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Record W4361208539 · doi:10.1007/s00148-023-00946-0

Children having children: early motherhood and offspring human capital in India

2023· article· en· W4361208539 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

VenueJournal of Population Economics · 2023
Typearticle
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsnot available
FundersDeutsche ForschungsgemeinschaftInternational Development Research Centre
KeywordsHuman capitalOffspringSiblingContext (archaeology)Developmental psychologyDeveloping countryPsychologySocial capitalFixed effects modelDemographyPanel dataDemographic economicsEconomicsPregnancySociologyGeographyEconomic growthEconometricsBiology

Abstract

fetched live from OpenAlex

Using panel data from India, this paper investigates the effect of early maternal age on offspring human capital, contributing to the scarce evidence on this phenomenon, especially in the context of a developing country. The analysis relies on mother fixed effects to allow for unobserved differences between mothers and employs a variety of empirical strategies to address remaining sibling-specific concerns. Our results indicate that children born to young mothers are shorter for their age, with stronger effects for girls born to very young mothers. We also find some evidence suggesting that children born to very young mothers perform worse in math. By exploring the evolution of effects over time for the first time in the literature, we find that the height effect weakens as children age. Further analysis suggests both biological and behavioral factors as transmission channels. Supplementary Information: The online version contains supplementary material available at 10.1007/s00148-023-00946-0.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.357

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 studies0.0000.000
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 head0.018
GPT teacher head0.276
Teacher spread0.258 · 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