Bibliographic record
Abstract
Une nouvelle pierre à l’édifice européen de la protection des données personnelles. Tel est l’apport de l’arrêt rendu le 18 septembre 2014 par la Cour européenne des droits de l’homme. En condamnant la France pour violation du droit au respect de la vie privée, la juridiction strasbourgeoise n’a pas seulement mis à l’index un fichier STIC aujourd’hui disparu et dont la mauvaise réputation était établie de longue date. Le contrôle européen ainsi mené rétrospectivement a également permis d’éclairer les carences du fichage policier qui persistent encore à ce jour, en particulier avec le nouveau fichier TAJ. Au surplus, à l’heure où se profilent dans le prétoire européen plusieurs affaires relatives à la captation massive de données et à des systèmes de surveillance d’une ampleur inégalée, l’arrêt Brunet c. France révèle autant les forces que les faiblesses de la jurisprudence européenne au service de la protection des données personnelles.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".