Canada’s Hidden History of Medical Violence: An Intersectional Feminist Perspective
Bibliographic record
Abstract
Medical violence in the Canadian historical narrative is often overlooked in favour of progress and current advancements. Yet, to deliver compassionate care to all patients requires an understanding and acknowledgement of the medical community’s past and persisting transgressions. The legalization and forced sterilization of Indigenous women is not only an example of blatant disregard for informed consent, but an egregious and continued trauma highlighting the medical community’s policing of marginalized female bodies. In the 1900s and deeply rooted in eugenic theory, sexual sterilization in Canada was framed as the solution for vast disparities in economic classes and social inequities. Indigenous women were disproportionately targeted and vilified by both the Canadian government and the practicing medical body. Such measures nearly halved birth rates in Indigenous populations in as little as two decades. The sociocultural effects of Canada’s medical violence are clear today; laws have yet to pass banning forced sterilization in Indigenous communities, and stereotypes of the ‘promiscuous’ Indigenous woman are cited in current clinical cases with devastating consequences. This article aims to contribute to discourse regarding the violent history of forced sterilization of Indigenous women and describe its institutionalization by the Canadian government as a public health measure with ongoing implications in perpetuating structural racism.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.067 | 0.061 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".