L’évaluateur éthiquement engagé: sur le sens et la pertinence d’un nouveau référentiel
Bibliographic record
Abstract
Abstract: The concept of an evaluator’s “commitment,” also referred to as “advocacy” in the English literature and “plaidoyer” in the French literature, remains a subject of debate within the evaluation community. As evaluators, should we ban all forms of personal commitment to preserve the “neutrality” of our evaluations? Instead, should we commit ourselves to increasing the quality of evaluations, or to promoting certain values? What forms of commitment should then be recommended? Through a literature review, we attempt to clarify the different understandings underlying the use of this concept, and we examine how recent epistemological and moral changes in the field of evaluation have greatly amplified its meaning and its implications for the practice. We suggest that an “ethical commitment” may have a methodological and/or moral purpose, and that, ethical or not, the evaluator’s commitment is inevitably present throughout the evaluation process.
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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 | 0.092 | 0.199 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.009 | 0.027 |
| Scholarly communication | 0.021 | 0.013 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".