Unhealthy Policies: The Role of Citizenship in the Government Response to Tuberculosis in Indigenous Populations 1945-2015
Bibliographic record
Abstract
At a time when the overall national rates of tuberculosis in Canada are among the lowest in the world, the rates of tuberculosis among the Canadian Indigenous population are ten to twenty times higher than among the Canadian non-Indigenous population.In light of factors such as Canada's universal health care system and advancements in public health and medical interventions over the past century, the question remains as to why this disparity continues to exist.Finding the answer to that question lies at the core of this research project.It involves the analysis of a complex array of factors that lie at the intersection of public policy, politics, and the place in society that the Canadian federal government continues to attribute to Indigenous peoples.The relationship between federal policies and health and social inequalities in Indigenous communities is examined through the lens of state power and citizenship.It's the federal government who exercises the power to define the scope of its responsibility for 'Indians, and lands reserved for Indians' under Section 91 (24) of the Constitution Act.It is the federal government, not Indigenous peoples, who further decides who is an 'Indian' under the Indian Act for the purposes of determining who is eligible for federal services.This research project studies the impact of the federal government's position that it does not recognize a treaty or legal obligation for Indigenous health, and that it provides health services as a matter of policy only.Citizenship theories provide the analytical lens with which to review how the federal government chooses to include and exclude certain sub-groups of Indigenous peoples based on their Indian Status, whether they live on or off reserve, and based in which provincial or territorial jurisdiction they reside.The result is an ad-hoc network of service delivery across Canada.This research project demonstrates that the federal government's own Indigenous health policies play a central role in perpetuating the health and social inequalities that are contributing factors to the elevated rates of tuberculosis that persist in Indigenous communities.6 David Butler-Jones, "Tuberculosis-Past and Present", in The Chief Public Health Officer's Report on the State of Public Health in Canada: 2010.Public Health Agency of Canada, 2010; G. Alvarez, "TB in Canada -The Battle is not Over", in Canada Communicable Disease Report: Volume 41-S2, March 19, 2015, Public Health Agency of Canada, 2015.7 M. Jensen et al, A population-based study of tuberculosis epidemiology and innovative service delivery in Canada.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".