Bibliographic record
Abstract
Concept issu des sciences infirmières et ici appliqué de façon innovante à l’évaluation, la sécurisation culturelle désigne une démarche visant à faire en sorte que l’évaluation se déroule d’une façon « sûre » pour les parties prenantes et notamment les communautés minorisées cibles de l’intervention étudiée, c’est-à-dire que le processus d’évaluation évite de reproduire des mécanismes de domination (agression, déni d’identité…) liés à des inégalités structurelles. Pour cela, diverses techniques participatives sont mobilisées à toutes les étapes de l’évaluation. La sécurisation culturelle est compatible avec tous types de méthodes. Elle contribue à rendre l’évaluation plus pertinente et utile pour les parties prenantes, et est susceptible d’accroître leurautodétermination.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.021 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.021 |
| Scholarly communication | 0.017 | 0.007 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".