Bibliographic record
Abstract
We examine the social mobility of the second generation in the Toronto metropolitan area by analyzing whether the adult children of immigrants live in more affluent and desirable neighbourhoods than the first generation. Using 2016 census microdata, we compare the social characteristics of census tracts where immigrants and the second and third‐plus (3+) generations concentrate. The index of dissimilarity indicates the degree of residential separation among generations and for five ethno‐racial second‐generation groups: Chinese, South Asian, Black, Southern European, and Northern and Western European. The empirical findings show that the neighbourhoods where the first generation is over‐represented are less affluent than those where the second and 3+ generations concentrate, with the largest improvements in social status occurring between the first and second generations. Although they frequently live in more distant suburban neighbourhoods than the first generation, the second generation still tends to live in inner and outer suburbs more than the exurban 3+ generation. For the second generation, the degree of residential concentration varies across ethno‐racial groups with persistent segregation marking the residential locations of racial minorities. The findings highlight the variegated geographies and social mobility of the second generation in Canada's largest metropolitan area.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.013 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".