Bibliographic record
Abstract
During my training and early years in practice as a radiation oncologist, I became aware that despite the many contributions of Canadians to the field, there was little written about the history of radiotherapy or cancer control in Canada.I began by asking questions about the history of radiotherapy in specific locations and uncovered the stories of Dr William Roberts and his radium supply in Saint John, New Brunswick, and Dr James Third and his X-ray apparatus in Kingston, Ontario.In the early 19905 cancer care waiting times lengthened considerably, and patients began to be openly dissatisfied with many aspects of their treatment.This crisis prompted me to begin a more thorough examination of the history of radiotherapy and cancer control across Canada to see if I could uncover the origins of the current problems.This book is the result, and I am surprised and humbled to say that it has taken ten years to research and write.Throughout that time, I have received the generous support and help of many individuals and organizations.Chief among them is Associated Medical Services, Inc./Hannah Institute for the History of Medicine Program for their financial support which enabled me to consult archives, libraries, and government records from coast to coast.I am very grateful to my research assistant, Christopher Rutty, for his diligence and hard work in retrieving material.I also am grateful to my friend and mentor in medical history, Jackie Duffin, a superb role model whose activities have taught a radiation oncologist how to frame historical questions and evaluate sources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.287 | 0.199 |
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".