Sécuriser le droit pour mieux gouverner les conduites : les enjeux sociopolitiques de la promotion contemporaine de la sécurité juridique
Bibliographic record
Abstract
Dans le troisième article, intitulé « Sécuriser le droit pour mieux gouverner les conduites : les enjeux sociopolitiques de la promotion contemporaine de la sécurité juridique », Rachel Vanneuville (CERAPS-CNRS, Université de Lille) propose dans un premier temps de montrer que le formatage de la question de l’insécurité juridique a conduit à mettre l’activité des juges au coeur de la remise en ordre du droit (I). Nous nous attacherons ensuite aux usages juridictionnels de la sécurité juridique pour saisir comment elle sert à justifier un contrôle accru des juges sur la production législative, comment également elle alimente une revendication à « gouverner » le droit qui confie à ces derniers un rôle sociopolitique étendu (II). Ces transformations, accompagnées d’efforts destinés à les mettre en forme démocratique, portent ainsi à interroger plus largement la redéfinition des lieux et modes de régulation des conduites sociales qui s’y joue.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.014 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".