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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".