Canadian report card on health equity across the life-course: Analysis of time trends and cross-national comparisons with the United Kingdom
Bibliographic record
Abstract
Addressing social determinants of health (SDoH) has been acknowledged as an essential objective for the promotion of both population health and health equity. Extant literature has identified seven potential areas of investment to address SDoH: investments in sexual and reproductive health and family planning, early learning and child care, education, universal health care, as well as investments to reduce child poverty, ensure sustainable economic development, and control health hazards. The aim of this paper is to produce a ‘report card’ on Canada’s success in reducing socioeconomic and health inequities pertaining to these seven policy domains, and to assess how Canadian trends compare to those in the United Kingdom (UK), a country with a similar health and welfare system. Summarising evidence from published studies and national statistics, we found that Canada’s best successes were in reducing socioeconomic inequalities in early learning and child care and reproductive health—specifically in improving equity in maternal employment and infant mortality. Comparative data suggest that Canada’s outcomes in the latter areas were like those in the UK. In contrast, Canada’s least promising equity outcomes were in relation to health hazard control (specifically, tobacco) and child poverty. Though Canada and the UK observed similar inequities in smoking, Canada’s slow upward trend in child poverty prevalence is distinct from the UK’s small but steady reduction of child poverty. This divergence from the UK’s trends indicates that alternative investment types and levels may be needed in Canada to achieve similar outcomes to those in the UK. • We summarize trends in health equity in Canada and compare Canadian trends to those in the United Kingdom (UK). • Trends were assessed according to seven previously-identified domains of societal-level investments. • Canada’s best improvements were in early learning and care and reproductive health. Trends were similar to those in the UK. • Canadian equity trends in employment and universal health care were stable, and outperformed by those in the UK. • Canada’s least promising trends were in smoking and child poverty. Unlike in the UK, child poverty has increaesd in Canada.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.032 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".