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Record W4312946464 · doi:10.1123/ssj.2022-0022

Racist State and the State of Race: An Analysis of Instagram Commentary Pertaining to LeBron James

2022· article· en· W4312946464 on OpenAlexaff
Evan Frederick, Nicholas Swim, Ajhanai C.I. Keaton, Ann Pegoraro

Bibliographic record

VenueSociology of Sport Journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCritical Race Theory in Education
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsOutrageRhetoricSkepticismPolice brutalityState (computer science)RacismCritical race theorySociologyRace (biology)Critical theoryCriminologyState of exceptionMedia studiesGender studiesPolitical scienceLawEpistemologyPhilosophyPoliticsTheology

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the evolution of social media commentary pertaining to LeBron James’ activism efforts during two pivotal moments of state-enacted anti-Blackness violence. Utilizing the lens of critical race theory and critical whiteness studies, we examined user commentary pertaining to James’ two Instagram posts responding to the state-enacted violence against Michael Brown in 2014 and George Floyd in 2020. While responses to LeBron’s activism certainly evolved between 2014 and 2020, it is wise to be skeptical of that newly found support for James’ message and the outrage toward a fundamentally racist society. Superficial rhetoric and virtue signaling are the norm, while progress toward substantive change remains stoic and still, often like the beliefs deeply etched within us.

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)0.006
metaresearch head score (Gemma)0.036
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 score0.016
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0120.007
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.016
GPT teacher head0.369
Teacher spread0.352 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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