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Record W2034726268 · doi:10.1177/1053825913498366

A Socio-environmental Case for Skill in Outdoor Adventure

2013· article· en· W2034726268 on OpenAlexaff
Philip M. Mullins

Bibliographic record

VenueJournal of Experiential Education · 2013
Typearticle
Languageen
FieldPsychology
TopicOutdoor and Experiential Education
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsRecreationOutdoor educationAdventureAdventure educationSustainabilityTourismEnvironmental educationPsychologyQualitative researchSociologyPedagogyPublic relationsPolitical scienceSocial scienceEcology

Abstract

fetched live from OpenAlex

In response to the crisis of sustainability, this paper revisits understandings of human–environment relations established through skill-based outdoor activities that are used commonly among adventure recreation, education, and tourism. Reconsidering a predominant focus on risk and a persistent tension between technical and environmental knowledge, a case is made for skill as an important avenue for research related to participants’ environmental learning and engagement. Diverse qualitative and quantitative research literature concerning outdoor education, recreation specialization, place, and skilled performance are reviewed. The author argues that developing theoretical and practical approaches to outdoor adventure education, recreation, and tourism within a sustainability paradigm will require perspectives that position humanity as belonging within environments, and that skill provides an important avenue for doing so. Ultimately, research and practice will need to account for skill development and performance as shaping—for better or worse—participants’ socioecological engagement.

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)0.002
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 score0.010
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.020
Scholarly communication0.0030.003
Open science0.0010.010
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.339
Teacher spread0.329 · 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

Citations25
Published2013
Admission routes1
Has abstractyes

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