Regulatory Autonomy Constraints from GATS' Unconditional Obligations: The Case of the European Union
Bibliographic record
Abstract
In this report, the inherent tension between regulatory autonomy and trade liberalisation is addressed with a focus on trade in services. Therefore, this report examines in detail what is meant by the term ‘(constraints on) regulatory autonomy’ in trade law literature and develops five dimensions of the term: (i) endogenous and exogenous regulatory autonomy, (ii) regulatory autonomy related to the interest which a measure aims to advance, (iii) macro level constraints stemming from trade agreements, (iv) regulatory autonomy concerns resulting from the three steps of establishing a trade law violation, and (v) constraints related to the nature of the obligation. Subsequently, this report addresses how, in the case of the European Union, GATS’ unconditional obligations constrain regulatory autonomy. Aside from the Most-Favoured-Nation obligation, we address a series of obligations related to transparency. Our preliminary conclusions reflect the partial nature of this report, but already highlight that these unconditional obligations contain a few possibly problematic constraints on regulatory autonomy.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".