Everyday Lives in Vertical Neighbourhoods: Exploring Bangladeshi Residential Spaces in Toronto's Inner Suburbs
Bibliographic record
Abstract
Abstract In the Toronto Census Metropolitan Area ( CMA ), almost a third of the total housing stock is comprised of high‐rise apartment buildings. Not only do most new immigrants reside in these structures upon arrival, they often continue living here for a prolonged period, for a variety of interrelated economic and psychological reasons. It is therefore important to ask: How do these vertical structures affect the life worlds of the residents? What functions do these spaces perform? How do immigrants develop attachments to these spaces, and how do they make them their own? By drawing upon the experiences of 30 Bangladeshi immigrant households in Toronto's inner suburbs, I demonstrate that even though these vertical stacks are not conducive to frequent social interaction by design, the residents variously transform such functional spaces into unique ‘ B engali’ neighbourhoods that are filled with ambivalent feelings of hope and despair, imaginations of the future, becoming a place they can call home away from home.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".