Bibliographic record
Abstract
Dans quelle mesure la culture mémorielle forgée dans le sillage des catastrophes historiques du XX e siècle peut-elle éclairer la narration des pertes autres qu’humaines ? En cette période d’extinction massive des espèces animales et végétales, le massacre et la disparition des autres formes de vie travaille la culture dans des termes analogues à ceux de la mort en masse : deuil, mélancolie, pertes incommensurables. Mais cette extension du domaine du chagrin aux autres qu’humains n’est pas sans poser problème. Comment se souvenir de toutes les vies animales et végétales perdues, une à une, quand le vécu de tant de vies humaines, déjà, nous échappe ? De quelle manière la littérature ou les sciences sociales pourraient-elles réparer des pertes que nous n’appréhendons qu’en masse, ou pas du tout ?
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".