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Record W2086366156 · doi:10.1300/j047v16n01_07

The Effects of NAFTA on Trade and Welfare in the U.S. Fresh Tomato Industry

2004· article· en· W2086366156 on OpenAlexaboutno aff
Gustavo Acosta, Kenneth A. Foster, Glenn H. Sullivan

Bibliographic record

VenueJournal of International Food & Agribusiness Marketing · 2004
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomics of Agriculture and Food Markets
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic surplusAgricultural economicsWelfareEconomicsFree trade agreementInternational tradeConsumer welfareBusinessInternational economicsFree tradeMarket economy

Abstract

fetched live from OpenAlex

The purpose of this study was to measure NAFTA's impact to date and quantify how the producers and consumers of fresh tomatoes in the United States, Canada and Mexico have benefited or lost. Changes in consumer and producer surpluses were calculated in 2001 US dollars based on simulations of two scenarios. The analysis found that U.S. consumers captured $12.1 billion more surplus than they would have captured had NAFTA not been enacted. Mexican fresh tomato producers gained an additional $2.08 billion in surplus due to NAFTA. In contrast to Mexican growers, U.S. and Canadian producers appear not to have benefited economically from NAFTA. Findings suggest that U.S. producers would have earned $3.29 billion more if NAFTA had not gone into effect. Canadian producer surplus with NAFTA was estimated to be approximately $20 million less with NAFTA, and the total net benefit from NAFTA was found to be a positive $10.87 billion.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.245

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.008
GPT teacher head0.195
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2004
Admission routes1
Has abstractyes

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