The Impact of the Triple P Seminar Series on Canadian Parents’ Use of Physical Punishment, Non-Physical Punishment and Non-Punitive Responses
Bibliographic record
Abstract
Abstract Physical punishment of children is linked to negative developmental outcomes. The widely used Positive Parenting Program (Triple P) promotes alternative responses to physical punishment. Data on the effectiveness of the Triple P Seminar Series is limited. In this study, Canadian parents’ reports of physical punishment, non-physical punishment, and non-punitive responses were compared before and after they attended the Triple P Seminar Series. Twenty-seven parents of children aged 2 to 6 years attended the Seminar Series and completed pre- and post-intervention questionnaires measuring the number of times they used various physical punishments, non-physical punishments, and non-punitive responses in the past month. Hypotheses were tested using univariate descriptive analyses, paired samples t tests, and Wilcoxon Signed Rank Tests. Parents’ reports of physical punishment decreased on only one of the four physical punishment items (shaking/grabbing) from pre- to post-intervention. Over the course of the Seminar Series, parents became more likely to emphasise rules and to punish their children by taking things away from them. The findings suggest that the Seminar Series has limited effectiveness in reducing physical punishments or increasing non-punitive responses. Further research on this question is needed.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".