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Record W1994562683 · doi:10.4018/jagr.2013010103

Retail Development in Urban Canada

2013· article· en· W1994562683 on OpenAlexaffabout
Ron Buliung, Tony Hernández

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.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.575

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.010
Science and technology studies0.0040.001
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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

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 designObservational
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

Citations6
Published2013
Admission routes2
Has abstractyes

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