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Record W4389190066 · doi:10.1177/0308518x231214419

The geometry of (anti)imperialism in food regime analysis

2023· article· en· W4389190066 on OpenAlexaff
Kasim Ali Tirmizey

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsYork University
Fundersnot available
KeywordsContext (archaeology)ColonialismSubsistence agricultureFood processingState (computer science)Food systemsCapital (architecture)Political scienceEconomyDevelopment economicsPolitical economyEconomicsGeographyFood securityEcologyBiologyAgriculture

Abstract

fetched live from OpenAlex

This article examines the formation and collapse of the first global food regime of capital, focusing on the impact of tropical colonies like India. It also explores the role of anti-imperialist movements in this transition. While the literature on food regimes has shed light on the evolution of a worldwide food system, it has overlooked the contribution of South Asia to the first food regime or its struggles against colonialism. This study analyses the Ghadar Party in Punjab, British India, in the context of changes in the global wheat market. By incorporating a Gramscian conjunctural analysis, this article offers a refined understanding of transitional moments. It investigates why Punjab shifted from being a significant wheat exporter to Britain in the 1870s to primarily producing for the Indian domestic market by the 1920s. The article concludes that the colonial state implemented targeted policies to mitigate resistance from anti-imperialist movements, such as the Ghadar Party. These policies aimed to delink domestic wheat production from the global market due to subsistence crises related to the global food system. Lastly, the article outlines a method to analyse the link between place-based struggles and structural crises in a global food regime.

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: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.118

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 head0.012
GPT teacher head0.181
Teacher spread0.168 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

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