Bibliographic record
Abstract
The Ottawa Charter for Health Promotion calls for building healthy public policy, that is for '[putting] health on the agenda of policy makers in all sectors and at all levels, directing them to be aware of the health consequences of their decisions and to accept their responsibilities for health'. The objective of this study was to assess the past and potential future influence of information about the health consequences of unemployment and job insecurity on policy making and to identify the barriers to the use of such information in policy making. We conducted telephone interviews with 38 policy makers in the health and employment sectors of all three levels of Canadian government, as well as the executive directors of 10 Canadian non-governmental organizations that are active on employment issues. The interviews included both numerical ratings of the influence of this information and semi-structured questions about how this information could be used in policy making. Using an interpretive approach grounded in the political science literature, we identified barriers to using this information in their responses to these questions. Respondents rated the potential future influence of this information (mean 4.2 and median 5 on a seven-point Likert scale) higher than its past influence (mean 3.5 and median 3 on a seven-point Likert scale). Barriers related to the information itself or more commonly to the values of those who could respond to the information (i.e. idea-related barriers) were cited more frequently than either barriers related to how decisions are made (i.e. institution-related barriers) or barriers related to who would win and who would lose if the information were acted upon (i.e. interest-related barriers). We concluded that to build employment-related healthy public policy, these barriers would have to be overcome. Policy makers in health departments could, for example, frame information about health consequences in language that fits more easily with the values of other departments and advocate for institutional innovations that establish cross-departmental or cross-governmental accountability for health.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".