Services juridiques à l’entreprise et création de valeur selon Gilson
Bibliographic record
Abstract
La valeur des services juridiques aux entreprises est un thème récurrent dans les réflexions des avocats sur leur profession. Un article, largement cité sur le sujet, est celui de Ronald Gilson paru en 1984 dans le Yale Law Journal. L’étude de Gilson s’intéresse plus particulièrement aux acquisitions d’entreprises et procède à une analyse par les coûts de transaction pour évaluer la contribution des avocats à la création de valeur. Certaines analyses économiques du droit ainsi que l’analyse économique de Coase sur la nature de l’entreprise font une hypothèse concernant la détermination des prix. La contribution des avocats avancée par l’analyse est en partie tributaire de cette hypothèse. Après une synthèse des principaux éléments de l’étude de Gilson, l’article en présente les fondements et limites.
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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 | 0.005 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.017 | 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".