Child Development Centers of their global identities related-attitudes toward early childhood education to rural communities and social participations
Bibliographic record
Abstract
Designed the quantitative research method to assess the children's parents', teachers', and caregivers' perceptions of their 30-Local Child Development Centers in the six regions, each region was selected from the five CDCs provided.The CDCs' perceptions were obtained using the 25-item My CDC Identity Inventory (MCDCII) on five scales on three options.Teacher and Caregiver-Early Childhood interactions were assessed with the 30-item Questionnaires on Teacher Identity Interaction (QTII) on five scales on five options.The 10-item Test of Identity-Related Attitude (TIRA) was used to administer with a sample size of 300 children's parents, teachers, and caregivers.The R 2 value indicates that 30% of the variance in early childhoods' attitudes on five scales to the global identities related-attitudes toward early childhoods at the Child Development Centers, relatively.74% of teachers and caregivers' perceptions of their CDCs are able to protect educational asylum of early childhoods from rural communities to the schooling cities with their identities, significantly.49% of the variance in children's parents' perceptions inventory was Child Development … P. Saihong, T. Pengchan, and T.T.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".