The Relationship between Maternal Acceptance-Rejection Levels and Preschoolers’ Social Competence and Emotion Regulation Skills
Bibliographic record
Abstract
The purpose of this research was to examine the relationship between maternal acceptance-rejection levels and preschool children’s social competence and emotion regulation skills. The study group of the research, which was designed in survey method, consisted of 303 voluntary mother-child dyad. The participant children were attending a preschool in 2014-2015 academic year, in Istanbul and they were selected by random cluster sampling method. The “Personal Information Form”, the “Parental Acceptance-Rejection Questionnaire-Mother Form (PARQ)”, the “Social Competence and Behavior Evaluation-30 (SCBE-30)” and the “Emotion Regulation Checklist” were used as data collection tools.As a result of the study, it has been found that there is a positive significant relationship between maternal acceptance level and children’s “Social Competence” subscale of SCBE-30 and their emotional regulation skills. In addition to this result, it has been found that maternal acceptance level didn’t differentiated according to age and gender of the child; however the average scores of PARQ’s “Warmth/Affection” subscale have been differentiated in favor of the girls. It has been found that “Social Competence” and “Anger-Aggression” subscales of SCBE-30 were significantly differentiated according to gender; “Anger-Aggression” scores of the boys were higher than the girls, whereas “Social Competence” scores of the girls were higher than the boys. Moreover, it has been found that “Lability-Negativity” subscale scores of Emotion Regulation Checklist have been differentiated according to gender; girls showing less labile/negative emotional reactions. Finally, it has been found that child’s social competence and emotional regulation skills increase as the age increases.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".