Les dispositifs de la participation aux étapes stratégiques de l’évaluation
Bibliographic record
Abstract
Abstract: A growing number of tools are now available to enhance the validity and social relevance of knowledge produced through the participatory spaces that program evaluation makes possible. Tools that facilitate a shared understanding of a program and its results are of this nature. However, evaluation teams are generally less equipped to support participation through the strategic processes of planning an evaluation or of redesigning a program based on evaluation results. This article presents social and technical processes that can enhance the participation of actors from the program system in these strategic choices. In addition to the usual tools that support program modeling mechanisms and validation of research results, the instruments presented address the implementation of a participatory space, choice of evaluation questions, assessment of findings, and purposeful deliberation on future program directions. These instruments enhance the social contribution of evaluation by introducing greater rationality in participatory evaluation.
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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 | 0.194 | 0.298 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.025 | 0.015 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".