How Long Do People Live in Low-income Neighbourhoods? Evidence for Toronto, Montreal and Vancouver
Bibliographic record
Abstract
This study uses longitudinal tax data to explore several undocumented aspects regarding the duration of time spent residing in low-income neighbourhoods (residential 'spells'). Although the length of new spells is generally substantial (at least compared with low-income spells), there is quite a lot of variation in this regard. Low-income neighbourhood spells exhibit negative duration dependence, implying that the longer people live in low-income neighbourhoods, the less likely they are to leave. Length of spell varies substantially by age and city of residence and, to a lesser extent, by family income and family type. Specifically, older individuals remain in low-income neighbourhoods for longer periods of time than younger individuals, as do residents of Toronto and Vancouver (in relation to Montreal). Individuals in low-income families have longer spell lengths than those in higher income families and, among these low-income families, lone-parents and couples with children generally spend more time living in low-income neighbourhoods than childless couples and unattached individuals.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".