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Record W3113800085 · doi:10.1108/arch-08-2020-0159

How our homes impact our health: using a COVID-19 informed approach to examine urban apartment housing

2020· article· en· W3113800085 on OpenAlexaff
Terri Peters, Anna Halleran

Bibliographic record

VenueInternational Journal of Architectural Research Archnet-IJAR · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsApartmentUrban designArchitectural engineeringBuilt environmentBuilding designPublic housingArchitectureEnvironmental planningPsychologyUrban planningEngineeringCivil engineeringGeography

Abstract

fetched live from OpenAlex

Purpose The COVID-19 global health crisis is undeniably a global housing crisis. Our study focuses on quality of life in urban mid- and high-rise apartment housing, the fastest growing housing types in many cities around the world. This housing typology presents unique challenges relating to connection to nature, daylight and fresh air. Design/methodology/approach This multi-disciplinary literature review analyzes more than 100 published papers from peer-reviewed sources from environmental psychology, building science and architecture relevant to quality of life in high-rise housing, as well as more than 40 recent newspaper and magazine articles about the possible impacts of COVID-19 on housing. We identify synergies between passive design strategies and health-promoting architecture or “restorative environmental design” principles. Findings Post-pandemic, health-promoting apartment housing design must prioritize (1) window placement and views that support stress recovery and restoration; (2) lighting levels based on spaces that can satisfy multiple uses and users; (3) bedrooms designed for restful sleep that contribute to circadian regulation; (4) living rooms with better indoor air quality, with a focus on natural ventilation; (5) access to nature, through the purposeful design of balconies and (6) unit sizes and layouts that enable physical distancing and prevent crowding. Originality/value We identify new social and environmental design priorities in the form of evidence-based design principles to inform and promote healthy and restorative living environments for residents in apartment housing.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.195
GPT teacher head0.444
Teacher spread0.249 · 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 designObservational
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

Citations191
Published2020
Admission routes1
Has abstractyes

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