Protectionism and Multilateral Accountability during the Great Recession: Drawing Inferences from Dogs Not Barking
Bibliographic record
Abstract
Economic stress is often thought to be a source of protectionism, which motivated Leaders of the new G-20 to promise repeatedly that they would refrain from trade restrictions in response to the global financial crisis that became apparent in 2008.They also promised to hold themselves accountable for this commitment using a novel transparency mechanism based in the World Trade Organization. At the same time a civil society organization, the Global Trade Alert, set itself up as an alternative accountability mechanism. The WTO and the GTA reached different conclusions both about how loudly the protectionist dog barked, and about whether G-20 governments kept their promises. I conclude from a detailed comparison of GTA and WTO data and interpretations using the notion of an 'accountability regime' that the protectionist dog did not bark, allowing inferences to be drawn from this curious incident about how transparency can help to close the gap between commitment and action, thereby contributing to accountable global governance.
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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 | 0.018 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.023 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".