The Spectrum of Accessible Architectures: Designing for Neurodivergence
Bibliographic record
Abstract
In the field of architecture, “accessibility” all too often addresses only “physical accessibility.” Consequently, the sensory barriers facing neurodivergent individuals as they navigate the built environment beg to be considered and addressed. This thesis embraces truly inclusive accessibility via an exploration of sensory perception and its relationship to architectural experience. From this exploration there emerges a neuro-inclusive design methodology that promises to close the gap between the built environment and sensory impairment. The use of the term “spectrum” refers to the span extending from hyper- to hypo-sensitivity and encapsulates the diversity of sensory ability experienced by the neurodivergent population. As an architectural approach, the spectrum construct is well-suited to welcoming flexibility and adaptations and holds promise in inclusive architectural design. To showcase the potential of a “spectrum design” methodology in a real-world context, this thesis concludes in an architectural proposal for a neuro-inclusive student centre on Carleton University’s Campus.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".