Dispute settlement, labor and environmental provisions in PTAs: When will business interests shift positions?
Bibliographic record
Abstract
Abstract Some protrade business interests that are against hard enforcement of labor and environmental provisions in trade deals may end up eventually supporting it, while others stick to their initial opposition. Why? When will their positions change? The existing literature would expect protrade interests to be more or less in favor of non-trade issues in trade policies according to how dependent on the international economy they are. However, longitudinal variation in export- and import-dependence does not suffice to explain change of the sort I am interested in. I argue that the position of protrade business interests change as they accumulate experiences on the negotiation/ratification of trade deals. To probe that argument, I present two paired comparisons analyzing the position of protrade business interests as pertains to the use of sanctions to enforce labor and environmental provisions in preferential trade agreements (PTAs) signed by Canada and Australia, and by the United States (US) and European Union (EU) between 1993 and 2019. My analysis points to the overall plausibility of my hypothesis and to avenues for future research. The paper helps understand the political activity of business interests on trade and sustainable development and can shed new light on the politics behind the design of social and environmental provisions in PTAs.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".