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Record W3199112799 · doi:10.1080/02697459.2021.1979786

Smart Growth in Canada’s Provincial North

2021· article· en· W3199112799 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

VenuePlanning Practice and Research · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversity of Northern British Columbia
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Northern British Columbia
KeywordsSmart growthNeighbourhood (mathematics)SustainabilityContext (archaeology)Urban sustainabilitySmart citySustainable growth rateGrowth managementGeographyCapital (architecture)Economic geographyCapital cityRegional scienceEnvironmental planningUrban planningEconomic growthBusinessEconomicsLand useInternet of ThingsEngineeringCivil engineeringComputer scienceEcologyComputer security

Abstract

fetched live from OpenAlex

Smart growth promotes urban sustainability by encouraging increased densities, mixed use, walkable design, and access to diverse transportation and housing options. This study applies literature-derived indicators to examine urban change in the city of Prince George; British Columbia’s northern capital. Findings illustrate that key growth nodes have largely performed (e.g., densified) at or below the level of their surrounding neighbourhood over time despite a robust set of policy tools associated with smart growth. This research is one of few to examine smart growth in a northern urban context, and situates the concept within the slow growth/no growth realities of many rural and remote regions.

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)0.003
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 score0.089
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.086
GPT teacher head0.406
Teacher spread0.320 · 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