Les clauses abusives des contrats de construction
Bibliographic record
Abstract
Depuis quelques années, les entrepreneurs soumissionnent moins en vue de l’obtention de contrats publics de construction : ils allèguent notamment que ceux-ci contiennent des clauses abusives. Les contrats de construction octroyés selon un processus d’appel d’offres sont des contrats d’adhésion, considérant que le donneur d’ouvrage élabore unilatéralement les stipulations contractuelles et qu’il les impose à l’entrepreneur. Bien que les tribunaux puissent annuler les clauses abusives que comportent les contrats d’adhésion, ils interviennent peu fréquemment. Dans le présent texte, l’auteure vise à faciliter l’identification des clauses abusives des contrats d’entreprise de construction et détaille cinq types de clauses susceptibles de désavantager un entrepreneur d’une manière excessive et déraisonnable ou de dénaturer un contrat de construction.
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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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.015 | 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".