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Record W2915146002

Análisis comparativo de tres redes agroalimentarias alternativas en México y Canadá

2018· article· es· W2915146002 on OpenAlexaboutno aff
César Jerónimo Hernández Morales, Marie‐Christine Renard

Bibliographic record

VenueRevista Latinoamericana de Estudios Rurales · 2018
Typearticle
Languagees
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Production Studies
Canadian institutionsnot available
Fundersnot available
KeywordsConceptualizationMetropolitan areaGrassrootsOrder (exchange)Mexico cityState (computer science)SociologyWelfare economicsPolitical scienceEconomyGeographyBusinessEthnologyEconomicsComputer science
DOInot available

Abstract

fetched live from OpenAlex

This article examines the case of three alternative agri-food networks which are considered alternative mechanisms of purchase and sale of agri-food products, namely the Organic Tianguis of Chapingo in the State of Mexico in Mexico; the grassroots organization Zacahuitzco, in Mexico City, and the farmers markets of the metropolitan area of Vancouver, Canada. The main objective of this study is to recognize, from the perspective of the Conventions theory and the Alternative Rationalities approach, the parallelism, as well as and the differences of this networks in their own unique contexts, in order to deepen conceptualization and theorization on the issue of constructing alternatives in the contemporary agri-food field. The main findings of this research are contradictory: some progresses related to the reconstruction of alternative relationships between small producers and consumers were identified. However, the commercial aspects of the exchange process have become more and more significant, undermining the core values that motivated the emergence of these networks in the first place.

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)0.004
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 score0.064
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.008
Science and technology studies0.0040.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.001
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 head0.025
GPT teacher head0.275
Teacher spread0.250 · 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
Published2018
Admission routes1
Has abstractyes

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