The geography of school choice in a city with growing inequality: the case of Vancouver
Bibliographic record
Abstract
This analysis aims to measure the impact of school choice policy on secondary school students’ enrolment patterns within the social geography of Vancouver, an increasingly polarized global city. The rationale for the study is to examine the impact of ‘education market’ reforms on the socio-economic composition of schools in a Canadian context, where a social welfare commitment to educational equality is being replaced by market-oriented policies and increasing social inequality. Our study is guided by Bourdieu’s theory of site in considering whether growing inequality and polarization of wealth in a city are correlated with the ways families choose schools. We apply a geographical methodology (Geographic Information System) to delineate spatial patterns of choosing schools. Our analysis shows that those who opt out of the under-subscribed schools come from the neighborhoods with relatively higher capital than those who remain in their assigned schools. Also, those who opt into the over-subscribed schools in the affluent areas come from the neighborhoods with above-average levels of capital in Vancouver. Overall, we find that the spatial inequality in school choice generally follows the uneven distribution of capital/wealth across the city. The pattern of student mobility indicates an increasing level of segregation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".