Daubert et les limites de la phénoménologie : Étude sur le donné et l'évidence
Bibliographic record
Abstract
Johannes Daubert (1887-1947) est la figure centrale du Cercle de Munich ainsi que le premier véritable lecteur et critique de Husserl. Ses manuscrits contiennent, en plus d'une critique de la phénoménologie husserlienne, une conception originale de la phénoménologie laissant notamment une place importante aux analyses perceptives. Le présent article s'intéresse d'abord aux thèmes du donné ( gegeben, Selbstgegeben ) et de l'évidence en tant qu'ils sont des motifs centraux à la fois chez Husserl et Daubert, pour ensuite relever, à partir d'une étude des manuscrits pertinents, la particularité des analyses daubertiennes concernant ces thèmes, ainsi que les contraintes ou limites que la phénoménologie doit s'imposer pour notamment se distinguer du rationalisme.
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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 | 0.019 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.010 | 0.062 |
| Scholarly communication | 0.011 | 0.024 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".