Preschoolers’ Developmental Profiles and School-Readiness in a Low-Income Canadian City: A Cross-Sectional Survey
Bibliographic record
Abstract
A joint initiative between community and public health stakeholders in a low-income Canadian city was created to describe the developmental profiles of children aged 2-5 years. A two-phase, cross-sectional design was used. Children's development was assessed using an online screening procedure. Those at risk of delays were invited for a school-readiness face-to-face brief assessment. Descriptive and exploratory analyses were conducted. In Phase 1, 223 families were screened; 100 children were at risk of delays (45%); 13% were at risk in ≥3 developmental domains; 26% were at risk in the fine motor domain. Risk of delay was associated with parental concerns, accessing more healthcare professionals, and using fewer public health/community programs. Lower incomes, and not attending day care showed trends towards an increased risk of delay. In Phase 2, 49 children were assessed; 69% were at risk of school-readiness delays; 22% had potential motor delays; 37% were at risk in the social domain. This study found a higher proportion of children at risk of delay than typically reported. Creating community partnerships could help identify all children needing developmental and school-readiness support. More research is needed to ensure these community-based partnerships are integrated into health/community programs responding to children's needs and parental concerns.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 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 | 0.000 |
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".