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Record W4296208561 · doi:10.1123/ssj.2021-0125

“They Just Dash Us to the Side”: Race, Gender, and Negotiating Access to Basketball Spaces

2022· article· en· W4296208561 on OpenAlexaboutno aff
Rhonda C. George

Bibliographic record

VenueSociology of Sport Journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsnot available
Fundersnot available
KeywordsNegotiationBasketballScholarshipRace (biology)RecreationAthletesGender studiesBlack womenIntersectionalitySociologyPsychologyPolitical scienceSocial psychologyMedicineSocial scienceGeographyPhysical therapy

Abstract

fetched live from OpenAlex

Using Black Feminist Theory and qualitative data gathered from 20 Black Canadian female U.S. athletic scholarship recipients, this article identifies race–gender barriers to accessing informal athletic spaces for athletic training such as recreation centers and public gyms. I argue that these access barriers are rooted in a sexist anti-Blackness, while also examining the resistance and navigational strategies employed by the participants such as playing back and avoidance and considering how those efforts often led to additional financial expense and psychological and navigational labor. In so doing, I elucidate how the race and gender of the participants intersected to create social and athletic experiences and opportunities that are distinct from existing dominant discourses in collegiate athlete research, which tend to center American and Black males, while often neglecting the specific and more granular experiences of Black (Canadian) female athletes.

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)0.005
metaresearch head score (Gemma)0.005
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 score0.536
Threshold uncertainty score0.934

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0250.022
Scholarly communication0.0080.004
Open science0.0020.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.069
GPT teacher head0.355
Teacher spread0.286 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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