Bibliographic record
Abstract
En l’absence des manuscrits originaux, la collecte considérée comme la plus riche de Basse-Bretagne n’est pas sans poser de problèmes. Outre le fait de passer d’un oral breton à un écrit français, le collecteur, s’adressant à un public qui n’est pas celui qui portait les récits qu’il publie, éprouve le besoin de les accompagner d’ajouts, de « commentaires explicatifs », de notes. Au-delà de cette situation singulière, cela me semble poser un problème plus général lié à l’édition de récits oraux : la possession par un auditoire homogène de références communes, de croyances partagées, conduit celui qui parle à faire l’impasse sur bien des éléments connus de tous. La transcription fidèle de la parole du conteur ne peut évidemment rendre compte de ce non-dit. Convient-il alors, en passant de l’oral à l’écrit, d’expliciter ce référent que ne possède généralement pas le lecteur « non initié »? Si oui, comment et sous quelle forme?
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".