Bibliographic record
Abstract
In the summer of 2021, Cleveland’s Major League Baseball franchise announced the rebranding of the club’s nickname from the decades-long controversial “Indians” to the” Guardians.” The long-standing use of Native American imagery in sport has long been the source of contention, and for this reason, the Cleveland Guardians have continually been in the public eye prior to their rebrand. This article examines both the organization’s rebranding efforts and media coverage surrounding the team’s new identity. Guided by the theory of framing, this study applies themes of sports rebranding to analyze the team’s announcement video and sequentially deploys an inductive approach to identify the media frames present following the rebranding. Three sports rebrand frames were identified from the Cleveland Guardians’ announcement: regional pride, nostalgia, and rebirth. The media response looked at 79 articles and found two higher-order frames - broader movements and branding commentary – with six subcategories. In total, these frames indicated that rebranding efforts sought to center the new identity around the city of Cleveland while deemphasizing damages from the use of derogatory racial Native American imagery. The media response also shows that the rebrand is contextualized through broader movements and is politically contentious. Future directions of framing theory in sports rebranding and the discourse around the use and removal of racial imagery in sports is discussed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.002 |
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".