A tale of two methods: Comparing regression and instrumental variables estimates of the effects of preschool child care type on the subsequent externalizing behavior of children in low-income families.
Bibliographic record
Abstract
We apply instrumental variables (IV) techniques to a pooled data set of employment-focused experiments to examine the relation between type of preschool childcare and subsequent externalizing problem behavior for a large sample of low-income children. To assess the potential usefulness of this approach for addressing biases that can confound causal inferences in child care research, we compare instrumental variables results with those obtained using ordinary least squares (OLS) regression. We find that our OLS estimates concur with prior studies showing small positive associations between center-based care and later externalizing behavior. By contrast, our IV estimates indicate that preschool-aged children with center care experience are rated by mothers and teachers as having fewer externalizing problems on entering elementary school than their peers who were not in child care as preschoolers. Findings are discussed in relation to the literature on associations between different types of community-based child care and children's social behavior, particularly within low-income populations. Moreover, we use this study to highlight the relative strengths and weaknesses of each analytic method for addressing causal questions in developmental research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".