirs and popular histories, the role of work and workplace conditions clarifies how health was managed or how it suffered as the exploitation of the provinces natural resources began in earnest. The impact of World War One caused a wholesale change in the scale and importance of the mines and the men that worked them. This was seen in their solidarity, strength and successful strike immediately after the war and in fewer accidents and fatalities. The pace of change however faded in the post-war era. The gains that were made were kept and men’s health and safety never again saw the alarming losses as those enumerated here.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".