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Record W1999509740 · doi:10.1080/09692290.2011.561125

Transnational actors and the politics of pension reform in Sub-Saharan Africa

2011· article· en· W1999509740 on OpenAlexafffund
Michael Kpessa-Whyte, Daniel Béland

Bibliographic record

VenueReview of International Political Economy · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsUniversity of Saskatchewan
FundersSocial Sciences and Humanities Research Council of CanadaCanada Research ChairsInter-American Development BankWorld Bank Group
KeywordsPensionScholarshipLatin AmericansContext (archaeology)PoliticsPolitical scienceConditionalityPolitical economyCompetition (biology)EconomicsEconomic growth

Abstract

fetched live from OpenAlex

ABSTRACT Drawing on recent scholarship on transnational actors and on the role of ideas in policy change, this paper analyzes the regional context of the pension reform debate in Sub-Saharan Africa, and shows that, at least since the 1980s, there was significant attention to pension reforms in Africa by global policy actors, including the World Bank. However, unlike in Latin America and Central and Eastern Europe, where the World Bank proved dominant, the regional environment of pension reform in Sub-Saharan Africa was characterized by a fierce competition between the World Bank and the International Labour Organization (ILO), with each institution promoting different policy preferences. As demonstrated, in Sub-Saharan Africa pension reform, the ILO has proved more influential than the World Bank. Theoretically, the paper stresses the role of transnational actors in the global diffusion of social policy ideas. Recognizing the need to explore the interactions between national and transnational actors, as well as between transnational actors themselves, the analysis explores the dialogical and competitive nature of the global politics of ideas.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.973
Threshold uncertainty score0.378

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 studies0.0000.001
Scholarly communication0.0000.000
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 head0.050
GPT teacher head0.327
Teacher spread0.277 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations31
Published2011
Admission routes2
Has abstractyes

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