Bibliographic record
Abstract
L’objectif de cet article est de cerner la nature de l’idéal d’authenticité, si répandu dans notre culture et nos sociétés contemporaines. Tout d’abord, l’authenticité ne joue-t-elle pas un rôle analogue, par son ampleur et sa vocation à s’appliquer à la totalité de la vie, de ce qu’a été l’idéal de sagesse pour l’Antiquité ? D’autre part, l’authenticité peut-elle se définir simplement comme une sincérité intégrale ? N’est-elle pas plus proche de la vertu d’intégrité ? Nous nous efforçons de montrer l’insuffisance des deux principales voies pour approcher cette notion, celle des théories expressivistes de l’authenticité, d’inspiration romantique, et celle des théories volontaristes qui se sont développées dans le sillage de l’existentialisme : aucune de ces deux approches ne permet de répondre à ce que nous avons appelé le « problème difficile » de l’authenticité.
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 | 0.019 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.094 |
| Scholarly communication | 0.022 | 0.035 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.007 | 0.016 |
| Insufficient payload (model declined to judge) | 0.006 | 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".