Bibliographic record
Abstract
Tuberculosis, once a leading cause of death in Europe and North America, was understood to be preventable and even curable by the early twentieth century. Yet despite growing knowledge about the disease and interventions that would slow its spread, tuberculosis deaths among First Nations in Canada remained staggeringly high. Government policies rooted in colonialism exacerbated a tuberculosis epidemic. Wilful Neglect explores the devastating consequences of the Department of Indian Affairs’ failed responses to tuberculosis among First Nations in Canada from 1867 to 1945. Even when medical treatment for tuberculosis became widely available, and despite the federal government’s obligations being written into treaties and other legislation, the basic health needs of First Nations remained unmet. The government instead prioritized an assimilationist agenda, including the placement of Indigenous children in residential schools, which became hotbeds for the spread of the infection. Drawing on the department’s own annual reports, memoranda, and budgets over more than seventy years, Jane Thomas traces key moments, decisions, and individuals involved in shaping federal health policy, laying bare the consequences of racializing a disease. Health policies developed by colonial governments without the involvement of First Nations have always failed. Wilful Neglect demonstrates a direct link between the federal government’s historic health policies and the disparities that continue into the present.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.017 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".