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Record W4250682509 · doi:10.32920/ryerson.14654670

Where to move? Evaluating the potential of BMO field and Varsity Centre to host the Toronto Argonauts

2021· preprint· en· W4250682509 on OpenAlexaffabout
Jake M. Garland

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of GuelphToronto Metropolitan University
Fundersnot available
KeywordsRedevelopmentLeaseLeagueLocale (computer software)FootballHost (biology)Agency (philosophy)AtlantaBusinessManagementMarketingMetropolitan areaEngineeringSociologyGeographyCivil engineeringArchaeologyFinanceComputer scienceEconomics

Abstract

fetched live from OpenAlex

The Toronto Argonauts are the oldest continuously running professional football team in North America and a storied franchise within the Canadian Football League. However, they are also a team facing vagrancy, with their lease at Rogers Centre expiring on December 31, 2017 and have historically had trouble-selling tickets at this locale. The team is now looking to play in a smaller established venue that is more realistic to fill and such stadiums suggested have included BMO Field and Varsity Centre. Therefore, the research within this paper addresses the gap in the planning knowledge of which of these two stadiums should be chosen to move the team to from evaluations that include redevelopment cost, site location, accessibility, and a surrounding land use. The research highlights that Varsity Centre has the greatest potential, while also providing a set of recommendations for either site to optimize the potential to host the team.

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)0.006
metaresearch head score (Gemma)0.016
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 score0.694
Threshold uncertainty score0.608

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.035
GPT teacher head0.353
Teacher spread0.318 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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