Mothers' Knowledge of What Distresses and What Comforts Their Children Predicts Children's Coping, Empathy, and Prosocial Behavior
Bibliographic record
Abstract
SYNOPOSIS Objective. The authors aimed to determine whether mothers' knowledge of what is upsetting and what is comforting to their children predicts their children's coping, empathy, and concern for others. Design. One hundred forty 10- to 12-year-old children were asked to identify distressing events as well as what they found comforting, and their mothers were asked to say how they thought their children would respond. Children were assessed for coping and empathy, and teachers were asked to report on children's prosocial behavior in the classroom. Results. Mothers' accuracy about what distressed their children predicted the children's coping and, to an extent, their empathy. Accuracy about comforting interventions predicted coping and prosocial behavior for children prone to distress. Conclusion. Mothers' knowledge of how their children think and feel makes it easier for them to socialize their children effectively.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".