Persistence and change of the relative difference in educational attainment by ethno-cultural group and gender in Canada
Bibliographic record
Abstract
This article presents analytical findings on the persistence and change of the relative difference in educational attainment by ethno-cultural group and gender in Canada. As these trends cannot be observed from a single data source, a modelling technique to integrate longitudinal data lacking ethno-cultural detail with cross-sectional Census data was developed. First- and second-generation immigrants and/or members of most visible minority groups on average reach higher educational levels than their Canadian-born peers not belonging to a visible minority. This study reveals that the relative educational differences between the studied groups are both important in extent and remarkably stable over birth cohorts. The research presented in this paper was conducted in the context of Statistics Canada’s population projection microsimulation model Demosim. Demosim marks an important milestone in establishing microsimulation for official population projections. It reflects the demand for models which can go beyond age and sex, capturing geographical detail, ethnic diversity, educational attainment and other characteristics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".