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Record W2998199505 · doi:10.17742/image.oi.10.2.1

On the Mediality of Two Towers: Calgary—Toronto

2019· article· en· W2998199505 on OpenAlexvenueaboutno aff
Ira Wagman, Liam Cole Young

Bibliographic record

VenueImaginations Journal of Cross-Cultural Image Studies · 2019
Typearticle
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsnot available
Fundersnot available
KeywordsArtVisual arts

Abstract

fetched live from OpenAlex

This article uses the CN Tower and Calgary Tower to explore how the architectural form of the tower possesses a number of characteristics we typically associate with media technologies. To appreciate what we call “tower-mediality,” we start first with a brief discussion of the scholarly literature on towers, highlighting that while much is said about towers’ symbolic value, little attention has been devoted to thinking of these forms in material and infrastructural terms. Then we turn to the Canadian towers themselves, asking, first, why they have received so little scholarly attention, before suggesting some points of intersection between architecture and communication research. Finally, we offer three registers—ritual, perspective, and spectacle—by which to explore the mediality of the CN and Calgary Towers. In undertaking this analysis, we attempt to expand the vocabulary available for understanding how towers are platforms that mediate the temporal and spatial elements of civic culture and to invite further considerations of the mediating and communicative work that occurs along the vertical axis.

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)0.002
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: none
Teacher disagreement score0.078
Threshold uncertainty score0.566

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0270.018
Scholarly communication0.0070.003
Open science0.0010.004
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 head0.020
GPT teacher head0.363
Teacher spread0.343 · 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

Citations1
Published2019
Admission routes2
Has abstractyes

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