Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.023 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".