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Record W1994562683 · doi:10.4018/jagr.2013010103

Retail Development in Urban Canada

2013· article· en· W1994562683 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Applied Geospatial Research · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSpatial and Panel Data Analysis
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsMetropolitan areaBivariate analysisGeographyRegional scienceSituatedKernel density estimationKernel (algebra)Work (physics)Economic geographySpatial ecologyBusinessComputer scienceEngineeringStatisticsMathematics

Abstract

fetched live from OpenAlex

During the last decade, rapid changes have occurred in the retail economy of North America that has brought about a functional transformation of retailing. Using data from a longitudinal database of commercial activity, this paper explores spatio-temporal patterns of retail development within Canada’s largest metropolitan region, the Greater Toronto Area (GTA). The paper provides an overview of the evolution of retailing in Canada and spatio-temporal analysis of the developing retail structure of the GTA. The work is situated within the branch of spatial statistics concerned with the description of spatial point processes. Bivariate kernel estimation and the G function are used to describe spatial patterns of retailing over time and by retail format type. The results highlight the wave of power centre retailing that swept across the GTA between 1996 and 2005. The paper concludes with a discussion of the gap between policy and planning and an emerging retail reality.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.064
GPT teacher head0.274
Teacher spread0.211 · 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