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Record W7132944210

Mistakes by the Lake: Making and Unmaking Space at the Canadian National Exhibition

2021· dissertation· W7132944210 on OpenAlexaboutno aff
Jesse Allan Munroe

Bibliographic record

VenueTSpace · 2021
Typedissertation
Language
FieldEngineering
TopicArchitecture, Modernity, and Design
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionInvisibilityNewspaperValue (mathematics)ArchitecturePublic spaceSpace (punctuation)
DOInot available

Abstract

fetched live from OpenAlex

This dissertation examines the Canadian National Exhibition and its site, Exhibition Place in Toronto, to explore the changing constellation of meanings surrounding public architecture over the past century. It reveals the cultural, financial, spatial and emotional dimensions of the built environment. It argues that public structures carry deep-rooted, variegated societal implications, which can be recovered by examining their “lives” and the furor sometimes surrounding their “deaths.” Landmarks are invaluable pieces of civic machinery; they are storehouses of memory and focuses of ritual, and through them we can learn a great deal about the concerns and values of Canadians in the past. As a city-owned site, Exhibition Place offers a uniquely abundant array of archival and newspaper sources for such an intervention. From the 1900s, when the CNE remade itself in the image of Chicago's White City fairground, to the post-war era when it became Toronto's proving ground for modern architecture, to the present day when the trend is to destroy rather than to create functional public spaces, the city's waterfront has experienced far more change than continuity. Each generation has interpreted their forebears' legacies in a different light, and found new ways to adapt, corrupt, or misuse them. Financial concerns have transformed Exhibition Place from a working site of memory to a nearly featureless, antiseptic trade show complex. Few Torontonians have appreciated the value of their old buildings, a situation worsened by the CNE's invisibility during the fifty weeks each year during which it does not operate. This has made any attempt at historical preservation an extremely fraught affair. By studying the evolution and devolution of public architecture, then, we are also studying the evolution and devolution of our senses of self.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.065
Threshold uncertainty score0.469

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0490.015
Scholarly communication0.0090.003
Open science0.0030.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0160.001

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 head0.024
GPT teacher head0.282
Teacher spread0.257 · 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 routes1
Has abstractyes

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