Status (in)consistency in education and violent parenting practices towards children
Bibliographic record
Abstract
Violent childrearing practices represent an invisible threat for global health and human development. Leveraging underused information on child discipline methods, this study explores the relationship between parental educational similarity and violent childrearing practices, testing a new potential pathway through which parental educational similarity may relate to child health and wellbeing over the life course. The study uses data from Multiple Indicator Cluster Surveys (MICS) and Demographic and Health Surveys (DHS) covering 27 sub-Saharan African (SSA) countries. Results suggest that couples where partners share the same level of education (homogamy) are less likely to adopt violent childrearing practices relative to couples where partners face status inconsistency in education (heterogamy), with differences by age of the child, yet less so by sex and birth order. Homogamous couples where both partners share high levels of education are also less (more) likely to adopt physically violent (non-violent) practices relative to homogamous couples with low levels of education. Relationships are stronger in countries characterized by higher GDP per capita, Human Development Index, and female education, yet also in countries with higher income and gender inequalities. Besides stressing the importance of female education, these findings underscore the key role of status concordance vs discordance in SSA partnerships. Tested micro-level mechanisms and country-level moderators only weakly explain result heterogeneity, calling for more research on the topic.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".