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Record W1955163175 · doi:10.1111/joac.12023

Maize Diversity and the Political Economy of Agrarian Restructuring in Guatemala

2013· article· en· W1955163175 on OpenAlexaff
S. Ryan Isakson

Bibliographic record

VenueJournal of Agrarian Change · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFood securityRestructuringFood systemsAgricultureAgrarian societySustainabilityFood sovereigntySustainable agricultureEnvironmental degradationAgricultural biodiversityLiberalizationEconomicsBusinessNatural resource economicsAgricultural economicsMarket economyGeography

Abstract

fetched live from OpenAlex

The neoliberal restructuring of agriculture is often predicated on the promise of a more efficient food system: other objectives, such as access to food, the environmental sustainability of production practices, the nutritional composition of diets and the rights of food producers, are largely ignored. In this paper, I document how the liberalization of trade and agricultural policies in Guatemala has undermined the latter set of objectives, thereby compromising domestic food sovereignty and global food security. In particular, I demonstrate how neoliberal policies have undermined maize agriculture and contributed to the loss of crop genetic resources in the Guatemalan ‘megacentre’ of agricultural biodiversity. In its place, small‐scale farmers have been encouraged to conform to the country's purported comparative advantage in non‐traditional export crops. The results have been widening inequality, a growing dependence upon imported grain and agrochemicals, environmental degradation and decreased food security.

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)0.001
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 score0.058
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.003
Scholarly communication0.0020.001
Open science0.0000.002
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 head0.031
GPT teacher head0.189
Teacher spread0.159 · 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

Citations45
Published2013
Admission routes1
Has abstractyes

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