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Record W7067988667

Moving Differently - Exploring Neurodivergent Mobility through Scholarship, Lived Experience, and Urban Policy

2025· other· en· W7067988667 on OpenAlexaboutno aff

Bibliographic record

VenueQSpace (Queen's University Library) · 2025
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEquity (law)Lived experienceQualitative researchUrban planningQualitative analysisPublic policyUrban policy
DOInot available

Abstract

fetched live from OpenAlex

This report, Exploring the Neurodivergent Travel Experience, investigates the lived urban travel experiences of students with attention deficit hyperactivity disorder (ADHD) at Queen’s University, while also examining the extent to which neurodiversity is represented in Canadian planning policy. Despite the growing interest in inclusive urban design and differentiated mobility experiences, the unique needs of neurodivergent travelers, particularly those with ADHD, remain underexplored in academic literature and policy frameworks. To address this gap, this study employed a mixed-methods approach, consisting of (1) a comprehensive literature review, (2) an environmental scan of 28 transportation, accessibility, and equity policy documents from large Canadian cities, and (3) a qualitative analysis of semi-structured interviews with seven Queen’s students with ADHD.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.742
Threshold uncertainty score0.518

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0150.016
Scholarly communication0.0090.004
Open science0.0010.009
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.046
GPT teacher head0.205
Teacher spread0.159 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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