An Examination of Attachment Status of Preschool Children
Bibliographic record
Abstract
The goal of this study is to study factors that influence attachment status of preschool children. Type of the study is relational screening and its sample comprise 78 typically developing children between 60-77 months who attend a Kindergarten affiliated to the Directorate of National Education in Suleymanpasa district of Tekirdag province. The obtained data about several demographic features of children “General Information Form” and “Incomplete Doll Family Story Scale (IDFSS)” which was developed by Cassidy (1988) and adapted to Turkish language by Seven (2006). Data frequency, percentage and distribution were found with General Information Form and data was found typically distributed. In statistical analysis, t test was used in cases where number of groups was two and one-way variance analysis in cases where it was three or higher. Data was analyzed in SPSS 22.0 at 0.05 significance level. Total attachment score of children aged 60-77 months was found 21.38 at the end of the study. Avoidant attachment was observed in 53.8 of children while 15.4% were negatively and 30.8% were securely attached. Thus, it was found that 69.2% of children were insecurely attached while 30.8% were securely attached. Study findings suggest that attachment level of children differed in favor of girls with regards gender while it did not differ in terms of other variables such as number of siblings, family type, socio-economic status of families, post-natal working status of mothers, caretaker person between 0-1 ages.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".