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Record W2189601708 · doi:10.22004/ag.econ.401298

Recent Agricultural Policy Reforms in North America

2005· article· en· W2189601708 on OpenAlexaboutno aff
Steven Zahniser, Ed. Young, John Wainio

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Production Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureCommodityBusinessCompetition (biology)Agricultural policyAgricultural economicsAgricultural productivityEconomic policyProduction (economics)Farm programsEconomic growthEconomicsNatural resource economicsFinanceGeography

Abstract

fetched live from OpenAlex

The United States, Mexico, and Canada have each made significant changes to their agricultural policies over the past several years. In the area of income supports, each country has instituted a countercyclical program that provides additional assistance to producers during downturns in commodity prices, and each continues to decouple key support programs from production decisions. In other areas, the reforms of the three countries have different points of emphasis. The United States has expanded spending on conservation activities, especially on lands in production; it has made important changes to peanut and tobacco programs; and it has implemented a new program that assists producers who are adversely affected by competition with imports. Mexico’s new efforts to strengthen the competitiveness of its agricultural sector include energy discounts for producers, and a revamped approach to agricultural finance. And Canada’s comprehensive evaluation of its farm programs is leading to new efforts concerning the environment, food safety and food quality, science, and the renewal of the agricultural sector.

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)0.003
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.663
Threshold uncertainty score0.670

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0050.002
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.021
GPT teacher head0.225
Teacher spread0.204 · 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

Citations13
Published2005
Admission routes1
Has abstractyes

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