Facebook et les dispositifs de traçabilité vus sous l’angle du droit canadien
Bibliographic record
Abstract
Aujourd’hui, on parle du Web social. Facebook par exemple, porte bien la marque de son époque ; il est devenu le réseau social le plus convoité dans le monde. Toutefois, l’entreprise a été souvent critiquée en raison de sa politique qui porte atteinte à la vie privée des personnes. Par le truchement de ses modules sociaux, Facebook a le potentiel de collecter et d’utiliser des informations considérables sur les internautes à leur insu et sans leur consentement. Ce fait est malheureusement méconnu de la majorité d’entre eux. Certes, l’entreprise doit vivre économiquement et l’exploitation des renseignements personnels constitue pour elle une source de revenu. Toutefois, cette quête de subsistance ne doit pas se faire au détriment de la vie privée des gens. En dépit des outils juridiques dont le Canada dispose en matière de protection de la vie privée, des entreprises du Web à l’image de Facebook réussissent à les contourner.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 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".