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Record W3172205990 · doi:10.25082/he.2021.01.001

Repurposing a community asset for revitalizing cities: The future of FirstOntario Centre in Hamilton

2021· article· en· W3172205990 on OpenAlexaffabout
Ahmed Taha Qureshi, Gail Krantzberg

Bibliographic record

VenueHealth and Environment · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRepurposingAsset (computer security)ExcellenceOrder (exchange)StadiumSpace (punctuation)BusinessSustainable communitySustainable developmentMarketingEngineeringFinancePolitical scienceComputer scienceComputer security

Abstract

fetched live from OpenAlex

This paper explores the possibility of renovating the FirstOntario Centre in Hamilton, Ontario, a large hockey stadium that can also be used to host concerts and similar events. Presently the facility is too big to fit the needs of Hamiltonians in a sustainable way and the excess space/seating raise the cost of maintenance unnecessarily while leaving the arena severely underutilized at around an average of just over 50% utilization. In other words, FirstOntario Centre is a case study in regenerating excellence. We describe the challenges and potential solutions to repurpose this space in order to regenerate social, economic, and environmental excellence in the heart of this mid-sized Ontario city. This case study can inform others seeking to reinvigorate attributes of livable cities.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.277

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0150.007
Scholarly communication0.0060.002
Open science0.0020.006
Research integrity0.0020.001
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 head0.044
GPT teacher head0.313
Teacher spread0.269 · 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 designNot applicable
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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