Bibliographic record
Abstract
Qu’est-ce que lire les autres avec soin lorsque Brayan, étudiant de 16 ans, exprime son désarroi et celui de la classe lors de la lecture d’un dialogue parodique de la Quête du Graal ? Alors que tous, nous étions supposés rire des atermoiements lexicaux d’un Perceval sujet aux sarcasmes d’Arthur et incapable de faire entendre ses demandes, Brayan me fait comprendre que lui et ses camarades se trouvent bien souvent aux prises avec des exigences langagières dans lesquelles ils ne parviennent pas à trouver leur voix. Dans l’arrêt que marque cette revendication, Brayan me fait comprendre que j’avais attribué à la classe un rôle surplombant qui n’était guère que le mien. Ce moment de contre-rythme pédagogique rend l’éthique visible et me fait comprendre le problème moral de la question de l’attention et du soin de la voix d’autrui.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.023 | 0.005 |
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".