A Meta-Analysis of the Published Research on the Affective, Cognitive, and Behavioral Effects of Corporal Punishment
Bibliographic record
Abstract
The present study is a meta-analysis of the published research on the effects of corporal punishment on affective, cognitive, and behavioral outcomes. The authors included 70 studies published between 1961 and 2000 and involving 47,751 people. Most of the studies were published between 1990 and 2000 (i.e., 53 or 68%) and were conducted in the United States (65 or 83.3%). Each of the dependent variables was coded, and effect sizes (ds) were computed. Average unweighted and weighted ds for each of the outcome variables were .35 and .20 for affective outcomes, .33 and .06 for cognitive outcomes, and .25 and .21 for behavioral outcomes, respectively. The analyses suggested small negative behavioral and emotional effects of corporal punishment and almost no effect of such punishment on cognition. Analyses of several potentially moderating variables, such as gender or socioeconomic status, and the frequency or age of first experience of corporal punishment, the relationship of the person administering the discipline, and the technique of the discipline all had no affect on effect size outcome. There was insufficient data about a number of the moderator variables to conduct meaningful analyses. The results of the present meta-analysis suggest that exposure to corporal punishment does not substantially increase the risk to youth of developing affective, cognitive, or behavioral pathologies.
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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 | 0.015 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.024 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".