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Record W4384697887 · doi:10.22215/etd/2023-15637

Human Scale: Towards Supportive Housing in Ottawa's Byward Market

2023· dissertation· en· W4384697887 on OpenAlexaboutno aff
Mathieu Mark Denis

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsDocumentationArchitecturePlan (archaeology)Work (physics)Public housingPublic relationsScale (ratio)Political scienceSociologyArchitectural engineeringEngineeringCivil engineeringGeographyComputer science

Abstract

fetched live from OpenAlex

In 2014, the City of Ottawa adopted a 10-year plan that committed to ending chronic homelessness by 2024. Despite efforts, the waiting list for social housing has expanded dramatically, leaving many still reliant on shelters. Building on the notion that presence prompts awareness, the work argues that an architecture that promotes social interaction between community members and people who are unhoused benefits all. Through on-site documentation and interviews, the thesis first demonstrates the importance of design knowledge acquired through designer presence. Then, a proposal examines the opportunities for a multi-building inclusive site—one providing residential, social support, and community spaces while being conscious of its historical, environmental, psychological, and economic impacts. Overall, the work aims to raise awareness on homelessness and to provide innovative design strategies that invite discussion on the importance of architecture in providing spaces better acknowledging housing as a basic human right.

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 score0.220
Threshold uncertainty score0.442

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.013
Scholarly communication0.0070.003
Open science0.0020.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.001

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 head0.052
GPT teacher head0.456
Teacher spread0.403 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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