Bibliographic record
Abstract
Les actifs de propriete intellectuelle sont regis par des lois federales. Tous, sauf un : les secrets de commerce. Pour beaucoup, les secrets de commerce sont depourvus de protection et il revient a leur proprietaire de les proteger en amont plutot que de courir le risque de les perdre, sans rien pouvoir y faire. Pour d’autres, il s’agit plutot d’une competence provinciale. Au Quebec, ce serait donc regi principalement par le Code civil du Quebec, au meme titre que toute autre information de nature confidentielle, incluant deux dispositions les mentionnant explicitement. Quant a nous, nous argumentons plutot qu’il s’agit parfois d’une competence partagee, si ce n’est par volonte, du moins par necessite. Ainsi, tant les legislateurs federal que quebecois ont tour a tour et souvent bien malgre eux redige des dispositions ayant pour consequence la protection des secrets de commerce. Nous allons tout particulierement nous pencher vers ce qui nous semble etre les allies naturels de ces secrets : le droit de l’emploi et la protection des renseignements personnels, analysant des dispositions legislatives specifiques etablies par les deux paliers de gouvernement et les interpretations jurisprudentielles qui en decoulent. Ces deux domaines de droit nous ameneront fi nalement a discuter des bases necessaires a l’etablissement d’une loi specifique aux secrets de commerce.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.033 | 0.006 |
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".