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Record W7011485201

A multidimensional approach to food security and non-traditional export agriculture: a case study in Guatemala

2014· other· en· W7011485201 on OpenAlexvenueno aff

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2014
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsnot available
Fundersnot available
KeywordsFood securityFood systemsAgricultureFood processingFood insecurityPovertyGood agricultural practiceFood industry
DOInot available

Abstract

fetched live from OpenAlex

There are four important dimensions of food security: food availability, food access, food utilization and food system stability. However, although the concept of food security has come of age, food security remains difficult to measure across these dimensions. In the first chapter of this thesis, I review the concepts and indicators used to assess the four dimensions of food security at the household level, and argue that a multidimensional approach to food security analysis is fundamental to understanding the overall impacts of development strategies on the food security of households. This is an important area of research because many strategies to improve food security in the developing world focus on income (supposedly an indicator of food access) and neglect to consider the other three dimensions of food security and associated indicators. Food system stability, in particular, is often overlooked in assessments of food security.In the second chapter of this thesis, I present a case study exploring the food security implications of farming broccoli for export in Guatemala, recognizing that broccoli, a non-traditional export crop, is widely promoted in this region as a means to increase smallholder incomes and food security. I use a multidimensional approach to explore the four dimensions of household food security, and compare the food security of broccoli farmers (adopters) and corn farmers (non-adopters) in the community of Chilascó, in Central Guatemala. Neither food availability nor food utilization differed significantly between adopters and non-adopters. Although adopters earned significantly higher income (40%) than non-adopters, income gains did not translate into improvements in food access according to outcome indicators. The majority of adopters and non-adopters alike were categorized as moderately to extremely food insecure according to the Household Food Insecurity Access Scale. Households in the top income tercile had significantly higher dietary diversity (an indicator of food access) compared to households in the bottom tercile. A nuanced conclusion from this work is that income can lead to positive food security outcomes, but does not guarantee them. In terms of food system stability, adopters applied twice as much manure per hectare, three times more inorganic fertilizer per hectare, and had a higher environmental impact associated with pesticide use. Taken together, there are trade-offs among the different dimensions of food security, whereby some indicators improve (e.g. income), others remain unchanged (e.g., staple crop production), and others degrade (e.g. the ecosystem service of biological pest control) for adopters relative to non-adopters. My results show that narrow, often income-oriented approaches to food security analysis may mask important differences among the four dimensions of food security. Future research into the food security implications of non-traditional export agriculture must move beyond the dualistic understanding of food security outcomes (better/worse) in order to better target interventions. This will require a systematic consideration of all four dimensions of food security in assessments and development planning.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.629
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.159
Teacher spread0.148 · 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 teacher head, 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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

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