« We have our own kitchen » : distance et légitimité dans la production de savoir pour la procédure d’asile
Bibliographic record
Abstract
La stricte séparation entre la production d’informations sur les pays d’origine (COI pour country of origin information) et l’évaluation des demandes d’asile est une norme fondamentale de la pratique professionnelle des producteurs de COI. En se penchant sur l’unité COI norvégienne, cet article examine la manière dont cette séparation est matérialisée à travers une véritable infrastructure de distanciation mise en place autour des sites de production des COI. Ce dispositif se manifeste non seulement dans les discours et les pratiques, mais aussi dans les structures organisationnelles, les lieux et les normes légales qui participent à l’écologie de la situation d’expertise particulière que constituent les COI. Il participe à la construction de la légitimité des institutions, mais aussi des acteurs impliqués dans la production du savoir.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.025 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".