Beyond ‘Run, Knit and Relax’: Can Health Promotion in Canada Advance the Social Determinants of Health Agenda?
Bibliographic record
Abstract
Can health promotion in Canada effectively respond to the challenge of reducing health inequities presented by the WHO Commission on Social Determinants of Health?Against a background of failure to take seriously issues of social structure, I focus in particular on treatments of stress and its effects on health, and on the destructive congruence of Canadian health promotion initiatives with the neoliberal "individualization" of responsibility for (ill) health.I suggest that the necessary reinvention of the health promotion enterprise is possible, but implausible. RésuméLa promotion de la santé au Canada peut-elle vraiment relever le défi d'une réduction des inégalités en matière de santé, tel que présenté par la commission des déterminants sociaux de la santé de l'OMS?Dans le contexte où les enjeux de la structure sociale ne sont pas vraiment pris au sérieux, je me penche sur le traitement du stress et ses effets sur la santé ainsi que sur la congruence destructive entre les initiatives canadiennes de promotion de la santé et l'« individualisation » néolibérale des responsabilités quant à la (mauvaise) santé.J' avance qu'une réinvention nécessaire du projet de promotion de la santé est possible, bien que peu plausible. Beyond 'Run, Knit and Relax': Can Health Promotion in Canada Advance the SocialDeterminants of Health Agenda?Au-delà de « courir, tricoter et relaxer » : la promotion de la santé au Canada peut-elle faire progresser les déterminants sociaux du programme de santé ?
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.022 | 0.012 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".