Use and effectiveness of policy briefs as a knowledge transfer tool: a scoping review
Bibliographic record
Abstract
Abstract There is a significant gap between researchers’ production of evidence and its use by policymakers. Several knowledge transfer strategies have emerged in the past years to promote the use of research. One of those strategies is the policy brief; a short document synthesizing the results of one or multiple studies. This scoping study aims to identify the use and effectiveness of policy briefs as a knowledge transfer strategy. Twenty-two empirical articles were identified, spanning 35 countries. Results show that policy briefs are considered generally useful, credible and easy to understand. The type of audience is an essential component to consider when writing a policy brief. Introducing a policy brief sooner rather than later might have a bigger impact since it is more effective in creating a belief rather than changing one. The credibility of the policy brief’s author is also a factor taken into consideration by decision-makers. Further research needs to be done to evaluate the various forms of uses of policy briefs by decision-makers.
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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 | 0.199 | 0.434 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.033 | 0.026 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".