Father Presence, Father Engagement, and Child Outcomes in Mongolia
Bibliographic record
Abstract
This study explored father involvement as a social determinant of child health within the context of macro-environmental changes in Mongolia. Using data for children aged 3-4 from UNICEF’s Multiple Indicator Cluster Surveys, this cross-sectional analysis examined the association between father presence and engagement with child health and educational outcomes. Multivariate regression modeling was employed to identify associations between father presence, engagement, and child outcomes including fever, respiratory illness, diarrhea and preschool attendance. In unadjusted analyses, father engagement was associated with higher odds of pre-school attendance (OR=1.12; 95% CI 1.04-1.20) but not with child illness (OR=1.04; 95% CI 0.95-1.14). Father engagement was no longer associated with pre-school attendance after controlling for potentially confounding variables (ORadj = 0.95; 95% CI 0.88-1.03). Unadjusted and adjusted analyses showed that father presence was not associated with acute illness or preschool attendance. Results also suggest that a larger proportion of children were engaged in activities by their mother compared to their father or other adults. Data indicate that father presence and engagement were not associated with child illness or pre-school attendance. Factors such as maternal education, household wealth, and region of residence are stronger predictors of preschool attendance and should continue to be considered for promoting child health and development in Mongolia.
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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 | 0.001 |
| 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) | 0.001 | 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".