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Record W2124175301 · doi:10.1111/1468-2427.12170

Everyday Lives in Vertical Neighbourhoods: Exploring Bangladeshi Residential Spaces in Toronto's Inner Suburbs

2014· article· en· W2124175301 on OpenAlexaffabout
Sutama Ghosh

Bibliographic record

VenueInternational Journal of Urban and Regional Research · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsApartmentImmigrationMetropolitan areaSociologyEveryday lifeAmbivalenceFeelingVariety (cybernetics)Gender studiesGeographySocial psychologyPsychologyPolitical science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.169
GPT teacher head0.478
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations71
Published2014
Admission routes2
Has abstractyes

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