VALIDATION OF A TEACHER MEASURE OF SCHOOL READINESS WITH PARENT AND CHILD-CARE PROVIDER REPORTS Magdalena Janus
Bibliographic record
Abstract
Early Development Instrument (EDI) is a relatively new tool, developed at the Canadian Centre for Studies of Children at Risk at McMaster University to assess readiness to learn at school among 5-year-old children, prior to their entry to Grade 1 (Janus & Offord 2000). Readiness to learn at school is defined as a child’s ability to meet the task demands of school, such as being cooperative, sitting quietly and listening to the teacher, and to benefit from the educational activities that are offered by the school (Doherty 1996). The key domains included in the measure are: physical health and well-being, social competence, emotional maturity, language and cognitive development, and communications skills/general knowledge. Teachers are the only informants and therefore it is imperative to establish the inter-rater reliability of the instrument. Moreover, additional data from other informants (child-care providers, parents, and children themselves) allow to identify correlates of readiness to learn outcomes. This study was carried out in six child care centres in Calgary, with the total of 51 families. Kindergarten teacher, child-care teacher, and parent completed the EDI. Parents were also
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".