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Conditional cash transfers for primary education: Which children are left out?

2018· article· en· W2782203857 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWorld Development · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsnot available
FundersGrand Challenges CanadaEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentBill and Melinda Gates FoundationBrandeis UniversityNational Science Foundation
KeywordsConditional cash transferCash transfersPrimary (astronomy)CashEconomicsBusinessFinanceEconomic growthPovertyPhysics

Abstract

fetched live from OpenAlex

Conditional cash transfer (CCT) programs to increase primary-school enrollment and attendance among low-income households have been shown to benefit children and households, but to date little is known about who joins such programs. We test three hypotheses about predictors of CCT program participation in indigenous societies in Bolivia, focusing on attributes of the household (ethnicity), parents (modern human capital), and children (age, sex). We model whether children receive a transfer from Bolivia’s CCT program (Bono Juancito Pinto), using data from 811 school-age children and nine ethnic groups. Children from the group least exposed to Westerners (Tsimane’) are 18–22 percentage points less likely to participate in the program than children from other lowland ethnic groups. Parental modern human capital and child sex do not predict participation. We discuss possible mechanisms underlying the findings and conclude that the Tsimane’s current lower returns to schooling are the most likely explanation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.559
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.015
GPT teacher head0.286
Teacher spread0.271 · 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