Sports Media: Transformation, Integration, Consumption
Bibliographic record
Abstract
Chapter 1: Keeping Score: Reflections and Suggestions for Scholarship on Sports and Media Walter Gantz, Indiana University, USA Chapter 2: Theorizing the Sports-Television Dream Marriage: Why Sports Fit Television So Well Michael Real, Royal Roads University, Canada Chapter 3: The Power of a Fragmented Collective: Radical Pluralist Feminism and Technologies of the Self in the Sports Blogosphere Marie Hardin, Pennsylvania State University, USA Chapter 4: Mocking the Fan for Fun and Profit: Sports Dirt, Fanship Identity, and Commercial Narratives Lawrence A. Wenner, Loyola Marymount University, USA Chapter 5: Fair Ball: Exploring the Relationship between Media Sports and Viewer Morality Arthur A. Raney, Florida State University, USA Chapter 6: Sports Media: Beyond Broadcasting, Beyond Sports, Beyond Societies? David Rowe, University of Western Sydney, Australia Chapter 7: Tweets and Blogs: Transformative, Adversarial, and Integrative Developments in Sports Media Jimmy Sanderson, Arizona State University, USA and Jeffrey W. Kassing, Arizona State University, USA Chapter 8: Instant Replay: From Analysis to Aggression. The Nature of Fan Emotion, Cognition, and Behavior in Internet Sports Communities Lance Porter, Louisiana State University, USA Chris Wood, JWA Communications, USA, and Vince Benigni, College of Charleston, USA Chapter 9: The Less You Say: An Initial Study of Gender Coverage in Sports on Twitter Lauren Reichart Smith, Auburn University, USA Chapter 10: Sport, Identities, and Consumption: The Construction of Sport at ESPN.com Lindsey J. Mean, Arizona State University, USA Chapter 11: Reaction Time: Assessing the Record and Advancing a Future of Sports Media Scholarship Andrew C. Billings, Clemson University, USA Appendix: Contributions to Sports Media Scholarship: A Comprehensive Reference List
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 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".