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Record W2313168291 · doi:10.1177/0738894213499486

Aid, minds and hearts: The impact of aid in conflict zones

2013· article· en· W2313168291 on OpenAlexaff
Jan R. Böhnke, Christoph Zürcher

Bibliographic record

VenueConflict Management and Peace Science · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsUniversity of Ottawa
FundersEidgenössische Technische Hochschule Zürich
KeywordsLegitimacyState (computer science)Political scienceDevelopment aidSocial psychologyDevelopment economicsPsychologyPolitical economyEconomicsPoliticsComputer scienceLaw

Abstract

fetched live from OpenAlex

It is widely assumed that development aid can help to stabilize regions in or after conflict. However, we lack empirical evidence for this assumption, and the assumed causal mechanisms are poorly specified. We conducted a micro-level longitudinal study of 80 communities in northeast Afghanistan between 2007 and 2009 and investigated the impact of aid on (perceived) security. We also investigated two possible causal mechanisms that may link aid to security: whether aid has an impact on attitudes toward international civilian and military actors (“hearts and minds”) and whether aid can help to increase the legitimacy of the state (“state reach”). While we find that aid neither increases perceived security nor fosters more positive attitudes toward international actors, we also find that aid is positively correlated with state legitimacy.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.026
GPT teacher head0.323
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), 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

Citations113
Published2013
Admission routes1
Has abstractyes

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