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Record W3015721032 · doi:10.5267/j.msl.2020.4.008

Cultural aspects that influence the associative work of agricultural production chains in the Mantaro Valley of Peru

2020· article· en· W3015721032 on OpenAlexvenueno aff
Wiliam Rodríguez-Giraldez, Wagner Vicente-Ramos

Bibliographic record

VenueManagement Science Letters · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Production Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAssociative propertyAgricultureProduction (economics)Work (physics)BusinessAgricultural productivityComputer scienceAgricultural engineeringAgricultural economicsGeographyEconomicsMathematicsArchaeologyMicroeconomicsEngineering

Abstract

fetched live from OpenAlex

The purpose of this research was to determine how cultural aspects or beliefs of agricultural producers such as collectivism, trust, formality in land titling and productive planning influence the associative work of agricultural productive chains.Considering that for many years productive chains have been promoted as a development alternative for small agricultural producers in the Mantaro Valley, they have received training services, technical assistance, market articulation, etc., but very few remain today.The applied and descriptive research was carried out from July 2016 to May 2017 with the participation of 383 agricultural producers from four provinces of the Mantaro Valley, Junín, Peru.The results obtained show that the factors of trust and productive planning directly influence the associative work, while the aspects of collectivism and formality do not influence.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.217
Teacher spread0.189 · 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 designQualitative
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

Citations4
Published2020
Admission routes1
Has abstractyes

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