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Record W2108107251 · doi:10.5539/jms.v3n2p145

Beyond Management and Sustainability: Visitor Experiences of Physical Accessibility in the Great Smoky Mountains National Park, USA

2013· article· en· W2108107251 on OpenAlexvenueno aff
Rachel J. C. Chen

Bibliographic record

VenueJournal of Management and Sustainability · 2013
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsnot available
Fundersnot available
KeywordsNational parkVisitor patternGeographySignageSustainabilityPerceptionEnvironmental resource managementPsychologyEnvironmental planningBusinessAdvertising

Abstract

fetched live from OpenAlex

The National Center on Accessibility sponsored this study to identify the perceptions and attitudes of people with physical disabilities toward their experiences related to physical accessibility in the Great Smoky Mountains National Park. A total of 300 questionnaires were distributed to individuals with disabilities onsite. Of these questionnaires, 122 completed and usable questionnaires were collected. The physical accessibility problems in the park identified by visitors with physical disabilities were lack of the width of doorways in restrooms, followed by lack of accessible trails, lack of grab bars in restrooms, and lack of curb cuts. The uniqueness of this project is that it represents the first time focusing on the perceptions and expectations of visitors with physical disabilities regarding the accessibility in an individual national park. In order to further understand accessibility in the US National Park Service, future research may consider collecting these patterns and attitudes from people with and without different disabilities (such as physical disabilities, hearing impairment, visual impairment) at various national park units (national parks, national historical sites, national parkways, and national monuments) at the state, regional, and national levels.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.157
Threshold uncertainty score0.890

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.322
Teacher spread0.308 · 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 teacher head, 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

Citations6
Published2013
Admission routes1
Has abstractyes

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