Predictors of harsh discipline practices among rural households in Côte d'Ivoire
Bibliographic record
Abstract
Harsh discipline is associated with adverse child outcomes across diverse contexts, but research is limited in sub–Saharan Africa. We assess the prevalence and identify predictors of harsh disciplinary practices at home in a sample of rural primary school-aged children in Côte d'Ivoire ( N = 1574). Hierarchical regression analyses were used to identify household and family characteristics associated with household harsh disciplinary practices. Maternal age, child age, and higher expectation of children's educational attainment were associated with lower use of harsh discipline in the home, while stress, depressive and anxiety symptoms, number of children, food insecurity, and accepting attitudes toward harsh discipline were associated with more use of harsh discipline at home. Moderation analyses revealed that the association between accepting attitudes and household harsh disciplinary practices was magnified under conditions of higher maternal stress. Supporting parental mental health may improve family functioning and reduce household harsh disciplinary practices. • Examines factors linked to harsh disciplinary practices in rural Côte d'Ivoire. • Older mothers, high education expectations linked to fewer harsh disciplinary practices. • Stress, anxiety, and younger child age linked to more harsh disciplinary practices. • Food insecurity, accepting attitudes were top predictors of harsh disciplinary practices. • Accepting attitudes magnified stress's association with harsh disciplinary practices.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".