Digital Trade and Dispute Settlement in RTAs: An Evolving Standard?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There were 288 regional trade agreements (RTAs) in force at the end of 2018, approximately one quarter (27%) of which included digital trade provisions. These e-commerce chapters have evolved from simple statements, to more comprehensive attempts to cultivate digital trade. This article tests the hypothesis that as e-commerce chapters have become more common and more detailed, their legal enforceability has also risen. Enforceability is measured using a qualitative empirical analysis of seventy-eight e-commerce chapters in RTAs notified to the World Trade Organization. The first section reviews recent initiatives to map and track e-commerce provisions in RTAs. The second section uses count data and text-as-data to develop a time-sequence, process tracing examination of the relationship between e-commerce chapters and dispute settlement. The analysis emphasizes the trajectory of development, from earliest related provisions in 2001 to next-generation agreements such as the Trans-Pacific Partnership (CPTPP) and the newNorth American agreement, the United States-Mexico-Canada Free Trade Agreement (USMCA). The conclusion provides a discussion of the consequences of this evolving relationship for the multilateral governance of trade at the WTO.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it