Child development of kindergarten immigrant and non-immigrant boys and girls in Manitoba, Canada
Bibliographic record
Abstract
Abstract Background The child development of immigrant children faces challenges related to integration and discrimination. Yet, little is known about differences in child developmental vulnerability before school entry according to maternal birthplace and sex. Methods Official immigration records were linked with the Early Development Instrument (EDI) assessments among 77,085 children in kindergarten in the province of Manitoba, Canada (2005-2017), 11,773 (15.3%) of whom had an immigrant mother. The EDI is a 103-item validated questionnaire completed by kindergarten teachers in publicly funded schools across five domains covering physical, emotional, social and cognitive skills. Logistic regression was used to estimate odds ratios of developmental vulnerability associated with 11 maternal birthplaces and child sex. Results Children of immigrant mothers from most birthplaces had higher adjusted odds of developmental vulnerability than non-immigrants in domains related to language, communication skills and general knowledge (Adjusted Odds Ratios ranging from 1.2 to 5.9), except those of the rest of North America & Oceania. Children of Sub-Saharan African mothers were more vulnerable in four domains. Boys were consistently more vulnerable than girls across domains and maternal birthplaces. Conclusions Children of immigrant mothers exhibited higher developmental vulnerability than non-immigrants in domains related to language and communication skills, potentially reflecting exposure to English and French as second languages, but not on physical health or emotional maturity. Key messages • Children of immigrants experience language and communication developmental challenges. • The girl’s advantage in early development is confirmed among immigrant children from various origins.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".