Stacie Burke, Building Resistance: Children, Tuberculosis, and the Toronto Sanatorium
Bibliographic record
Abstract
When 13-year-old Charlotte was admitted to the Toronto sanatorium in November 1933, her brother Carl was already a patient, and they had lost their parents and two siblings to tuberculosis. Canada’s tuberculosis death rate that year was 41.6 per 100,000. Although a significant reduction from the 180 to 200 deaths per 100,000 in 1900, tuberculosis remained a common cause of premature mortality and morbidity until the rise of institutionalised systems to tackle social inequalities and the advent, during the 1950s, of drug therapies. William Dobbie (1873–1942), physician-in-chief of the Toronto sanatorium from its opening in 1905 to 1939, suggested that the proportion of children infected with tuberculosis bacteria reached 90 per cent at age 15. However, it was the observation that only 10 per cent of those latently infected actually experienced active disease that encouraged investment in resistance building, both in family homes and sanatoria. Stacie Burke’s in-depth qualitative study, based on 822 case histories from the Toronto sanatorium over a 50-year period (c.1905–1950), is an excellent, authoritative and very readable addition to the growing historiography of childhood tuberculosis and the lived experience of tuberculosis among child sanatorium patients. The children in this study range in age from infancy to 17 years. The author’s intention, as a biological anthropologist, has been to intertwine social and biological dynamics in tuberculosis. She argues that the biology of the body and tuberculosis came to be understood via scientific principles, but there were differing interpretive aspects among patients, families and physicians. She explores the growing research into lung physiology, immunological mechanisms in tuberculosis and the behaviour of the tuberculosis bacteria. New knowledge underpinned the development of treatments from ‘noninterventionist’ bedrest to direct bodily manipulations. All of the treatments aimed to slow the progression of the disease and give the immune system time to respond more effectively.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.014 | 0.012 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| 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".