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Record W4242031014 · doi:10.32920/ryerson.14666292

Defining Accessibility: A Snapshot of Accessibility Planning and a Review of Practice in Ontario

2021· review· en· W4242031014 on OpenAlexaffabout
Ashley E. Varajão

Bibliographic record

Venuenot available
Typereview
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsSnapshot (computer storage)Point (geometry)Field (mathematics)Political scienceEnvironmental planningBusinessPublic relationsGeographyComputer science

Abstract

fetched live from OpenAlex

Despite the growing importance of accessibility planning and the legislated recognition of Human Rights in the planning profession, there is no universal, operational definition of accessibility planning. Moreover, the objectives of accessibility planning for municipalities and the private sector are largely ambiguous beyond the point of minimum Ontario Building Code standards. This MRP provides an annotated bibliography on the various subcategories that inform accessibility planning, which can act as a starting point for practitioners who are unfamiliar with the subject. The paper also analyzes the current understanding of accessibility in planning and related fields to provide an immediate understanding of accessibility, as well as note areas of similarity or conflict in varying sectors. The report concludes with a discussion of some potential areas for future research and development within the field.

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)0.006
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 score0.211
Threshold uncertainty score0.425

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.027
Science and technology studies0.0020.003
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.101
GPT teacher head0.437
Teacher spread0.337 · 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
Published2021
Admission routes2
Has abstractyes

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