Bibliographic record
Abstract
Le chapitre 19 de l’ACÉUM sur le commerce numérique est, parmi les accords commerciaux préférentiels (ACP), celui qui va le plus loin pour libéraliser le commerce numérique entre les pays signataires. En fait, les États-Unis, contrairement à l’Union européenne et la Chine, par exemple, voient les ACP comme le meilleur moyen pour assurer la libre circulation des biens et services numériques au-delà des frontières tout en gouvernant les flux de données qui rendent possibles ces transactions commerciales. Pourquoi les États-Unis ont-ils choisi de faire de ces accords commerciaux le véhicule principal pour gouverner le commerce numérique et les flux de données avec le reste du monde ? Et pourquoi un partenaire comme le Canada a-t-il accepté des dispositions au sein de l’ACÉUM qui imposent des limites potentielles importantes à la régulation des données et des plateformes numériques ? En utilisant une perspective d’économie politique, le présent article répond à ces questions.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 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".