MétaCan
Menu
Back to cohort
Record W4386510854 · doi:10.5539/jsd.v16n5p76

Socio-Environmental Impacts of Certifica Minas Café Program on Coffee Plantations in Southern Minas Gerais

2023· article· en· W4386510854 on OpenAlexvenueno aff
Cláudio Vieira de Castro, Jean Marcel Sousa Lira, Eduardo Gomes Salgado, Luiz Alberto Beijo

Bibliographic record

VenueJournal of Sustainable Development · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsnot available
Fundersnot available
KeywordsCertificationBusinessAgricultural scienceAuditProduction (economics)AgrochemicalSustainable productionTraceabilityEnvironmental protectionAgricultural economicsAgricultureGeographyEnvironmental scienceAccountingMathematicsManagementEconomics

Abstract

fetched live from OpenAlex

The Certifica Minas Café (Minas Coffee Certification) is the only public program in Brazil for coffee plantation certification. Therefore, this study aimed to evaluate the environmental and social impacts, as well as the best production practices on the properties that adopted the Certifica Minas Café certification program. The research sampled 46 certified properties, which were evaluated in the years 2013 and 2015, based on the same criteria used in the official audits of the program. The results demonstrate that certified properties tend to show significant improvements in the criteria for property management and capacity building of rural workers. On the other hand, certification adoption did not show significant changes in traceability and environmental responsibility despite the reduction of agrochemical pollution found on certified farms. The research also pointed out the challenges faced by program managers. However, we affirm that the Minas Gerais certification program is helpful, but adjustments are necessary to meet the objectives of sustainable coffee production.

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)0.001
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.261
Teacher spread0.239 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Sustainable DevelopmentSame topicGlobal trade, sustainability, and social impactFrench-language works237,207