Disentangling Market Access Effects of Preferential Trading Arrangements with an Application for ASEAN Members under an ASEAN-EU FTA
Why this work is in the frame
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Bibliographic record
Abstract
The paper develops two synthetic measures at the HS-10 level to depict effective market access for a country receiving preferential access and applies these to the market access ASEAN members would receive following the implementation of an FTA with the EU. First, the measures show that current effective market access for ASEAN EBA members is cut in half by the preferences granted by the EU to countries that compete with these countries in the EU markets. Second, the measures show that about one-quarter of the preferential margin under the proposed FTA for EBA members would be lost as a result of preferential access granted to ASEAN GSP members. Third, disaggregated estimates of the restrictiveness of rules of origin confirm that rules are more restrictive for products with higher preferential margins and that ASEAN countries usually face tougher rules of origin in the EU because of the composition of their exports.
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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