Bibliographic record
Abstract
En 1938, Joseph-Médard Carrière a noté à la main des contes du Détroit — la technologie ne permettant pas alors l’enregistrement des récits — et les a laissés sous forme d’un manuscrit dactylographié en orthographe phonétique qui reproduit de façon intéressante la prononciation du français régional. Comment conserver les particularités de ce parler régional tout en rendant les contes accessibles au plus grand public possible? Soucieux de faciliter la lecture et de conserver la nature orale des textes, nous avons décidé, pour des raisons qui seront discutées en atelier, de transcrire cette collection en orthographe normalisée, puisque la représentation orthographique ne fonctionne relativement bien que si tous les lecteurs suivent les mêmes conventions. La régularisation de l’orthographe semble une tâche facile… Mais quels pièges se cachent à l’intérieur de cette déclaration anodine!
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.016 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".