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
Background and context: Healthy school communities aim to optimise student health and educational achievement. Various models, terms and resources have been used to describe healthy school communities. Policy makers and practitioners have reported confusion around many of the key concepts involved because of the varying models and terms. Importantly, practitioners have reported that the lack of clarity impedes progress related to advancing healthy school work. To address these issues and work towards a common understanding of healthy school communities within the Canadian context, a collaborative process involving practitioners, policy makers and researchers culminated in the production of a concept paper. Objective: Here, we describe the process used to develop the concept paper and summarise what is known about healthy school communities and the effectiveness of the approach. Method: Guided by a steering committee and expert panel, we identified, reviewed and summarised key resources to identify common components and principles necessary for a healthy school communities approach. Results: Core components of healthy school communities that emerged include the presence of education, social and physical environments, policy, community partnerships and the use of evidence. Fundamental principles for creating healthy school communities include the adoption of a whole school approach, education and health service synergy, planning and assessment, leadership and sustainability. Here, we describe the iterative and collaborative process to identify these key components and principles. Conclusion: Beyond the Canadian context, this discussion paper describes a process for enhancing communication among organisations and stakeholders invested in healthy school communities internationally.
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 | 0.004 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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