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Record W4234319952 · doi:10.32920/ryerson.14647233.v1

Material Politics of Micro Urban Housing

2021· preprint· en· W4234319952 on OpenAlexaffabout
Shea MacDougall

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicArchitecture, Design, and Social History
Canadian institutionsToronto Metropolitan University
FundersDivision of Graduate EducationUniversity of Cambridge
KeywordsArchitecturePoliticsUrban designAgency (philosophy)Flexibility (engineering)Architectural engineeringSpace (punctuation)Economic geographyProcess (computing)Set (abstract data type)Regional scienceEconomyBusinessSociologyPolitical scienceGeographyEngineeringComputer scienceSocial scienceEconomicsManagement

Abstract

fetched live from OpenAlex

This thesis investigates various socio-material trends that influence housing culture within increasingly intensified urban conditions. These trends indicate emerging societal values relating to affordability, the sharing economy and the reterritorialization of both domestic and urban environments. Design research contemplates how these values align with emerging theories related to material politics and how the design of our built environment can inform society’s perception of a greater affective density. These theories describe the interrelationships between architecture, our shared consumption of energy and resources, material agency, and designed flexibility of urban and domestic space. These interrelationships define a set of objective comparators that are used in the evaluation of various housing types that are familiar to western cultures. An analysis of this evaluation describes a morphology of domestic architecture that guides the design process of creating a micro housing model located in Toronto’s urban core.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.032
GPT teacher head0.222
Teacher spread0.190 · 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 routes2
Has abstractyes

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