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Record W3111245299 · doi:10.22215/etd/2020-14233

Canopies and Catwalks: An Architectural Intervention of the Calgary Stampede Grounds

2020· dissertation· en· W3111245299 on OpenAlexaffabout
Jason Vandenberg

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsCarleton University
Fundersnot available
KeywordsDowntownExhibitionIntervention (counseling)Space (punctuation)ArchitectureVisual artsGeographyPsychologyArtComputer scienceArchaeology

Abstract

fetched live from OpenAlex

This thesis argues that there is a disconnect between exhibition space and daily life within Calgary, Alberta. The proposed design will be an intervention into Calgary's oldest exhibition space, the Calgary Stampede Grounds. While the site is host to numerous annual events, in its current state it is uninviting and underutilized considering its proximity to downtown Calgary. As an intervention the intention of this project is not to disrupt the integral programs of the site. Buildings that include The Saddledome, large event and conference buildings and the Calgary Stampede's Grandstand are important pieces of Calgary's identity. Rather, the intervention will focus on a form of urban densification, renewing the site and creates an inviting space for Calgarians to enjoy everyday. By attracting visitors to the site on a broader scale, the Calgary Stampede Grounds will become a destination for both daily life and Calgary's largest events.

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 score0.563
Threshold uncertainty score0.869

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.008
Scholarly communication0.0040.001
Open science0.0020.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.029
GPT teacher head0.305
Teacher spread0.276 · 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
Published2020
Admission routes2
Has abstractyes

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