Settings for Health Promotion: Linking Theory and Practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Settings Approach to Health Promotion - Lawrence W Green, Irving Rootman and Blake D Poland Home and Families as Health Promotion Settings - Hassan Soubh and Louise Potvin Commentary - Lawrence Fisher Commentary - Ilze Kalnins The School as a Setting for Health Promotion - Guy Parcel, Steven Kelder and Karen Basen-Enquist Commentary - Cheryl Perry Commentary - Peter McLaren, Zeus Leonardo, Xochitl Perez Promoting the Determinates of Good Health in the Workplace - Michael Polanyi et al Commentary - Robert Bertera Commentary - Joan Eakin The Health Care Institutions as Settings for Health Promotion - Joy Johnson Commentary - Jane Lethbridge Commentary - Patricia Mullen and L Kay Bartholomew Health Promotion in Clinical Practice - Vivek Goel and Warren McIsaac Commentary - David Butler-Jones Commentary - Jane Zapka Community as a Setting for Health Promotion - Marie Boutilier, Shelley Cleverly and Ronald Labonte Commentary - John Raeburn Commentary - Evelyn deLeeuw The State as a Setting - John Lavis and Terrence Sullivan Commentary - Marshal Kreuter Reflections on Settings for Health Promotion - Blake D Poland, Lawrence W Green and Irving Rootman
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it