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Record W2058587391 · doi:10.1093/aepp/ppt016

The Disadoption of rbST and Its Economic Impact: A Switching Regression Approach

2013· article· en· W2058587391 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Economic Perspectives and Policy · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomics of Agriculture and Food Markets
Canadian institutionsUniversity of Alberta
FundersEconomic Research Service
KeywordsProfitability indexMultivariate probit modelEarningsBivariate analysisObservabilityEconometricsEconomicsOrdered probitAgricultural scienceStatisticsMathematicsFinance

Abstract

fetched live from OpenAlex

Abstract This paper focuses on the disadoption of rbST and addresses two key questions related to rbST use and its effects on dairy profitability. First, what are the determinants of the disadoption decision, and do they differ from those of the adoption decision? Second, do the earnings of disadopters differ from those of current adopters? Using a nationally representative dataset of U.S. dairies from 2010, a bivariate probit model with partial observability and an endogenous switching model is estimated. Consistent with other studies, the results show that rbST use does not have a statistically significant effect on dairy profitability. However, within the group of producers who have adopted rbST, I present some empirical evidence that disadopters are doing worse off than those who are still using rbST.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score0.800

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 head0.010
GPT teacher head0.227
Teacher spread0.217 · 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