Presentation and Analysis of Recent Developments in Trade in Tuna Products; An EU Perspective
Bibliographic record
Abstract
Trade in tuna products with the EU faces systemic changes. In 2013, the EU launched a raft of large-scale negotiations, with countries including the United States and Japan. This comes on top of a number of ongoing negotiations (e.g., Mercosur, Thailand, and Vietnam), as well as recently concluded ones (e.g., Korea, Canada, Andean Community). Equally important for the tuna sector is a cluster of EU development-oriented negotiations known as Economic Partnership Agreements with African, Caribbean and Pacific countries. Finally, it is particularly important that the tuna sector is aware of the modernisation of the EU's scheme of trade concessions for developing countries, known as the Generalised Scheme of Preferences (GSP). The new rules entered into force on 1 January 2014 and will have an impact on the sector. Looking at the most recent trade figures, it seems that for the moment significant changes have not materialised yet. It will take more time before the trade flows are impacted.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".