Bibliographic record
Abstract
Digital trade is one of the very few areas of trade law, where one can observe a willingness shared by the international community to move forward and actively engage in new rule-making. The article contextualizes and explores this development by looking at the relevant e-commerce provisions in preferential agreements, in particularly by highlighting the legal innovation in the most advanced templates of the Comprehensive and Progressive Agreement for Transpacific Partnership (CPTPP) and the United States Mexico Canada Agreement (USMCA), as well as in dedicated digital trade agreements, such as the ones between the United States and Japan and between Chile, New Zealand and Singapore. The article then looks at the WTO negotiations and tries to identify points of convergence and divergence reflected in the latest negotiation proposals tabled by WTO members. It is the article’s objective to test these proposals, as to their potential to permit the adoption of a new treaty on digital trade and to their ability to adequately address the practical reality of the data-driven economy. digital trade, electronic commerce, World Trade Organization, preferential trade agreements, data and data flows, CPTPP, USMCA, DEPA
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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 | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.020 |
| Scholarly communication | 0.014 | 0.020 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.014 | 0.022 |
| Insufficient payload (model declined to judge) | 0.009 | 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".