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Record W6902935166 · doi:10.7939/r3-vcs4-a174

Skiing Racialized Geographies

2022· dissertation· en· W6902935166 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2022
Typedissertation
Languageen
FieldPsychology
TopicAdventure Sports and Sensation Seeking
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousDiversity (politics)RecreationLegislationEthnic groupRacismColonialismRace (biology)

Abstract

fetched live from OpenAlex

“Skiing Racialized Geographies” examines how Black and Indigenous peoples are excluded in snow sports and how this lack of diversity can be addressed. Snow sports is a CAD $56.4 billion dollar industry, and the snow sports industry acknowledges that the lack of diversity contributes to industry stagnation. This is in spite of decades long efforts from both Black and Indigenous organizations working to foster participation. The snow sports industry has subsequently employed both the leisure theory marginality and ethnicity theses to explain the lack of racialized participation. The marginality thesis argues that racialized participation in leisure activities is statistically lower because of the inaccessible cost of participation and the unavailability of suitable facilities. The ethnicity thesis argues that racialized peoples have fundamentally different interests in terms of sport, leisure, and tourism, to explain lack of diversified participation in specific activities. Guided by Critical Race Theory (CRT) and Critical Indigenous Theory (CIT), this thesis first explores how colour-evasive and power-evasive logics, which ignore the underlying history and social construction of space, result in the lack of diversity in snow sports. This thesis explores the initial construction of outdoor recreational spaces, where snow sports take place, as spaces reserved for whiteness by starting with the history of the preservationist movement prior to 1930 and legislation enacted to create the first North American national parks. I then interrogate the history and social construction of outdoor recreational spaces through the lens of CIT to examine how the power-evasive colonial logics maintain imbalanced societal power relationships to justify settler occupation of space. Finally, I employ CRT to expose the colour-evasive neutral standard of whiteness and ontological individualism that falsely asserts that outdoor space is available to everyone equally while absolving dominant society of the responsibility of racialized inequity. Second, guided by the ethic of Indigenous storywork, this thesis examines how outdoor recreational spaces might be reconstructed in ways meaningful to racialized individuals to precipitate their participation in snow sports. This examination was undertaken as a qualitative research creation project using an original podcast to gather and share insights from 12 experts in the snow sports community, racialized as non-white, from Canada and the US. I analyzed the podcast transcripts using a thematic analysis which revealed six emergent themes: community engagement, education, leadership, and secret handshakes, barrier reductions, representation, Indigenous relationship with land, and common grounds. My findings show that the marginality and ethnicity theses insufficiently explain the lack of diversity in snow sports. Instead, the podcast data indicates that the exclusionary culture of the snow sports industry is responsible for the lack of diversity in participation. My research can be used by communities and industry because it points to appropriate solutions to consider when working to increase participation in snow sports in racialized communities. Finally, this study contributes to scholarly debates on resisting damage-centred research, critical geography, meaningful community engagement and representation, and research creation and podcasting as methodology.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.654
Threshold uncertainty score0.903

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)0.0980.000

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 head0.008
GPT teacher head0.235
Teacher spread0.226 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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