Bibliographic record
Abstract
By “taking a knee” during the performance of the U.S. national anthem, National Football League (NFL) players have been protesting “the oppression of people of colour and ongoing issues with police brutality” in America (Colin Kaepernick, the movement’s founder, quoted in Coombs et. al., 2017). Despite this clarity of intention, the meaning of these protests (whether they are necessary and patriotic or counterproductive and ‘un-American’, for example) has been hotly contested in the public sphere, indicating the presence of a deeply seated counter-hegemonic struggle that is both expressed and contributed to by the anthem protest discourse. This project explores this struggle through the lens of narrative assembly, or the individual and intertextual construction of meaning through the selection and arrangement of narrative objects. Special attention is paid to the treatment of social, symbolic, and normative boundaries by storytellers responding to the anthem protest and by the anthem protesters themselves, especially those related to political expression in professional sports, American national and racial identity, and racial exclusion and marginalization. The project utilizes a structural approach to narrative analysis called the Qualitative Narrative Policy Framework (QNPF) supplemented by insights from Arthur Frank’s (2010) method of Dialogical Narrative Analysis (DNA). These methods are applied in a sociological study of a segment of the NFL anthem protest discourse published in newspaper articles during the first 16 months following the start of the controversy. This sample captures narrative responses to three significant moments—Kaepernick’s initiation of the protest, U.S. president Donald Trump’s verbal attack on protesting players in speeches and over social media (which also resulted in mass-displays of unified resistance from NFL players), and Kaepernick’s failure to obtain an NFL contract the year following his protest. Findings indicate that by transgressing several normative boundaries related to work, sports, protest, and signalling patriotism, NFL anthem protest subverts a hegemonic tale of national unity and exposes the systemic discrimination and symbolic/social exclusion that continue to produce experiences of oppression for people of colour and others in the United States. By attending to their assembly of settings, characters, plotlines, memories, solutions, and moral lessons, authors that support the protests are shown forming an intertextual or collective narrative around a central demand for justice that challenges the American status quo and projects a preferred future of enhanced racial equality yet to be achieved by the nation. Alternately, authors who oppose the protests are observed assembling a collective narrative around a demand for respect that defends boundaries essential to the maintenance of the status quo and expresses a desire to return to a past America of uninterrupted white dominance. In addition to providing a detailed case study that focuses on processes of narrative assembly in relation to counter-hegemony and social, symbolic, and normative boundaries, the project serves as an example of how the emergent methodology of the QNPF can be applied to the study of dynamic instances of everyday cultural-political struggle that may fall outside the sphere of policy research in which it has typically been employed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.027 | 0.029 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".