Six essential roles of health promotion research centres: the Atlantic Canada experience
Bibliographic record
Abstract
Over the past 20 years, the federal government and universities across Canada have directed resources towards the development of university-based health promotion research centres. Researchers at health promotion research centres in Canada have produced peer-reviewed papers and policy documents based on their work, but no publications have emerged that focus on the specific roles of the health promotion research centres themselves. The purpose of this paper is to propose a framework, based on an in-depth examination of one centre, to help identify the unique roles of health promotion research centres and to clarify the value they add to promoting health and advancing university goals. Considering the shifting federal discourse on health promotion over time and the vulnerability of social and health sciences to changes in research funding priorities, health promotion research centres in Canada and elsewhere may need to articulate their unique roles and contributions in order to maintain a critical focus on health promotion research. The authors briefly describe the Atlantic Health Promotion Research Centre (AHPRC), propose a framework that illustrates six essential roles of health promotion research centres and describe the policy contexts and challenges of health promotion research centres. The analysis of research and knowledge translation activities over 15 years at AHPRC sheds light on the roles that health promotion research centres play in applied research. The conclusion raises questions regarding the value of university-based research centres and challenges to their sustainability.
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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 | 0.040 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.054 | 0.032 |
| Scholarly communication | 0.022 | 0.007 |
| Open science | 0.005 | 0.016 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".