Involving Decision-Makers in Producing Research Syntheses: The Case of the Research Collective on Primary Healthcare in Quebec
Bibliographic record
Abstract
This paper reports on a research collective on primary healthcare (PHC) conducted in Quebec in 2004. Thirty ongoing or recently completed studies were synthesized through a process involving a high degree of exchange among researchers who conducted the original studies, investigators and decision-makers. The viewpoints expressed by decision-makers who participated in the process were analyzed in terms of convergence with and divergence from the researchers’ viewpoints. In four cases, there was convergence between the decision-makers’ and the researchers’ viewpoints, thus increasing the validity of the collective’s findings. The main divergence between the two groups’ viewpoints concerns the strategy adopted in Quebec to create local health and social services networks. Such divergence reflects the distinction made by Klein between scientific evidence and organizational and political evidence. Our study results illustrate that decision-makers’ viewpoints can play an important interpretive and complementary role in producing research syntheses. Although integrating decision-makers’ viewpoints into syntheses has been regarded as a strategy for improving the use of research findings, our analysis shows that decision-makers’ view-points do not necessarily have to be integrated into syntheses but can, instead, be examined for convergence with or divergence from researchers’ viewpoints. This deliberative process can enrich discussions and lead to enlightened decision- and policy making.
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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 | 0.015 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".