L’enseignement du droit et les nouvelles technologies : sommes-nous prêts pour un enseignement-apprentissage en réseau ? Le cas d’un projet pilote d’enseignement de la légistique
Bibliographic record
Abstract
Les modes de formation et de circulation des modèles juridiques, et la circulation de ces modes eux-mêmes à l’ère technologique, impliquent une nouvelle approche de l’enseignement et de l’apprentissage du droit. Dans ce nouveau cadre, qui n’est déjà plus de l’ordre de l’imaginaire, réfléchir, enseigner et transmettre des compétences relatives à la conception et à l’élaboration d’actes normatifs n’est pas une tâche facile pour les facultés de droit. C’est ce qui a amené l’auteure à tenter cette expérience qu’a été et que reste le réseau legistica.ning comme milieu d’enseignement et d’apprentissage dans le contexte du cours de légistique donné à la Faculté de droit de l’Universidade Federal de Minas Gerais (UFMG).
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 | 0.018 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.019 | 0.016 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".