Water Wars by Other Means: Virtual Water and Global Economic Restructuring
Bibliographic record
Abstract
In the mid-1990s, Tony Allan coined the term “virtual water” to describe international grain shipments, arguing that for purposes of economic efficiency and political legitimacy, governments in water-scarce nations would be better served by importing grain and diverting limited domestic water supplies to higher-value purposes than by producing grain. This concept has gained considerable traction in explaining the absence of “water wars,” particularly in the Middle East and North Africa (MENA). As a prescriptive policy measure, I argue first that the exemplarity of the MENA serves an ideological function, premised on a market environmentalist approach, and framing “water crisis” as a problem of physical scarcity rather than underdevelopment. Historical trends in virtual water imports, as well as the problem of American primacy in virtual water exports, are then used to develop an account of virtual water trade that situates it within the political and economic restructuring associated with US-led globalization.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.021 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.000 | 0.006 |
| Research integrity | 0.002 | 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".