MétaCan
Menu
Back to cohort
Record W4402199790 · doi:10.32920/26866612

Sensorial Stimuli in the Built Environment: A Review of the Effects of Stimuli for People Living with Autism and Solutions to Creating More Equitable Cities

2024· review· en· W4402199790 on OpenAlexaff
Katrina Munshaw

Bibliographic record

Venuenot available
Typereview
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsCarleton UniversityToronto Metropolitan University
Fundersnot available
KeywordsAutismPsychologyCognitive psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Sensorial stimuli is an important feature of the built environment that is often overlooked. Sensory components of the built environment have a direct effect on autistic individuals. This scoping review aims to answer the following questions: (1) What does the literature say about design for autism, particularly in reference to sensorial experiences of the built environment? (2) What design features can urban planners/designers use to potentially mitigate the severity of sensorial stimuli? This study has identified the issues, themes, and contradictions in the current literature and applies a just city framework to potential design and policy solutions.

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.068
GPT teacher head0.410
Teacher spread0.342 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicNoise Effects and ManagementFrench-language works237,207