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Record W4384665956 · doi:10.22215/etd/2023-15630

An Alternative City: Tracing Mental Health Consequences Across Ottawa's Urban Fabric

2023· dissertation· en· W4384665956 on OpenAlexaboutno aff
Emily Ann Eikeland

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsLonelinessMental healthPublic spaceDowntownRealmHappinessPsychological interventionMateriality (auditing)Isolation (microbiology)Public healthSocial isolationBuilt environmentPsychologyPublic relationsSociologyGeographyEngineeringPolitical scienceCivil engineeringArchitectural engineeringSocial psychologyMedicineNursing

Abstract

fetched live from OpenAlex

The quality of our built environment affects our happiness, well-being, and mental health through conditions of loneliness and isolation. Ottawa’s urban realm fosters many ‘devices of isolation’ throughout its landscape, as displayed through its materiality, privatized living, and lack of engaging public space at the street level. Research has found these conditions of social isolation among urban residents negatively affect one’s health and well-being. However, cities still lack consideration for the quality and quantity of their social spaces. In order to provide opportunities for social interaction to improve mental health conditions among residents and reinforce a sense of human-centered design, a reconsideration of Ottawa’s public and private-public-facing space is needed. By proposing a network of interventions that reimagine existing plazas in downtown Ottawa, this project aims to question how we can use our cities to foster human connection to reduce urban isolation and subsequent mental health conditions.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.337

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0080.004
Scholarly communication0.0040.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.065
GPT teacher head0.373
Teacher spread0.308 · 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
Published2023
Admission routes1
Has abstractyes

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