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Record W2945981492 · doi:10.3390/socsci8050156

Economic Development and the World Bank

2019· article· en· W2945981492 on OpenAlexaff
M. Rodwan Abouharb, Érick Duchesne

Bibliographic record

VenueSocial Sciences · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsUniversité Laval
FundersWorld Bank Group
KeywordsEndogeneityEconomicsDeveloping countryEstimationDevelopment economicsMacroeconomicsEconomic policyEconomic growth

Abstract

fetched live from OpenAlex

We contribute to the research stream examining the effects of World Bank lending programs on economic growth in developing economies. We contend that it is important to distinguish between the short-term effects and extended exposure of countries to these lending programs and also to assess the Bank’s (late 1990s) reforms to improve the effectiveness of these programs in recipient countries to assess whether program lending has any positive impacts on economic growth. Our comparative cross-national findings using instrumental variables analysis to control for endogeneity between program participation and economic growth demonstrate that both the short-term and longer exposure to program lending worsens economic growth. We find no evidence that World Bank reforms improved economic growth rates in the post-reform (1999–2009) period. Our findings are robust to changes in model specifications and estimation techniques. Future research should examine whether these reforms had beneficial impacts in other societal areas affected by program lending.

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 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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score1.000

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.311
Teacher spread0.288 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations3
Published2019
Admission routes1
Has abstractyes

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