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Record W2266920115 · doi:10.1111/infi.12073

Food Price Uncertainty and Political Conflict

2015· article· en· W2266920115 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Finance · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsGlobal Affairs Canada
Fundersnot available
KeywordsCommodityEconomicsPoliticsPrice shockCivil ConflictMacroeconomicsFood pricesInternational economicsFood securityMonetary economicsMarket economyPolitical science

Abstract

fetched live from OpenAlex

Abstract Waves of concurrent, cross‐country political turmoil suggest that global economic forces can serve as a catalyst for intrastate conflict. This article analyses the role of uncertainty shocks to global food commodity prices in generating political conflict in developing countries. I build a simple model to show that shocks to the uncertainty of commodity export prices can elicit civil conflict in a small open economy. Econometric evidence from a cross‐country panel data set documenting intrastate civil conflict and global food commodity prices from 1966–90 lends support to this hypothesis. The results suggest that policies which reduce the uncertainty of export prices faced by food commodity exporters can facilitate political stability in conflict‐vulnerable countries.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.939
Threshold uncertainty score0.231

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 head0.049
GPT teacher head0.333
Teacher spread0.284 · 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