Idle hands are the devilâs tools: The geopolitics and geoeconomics of hunger
Bibliographic record
Abstract
In current geopolitical and geoeconomic discourses, hunger is understood as both a threat to be contained, resulting in an often severe social and spatial localization of food insecurity, and a humanitarian problem to be solved through diffuse global flows of food and other aid. The resulting scalar tensions demonstrate the potentially contradictory alignment of geopolitics and geoeconomics within processes of globalization and neoliberalization. This article examines the geopolitical and geoeconomic place of hunger and the hungry through a critical analysis of the food-for-work (FFW) approach to combating hunger. FFW programs distribute food aid in exchange for labor, and have long been used to plan and deliver food aid. While debate continues as to whether and under what conditions FFW programs are socially and economically just, governments, international institutions, and NGOs tout them as a flexible and efficient way to deliver targeted aid, promote community development, and improve long-term prospects for economic development and food security. In the post-9/11 period, FFW programs are also cited as effective deterrents to terrorist recruitment strategies, while development and food security more broadly have been incorporated into national security strategies, especially but not only in the United States. The food-for-work approach attempts to resolve the scalar contradictions of hunger through the imposition of a labor requirement that disciplines the threat of the hungry while enforcing global connection. Case studies of FFW programs in Bangladesh, Ethiopia, and Indonesia illustrate this contradiction, and highlight the development and possible future of approaches to hunger under neoliberal geopolitics.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.047 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".