Acceptability of corporal punishment and use of different parenting practices across high‐income countries
Bibliographic record
Abstract
Abstract Worldwide, many children experience corporal punishment. Most research on corporal punishment has focused on parents' attitudes and use of corporal punishment; however, other relevant parenting factors and practices have rarely been examined. This study explored differences among countries with various levels of progress toward a total legal ban of corporal punishment in parents' acceptability of corporal punishment, perception of parenting as a private concern, relationship with their child and parenting practices: consistency, coercive parenting, use of smacking and positive encouragement. Parents (N = 6760) of 2 to 12‐year‐old children from Australia, Belgium, Canada, Germany, Hong Kong, Spain, Switzerland and the United Kingdom completed the International Parenting Survey, an online cross‐sectional survey. One‐way ANOVAs, and MANCOVAs (after controlling for parent age, gender and educational level), indicated significant country differences. Overall, there was no clear link between corporal punishment bans and positive parenting beliefs, practices and behaviours. The two countries where corporal punishment is banned showed different patterns. Parents in Germany showed less acceptability and use of smacking; however, parents in Spain reported the highest use of coercive parenting. Country differences suggest that beyond a legal ban, attention is needed on how to support parents to raise their children in a positive, nurturing environment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".