Supporting the diffusion of healthy public policy in Canada: the Prevention Policies Directory
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
Healthy public policy plays an essential role in a comprehensive public health approach to preventing cancer and chronic disease. Public policies spread through the 'policy diffusion' process, enabling governments to learn from another's enacted policy solutions. The Prevention Policies Directory (the Directory), an online database of municipal, provincial/territorial, and federal cancer and chronic disease prevention policies from across Canada, was developed to facilitate the diffusion of healthy public policies and support the work of prevention researchers, practitioners, and policy specialists. This information technology solution was implemented, through a participatory engagement approach, as a communication channel or policy knowledge transfer tool. It also addressed the intrinsic shortcomings of environmental scanning for policy surveillance and monitoring. A combination of quantitative web metrics and qualitative anecdotal evidence have illustrated that the Directory is becoming an important tool for healthy public policy surveillance and policy diffusion in Canada.
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 | 0.034 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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