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Record W2773850956

Designing Inclusive Playscapes Across Sensorial + Socio-Spatial Boundaries

2017· other· en· W2773850956 on OpenAlexaboutno aff

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2017
Typeother
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Urban designDelphi methodPublic spaceSociologySpace (punctuation)ArchitecturePublic relationsUrban planningArchitectural engineeringGeographyPolitical scienceEngineeringComputer scienceCivil engineering
DOInot available

Abstract

fetched live from OpenAlex

Our emotional experience in public environments is considered to be superficial, although their configurations impact how well we can see, hear, move around, and interact in them daily. ‘Lonely, but not alone’ describes many of today’s urban dwellers. For some people, participation in civic life can be challenging, especially since the barriers (physical, psychological, etc.) faced by some are not always apparent to others, even to designers. This Major Research Project explores the relationship between the level of playfulness expressed in an urban space and user experience. Along with case study investigations and the Delphi method, 42 citizens (estimated to be 21 years of age or older) participated via interviews in Toronto, Canada. An urban design framework of 64 playful design features called The Multi-Playscape Toolkit, which can be used by urban designers and architects, has been developed and now contributes to the knowledge base. 
\n Using the Toronto context, recommendations are provided to promote more urban playfulness, more lenient policymaking, and more inclusive design practices in our public spaces.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity
Consensus categoriesScience and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.900
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0100.004
Scholarly communication0.0030.003
Open science0.0100.007
Research integrity0.0010.003
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 head0.052
GPT teacher head0.348
Teacher spread0.297 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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