Ntms, Agricultural and Food Trade, and Competitiveness. A Special Issue of The World Economy
Bibliographic record
Abstract
NTMs, Agricultural and Food Trade, and Competitiveness Special Issue of The World Economy (forthcoming). Selected Papers from a European Commission co-funded Project on Assessment the Impacts of Non-tariff Measures on Competitiveness of the EU and Selected Trade Partners. Guest Editors: John Beghin and David Orden. The PDF file has the Table of Contents and teh introduction. Please contact the authors for individual papers. Once the articles are available on line, we will link directly to them.Contents:Overview Key Findings of the NTM-Impact Project David Orden, John Beghin, and Guy Henry The Impact of Regulatory Heterogeneity on Agri-food Trade Niven Winchester, Marie-Luise Rau, Christian Goetz, Bruno Larue, Tsunehiro Otsuki, Karl Shutes, Christine Wieck, Heloisa Lee Burnquist, Maurício Jorge Pinto de Souza, and Rosane Nunes de Faria Convergence of US and EU Production Practices under the New FDA Food Safety Modernization Act John Humphrey Case Studies The Trade and Welfare Impacts of Australian Quarantine Policies: The Case of Pigmeat John Beghin and Mark Melatos Potential of Regional and Seasonal Requirements in US Regulation of Fresh Lemon Imports Caesar Cororaton and Everett Peterson Assessment of the Impact of Avian Influenza Related Regulatory Policies on Poultry Meat Trade and Welfare Christine Wieck, Simon Schlueter and Wolfgang Britz Compositional Standards, Import Permits and Market Structure: The Case of Canadian Cheese Imports Marie-Hélène Felt, Bruno Larue and Jean-Philippe Gervais Effects of GlobalGAP on Horticultural Exports and Employment in Senegal Liesbeth Colen, Miet Maertens and Jo Swinnen
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".