Disproportionate Patterns of Retaliatory Antidumping Filings by Developing and Developed Countries
Bibliographic record
Abstract
Using global antidumping cases for 72 manufacturing sectors, in 28 countries from 1991 to 2006, we investigated whether there are different patterns of retaliatory antidumping duties (AD) between the developed and developing countries. We find that the four traditional AD heavy users, which are the developed countries, such as Australia, Canada, EU and US, tend to be more sensitive to initiated AD than measured AD of exporting countries, while the five new AD heavy users, which are the developing countries, such as Argentina, Brazil, India, Mexico, South Africa, tend to be more sensitive to measured AD than initiated AD. However, the disproportionate reactions of countries disappear for the period of 1998-2006, which implies an institutional learning from past experience of retaliatory AD. For the whole period, we also find that it disappears only at the country level.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".