NON-TARIFF DIMENSION OF NEOPROTECTIONISM IN WORLD TRADE IN AGRI-FOOD PRODUCTS
Bibliographic record
Abstract
The aim of this paper was to determine the scope of non-tariff measures used in the world agri-food trade in 2020. This study used data of the United Nations Conference on Trade and Development (UNCTAD) and the Global Trade Alert data. Applying the methodology developed by the UNCTAD and the World Trade Organization (WTO) three indexes were established to describe the use of non-tariff measures (NTMs) to trade, i.e., the Frequency Index, the Coverage Ratio and the Prevalence Ratio. The number of trade preferences and trade restrictions used by the largest exporters and importers of agri-food products was also measured. The analysis showed that the scope of use of non-tariff protection measures in world trade in agri-food products is much greater compared to other branches of the economy. In countries implementing a highly protectionist trade policy, such as Brazil, China, India, Indonesia, Canada, the USA and Vietnam, non-tariff instruments were used in relation to all tariff lines and the entire value of import. To the greatest extent, non-tariff protection measures were adopted in the trade of non-processed plant origin products, including cereals, oilseeds and oleaginous fruit, fruit and vegetables, as well as dairy products. Countries most commonly implementing trade restrictions against their partners and, at the same time, at greatest risk of retaliatory actions on their part included EU countries, the USA and China.
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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 | 0.001 |
| 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".