Bibliographic record
Abstract
Cet article a pour objectif d’examiner le rôle des intuitions dans le cadre du problème de la justification des lois logiques de base. Une revue des différentes conceptions de l’intuition permet de mettre les choses en place et d’identifier la conception qui convient le mieux au problème — c’est une conception modale qui sera retenue. Je soumettrai ensuite cette conception à un examen critique, lequel se fera en deux temps. D’une part, il s’agira de montrer la difficulté d’en arriver à une formulation plausible de la conception modale. Je soulèverai d’autre part certains problèmes qui surgissent, même si l’on fait le pari que la question de la formulation peut être résolue. En définitive, je soutiens que, lorsqu’il s’agit d’utiliser les intuitions comme fondement de la connaissance des lois logiques de base, nous devons adopter une conception modale, laquelle n’est pas en mesure de remplir son rôle. Le recours aux intuitions est donc voué à l’échec en épistémologie de la logique.
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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.022 |
| Scholarly communication | 0.009 | 0.015 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".