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Record W4211058287 · doi:10.32920/ryerson.14657889.v1

Rethinking space + place: negotiating a social realm between mobile technology and architecture

2021· preprint· en· W4211058287 on OpenAlexaffabout
Thomas Chan

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRealmArchitectureNegotiationPublic spaceSpace (punctuation)SociologyPerceptionSocial spaceSpatial designComputer sciencePolitical scienceEngineeringArchitectural engineeringEpistemologyVisual artsSocial scienceArt

Abstract

fetched live from OpenAlex

The thesis examines the relationship between mobile technology and architecture, and argues that architecture can better address the proliferation of mobile and communication technology through its social and perceptual implications. The thesis examines changing social conditions and spatial perception, through an investigation of our sense of space and place, and confirms the need to revisit the role of architecture in the physical public realm. Through observation and analysis in the underground PATH network in Toronto, the thesis tests these social and perceptual implications against real experiences, and establishes a role in which architecture can take part in rethinking space in the public realm. Through the design of a prototypical environment in Nathan Phillips Square, the thesis demonstrates that architecture, negotiating between direct, mediated, and virtual experiences, is capable of generating an augmented environment that enhances social engagement and encounters, making public space into places of public social encounters.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.021
Scholarly communication0.0070.007
Open science0.0010.009
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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 designTheoretical or conceptual
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 routes2
Has abstractyes

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