An Examination of Parents’ Adverse Childhood Experiences (ACEs) History and Reported Spanking of Their Child: Informing Child Maltreatment Prevention Efforts
Bibliographic record
Abstract
The current evidence indicates that spanking is harmful to children’s health and development and should never be used by parents or other caregivers. However, the critical factors that inform effective spanking prevention strategies are still not well understood. The objective of the current study was to determine if a parent’s own adverse childhood experiences (ACEs) history was associated with increased likelihood of reporting their child being spanked at age 10 or younger. Data were drawn from the Well-Being and Experiences Study (the WE Study), a community survey of parents and adolescents from 2017–2018 (N = 1000) from Canada. The results indicated that a parent’s own history of physical abuse, emotional abuse, spanking, and household mental illness in childhood were associated with an increased likelihood that their child would have been spanked. These findings indicate that a parent’s ACEs history may be related to how their own child is parented and identify families who may be more likely to rely on spanking. Preventing physical punishment is necessary for healthy child development, reducing the risk of further violence, and upholding children’s rights to protection. Parent’s ACEs history may be an important factor to consider when developing and implementing child maltreatment prevention efforts.
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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 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".