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Foreign Aid in the Presence of Corruption: Differential Games among Donors

2009· article· en· W2003132118 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReview of International Economics · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsMcGill University
Fundersnot available
KeywordsEconomicsLanguage changeDifferential gameDifferential (mechanical device)Pareto principleFlow (mathematics)MicroeconomicsMathematical economicsOperations managementMathematical optimizationMathematicsMechanicsPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Abstract We consider two dynamic games of foreign aid. Model 1 deals with the case where donor countries continually feel the warm glow from the act of giving. Model 2 postulates that donors will stop giving aid when a target level of development is reached. In Model 1 , there are multiple equilibria that can be Pareto ranked. In Model 2 , the equilibrium strategies are nonlinear functions of the level of development. The flow of aid falls at a faster and faster rate as the target is approached. An increase in corruption will increase the flow of aid.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.874
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.298
Teacher spread0.280 · 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