Care‐giver advice as a preventive measure for drinking during pregnancy: zeros, categorical outcome responses, and endogeneity
Bibliographic record
Abstract
We conduct an empirical investigation of the impact of prenatal care-giver advice on alcohol consumption by pregnant women. In the design of the model and estimator, we pay particular attention to three aspects of the data. First, a large proportion of pregnant women do not drink at all. To accommodate this aspect of the sample we base the essential formulation of the model on the modified version of the two-part approach of Duan et al. (Journal of Business and Economic Statistics 1983; 1: 115-126.) suggested by Mullahy (Journal of Health Economics 1998; 17: 247-281.). Second, in the survey that we analyze (the 1988 National Maternal and Infant Health Survey - NMIHS), respondents were only required to report their consumption up to a specified range of values (e.g. 1-2 drinks per week, 2-5 drinks per week, and so on). For this reason, the model is cast in the grouped regression framework of Stewart (Review of Economic Studies 1983; 50: 141-149.). Third, the binary physician advice variable is likely to be endogenous and the econometric specification explicitly accounts for this possibility. To summarize the results, we find that failing to account for endogeneity leads to the counterintuitive conclusion that advice has a positive and statistically significant influence on drinking during pregnancy. When the model is extended to allow for potential endogeneity, we find that advice has a negative and statistically significant impact.
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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 | 0.001 | 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".