Nontariff measures and product differentiation: Hormone‐treated beef trade from the United States and Canada to the European Union
Bibliographic record
Abstract
Abstract We investigate how a combination of the sanitary and phytosanitary (SPS) measure and product differentiation affects beef trade and the consequences for the United States (US)–European Union (EU) hormone‐treated beef trade dispute. We develop a partial equilibrium model to represent the global beef markets and product differentiation between non‐hormone‐treated beef, hormone‐treated beef, and other beef. The results show that removing the SPS measure increases EU hormone‐treated beef imports from the US and Canada and decrease beef consumption. In addition, EU hormone‐treated beef consumption and imports can be related to a few key indicators of product differentiation. The framework we develop can estimate EU hormone‐treated beef consumption and imports based on a minimum of parameters relating to product differentiation, thereby providing useful applied economic analysis of a key trade measure.
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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 | 0.001 | 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 | 0.000 |
| 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".