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Record W2950778694 · doi:10.1596/1813-9450-8889

Better Policies from Policy-Selective Aid?

2019· book· en· W2950778694 on OpenAlexaff
Kurt Annen, Stephen Knack

Bibliographic record

VenueWorld Bank, Washington, DC eBooks · 2019
Typebook
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBusinessPolitical science

Abstract

fetched live from OpenAlex

This paper shows that the increased policy-selectivity of aid allocations observed in recent years provides recipient countries an incentive to improve policies. The paper estimates that a change in the World Banks Country Policy and Institutional Assessment policy index from 1.5 to 2 for a recipient is associated with an increase of about 13 percent in aid. The analysis also finds a modest but statistically significant positive relationship between the share of policy-selective aid in the global aid budget and policy, suggesting that policy-selective aid improves policies. This effect is properly identified, as the share of policy-selective aid in the global aid budget is exogenous to recipient country policy choices. Furthermore, the paper provides a game theoretic model that establishes the link between the policy-selectivity of the global budget and better recipient country policies in equilibrium.

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)0.002
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0290.002

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 head0.016
GPT teacher head0.277
Teacher spread0.261 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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