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Record W2074394425 · doi:10.4018/jagr.2013010104

Recent Trends of Ethnic Chinese Retailing in Metropolitan Toronto

2013· article· en· W2074394425 on OpenAlexaffabout
Shuguang Wang, Rebecca Hii, Jason Zhong, Paul Du

Bibliographic record

VenueInternational Journal of Applied Geospatial Research · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsUniversity of AlbertaToronto Metropolitan University
Fundersnot available
KeywordsEthnic groupMetropolitan areaRedressImmigrationMainstreamEconomic geographyGeographyScale (ratio)PopulationBusinessEconomyPolitical scienceSociologyCartographyEconomics

Abstract

fetched live from OpenAlex

As the population diversifies in many North American cities due to increased immigration, ethnic retailing has become an important and increasingly visible component of the local retail economy. To date, business geographers have paid little attention to ethnic retailing. This paper attempts to redress this gap by providing a spatial analytical study of the demand for and supply of ethnic retail in the largest Canadian urban market, Toronto. The findings highlight that since the late 1990s, ethnic Chinese retailing in the Toronto market has continued to expand. Three key trends are identified. First, there has been a resurgence of food retailing and growth of modern large-scale supermarkets. Second, developments have begun to shift away from clusters of exclusive ethnic retailing towards a mix with mainstream businesses. Third, a new corridor of ethnic Chinese retailing has developed forming the geographical center of an emerging Chinese-dominated ethnoburb.

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)0.001
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 score0.044
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.062
GPT teacher head0.424
Teacher spread0.362 · 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

Citations9
Published2013
Admission routes2
Has abstractyes

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Same venueInternational Journal of Applied Geospatial ResearchSame topicMigration, Ethnicity, and EconomyFrench-language works237,207