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Record W2008934895 · doi:10.1007/s13524-014-0355-0

Fertility Decline and Child Schooling in Urban Settings of Burkina Faso

2014· article· en· W2008934895 on OpenAlexaff
Moussa Bougma, Thomas Legrand, Jean‐François Kobiané

Bibliographic record

VenueDemography · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policies and Family
Canadian institutionsUniversité de Montréal
FundersAgence Française de DéveloppementInstitut de Recherche pour le Développement
KeywordsFertilityGeographySocioeconomicsDemographyPopulationEconomicsSociology

Abstract

fetched live from OpenAlex

As evidenced in Western rich countries, Asia, and Latin America, lower fertility allows couples to invest more in each of their children's schooling. This postulate is the key rationale of family planning policies in sub-Saharan Africa. Yet, most studies on Africa have found no correlation or even a positive relationship between the number of children in a family and their educational attainment. These mixed results are usually explained by African family solidarity and resource transfers that might reduce pressures on household resources occasioned by many births as well as methodological problems that have afflicted much research on the region. Our study aims to assess the impact of family size on children's schooling in Ouagadougou (capital of Burkina Faso), using a better measure of household budget constraints and taking into account the simultaneity of fertility and schooling decisions. In contrast to most prior studies on sub-Saharan Africa, we find a net negative effect of sibship size on the level of schooling achieved by children--one that grows stronger as they progress through the educational system.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.289

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.264
Teacher spread0.256 · 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 designObservational
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

Citations22
Published2014
Admission routes1
Has abstractyes

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