Media Coverage of the Paralympics: Recommendations for Sport Journalism Practice and Education
Bibliographic record
Abstract
Researchers have extensively documented the issues in quantity and quality of media coverage of the Paralympic Games. The lack of coverage and stereotypical representations can be attributed to a variety of structural and cultural factors, notably including journalistic norms and values. This scholarly commentary proposes a reconsideration of journalistic values in order to argue that sports journalists have a professional responsibility to cover the Paralympics and issues of disability for at least three reasons: (a) The Paralympics are an elite-level, international sporting event and thus merit sport-focused coverage, (b) sport journalists have an ethical obligation to include diverse perspectives in reporting and to challenge stereotypes, and (c) sport is intertwined with social issues and requires contextualized reporting. The commentary concludes with recommendations for sport communication and journalism education.
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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 | 0.097 | 0.250 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.011 | 0.013 |
| Scholarly communication | 0.027 | 0.024 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.028 | 0.018 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".