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Adventure and the Gender Gap: Acknowledging Diversity of Experience

2005· article· en· W2009518405 on OpenAlexvenueno aff
Donna E. Little, Erica Wilson

Bibliographic record

VenueLoisir et Société / Society and Leisure · 2005
Typearticle
Languageen
FieldPsychology
TopicAdventure Sports and Sensation Seeking
Canadian institutionsnot available
Fundersnot available
KeywordsAdventureRecreationPremiseDiversity (politics)PsychologyOutdoor educationAdventure educationSociologyPolitical scienceHistoryPedagogyLaw

Abstract

fetched live from OpenAlex

Traditionally, descriptions of adventure recreation have tended to incorporate a limited range of physically isolated and challenging activities (Attarian, 1991; Ewert, 1986). More recently, the concept of adventure has been used quite broadly within the leisure field (e.g. the 'adventure' of visiting nature; tourist promotions of 'adventurous' fun), but popular media portrayals of adventure continue to promote the extreme and remote. While these latter risk-laden portrayals reflect the experiences of a few, it is the premise of the authors that a broader perception and experience of adventure can be found in more everyday events and activities. In support of recent feminist research (Collins, 2000; Humberstone, 2000), this paper describes women's perceptions and experiences of adventure and suggests that adventure recreation has wider parameters than previously acknowledged. Based on results of semi-structured in-depth interviews with eighty two women participants in adventure activities (e.g. solo travel, white water kayaking), the findings show that women struggle to identify with popular media presentations of adventure, but they do experience individual adventure in multiple ways. Through personal challenges and newness, adventure can be experienced without the requisite of extreme physical challenge or exclusive remoteness. Subsequently, we suggest that broader social and professional meanings of adventure need to be acknowledged, allowing people to identify with adventure and the benefits to be gained from adventure recreation.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.569

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.041
GPT teacher head0.333
Teacher spread0.293 · 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 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

Citations29
Published2005
Admission routes1
Has abstractyes

Explore more

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