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Record W7061417258

Policy Harmonization and Adjustment in the North American Agricultural and Food Industry

2017· article· en· W7061417258 on OpenAlexfundaboutno aff

Bibliographic record

VenueAgEcon Search (University of Minnesota, USA) · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGyrotron and Vacuum Electronics Research
Canadian institutionsnot available
FundersAgriculture and Agri-Food CanadaInternational Fine Particle Research InstituteInter-American Institute for Global Change ResearchCooperative State Research, Education, and Extension ServiceEuropean CommissionJohns Hopkins University
KeywordsAgricultureGovernment (linguistics)Private sectorHarmonizationTechnical barriers to tradeCommercial policyPublic policyFree tradeTrade barrier
DOInot available

Abstract

fetched live from OpenAlex

This is the fifth publication emanating from a series of annual workshops designed to enhance communication among the three partners in the NAFTA Agreement.The workshops bring together business and interest group representatives, government officials and academics from Mexico, the United States and Canada to develop economic information related to agricultural and food markets.The primary purpose of the workshops and the publication is to contribute to lessening of trade tensions among the three countries, and thereby head off wasteful trade disputes.Previous workshops have focused on grain and dairy disputes, and analyzed the meaning and conditions for "policy harmonization".Each of these workshops was characterized by a macro and public policy focus because the public domain is the obvious arena in which trade tensions are played out.But the individual components of the private sector and, therefore, private sector adjustment are very much affected by trade agreements and policy change.In many respects, the private sector is the vehicle of change.This perspective of the agricultural/food industry and trade policy was the primary focus of the fifth workshop.Since Mexico was the site for this workshop, the program emphasized adjustment within the agricultural and food industry in Mexico.The book contains nine original papers by selected academic and government economists working in Mexico, the United States and Canada, written specifically for the workshop.Discussant

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.094
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.272
Teacher spread0.245 · 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 teacher head, 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

Citations0
Published2017
Admission routes2
Has abstractyes

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