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Record W4392308705 · doi:10.1123/ssj.2023-0073

Anti-Black Racism and Soccer in Canada: Is It Because I’m Black, Ref?

2024· article· en· W4392308705 on OpenAlexaffabout
Paul Nya, Jay Scherer

Bibliographic record

VenueSociology of Sport Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRacismOppressionGender studiesSociologyClubRecreationEthnographyCritical race theoryCritical ethnographyRace (biology)HierarchyPower (physics)Sociology of sportPolitical scienceAnthropologyPoliticsLaw

Abstract

fetched live from OpenAlex

This study critically examines the experiences of members of a sub-Saharan African men’s recreational soccer club with anti-Black racism in a Western Canadian city. Drawing from extensive ethnographic fieldwork, and working at the intersections of Critical Race Theory and Physical Cultural Studies, our analysis focuses on how team members navigate a racial hierarchy that privileges Whiteness and cements their status as outsiders through both overt and subtle forms of racism on the pitch, and the laborious, retraumatizing challenges of “proving” these racist incidents to those in positions of institutional power. We underline the need for anti-racist and anti-oppressive policies and training, and independent judiciaries to monitor and address racist incidents and systemic racism—and its intersections with other forms of oppression—in Canadian sport cultures.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.381

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0640.017
Scholarly communication0.0070.002
Open science0.0020.006
Research integrity0.0020.004
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 head0.040
GPT teacher head0.324
Teacher spread0.284 · 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 designObservational
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

Citations3
Published2024
Admission routes2
Has abstractyes

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