Mothers’ labor market choices and child development outcomes in Chile
Bibliographic record
Abstract
This paper examines associations between labor market participation of Chilean mothers and the cognitive, language, and socio-economic development of their children. Using a nationally-representative sample of 3-year-old children, we test if mothers' work intensity in the two previous years is associated with child development outcomes; data were collected in 2010 when children were one year old, and again in 2012, when they were three years old. We find that children who were three years old with mothers who worked for higher fractions of their children's lives in the previous two years perform significantly better on all tests (cognitive, language, socio-emotional) than children whose mothers had worked less, while controlling for baseline test performance. These main effects did not remain significant with the inclusion of a wide range of socio-economic, demographic control variables, however. Our results were similarly null when using an IV analysis or a propensity score matching approach. We provide descriptive information on theoretical pathways by which maternal work may influence child development. Though several of these pathways (e.g. preschool, toys, maternal stress) seem to be associated with both maternal work and child development outcomes, the pathways are not sufficiently strong to generate an association between maternal work and child development. We conclude that Chilean mothers' employment in early childhood generally does not have an effect on child development.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".