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Record W2102685493 · doi:10.1177/0042098014522721

Expectations, preferences and satisfaction levels among new and long-term residents in a gentrifying Toronto neighbourhood

2014· article· en· W2102685493 on OpenAlexaffabout
Emily McGirr, Andrejs Skaburskis, Tim Spence Donegani

Bibliographic record

VenueUrban Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsQueen's University
Fundersnot available
KeywordsGentrificationNeighbourhood (mathematics)RedressDemographic economicsPerceptionStock (firearms)GeographySociologyEconomic growthPolitical sciencePsychologyEconomics

Abstract

fetched live from OpenAlex

This study shows the remarkable similarity in the interests, motivations, perceptions and satisfaction levels of the long-term residents and the more recent arrivals in a gentrifying Toronto neighbourhood. The survey shows that long-term residents, mostly homeowners, welcome the changes and express their strong satisfaction with their neighbourhood and community. Gentrification did not create a large disparity between the established residents and newcomers and both groups appear to be motivated by similar interests. Both the new arrivals and the long-term residents are renovating and upgrading the neighbourhood. The findings depict gentrification – where sitting tenants are protected by rent controls – as a conflict free process welcomed by long-term residents. However, the ease of this neighbourhood’s transition makes it potentially more problematic as the indirect consequences of the reduction in the low priced housing stock are not apparent to the public and, therefore, less likely to be seen as a problem needing redress.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.246
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.054
GPT teacher head0.331
Teacher spread0.277 · 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

Citations26
Published2014
Admission routes2
Has abstractyes

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