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Record W1946265111 · doi:10.22231/asyd.v11i2.62

Políticas de nutrición y desarrollo rural en Latinoamérica. La Red de Iniciativa de Nutrición Humana.

2014· article· es· W1946265111 on OpenAlexaff
Juan F. Núñez-Espinoza, Erin Tace-Nelson

Bibliographic record

VenueAgricultura Sociedad y Desarrollo · 2014
Typearticle
Languagees
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Production Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

En Latinoamérica, las comunidades rurales están sufriendo cada vez más de problemas de salud relacionados con la inseguridad alimentaria y con las dietas poco nutritivas. De cara a la acción insuficiente de los gobiernos, los actores no estatales han tomado el liderazgo para atender este asunto, en muchos casos; sin embargo, su trabajo está profundamente entrelazado con los contextos de política en los que operan. Usando un enfoque de estudio de caso comparativo, este artículo propone que un contexto de política que ha llegado más allá de un enfoque de asistencia alimentaria, limitando el comercio libre y promoviendo la pequeña producción sustentable de alimentos, puede ser eficaz para afrontar problemas de nutrición, en parte debido a las sinergias creadas con instituciones no estatales. El artículo también resalta la importancia de establecer redes como una manera de reconstruir el tejido social de las comunidades rurales, promoviendo así los esfuerzos de desarrollo.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.094
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.005
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.012
GPT teacher head0.254
Teacher spread0.242 · 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 designNot applicable
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
Published2014
Admission routes1
Has abstractyes

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