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Record W4414667871 · doi:10.1017/aae.2025.10021

Factors Affecting Enrollment in General Conservation Reserve Program: A Duration Analysis of Producers in Southern United States

2025· article· en· W4414667871 on OpenAlexaff
Ashok Chaudhary, Parag Kadam, Puneet Dwivedi, Lincoln R. Larson, Wayde C. Morse, Ben Garber, Rich Iovanna

Bibliographic record

VenueJournal of Agricultural and Applied Economics · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsDepartment of Environment and Conservation
FundersUniversity of Cambridge
KeywordsConservation Reserve ProgramDuration (music)RentingAgricultureRanking (information retrieval)Conservation agriculture

Abstract

fetched live from OpenAlex

Abstract Since the Conservation Reserve Program (CRP) was created in 1985, producers in the United States (US) have voluntarily enrolled their environmentally sensitive agricultural lands for conservation in exchange for an annual rental payment. However, enrollment in General CRP has been decreasing over time. This study used a discrete-time duration analysis model to examine factors influencing the length of time producers in the southeastern US ( n = 5000) take to enroll in the General CRP. Younger producers enrolled relatively faster than their older counterparts. Furthermore, increased total land area, awareness about CRP, and positive perspectives on the sign-up ranking process reduced overall time to enrollment.

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)0.001
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 score0.154
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.049
GPT teacher head0.221
Teacher spread0.172 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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