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Record W4246269480 · doi:10.22215/etd/2017-11991

On Beauty and Being an Architect

2017· dissertation· en· W4246269480 on OpenAlexaboutno aff
André Pacheco de Assis

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldArts and Humanities
TopicArchitecture and Cultural Influences
Canadian institutionsnot available
Fundersnot available
KeywordsBeautyExcellenceObligationValue (mathematics)Independence (probability theory)Economic JusticeMoral obligationEnvironmental ethicsNatural (archaeology)SociologyAestheticsEngineeringManagementPolitical scienceEngineering ethicsLawArtHistoryPhilosophyComputer science

Abstract

fetched live from OpenAlex

The Ontario Association of Architects Code of Ethics states that "members should… strive for design excellence and in so doing, members should thoughtfully consider and respect both the natural and cultural environment of the communities in which they are practicing."But what exactly is design excellence?Does it in any way entail the obligation to make spaces and experiences that are beautiful?In her book, On Beauty and Being Just, Elaine Scarry argues that beauty presses us toward a greater concern for justice.Based on this work, this thesis explores the significance of beauty and the role that it plays in the experience of the built world.Specifically, the thesis asks, "What guides the hand of the architect when working to reintroduce a lost beauty."The thesis is tested through a proposal for a site in Ottawa's Lowertown that holds significant historical value, but has suffered from decades of neglect.Only two facades, supported by steel bracing, remain of the original Our Lady's School structure.The proposed design repurposes the existing structure as cooperative housing for senior women.Drawing upon studies documented in Atul Gawande's book, Being Mortal: Medicine and What Matters in the End, the project is designed as a supportive environment for senior women to keep their

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)0.004
metaresearch head score (Gemma)0.004
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: Other · Consensus signal: Other
Teacher disagreement score0.013
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.046
Scholarly communication0.0080.005
Open science0.0010.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.026
GPT teacher head0.277
Teacher spread0.252 · 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
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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