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Record W4414048430 · doi:10.25070/rea.v23i2.19421

THE ABC PROGRAM

2025· article· en· W4414048430 on OpenAlex
M. Silva, Athila Leandro de Oliveira, Alexander Silva de Resende, Luizmar de Assis Barros, Vanessa Maria Basso

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

VenueRevista de Economia e Agronegócio · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Health in Brazil
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPromotion (chess)Sample (material)Rural areaRural developmentCredit historyBank creditDescriptive statisticsCredit union

Abstract

fetched live from OpenAlex

This research draws on data from the Central Bank of Brazil’s rural credit matrix, the National Bank for Economic and Social Development (BNDES), and questionnaires administered in the municipality of Valença-RJ. All data were analyzed using descriptive statistics. The sample consisted of 40 farmers, 4 technical extension agents, and 11 employees of financial institutions that operate with rural credit in the municipality. Our findings indicate that the resources allocated to the ABC Program represent less than 15% of the government's initial rural credit budget. Despite the limited funding, some of the credit lines available remain underutilized. The most accessed line of credit is for the restoration of degraded pastureland, particularly in the Brazilian Midwest. Lastly, the case study reveals that even 13 years since the program's inception, the ABC credit lines remain largely unknown to producers, extension agents, and bank employees in Valença. This lack of awareness hinders the program’s promotion and likely contributes to its low uptake among rural producers.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.909
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.014
GPT teacher head0.371
Teacher spread0.357 · 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