Can Economic Assistance Shape Combatant Support in Wartime? Experimental Evidence from Afghanistan
Bibliographic record
Abstract
Governments, militaries, and aid organizations all rely on economic interventions to shape civilian attitudes toward combatants during wartime. We have, however, little individual-level evidence that these “hearts and minds” programs actually influence combatant support. We address this problem by conducting a factorial randomized control trial of two common interventions—vocational training and cash transfers—on combatant support among 2,597 at-risk youth in Kandahar, Afghanistan. We find that training only improved economic livelihoods modestly and had little effect on combatant support. Cash failed to lift incomes, producing a boom-and-bust dynamic in which pro-government sentiment initially spiked and then quickly reversed itself, leaving a residue of increased Taliban support. Conditional on training, cash failed to improve beneficiaries’ livelihoods but did increase support for the Afghan government for at least eight months after the intervention. These findings suggest that aid affects attitudes by providing information about government resolve and competence rather than by improving economic livelihoods.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".