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Record W4412819156 · doi:10.29173/spectrum295

Autoethnography of a Queer Racialized Athlete

2025· article· en· W4412819156 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSpectrum · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAutoethnographyQueerSociologyRacializationGender studiesRace (biology)

Abstract

fetched live from OpenAlex

Over four decades of research has suggested that there is a high prevalence of homophobia and transphobic attitudes, behaviors, policies, and practices within sport and physical activity. These realities serve as barriers or deterrents to participation for many 2SLGBTQIA+ people and groups and can also make sport and physical activity unwelcoming and even unsafe for those who choose to participate. In this important body of work, there remains a glaring absence of racialized 2SLGBTQIA+ athletes’ experiences. To help to address this gap, the primary purpose of my research was to explore how marginalized communities experience overlapping forms of discrimination in sport. Adopting an autoethnographic methodological approach, I wrote a series of vignettes about my own experiences as a queer racialized athlete in Western Canada. While writing the vignettes was a reflective process in and of itself, I also followed the tenets of critical discourse analysis to think about my experiences in relation to the broader cultural context. This resulted in the creation of three themes: intersectionality, microaggressions, and homophobia. Each worked independently and together to create an unsafe space for me, impacting my athletic experiences and life more broadly in negative ways. Reflecting on my experiences critically, however, also allowed me to think about resistance and resiliency. My hope is that my work contributes to existing literature and provide insight for other queer racialized athletes who may have had similar experiences in sport.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.785
Threshold uncertainty score0.612

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.020
GPT teacher head0.317
Teacher spread0.297 · 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