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Record W4415983933 · doi:10.1079/9781800621923.0004

Navigating Discourses of Racialized Bodies in Outdoor Leisure

2025· book-chapter· en· W4415983933 on OpenAlexaff
Mandi Baker, Alayna Schmidt

Bibliographic record

VenueCABI eBooks · 2025
Typebook-chapter
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsRace (biology)White (mutation)HegemonyPower (physics)NarrativeRepresentation (politics)Lived experienceMythology

Abstract

fetched live from OpenAlex

This chapter responds to Arai and Kivel’s (2009) call for a fourth wave of race research in leisure studies, emphasizing the need for critical reflection on how race and racialized bodies are shaped by white hegemony in outdoor leisure activities. The authors explore the entanglements of race, bodies, the outdoors and power dynamics through personal narratives from People of Colour, highlighting systemic barriers and lived experiences of exclusion. Drawing from leisure studies, Black geographies and critical race theory, this chapter critiques oppressive structures and calls for disassembling these and mobilizing social justice in outdoor leisure spaces. Personal accounts, such as those of Black, Iranian, Latina and Malaysian individuals, reveal the complexities of navigating predominantly white spaces, showcasing both challenges and potential for creating inclusive environments. The discussion extends to debunking myths surrounding race in leisure settings, equipping emerging professionals with strategies to address racial inequalities. Ultimately, the chapter aims to propel outdoor leisure practitioners towards radical change, encouraging justice, representation and equitable access in leisure spaces.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.903
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.348
Teacher spread0.320 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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