Seeds of Discord: The Politics of Radon Therapy in Canada in the 1930s
Bibliographic record
Abstract
In the early twentieth century, the therapeutic use of radon gas became an accepted medical practice. "Radium emanation" plants were established in many parts of North America to supply radon seeds to physicians. In Canada, these plants were usually established as part of state-supported cancer programs, creating concern among the medical profession, which had hitherto directed cancer treatment. This article explores how issues surrounding the ownership and distribution of radon played out in two Canadian provinces, Manitoba and Ontario. The main focus is an analysis of a computerized database created from more than two thousand radon order forms, dating from 1933 to 1940, preserved in the Archives of Ontario, which reveals interesting information about patients and the uses of radon in the 1930s, as well as discrepancies between policy and practice that illuminate the medical politics of the era. Although the radon seeds were intended for use in the government-supported central cancer clinics, they were widely distributed to practitioners throughout Ontario, and many patients received treatment for noncancerous conditions. These discrepancies are explored in the context of the struggles over cancer policy between the government and the Ontario medical profession. The article also shows how similar conflicts evolved in Manitoba. Finally, the distribution of radon is linked to the public acceptance of medical radiation despite contemporary reports of harm.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.035 | 0.023 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".