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Record W3044245071 · doi:10.1016/s2214-109x(20)30263-1

Liberal trade policy and food insecurity across the income distribution: an observational analysis in 132 countries, 2014–17

2020· article· en· W3044245071 on OpenAlexaff
Pepita Barlow, Rachel Loopstra, Valerie Tarasuk, Aaron Reeves

Bibliographic record

VenueThe Lancet Global Health · 2020
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversity of Toronto
FundersEconomic and Social Research CouncilJoseph Rowntree Foundation
KeywordsEconomicsPopulationDecileDemographic economicsEnvironmental healthMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Eradicating food insecurity is necessary for achieving global health goals. Liberal trade policies might increase food supplies but how these policies influence individual-level food insecurity remains uncertain. We aimed to assess the association between liberal trade policies and food insecurity at the individual level, and whether this association varies across country-income and household-income groups. METHODS: For this observational analysis, we combined individual-level data from the Food and Agricultural Organization of the UN with a country-level trade policy index from the Konjunkturforschungsstelle Swiss Economic Institute. We examined the association between a country's trade policy score and the probability of individuals reporting moderate-severe or severe food insecurity using regression models and algorithmic weighting procedures. We controlled for multiple covariates, including gross domestic product, democratisation level, and population size. Additionally, we examined heterogeneity by country and household income. RESULTS: Our sample comprised 460 102 individuals in 132 countries for the period of 2014-17. Liberal trade policy was not significantly associated with moderate-severe or severe food insecurity after covariate adjustment. However, among households in high-income countries with incomes higher than US$25 430 per person per year (adjusted for purchasing power parity), a unit increase in the trade policy index (more liberal) corresponded to a 0·07% (95% CI -0·10 to -0·04) reduction in the predicted probability of reporting moderate-severe food insecurity. Among households in the lowest income decile (<$450 per person per year) in low-income countries, a unit increase in the trade policy index was associated with a 0·35% (0·06 to 0·60) increase in the predicted probability of reporting moderate-severe food insecurity. INTERPRETATION: The relationship between liberal trade policy and food insecurity varied across countries and households. Liberal trade policy was predominantly associated with lower food insecurity in high-income countries but corresponded to increased food insecurity among the world's poorest households in low-income countries. FUNDING: Joseph Rowntree Foundation, Economic and Social Research Council.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.262
GPT teacher head0.503
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 teacher head, not a consensus.

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

Citations41
Published2020
Admission routes1
Has abstractyes

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