MétaCan
Menu
Back to cohort

U.S. Farm Safety Nets and the 2000 Agricultural Risk Protection Act

2001· article· en· W2025444522 on OpenAlexvenueno aff
Barry K. Goodwin

Bibliographic record

VenueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomie · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural risk and resilience
Canadian institutionsnot available
Fundersnot available
KeywordsSafety netSubsidyCrop insuranceFarm programsRevenueBusinessPaymentAgricultureAgricultural policyProduct (mathematics)Public economicsAgricultural economicsEconomicsFinancePolitical science

Abstract

fetched live from OpenAlex

Although crop insurance programs have been an important part of U.S. agricultural policy since the 1930s, the “safety net” matra has taken on new relevance and importance in recent policy deliberations and rhetoric. This paper contains a non technical review of issues underlying the safety net concept in U.S. agricultural policy. We outline recent changes in U.S. crop insurance programs and review provisions of the 2000 Agricultural Risk Protection Act (ARPA), which had a significant impact on U.S. risk management programs by expanding crop and revenue insurance subsidies and stimulating new product development. A simple empirical analysis of how these changes may have affected program participation is considered. We then outline points relevant to 2002 Farm Bill deliberations. As is pointed out, the safety net concept seems pervasive to all policy discussions. Countercylical payments, even when provided on an ad hoc basis, may distort production and trade conditions.

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)0.005
metaresearch head score (Gemma)0.010
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 score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0090.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.145
Teacher spread0.133 · 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

Citations10
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomieSame topicAgricultural risk and resilienceFrench-language works237,207