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Record W3009525874 · doi:10.13140/rg.2.2.21327.02720

Hurry Up and Wait: Spatial Strategies for Urban Stress Relief

2020· dissertation· en· W3009525874 on OpenAlexaboutno aff
Maighdlyn Hadley

Bibliographic record

VenueUWSpace (University of Waterloo) · 2020
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional resilience and development
Canadian institutionsnot available
Fundersnot available
KeywordsStress reliefStress (linguistics)Materials sciencePhilosophyComposite material

Abstract

fetched live from OpenAlex

In the midst of rising urban density and its projected impacts on infrastructures and city dwellers alike, the importance of understanding the effects of built space on our biology and mental well-being is becoming essential to responsible spatial design. This thesis casts the designer as a practitioner focused on human impacts and synthesizes the lessons of current environmental psychology theory and mixed-methods biometric research into an analytical design framework to promote stress recovery and restoration. Architectural factors of scale, lighting, social organization, materiality, visual complexity, and enclosure are used as lenses through which to analyse an existing transit terminal and propose a reimagined space for waiting. 
\nAn identification of waiting rooms as high-opportunity areas within existing urban infrastructures led to the choice of Toronto Coach Terminal as a theoretical site in which to test the framework and to assess the value of restorative waiting environments. The subsequent design exploration takes the form of an open-ended kit of parts which creates seating areas and enclosures through a system of frames, connectors and panels to promote psycho-physiological restoration for a variety of users. 
\nTopics of framework development and user testing methodologies are addressed in an attempt to make disciplinary boundaries more porous and to co-solve questions with spatial implications using all available resources. Since both waiting and stress impact city dwellers more severely and the world is becoming increasingly urbanized, better access to and more seamless integration of restorative environments in the incidental spaces of the public realm would play a role in the management of stress at a population level.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score0.994

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)0.0000.000

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 head0.020
GPT teacher head0.199
Teacher spread0.179 · 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.

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
Published2020
Admission routes1
Has abstractyes

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