Do Neighbourhoods Influence Long-term Labour Market Success? A Comparison of Adults Who Grew up in Different Public Housing Projects
Bibliographic record
Abstract
This paper examines whether long-run labour market outcomes depend on residential environment among adults who grew up in subsidized housing in Toronto. The housing program in Toronto provides a full spectrum of neighbourhood quality types to measure outcome differences, and offers a real-life example of large scale neighbourhood quality reform. A primary advantage with this approach is that, conditional on participation in public housing, residential choice is substantially limited. Families that applied for public housing could not specify which project they wished to be housed in and were constrained to what was offered based on availability at the time they applied and by family size. Unlike previous housing mobility experiments, the availability of administrative tax records are used to measure both short and long run outcomes. The results indicate almost no difference in educational attainment, adult earnings, income, and social assistance participation between children from different public housing types. Average outcomes, estimated wage distributions, and outcome correlations among unrelated project neighbours show no significant neighbourhood impact. In contrast, family differences seem to matter a great deal.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".