Comparing Federal Indigenous Health Policy Reform in Canada and the United States
Bibliographic record
Abstract
Federal governments in Canada and the United States have followed similar timelines and events in their efforts to support Indigenous self-determination in health care. Since colonization, both settler colonies have aimed to assimilate Indigenous Peoples into settler society, in disregard of inherent Indigenous self-determining rights and titles. By the 1970s their policy agendas shifted towards Indigenous self-determination, including in matters of health service planning and delivery at the community-level. This paper analyzes this shift in policy from a comparative perspective with the aim of informing future reforms. We identify and examine the policy instruments used in the process, finding a greater use of regulatory instruments in the United States, compared to informative tools in Canada. We also discuss the associated impacts of the reform on the ability to practice self-determining activities within communities, highlighting some of the administrative enablers and barriers within and around health care settings. As little research has compared health policy reforms related to matters of Indigenous health in Canada and the United States, this paper provides new insights into the drivers and nature of the policy shift toward self-determination at the federal level and suggests grounds for further investigation. Les gouvernements fédéraux du Canada et des États-Unis ont suivi des chemins parallèles dans leurs efforts pour soutenir l’auto-détermination autochtone en santé. Ces deux colonies de peuplement ont tenté dès l’aube de la colonisation d’assimiler les Peuples Autochtones dans la société des colons, sans égard pour les droits et acquis inhérents aux Autochtones. À partir des années 1970, le discours politique s’est infléchi vers l’auto-détermination autochtone, y compris en matière de planification et de prestation des services de santé au niveau communautaire. Cet article analyse cette inflexion de politique à partir d’une perspective comparative, avec pour objectif de renseigner les efforts futurs de réformes. Nous avons identifié et examiné les outils politiques utilisé dans ce processus, montrant une utilisation plus importante des outils de régulation aux États-Unis alors que le Canada recourait plutôt aux outils d’information. Nous discutons aussi les effets de cette réforme sur la capacité à pratiquer des activités auto-déterminées au sein des communautés, dévoilant certains des facilitateurs et barrières au sein et autour des établissements de soins. Sachant que la recherche comparative sur les politiques de santé autochtone au Canada et aux États-Unis est peu abondante, cet article apporte des éclairages nouveaux sur les facteurs et la nature de l’inflexion politique fédérale en direction de l’auto-détermination et suggère des pistes de recherche future.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".