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Record W1529441814 · doi:10.22004/ag.econ.21083

Food Insecurity, Food Storage, and Obesity

2006· preprint· en· W1529441814 on OpenAlexaff
Sean B. Cash, David Zilberman

Bibliographic record

VenueAgEcon Search (University of Minnesota, USA) · 2006
Typepreprint
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsOverweightFood securityFood insecurityObesityEnvironmental healthVariance (accounting)EconomicsFood intakeMedicineGeographyAgriculture

Abstract

fetched live from OpenAlex

Although individuals with poor food security might be expected to have reduced food intake, and therefore a lower likelihood of being overweight, some empirical evidence has indicated that overweight status is actually more prevalent among the food insecure. As obesity is associated with excessive energy intake, and hunger reflects an inadequate food supply, such observations would appear to be paradoxical. We develop an economic model that shows that this apparently paradoxical result is consistent with rational behavior regarding food availability risk and the effectiveness of food storage options. The amount of internal storage increases as the variance of food productivity in the second period increases, which is consistent with the empirical observation of a positive relationship between food insecurity and the incidence of overweight.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.171
GPT teacher head0.383
Teacher spread0.213 · 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
Published2006
Admission routes1
Has abstractyes

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