Regional Trade Patterns: The Impact of Voluntary Food Safety Standards
Bibliographic record
Abstract
Good Agricultural Practices (GAPs) are aimed at reducing farm level microbial contamination of fresh produce and include both fixed and variable cost components. We empirically analyze three scenarios of voluntary food safety practice adoption and third‐party certification in the North American fresh strawberry market using a spatial equilibrium model. The model incorporates GAPs adoption across production regions and across farm size. Transportation and product shrinkage, which are critical factors in inter‐regional trade of perishable products, are also included. Regional trade pattern impacts are assessed and used to draw inferences for pressure on market structure. Results indicate that competitive pressures are greatest on those regions with mid‐size volumes that are not able to take advantage of close market proximity, yet still must absorb additional costs. This suggests that adoption of food safety practices, even if voluntary, is likely to accelerate what is already a bi‐modal structure for this industry. Les bonnes pratiques agricoles (BPA) visent à réduire la contamination microbienne des produits frais à la ferme et comprennent des coûts fixes et des coûts variables. Nous avons effectué, à l'aide d'un modèle d'équilibre spatial, l'analyse empirique de trois scénarios d'adoption volontaire de pratiques de sécurité alimentaire et de certification par un tiers dans le marché nord‐américain des fraises fraîches. Le modèle intègre l'adoption de BPA dans toutes les régions productrices et les fermes de toute taille. Le transport et le flétrissement, qui constituent des facteurs critiques dans le commerce interrégional des denrées périssables, ont aussi été inclus. Nous avons évalué les répercussions de la structure de commerce régional et les avons utilisées pour tirer des conclusions sur la pression exercée sur la structure de marché. Les résultats ont indiqué que les pressions concurrentielles étaient plus importantes sur les régions qui produisent des volumes moyens, qui ne peuvent tirer profit des marchés de proximité, mais qui doivent pourtant absorber des coûts additionnels. Ces résultats autorisent à penser que l'adoption, même volontaire, de pratiques de sécurité alimentaire contribuera probablement à accélérer ce que est déjà une structure bimodale de l'industrie.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".