The Challenge of Exposing and Ending Health Inequalities through Social and Policy Change: Canadian Experiences
Bibliographic record
Abstract
The Canadian health system is often perceived as excellent. However, a closer examination of the political economy of health in Canada shows a radically different picture. It is a picture of persistent inequality and a history of the inability to address such inequality. Despite numerous public policy interventions to address preventable health inequalities-that is, health inequities-this societal problem persists. This research addresses how and why health inequities, especially class, race/ethnicity, and gender health inequities, persist in Canada and how to reduce such differences through public policy action. To address these questions, I performed a critical realist review, focusing on the political economy of health and policy change. Then I conducted a thematic analysis of the interview data gathered from 23 semi-structured interviews with leading Canadian policy academics, activists, and advocates. The results demonstrate that the capitalist economic system; the co-constitutives of capitalism, namely colonialism, racism, and sexism; and maldistributive public policies primarily cause health inequities in Canada. Canada's health inequities reduction requires pushing for redistributive public policies; uniting and strengthening labor unions, civil society groups, and social movements; and engaging in electoral politics. Reducing health inequities may involve struggling within and against capitalism and struggling for socialism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".