Staying Italian: Urban Change and Ethnic Life in Postwar Toronto and Philadelphia
Bibliographic record
Abstract
Despite their twin positions as two of North America's most iconic neighborhoods, South Philly and Toronto's Little Italy have functioned in dramatically different ways since World War II. Inviting readers into the churches, homes, and businesses at the heart of these communities, Staying Italian reveals that daily experience in each enclave created two distinct, yet still Italian, ethnicities. As Philadelphia struggled with deindustrialization, Jordan Stanger-Ross shows, ethnicity in South Philly remained closely linked with preserving turf and marking boundaries. Toronto's thriving Little Italy, on the other hand, drew Italians together from across the wider region. These distinctive ethnic enclaves, Stanger-Ross argues, were shaped by each city's response to suburbanization, segregation, and economic restructuring. By situating malleable ethnic bonds in the context of political economy and racial dynamics, he offers a fresh perspective on the potential of local environments to shape individual identities and social experience.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 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".