Repenser l’impact de la surveillance après l’affaire Snowden : sécurité nationale, droits de l’homme, démocratie, subjectivité et obéissance
Bibliographic record
Abstract
Les révélations autour des programmes secrets de la NSA ont confirmé l’existence d’une surveillance de grande envergure de nos communications par les autorités gouvernementales américaines, qui touche également les pays alliés des États-Unis en Europe et en Amérique latine. Les ramifications transnationales de la surveillance nous invitent à ré-examiner les pratiques contemporaines des affaires internationales. Le débat ne se limite pas aux relations des États-Unis avec le reste du monde, ni à la surveillance et à la vie privée : il est beaucoup plus large. Cet article collectif décrit les spécificités de la cyber-surveillance, y compris les pratiques hybrides des services de renseignement et des compagnies privées de télécommunications. Il analyse ensuite les impacts de ses pratiques sur la sécurité nationale, la diplomatie, les droits de l’homme, la démocratie, la subjectivité et l’obéissance.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".