MétaCan
Menu
Back to cohort
Record W4252916584 · doi:10.22215/etd/2021-14586

Fugitive Architecture: Obsolescence, Aspiration, and Adaptation in Vancouver's Urbanizing Industrial Areas

2021· dissertation· en· W4252916584 on OpenAlexaboutno aff
Michael Jaworski

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsnot available
Fundersnot available
KeywordsObsolescenceArchitectureArchitectural engineeringGentrificationBuilt environmentPoliticsAdaptabilityUrban designUrban planningSociologyEnvironmental planningEngineeringCivil engineeringEconomic geographyGeographyPolitical scienceBusinessArchaeologyMarketingManagementEconomicsLaw

Abstract

fetched live from OpenAlex

'Fugitive Architecture' is a provocation born as a response to development practices that commodify architecture through the dictum of "highest and best use." In contrast to market-driven aspirational architecture, this thesis problematizes notions of urban decay and renewal, unsettling norms of market economics and urban planning. Profit-driven design methodologies diminish a building's material quality and longevity, adversely impacting life-cycle outcomes. Central to this thesis is a new design approach that embraces obsolescence and uses adaptability to prolong building lifespans while anticipating aging. This expands material and temporal notions of transience to include socioeconomic and political factors in the built environment. Fieldwork, including the photographic documentation of existing conditions in Vancouver's urbanizing industrial landscapes, informs speculative design interventions over a continuum of scales, from infrastructures to assembly details. Fugitive architecture reciprocates the evolving needs of building inhabitants, area residents, and local communities as they face pervasive gentrification.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score0.792

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0110.010
Scholarly communication0.0070.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.199
Teacher spread0.182 · 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 designQualitative
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

Explore more

Same topicArchitecture and Computational DesignFrench-language works237,207