The Analysis of the Relation Between Preschool Teachers’ Decision Making and Attachment Styles
Bibliographic record
Abstract
The aim of this study is to analyze the relation between preschool teachers’ decision making styles and attachment styles in the context of classroom management. Correlational Survey Method, which is one of the quantitative research methods, has been used in the study. The universe of the study comprises preschool teachers working in state and private schools in the European part of İstanbul. The sample of the study, which is 380 preschool teachers, has been selected through random selection. The data of the study have been collected through Teacher Information Form, Melbourne Decision Making Questionnaire I-II and Relationship Scale. Considering the relation between decision making styles and attachment styles as a result of the study, no significant relation has been found between vigilance decision making and attachment styles. There is weak and very weak relation between buck-passing, procrastination and hypervigilance decision making styles and fearful, preoccupied and dismissing attachment styles. A significant relation has been observed between decision making styles and income level and fathers’ educational level. A significant relation has been noted between attachment styles and income level. There is no significant relation between other variables (sex, age, level of education) and the two styles.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".