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Record W2117785882 · doi:10.7202/1006405ar

A Model Suburb for Model Suburbanites: Order, Control, and Expertise in Thorncrest Village

2011· article· en· W2117785882 on OpenAlexvenueaboutno aff
Patrick Vitale

Bibliographic record

VenueUrban History Review · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsSuburbanizationElitePlannerConformitySociologyUrban planningOrder (exchange)SubdivisionGeographyEconomic growthPolitical scienceArchaeologyBusinessCivil engineeringDemographyLawEngineeringComputer scienceEconomics

Abstract

fetched live from OpenAlex

In 1945, Marshall Foss began construction of Thorncrest Village, a subdivision in Etobicoke just to the west of Toronto. Foss and urban planner Eugene Faludi envisioned Thorncrest Village as nothing less than a model suburb for postwar Canada. They created a community that embodied the ideals of modern suburban planning: conformity, community, privacy, stability, and a careful mixture of nature and city. They developed an orderly and controlled suburb that secured upper-middle-class residents’ financial investments and their social status. These residents, in turn, placed unbounded faith in Foss and Faludi’s expertise and identified with the Village as a landmark experiment in modern suburban living. Thorncrest Village became a key site that intertwined the expertise of modern urban planning and the identities of elite suburbanites. The values that developers and residents put into place in Thorncrest Village—particularly the pursuit of order and control—are significant components of suburbanization in Canada and elsewhere.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.100
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0090.011
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.090
GPT teacher head0.259
Teacher spread0.169 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations3
Published2011
Admission routes2
Has abstractyes

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