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Record W2903456438 · doi:10.29173/invoke29329

Adaptive Reuse of Sport Stadiums and Collective Memories: Rexall Place as a Site for the Continuation of the Oilers Dynasty and Civic Pride

2017· article· en· W2903456438 on OpenAlexvenueaboutno aff
SUSA Submissions, Alec Skillings

Bibliographic record

VenueINvoke · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsnot available
Fundersnot available
KeywordsPrideArchitectureAdaptive reusePoliticsIdeologyIdentity (music)SociologyCollective identityDemolitionRepresentation (politics)Political economyPolitical scienceMedia studiesAestheticsLawHistoryArchaeology

Abstract

fetched live from OpenAlex

Sports stadiums work to shape the identity of cities and reflect their cultural attitudes. From the Luzhniki Sports Complex’s material representation of Soviet Russia’s political leanings and ideologies to the Houston Astrodome’s display of technological advancement, stadia architecture has strong connections to regional zeitgeists. In this paper, I explain the importance of stadia architecture and how it is embedded in the collective memories of sports fans and citizens. As well, I explain how stadia architecture carries political and social consequences. Adaptive reuse or demolition of abandoned stadia also carries social and political consequences as stadia have the ability to embody the social history and civic imagination of their cities. I then present the case of Edmonton's Rexall Place arena, and provide an account of why it is important to repurpose the structure as a place for hockey. Ultimately Edmonton's collective memories and identity are held within the cement walls of Rexall Place, and the demolition of the structure would be detrimental to the hockey-centric civic identity and history.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.986
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0060.016
Scholarly communication0.0050.003
Open science0.0010.005
Research integrity0.0010.001
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 head0.079
GPT teacher head0.247
Teacher spread0.168 · 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 designQualitative
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
Published2017
Admission routes2
Has abstractyes

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