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Record W4206999097 · doi:10.32920/ryerson.14653959.v1

Thickening the Public Realm: Choreographing the Interaction of the Public Realm with the Built Environment

2021· preprint· en· W4206999097 on OpenAlexaff
Chowdhury Tasneem Rahman

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicRhetoric and Communication Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRealmPublic spaceVitalityArchitectural engineeringPublic spherePedestrianPublic domainAestheticsSociologyPolitical scienceGeographyPublic relationsCivil engineeringEngineeringArtArchaeologyLaw

Abstract

fetched live from OpenAlex

<p>The ground plane has always been the primary domain of public activities. However, cities developed under the Modernist influence demonstrate an “object-in-space” circumstance with proliferating sky-scrapers that fragment the city’s ground surface into mid-block spaces and vaguely defined plazas. The demands of motorized-transportation and private enterprise further scatter spaces for pedestrian activities across the plan, section and stratified layers of the city (subterranean or/and elevated networks).The result is an inconsistent public realm that remains from being animated by public vitality. Through the manipulation of the ground-plane, this thesis seeks to remedy such stratification. It posits that a thickening of the ground to create a three-dimensional spatial condition will amplify opportunities for social interaction within otherwise muted civic surfaces. Addressing the contemporary reality of the multiplied ground, this thesis advocates reactivating it as a thickened continuous public domain that dissolves the polarity between the built and social fabric of the city.</p>

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.881
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0020.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.084
GPT teacher head0.252
Teacher spread0.168 · 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 teacher head, not a consensus.

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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