Les fondements institutionnels du processus décisionnel de la Cour supérieure et de la Commission des affaires sociales
Bibliographic record
Abstract
Administrative justice implies a speedy resolution of a large number of cases, employing methods that are more informal, more accessible, and less costly than those which are inherent in the functioning of the traditional court system. Given these fundamental differences, the jurist can ask whether administrative tribunals, on the one hand, and traditional courts, on the other, arrive at similar judicial resolutions to similar legal problems. More pointedly, « Is administrative justice comparable in quality to that rendered by the traditional civil courts ? » This problem is addressed here through a methodical examination of the decision-making process, as employed by the Superior court of Quebec, and the Commission des affaires sociales, to give effect over the medium term (1976-1984) to two legal rules. A corpus of pertinent judgements and decisions is studied, with a view to discover how these rulings reflect the institutional and procedural differences underlying the decision-making process of the Superior court and of the Commission des affaires sociales. It is assumed that this process is the same for both institutions, and can be artificially fragmented and examined, in the light of the selected judgements and decisions. The result is a step-by-step, comparative commentary on the quality of justice as rendered by a traditional civil court and an administrative tribunal.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.025 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".