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Record W1978401338 · doi:10.3828/tpr.2014.22

Perspectives on mixing housing types in the suburbs

2014· article· en· W1978401338 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueTown Planning Review · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsDalhousie University
FundersYork University
KeywordsNeighbourhood (mathematics)Mixing (physics)Diversity (politics)Scale (ratio)BusinessGeographySociologyMathematicsCartography

Abstract

fetched live from OpenAlex

Planners typically promote diversity and mixing as desirable social objectives: they assume that mixing housing types will generate social interaction and tolerance. Our research considers what those producing (i.e. planners, developers and municipal leaders) and those consuming (i.e. residents) Canadian suburbs believe mixing housing types can and does achieve. We examined suburban development trends using a comparative case study approach in four provinces. While planners and municipal councillors often advocated the benefits of mixed housing types, developers mitigated the risk of mixing at the neighbourhood scale by employing design strategies that separated particular housing types into price-sensitive pods, and residents remained sceptical about desirability of individual difference at the block level. Planners' ability to encourage block-level mixing in new areas remains constrained by homeowner perspectives that have changed relatively little over decades.

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.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.913
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.061
GPT teacher head0.357
Teacher spread0.296 · 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