La reconnaissance des normes techniques en tant que normes informelles : sources de justice
Bibliographic record
Abstract
La justice, telle qu’on l’entend generalement, decoule d’une volonte du legislateur, qui lie ensuite les justiciables. On s’appuie sur l’election democratique des personnes ayant ce pouvoir pour justifier et legitimer les creations et modifications legislatives qui en decoulent. Or, certains aspects de la vie en societe evoluent trop rapidement pour que le legislateur puisse statuer en temps opportun. C’est dans cette avenue que certains types de normes informelles deviennent interessantes, et c’est notamment le cas des normes techniques. On pourrait definir les normes techniques comme une liste des meilleurs standards d’une industrie. Si on parvient a demontrer qu’on repond a certains criteres, on obtient une certification qui le confirme. Les normes techniques s’adaptent tres rapidement aux nouvelles technologies, mais de leur accorder une valeur juridique pose plusieurs questions. Cet article ne pretend pas pouvoir offrir de reponse a ces questions qui meritent une recherche et une etude beaucoup plus approfondie. Il tente simplement d’eveiller le lecteur a cette possibilite, a ses implications, aux portes qu’elle ouvre, mais aussi aux difficultes qu’elle pose. Notamment, il souleve l’aspect de la legitimite requise ou necessaire pour reconnaitre une valeur juridique plus formelle a ces normes. C’est en partant de ces bases que s’amorce la presente reflexion. Une presentation de la reflexion preliminaire de l’auteure est faite, suivie des mises en garde qui doivent etre soulevees.
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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 | 0.039 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.009 | 0.038 |
| Scholarly communication | 0.026 | 0.022 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 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".