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Record W4405697067 · doi:10.1080/09669582.2024.2442618

Catching feelings in nature: experiential insights about access and inclusion in parks, protected and other conserved areas

2024· article· en· W4405697067 on OpenAlexafffundabout
Mikhaila Carr, Mark Groulx, Nancy Harris, Heather Lamb

Bibliographic record

VenueJournal of Sustainable Tourism · 2024
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsSpinal Cord Injury BCUniversity of Northern British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsFeelingInclusion (mineral)Experiential learningBusinessMarketingEnvironmental resource managementPsychologySocial psychologyEconomicsPedagogy

Abstract

fetched live from OpenAlex

An ongoing lack of universally designed infrastructure and programming across the tourism system excludes persons with a disability and other accessibility seeking travelers. In nature-based tourism contexts, limited studies have documented interactions among the diversity of accessibility seeking travelers and the physical, attitudinal, and informational barriers known to exist in nature spaces. This research draws on the lived experiences of a small and diverse group of people as they navigate their accessibility requirements and rights to parks, protected and other conserved areas in northern British Columbia, Canada. Observations documenting in/accessible experiences in nature spaces are recorded using photovoice and field journals grounded in a collaborative auto-ethnographic approach. A thematic analysis surfaced themes relating to the importance of providing access to distinctive encounters in parks and how these experiences relate to infrastructure and social practices. Analysis also identified the need for cognitive space for tourists to embrace desired embodiments in nature and participate in information systems that connect tourists to diverse knowledge systems and sustainability thinking. Findings from this work offer important insights into the value of lived experience as a management input as well as options for engaging diverse communities in a conversation about park accessibility.

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)0.001
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 score0.290
Threshold uncertainty score0.655

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.010
GPT teacher head0.314
Teacher spread0.304 · 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

Citations2
Published2024
Admission routes3
Has abstractyes

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