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Record W1534967619 · doi:10.1123/apaq.28.1.1

Universal Accessibility of “Accessible” Fitness and Recreational Facilities for Persons With Mobility Disabilities

2011· article· en· W1534967619 on OpenAlexaffabout
Kelly P. Arbour‐Nicitopoulos, Kathleen A. Martin Ginis

Bibliographic record

VenueAdapted Physical Activity Quarterly · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRecreationPhysical fitnessUniversal designPsychologyGerontologyTransport engineeringComputer sciencePhysical therapyMedicineEngineeringWorld Wide WebBiologyEcology

Abstract

fetched live from OpenAlex

This study descriptively measured the universal accessibility of "accessible" fitness and recreational facilities for Ontarians living with mobility disabilities. The physical and social environments of 44 fitness and recreational facilities that identified as "accessible" were assessed using a modified version of the AIMFREE. None of the 44 facilities were completely accessible. Mean accessibility ratings ranged between 31 and 63 out of a possible 100. Overall, recreational facilities had higher accessibility scores than fitness centers, with significant differences found on professional support and training, entrance areas, and parking lot. A modest correlation was found between the availability of fitness programming and the overall accessibility of fitness-center specific facility areas. Overall, the physical and social environments of the 44 fitness and recreational facilities assessed were limited in their accessibility for persons with mobility disabilities. Future efforts should be directed at establishing and meeting universal accessibility guidelines for Canadian physical activity facilities.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score0.366

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.050
GPT teacher head0.294
Teacher spread0.244 · 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 designObservational
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

Citations75
Published2011
Admission routes2
Has abstractyes

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