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Record W4249745954 · doi:10.32920/ryerson.14661402

Rethinking planning in a digital marketplace: implications of e-commerce for land use policy in Toronto

2021· preprint· en· W4249745954 on OpenAlexaffabout
John F. Federici

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicUrbanization and City Planning
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsThrivingReal estateBusinessLand usePlan (archaeology)Government (linguistics)Key (lock)Land-use planningScenario planningMarketingEnvironmental planningFinanceGeographyEngineeringComputer science

Abstract

fetched live from OpenAlex

The intention of the Growth Plan for the Greater Golden Horseshoe is to create a planning framework that achieves complete communities and a thriving economy. However, there is minimal direction for municipalities planning for retail development to realize these goals. This is problematic, as e-commerce is disrupting the retail industry and is transforming the commercial and industrial real estate that support it. This paper examines e-commerce growth over the past thirteen years in Canada and demonstrates how this is prompting changes in both land markets through two case studies. Case studies identify implications that e-commerce will create for land use policy in Toronto moving forward. Recommendations presented to address these implications prompt upper levels of government to collect data to inform decision making at the municipal level. Recommendations for the City of Toronto are aimed at relaxing land use policies to create a strategy to facilitate efficient goods movement. Key words: E-commerce; Land Use Policy; Toronto, Canada

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 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)0.002
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 score0.174
Threshold uncertainty score0.920

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.068
GPT teacher head0.371
Teacher spread0.304 · 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 teacher head, 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

Citations0
Published2021
Admission routes2
Has abstractyes

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