Linking Canadian Administrative Data: Income Trajectories, Residential and School Mobility, and Grade 3 Academic Achievement.
Bibliographic record
Abstract
ObjectiveThe objective is to examine the association between trajectories of childhood residential and school mobility and academic achievement (literacy, numeracy) in Grade 3 using linked whole-population administrative data in Manitoba, Canada. Secondarily, we assessed childhood residential/school mobility based on neighbourhood income levels (moving in/out of low- or mid-/high-income neighbourhoods). ApproachThis retrospective cohort study used linkable, de-identified administrative data (health, education, national census, provincial survey) from the provincial Population Research Data Repository housed at the Manitoba Centre for Health Policy (MCHP). Among kindergarteners from 2005 to 2014 (n = 83,894), those not having continuous residency in Manitoba, valid education assessments, and relevant family-level covariates were excluded. We followed this eligible cohort from kindergarten to Grade 3 based on various neighbourhood income trajectories of residential and school mobility. To assess Grade 3 literacy and numeracy scores based on trajectories, log-binomial regression models were conducted using SAS® version 9.4. ResultsThe total cohort included 36,754 children; at the end of kindergarten, 14.2% resided in low-income neighbourhoods, and 84.8% lived in mid-/high-income neighbourhoods. Moving between two low-income neighborhoods between kindergarten to Grade 3 was associated with an increased risk of poor Grade 3 numeracy and literacy scores (numeracy aRR=1.39 [1.16,1.67]; literacy aRR=1.31 [1.08,1.59]). When moving between neighborhood income levels, the association was stronger for children moving into low-income neighbourhoods (e.g., mid-/high-income to low-income: numeracy aRR=1.41 [1.19,1.67]) than children moving into mid/high-income neighbourhoods (e.g., low-income to mid-/high-income: numeracy aRR=1.31 [1.08,1.59]). Changing schools between kindergarten and Grade 3 was also associated with poorer numeracy and literacy scores in Grade 3 (numeracy aRR=1.31 [1.22,1.40]; literacy aRR=1.34 [1.24,1.44]); however, the strength varied based on residential mobility patterns. ConclusionMoving homes/schools can differentially impact children’s educational attainment depending upon the income level of residing neighborhood(s). Stakeholders should recognize different levels of risks related to mobility and provide support accordingly to reduce the adverse impact. Support systems should be tailored to not only children but also families and neighbourhoods.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.016 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".