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Record W4394585706 · doi:10.1123/ssj.2023-0088

A Perfect Storm: Black Feminism and Women’s National Basketball Association Black Athlete Activism

2024· article· en· W4394585706 on OpenAlexaff
Letisha Engracia Cardoso Brown, A. Lamont Williams, Amanda N. Schweinbenz, Ann Pegoraro

Bibliographic record

VenueSociology of Sport Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of GuelphLaurentian University
FundersU.S. Bureau of Land Management
KeywordsBasketballFeminismGender studiesStormBlack womenAssociation (psychology)Political scienceSociologyHistoryPsychologyGeographyMeteorologyArchaeology

Abstract

fetched live from OpenAlex

This article pays homage to Black Women’s National Basketball Association (WNBA) players and their activist efforts. Such players are often-overlooked activists who are always “holdin it down” while simultaneously keeping activism at the forefront of their agenda. When the 2020 Women’s National Basketball Association season opened, the athletes in this league took the opportunity to highlight social injustice in the United States; not surprising given the history of Black feminism and athlete activism in this league. Using underwater waves as a metaphor, we examine how the intersectionality of Black feminism and Black athlete activism has largely gone unnoticed. Feminism and women’s rights movements have largely been associated with White women while Black activism has been associated with Black men. This manuscript aims to highlight the efforts of Black women and nonbinary athletes whose work has been instrumental in societal progression.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.011
Scholarly communication0.0040.002
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.026
GPT teacher head0.308
Teacher spread0.282 · 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

Citations14
Published2024
Admission routes1
Has abstractyes

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