Engaging with Policy Makers: The Need for Accessible and Timely Health Services and Systems Research in 2020
Bibliographic record
Abstract
In its conception, Healthcare Policy was a partnership between the canadian Institutes of Health Research's Institute of Health Services and Policy Research (IHSPR), the Canadian Association of Health Services and Policy Research and Longwoods Publishing. With the support of IHSPR's scientific director at the time, Dr. Morris Barer, the objective of the journal was to "stimulate communication and cross-fertilization between researchers and healthcare decision makers" (Government of Canada 2006). With a strong focus on knowledge translation and interdisciplinary research, the journal links policy makers with researchers, thus carrying its founding objective forward as a guiding principle for Healthcare Policy.
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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 | 0.052 | 0.126 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.035 | 0.020 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.038 | 0.037 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".