Bibliographic record
Abstract
Dans cet article, je me pose la question de l’emploi du concept de vérité par la critique littéraire et je me concentre sur la théorie : « pas de vérité en littérature », élaborée par Peter Lamarque et Stein Haughom Olsen. Je tâche de développer et d’approfondir certaines critiques de leurs thèses et arguments, afin d’en proposer une évaluation d’ensemble. Je conclus que le problème principal avec Lamarque et Olsen est qu’ils veulent exclure toute considération de vérité en littérature — endossant ainsi une conception de la création littéraire plus ou moins expressiviste — tout en sauvegardant la reconnaissance de la vérité de nos croyances concernant une série de notions de ce qui est d’intérêt humain et des valeurs universelles non formelles. Leur approche risque ainsi de sombrer dans l’incohérence.
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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.038 |
| Scholarly communication | 0.015 | 0.020 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 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".