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Record W2028075888 · doi:10.1177/1468018113484611

Are cash transfers a realistic policy tool for poverty reduction in Sub-Saharan Africa? Evidence from Congo-Brazzaville and Côte d’Ivoire

2013· article· en· W2028075888 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGlobal Social Policy · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsUniversité LavalUniversity of Ottawa
FundersUniversity of OttawaUniversité Laval
KeywordsCash transfersPovertyCote d ivoireContext (archaeology)CashDevelopment economicsEconomicsPoverty reductionPoliticsDeveloping countryEconomic growthBusinessPublic economicsGeographyPolitical scienceFinance

Abstract

fetched live from OpenAlex

This article uses evidence from two contrasting African countries, a middle-income oil producer (the Republic of Congo) and a low-income country (Côte d’Ivoire), on the potential role of cash transfers as instruments for poverty reduction and human development. Quantitative simulations of the targeting efficiency, impacts, cost, cost-effectiveness and affordability of different cash transfer options are combined with analysis of political and administrative feasibility. The analysis finds that cash transfers would have more impact on monetary poverty reduction than on human development, while a major practical challenge is to target efficiently in a context of mass poverty. Large-scale cash transfers could be financed domestically in Congo, but this is unlikely in Côte d’Ivoire, and political support is weak in both countries.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.847
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.028
GPT teacher head0.318
Teacher spread0.290 · 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