MétaCan
Menu
Back to cohort
Record W4310870444 · doi:10.18280/ijsdp.170717

Responsiveness and Adaptability of Housing Spatial Design to New Emerging Functions: The Case of COVID-19 Pandemic

2022· article· en· W4310870444 on OpenAlexvenueno aff
Mohammed Itma, Sameh Monna

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsAdaptabilityAdaptation (eye)Flexibility (engineering)Coronavirus disease 2019 (COVID-19)Merge (version control)PandemicMaladaptationArchitectural engineeringPlan (archaeology)Computer scienceBusinessRisk analysis (engineering)Process managementEngineeringPsychologyGeographyMedicineMathematicsEconomics

Abstract

fetched live from OpenAlex

The paper aims to measure the ability of housing design in Palestine to respond to any emerging functions and needs and the ability to adapt to new and possible sudden lifestyle changes. Four different interior house types were analyzed, two refer to the traditional approach of the closed plan, and another two types refer to the modern approaches of the open plan in terms of adaptation to new needs. These needs are adaptability to work from home, flexibility to change, separate or merge functions, and the adaptability to respond to health issues like quarantine. The study adopts the method of architectural analysis and questionnaire to measure people's opinions about all types in terms of sudden functions. The study takes the COVID-19 pandemic conditions as a case study. The main finding of the study is establishing a relationship between style of housing spatial design and the ability for adapting sudden changes in lifestyle. It shows that the traditional designs adapt to most changing lifestyles successfully, the independent guest room was converted into an office or guaranteed room. Moreover, the modern open plan house design with a T shape of the day wing is the best choice for adapting to the post-COVID-19.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.155
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.086
GPT teacher head0.343
Teacher spread0.257 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Sustainable Development and PlanningSame topicUrban and Rural Development ChallengesFrench-language works237,207