Understanding Health Equity: Key Concepts, Debates, and Developments in Canada
Bibliographic record
Abstract
Health inequalities exist and persist due to the quality and distribution of the social determinants of health, i.e., the day to day circumstances people live in. These circumstances are determined by governing policies and practices which are influenced by the State’s political ideology and its socio-economic structures. Using a political economy approach, this paper takes a critical review of the literature on health equity in the Canadian context and clarifies key concepts pertaining to health equity and human rights. Findings of this review show that Canada has been performing poorly in addressing growing health inequalities, in part because of Canada’s increasingly neo-liberal stance on public health over the last decade. This paper will argue that a human rights framework can offer a concrete tool for restructuring public policies and for taking action against these inequalities. By placing health equity on the policy agenda, Canada can help reduce social and income inequalities and optimize the health of its populations.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.014 |
| Science and technology studies | 0.017 | 0.024 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".