Autism spectrum disorder in architecture perspective: a review of the literature and bibliometric assessment of research indexed in Web of Science
Bibliographic record
Abstract
<ns4:p> <ns4:bold>Purpose:</ns4:bold> </ns4:p> <ns4:p>An increasing number of scholarly publications on autism spectrum disorder (ASD) have urged researcher interest in this topic; however, there is still a lack of quantitative analysis. Therefore, this study aims to cover the knowledge gap between the amount of literature published on ASD research on architectural and designers' perspectives compared to the medical and psychological fields. The study has analyzed global research output on ASD from a designer's perspective to recognize this gap related to designing the physical environment. </ns4:p> <ns4:p> <ns4:bold>Methodology:</ns4:bold> </ns4:p> <ns4:p>The bibliometric method was employed to analyze the published literature from 1992–to 2021. 812 papers were downloaded from the Web of Science for analysis based on annual growth of literature, prolific authors, authorship pattern, organizations, countries, international collaboration, and subject development by keywords and thematic map analyses. Various bibliometric and scientometric software was used to analyze the data, namely Bibexcel, Biblioshiny, and VOS viewer.</ns4:p> <ns4:p> <ns4:bold>Results:</ns4:bold> </ns4:p> <ns4:p> The812 research papers were published in 405 sources. 2019 appeared as a productive year (NP=101), and 2014 received the highest number of citations (TC=6634). Researchers preferred to publish as journal articles (NP=538; TC=24922). The University of Toronto, Canada, was identified as a productive institution with 42 publications and 5358 citations. The USA was the leading producing country with 433 publications, and most of the researchers published in the journal " <ns4:italic>Scientific Reports</ns4:italic> " (NP=16). The word autism (NP=257) and architecture (NP=165) were more frequently used keywords. </ns4:p> <ns4:p> <ns4:bold>Conclusion:</ns4:bold> </ns4:p> <ns4:p>The study identified a massive gap in the development of literature in ASD for architecture design and built environment perspective, the most important and trending keywords are missing, and the analyses also showed a lack of subject development. The authors have suggested areas and keywords for further research to fulfill the gap in the future.</ns4:p>
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | high |
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.095 | 0.365 |
| Science and technology studies | 0.000 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.000 | 0.007 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".