What do children learn from their parents? The intergenerational impact of residential mobility on the life outcomes of Canadian children and youth
Bibliographic record
Abstract
Early childhood and adolescence are marked by a period of important developments including starting school, establishing strong social networks, establishing life goals and aspirations, and leaving the family home. The opportunities provided in early childhood impact the outcomes in adolescence and early adulthood; therefore, any disruption that occurs during this period can have long lasting consequences. Childhood factors such as parental involvement and support, a stable home environment, social capital, family socioeconomic status, involvement in risky behaviours, and mental health have all shown to impact outcomes in adulthood. However, one of the most important indicators of future outcomes is educational attainment.\nResearch shows that a key indicator of childhood educational success is residential mobility. This dissertation includes three inter-related articles that look at the role of childhood residential mobility on outcomes in childhood, adolescence, and early adulthood. Applying a life course perspective to mobility, this dissertation contributes to the limited research done on childhood mobility in Canada. Results from the first study show that early childhood mobility results in a significant decrease in standardized mathematics scores, particularly amongst children that reside in low socioeconomic households. The second study finds that children who experience a residential move and a change in schools are less likely to graduate high school on-time. The final paper ties the results from the first two together and shows that childhood residential mobility is intergenerational, whereby children appear to inherit mobility behaviour from their parents.\nOverall, the findings from all three studies highlight the role of residential mobility on child outcomes particularly amongst households with lower socioeconomic status, a topic that is largely unstudied in Canada. Future research in this area would better help policy makers understand how moving homes and changing schools impacts declining national math scores along with the gap in high school graduation rates among disadvantaged households. More research is needed to understand the mechanisms that contribute to migration as a learned behaviour passed on from parent to child.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".