Promotion de la santé au Canada et au Québec, perspectives critiques
Bibliographic record
Abstract
Depuis la Charte d’Ottawa de 1986, le champ de la promotion de la santé a profondément influencé l’évolution des systèmes de santé partout au monde. Au cœur de cette évolution, le Canada et le Québec. Plus de 80 auteurs, incluant les experts les plus reconnus sur les scènes internationale, canadienne et québécoise de même que des auteurs des générations montantes, analysent de manière critique l’état du champ au Canada et au Québec ainsi que son influence internationale depuis 1994. Cette première édition en français d’un ouvrage classique passionnera les intervenants professionnels et communautaires, décideurs, étudiants, enseignants, chercheurs, militants et personnes du grand public de toute la Francophonie intéressés à comprendre ce qu’est la promotion de la santé ici et ailleurs. Ont contribué à cet ouvrage : Layla I. Al-Jasem, Monique Allain, Robert C. Annis, Hiram V. Arroyo, Winnie Banfield, Linda Bartlett, Nicole F. Bernier, Nathalie Boivin, Marie Boutilier, Deborah Bradley, Nancy Campbell, Dora Cardaci, Simon Carroll, Amy Caughey, Maria-Teresa Cerqueira, Fiona Chin-Yee, J. Hope Corbin, Sandra Crowell, Suraya Dalil, Irina Dinca, Milka Donchin, Tatiana Pluciennik Dowbor, Sophie Dupéré, Monica Eriksson, Stacey Forsberg-Wilson, Jim Frankish, Katherine L. Frohlich, Lise Gauvin, Natalie Gierman, Gaston Godin, Carmelle Golberg, Wayne Govereau, Lawrence W. Green, Carol Gregson, Laurence Guillaumie, Robert A. Hiatt, Marcia Hills, Brian Hyndman, Suzanne F. Jackson, Amal Hussain Jassem, Masamine Jimba, Margot Kaszap, llona Kickbusch, Nadiya Komarova, Ainiak Korgak, Ronald Labonte, Marie-Claude Lamarre, Diane Levin-Zamir, Bengt Lindström, Irit Livne, Kelly Loubert, Renee Lyons, Gordon Macdonald, Marlien MacKay, Rick Manuel, Moncef Marzouki, Robin Mason, David V. McQueen, Lilach Melville, Maurice B. Mittelmark, Maryna Murashova, Donna Murnaghan, Yuka Nomura, Michel O’Neill, Ann Pederson, Lavada Pinder, Blake Poland, Laraine Poole, Louise Potvin, Iraj M. Poureslami, Frances E. Racher, John Raeburn, Dennis Raphael, Colleen Reid, Helena E. Restrepo, Lucie Richard, Valéry Ridde, Jan Ritchie, Irving Rootman, Judith Salinas, Awa Seck, Louise Signal, Jean Simos, Shirley Solberg, Louise St-Pierre, Alison Stirling, Eleanor Swanson, Hélène Valentini, Ardene Vollman, Shukrrullah Wahidi, Márcia Faria Westphal, Lewis Williams, Patricia L. Williams, Doug Willms, Doug Wilson, Marilyn Wise
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.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.022 | 0.018 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| 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".