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Record W4402689450 · doi:10.29173/topo50

From Railyards to Hockey Games

2024· article· en· W4402689450 on OpenAlexaffvenueabout
Jaden Macyk

Bibliographic record

VenueTopophilia · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIce hockeyPhysical medicine and rehabilitationMedicine

Abstract

fetched live from OpenAlex

The impeccable revival of the land in which the current Ice District stands follows a narrative of overcoming challenges in the pursuit of long-term vibrancy and influential transformation. Examining the land-use history of the past century shows the undeniable impact of railways and suburbanization on Edmonton's downtown to the contemporary initiation of redevelopment plans set by the city and vital actors under the Katz Group. Through detailing the collaboration of the public and private sectors, necessary zoning changes, and key financial negotiations, the added complexity behind these large-scale projects is evident. This paper also acknowledges the challenges that arise from issuing dramatic transformations, such as the social issues of gentrification, displacement, and in the economic realm of funding. The concluding statements reflect on this urban development's success in influencing future development strategies while remembering there are necessary efforts we must engage in to consider a balance between addressing social issues alongside inspiring growth in Edmonton's downtown spheres.

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 score0.076
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.003
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0390.003

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 head0.029
GPT teacher head0.327
Teacher spread0.298 · 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
Published2024
Admission routes3
Has abstractyes

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