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Record W2888033653 · doi:10.1177/2167479518793625

An Analysis of Colin Kaepernick, Megan Rapinoe, and the National Anthem Protests

2018· article· en· W2888033653 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.

Bibliographic record

VenueCommunication & Sport · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsLaurentian University
Fundersnot available
KeywordsAnthemNarrativeFraming (construction)AthletesMedia studiesPolitical scienceGender studiesSociologyPsychologyHistoryArtLiteratureArt history

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate the Facebook narrative surrounding Colin Kaepernick and Megan Rapinoe’s activism as crafted through user comments on their respective public Facebook pages following the athletes’ protests during the national anthem. A total of 85,649 users’ comments were collected and analyzed within the context of framing. The themes emerging from the data suggested a strong nationalistic narrative, with some accompanying narratives addressing the issues Kaepernick and Rapinoe desired to highlight through their activism. The nationalistic frames discussed what constituted American values and the consequences for not conforming to those values. The non-nationalistic themes targeted the social issues related to the two athletes. In terms of differences between the two athletes, users attacked Kaepernick’s specific characteristics (i.e., race and sex), while Rapinoe’s data contained discussions surrounding the role of athletes. Implications of these findings will be discussed further.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.686

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 studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.047
GPT teacher head0.392
Teacher spread0.344 · 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