Medical Colonialism and the Power to Care: Unsettling Participatory Inclusion in the Settler-State Care Paradigm
Bibliographic record
Abstract
Abstract This article looks at the implications of medical colonialism in Canada for the feminist concept of care. Because medical colonialism is an ongoing material relation where “good” settler care cannot be separated from Indigenous dispossession, I defend the view that care and violence can be coextensive and suggest that a decolonial care ethic needs to disrupt the directionality of care as flowing from agential carers toward colonized care-receivers. I argue that contemporary medical colonialism should indeed be understood as a form of care if structural harm is to be addressed in practice, and trouble the notion of inclusion at work in some contemporary theories of care. By finding demands for assimilationist “participatory inclusion” in examples of government-run, Indigenous-serving care services, I caution against the implicit settler-colonial assumptions in notions of “caring democracies” and “caring societies” on the welfare-state model. If care is political and can participate in the normative pressures of civic assimilation, then to “decolonize” it through refraction, disruption, infiltration, disconnection, re-appropriation, and resistance also means to “decolonize” citizenship and civic life in the interests of Indigenous self-determination, rather than presumed inclusion in settler-state processes.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.128 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 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".