Public Policy and Population Health: Why Is There So Little Public Policy Attention in Support of Health?
Bibliographic record
Abstract
Intemational interest in the social determinants of heahh and their public policy antecedents is inqeasing. comparing with other weakhy nations, Canala presenl a mediocre population heabh profile cmd public policy enuironments increuingly less supportiorc of heabh. Howeuer, the cmadian public heabh gaze is firmly - and nmrowly - focused on hfestyle iswes ofadiet, physical actiotity cmd tobacco use. Reasctns for caneda's neglect of structwal ancl public policy issaes are explored and Ten Ttps for Cana.dian Public Heahh Resectrchers andWorkers a-e presented. Lintdr€t mondial poru les ditermincn'tts sociaux de la sant6 et bs politiEtes qui s'y rat. nchent est grandissant. En compm'aison aorcc les autres pals rlches, le Cauda prasente m profil de smt6 midiocre et le soutien apf>ort6 par I'enuiromtement des politiques publiques ua en diminuant. Malgr6 cette situatioll, la santi publique canadienne pose wt regard fixe - et €toit - centrd xn les questions reliles au srylr de uie telles que l'alimentation, I'actiuit| physiq,Le et la consommatictn de tabac. Les raisons de kr n6gligence du Cawdt des questions de structlzres et de politiques publiques sont explor6es et Dix con.seils poru bs cherchews et trauailbw's en sant€ pubtique , sont pr€sentls.
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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 | 0.021 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.005 | 0.025 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".