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Record W1917587781 · doi:10.14288/bcs.v0i173.2371

"Is Sutton Brown God?" Planning Expertise and the Local State in Vancouver, 1952-1973

2011· article· en· W1917587781 on OpenAlexaffabout
W. R. Langford

Bibliographic record

VenuecIRcle (University of British Columbia) · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLocal planningState (computer science)Context (archaeology)Local governmentDehumanizationPublic administrationGovernment (linguistics)Political scienceUrban planningSociologyManagementOperations researchLawEngineeringHistoryEnvironmental planningGeographyComputer scienceEconomicsArchaeologyCivil engineeringPhilosophy

Abstract

fetched live from OpenAlex

In the late 1940s and early 1950s, city planning was, for the first time, drawn into the processes of the local state in a meaningful way. Planning departments and new administrative structures were created that gave planners and planning expertise a privileged and central role in the operation of the local state. Gerald Sutton Brown, first as Director of Planning and then as City Commissioner, was one such expert and he worked to implement a number of commonly held high modernist planning solutions in Vancouver. However, in the context of the global Sixties, the dehumanizing and undemocratic nature of high modernist planning expertise was revealed and confronted. This paper endeavours to explore the contours of the entrenchment of planning expertise within local government and the way in which it was eventually challenged.

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.554

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0310.012
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.000

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 head0.013
GPT teacher head0.177
Teacher spread0.163 · 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

Citations5
Published2011
Admission routes2
Has abstractyes

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