L'arbitrage des différends en droit de la consommation : une nouvelle approche
Bibliographic record
Abstract
Dispute resolution is an important issue for corporations. Whether the disputes are with their suppliers, employees or with consumers, managing disputes effectively is integral to healthy business risk management. While arbitration is a well-known alternative in disputes with suppliers or employees, its use is infrequent in disputes with consumers. The purpose of this thesis is to introduce arbitration as an option for alternative dispute resolution between businesses and consumers. Banking institutions, insurance companies, businesses in the securities industry and most suppliers of good and services can usefully take advantage of this tool. In our view, the legislative framework in Quebec does not create any barriers to the use of this technique, but provides for some guidelines that corporations must comply with. We hope this paper encourages companies to exercise control of the management of their disputes with consumers with the help of arbitration mechanisms that are at the same time consistent with consumers' rights as set out in Quebec legislation.
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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 | 0.019 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".