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Record W2564036394 · doi:10.1111/ajps.12285

Foreign Aid and Undeserved Credit Claiming

2016· article· en· W2564036394 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

VenueAmerican Journal of Political Science · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsUniversity of British Columbia
FundersUniversity of California, San DiegoHellman Foundation
KeywordsReceiptExploitPoliticsBusinessControl (management)Variety (cybernetics)Order (exchange)FinanceLaw and economicsEconomicsInternational economicsAccountingPolitical scienceLawComputer security

Abstract

fetched live from OpenAlex

Abstract Politicians in developing countries misuse foreign aid to get reelected by fiscally manipulating foreign aid resources or domestic budgets. Our article suggests another mechanism that does not require politicians to have any control over foreign aid in order to make use of it for electoral purposes: undeserved credit claiming. We analyze the conditions under which local politicians can undeservedly take credit for the receipt of foreign aid and thereby boost their chances of reelection. We theorize that politicians can employ a variety of techniques to claim credit for development aid even when they have little or no influence on its actual allocation. Using a subnational World Bank development program in the Philippines, we demonstrate that credit claiming is an important strategy to exploit foreign aid inflows and that the political effects of aid can persist even when projects are designed to minimize the diversion or misuse of funds.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.431
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.023
GPT teacher head0.326
Teacher spread0.304 · 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