Bibliographic record
Abstract
La tolérance et la neutralité sont habituellement considérées comme des réponses interchangeables ou du moins complémentaires à des situations de conflit et de désaccord moral. Malgré cette association traditionnelle, plusieurs auteurs ont récemment contesté la complémentarité, voire même la compatibilité, de ces deux notions. Cet article examine tout d’abord deux arguments qui visent à établir l’incompatibilité de la tolérance et de la neutralité. Il montre ensuite que si ces arguments ne sont pas probants, en ce sens qu’ils ne parviennent pas à montrer l’impossibilité d’une conciliation entre tolérance et neutralité, ils mettent néanmoins en évidence deux difficultés qui se dressent sur le chemin d’une telle conciliation. Il introduit enfin une conception particulière de la tolérance fondée sur l’idée de justice et indique comment elle permet de remédier aux difficultés précédemment mises en évidence.
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 | 0.020 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.057 |
| Scholarly communication | 0.016 | 0.024 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.007 | 0.011 |
| 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".