Digitalisation de la commande publique: 6e Rapport de la Chaire de droit des contrats publics
Bibliographic record
Abstract
A travers son sixième rapport, la Chaire de droit des contrats publics entend mesurer l'effectivité des règles encadrant la modification des contrats de la commande publique.En particulier, les enquêtes se sont concentrées sur la pratique du Building information modeling (BIM), de l'open data et du partage des données, de la LegalTech et de la dématérialisation de l'exécution des contrats de la commande publique, ainsi que des éventuelles difficultés rencontrées par les praticiens (avocats, juristes d’entreprises titulaires de marchés publics ou concessionnaires, juristes d’autorités contractantes). Une attention particulière a également été portée sur l'intelligence artificielle, la blockchain et les smart contracts, des outils encore en développement et très peu utilisés dans la pratique de la commande publique.Les enquêtes ont permis de proposer plusieurs recommandations, en particulier pour reconnaître dans le Code de la commande publique le BIM.
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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 | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.041 | 0.007 |
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".