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Record W2050878681 · doi:10.1017/s0145553200011664

Trading Places

2011· article· en· W2050878681 on OpenAlexaboutno aff
Mathew Novak, Jason Gilliland

Bibliographic record

VenueSocial Science History · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Crisis of the 21st Century
Canadian institutionsnot available
Fundersnot available
KeywordsDowntownVariety (cybernetics)GeographyEconomic geographyRetail tradeRationalityRetail salesBusinessEconomyRegional scienceMarketingCommerceArchaeologyEconomicsPolitical scienceComputer science

Abstract

fetched live from OpenAlex

The economies of modern cities are dependent on an advanced retail system; so too are the people who inhabit them. The origin and evolution of retailing in London, Canada, was studied using a historical geographic information system (GIS) to document the relationship between a city and its retail sector. Visualization and spatial-statistical techniques afforded by the historical GIS were implemented to study change over time. The locations of retailers and the types of the goods they sold were examined for four periods in the city’s early history: 1844, 1863, 1881, and 1916. The distances traveled to shop were also calculated for a variety of goods. The results indicate that the retail system was ingrained in the development of the city, showing marked locational patterns and a high degree of rationality in the shopkeepers' business strategies. Mapping the retail landscape in each era using historical GIS allowed for the examination of the relationship between retail and residential development in the growing city. While the downtown area remained the primary retail district for the city, considerable retail expansion also occurred at the urban periphery during this early stage of the city's development.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.205
Threshold uncertainty score0.686

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.2050.053

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 head0.094
GPT teacher head0.209
Teacher spread0.116 · 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

Citations7
Published2011
Admission routes1
Has abstractyes

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