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Record W4364376179 · doi:10.1080/02255189.2023.2192466

Neoliberalism, social policy and the state: searching for the transformative potential of Zambia’s Social Cash Transfer

2023· article· en· W4364376179 on OpenAlexvenueno aff
Anna Wolkenhauer

Bibliographic record

VenueCanadian Journal of Development Studies/Revue canadienne d études du développement · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsnot available
FundersBremen International Graduate School of Social Sciences
KeywordsNeoliberalism (international relations)Transformative learningState (computer science)PovertyPolitical sciencePolitical economyCash transfersSocial policySocial protectionCashSociologyEconomic systemDevelopment economicsEconomic growthEconomicsLaw

Abstract

fetched live from OpenAlex

This paper investigates the effects of the Zambian Social Cash Transfer (SCT) on the state. It aims to contribute to our deepening understanding of neoliberal social policy in Africa by teasing out how donor-driven, evidence-based policymaking and neoliberalism reinforce each other, but also by highlighting how even a poverty-focused and targeted scheme like the SCT can rehabilitate the state along two key dimensions: by forging new epistemic connections with citizens and by opening up space for intra-state learning. While inevitably fraught with ambiguities under mature neoliberalism, both are important for developing a more encompassing vision and strategy for transformative social policy.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.010
Scholarly communication0.0050.004
Open science0.0000.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.095
GPT teacher head0.272
Teacher spread0.176 · 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 designQualitative
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

Citations1
Published2023
Admission routes1
Has abstractyes

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