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Record W2804315065 · doi:10.1371/journal.pone.0198113

Reconsidering non-traditional export agriculture and household food security: A case study in rural Guatemala

2018· article· en· W2804315065 on OpenAlexafffund
Josée Méthot, Elena M. Bennett

Bibliographic record

VenuePLoS ONE · 2018
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsMcGill University
FundersMinistry of EnvironmentNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsFood securityAgricultureFood processingBusinessAgricultural productivityProduction (economics)Agricultural economicsEarly adopterPsychological interventionFood systemsAgricultural scienceEconomicsMarketingGeographyFood scienceBiology

Abstract

fetched live from OpenAlex

As the production of non-traditional export (NTX) crops by smallholder households in developing countries expands, there is a compelling need to understand the potential effects of this type of agricultural production on household food security and nutrition. We use two household surveys with a sample of 52 households, interviews, and focus groups to examine whether smallholder farmers who produce broccoli for export in a rural Guatemalan community have different household food security than farmers in the same community who are still growing traditional maize and bean crops. We explore and compare the food security status of broccoli farmers (adopters) and traditional farmers (non-adopters) across four dimensions of food security: availability, access, utilization, and stability. Adopters earned significantly more income (40%) than non-adopters, but higher incomes did not coincide with improvements in food availability, food access, or food utilization. Results indicate that adopters and non-adopters alike struggle with access to food, while the intensity of broccoli production may be undermining the ability of local agricultural systems to naturally control pests and regulate nutrients. More systematic approaches to food security assessment, especially those that consider all four dimensions of food security, are needed to better target interventions designed to alleviate food insecurity among rural smallholders.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.277

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.003
Scholarly communication0.0010.001
Open science0.0010.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.476
GPT teacher head0.383
Teacher spread0.092 · 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

Citations25
Published2018
Admission routes2
Has abstractyes

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Same venuePLoS ONESame topicFood Security and Health in Diverse PopulationsFrench-language works237,207