Do Minority Immigrants Behave Differently with Respect to Time Spent on Childcare from Ohers? Evidence from Canada
Bibliographic record
Abstract
Childcare is an important issue in Canada and elsewhere. Some have suggested that immigrants behave differently towards childcare relative to others; others have suggested that it is no being an immigrant, per se, that affects their decisions, rather childcare choices are influenced by ethnic background an culture. In this major paper, I examine the choice of time spent on childcare by minority immigrants in Canada. Taking advantage of time diary data in Canada from 2010 and regressing time spent on childcare on various factors, I find that gender, family structure, age, income level and place of residence are all linked to the time allocated by parents in raising their childre. Both descriptive statistics and regression results demonstrate that minority immigrants will devote less time to chidcare. My findings suggest that indentifying as a minority individuals has a larger impact on the amonunt of time devoted to childcare relative to identifying oneself solely on the basis of being an immigrant or not.. Given the large percentage of Asian immigrants in Canada, some features of Asian culture may held to explain why this is the case.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".