Fishy SPS Measures? The WTO's <i>Korea – Radionuclides</i> Dispute
Bibliographic record
Abstract
Abstract The Korea–Radionuclides case addresses Korean SPS measures imposed on Japanese fishery products after the Fukushima Dai-ichi nuclear plant meltdown in 2011. Japan challenged these measures as more restrictive than necessary under the SPS Agreement. The panel agreed with Japan, but this ruling was largely reversed by the Appellate Body. Korea's victory at the Appellate Body was based on procedure. The panel accepted Korea's appropriate level of protection (ALOP), which included both quantitative and qualitative elements. However, the Appellate Body found that the panel only addressed the quantitative aspect of Korea's ALOP and reversed on that basis. The Appellate Body's ruling did not affirmatively find that Korea's SPS measures were legal under WTO rules. Instead, the Appellate Body found that panel had not sufficiently addressed Korea's arguments and, thereby, the panel could not determine that the SPS measures were more restrictive than necessary. The case highlights the need for the Appellate Body to be able to conduct its own factual analysis, a power it could be given if the dispute settlement system is reformed. Without independent fact-finding power, the Appellate Body cannot correct panels’ mistakes, and respondents can prevail based on panel error.
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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 | 0.016 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.014 | 0.008 |
| 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".