Boosters or Watchdogs? American Sports Journalists’ Perception of their Professional Roles
Bibliographic record
Abstract
In the mid-nineteenth century, media generated sales based on their sports coverage, and sport grew in popularity, due to the media attention it received. This historically symbiotic relationship distinguishes sports journalism routines and practices from its news count erpart. Though David Weaver and his colleagues have conducted a national study of journalists’ perceptions of their roles and responsibilities since the 1980s, these studies did not isolate sports journalists. It is not clear how sports journalists perceive their roles, let alone if they align differently in Weaver and his colleagues’ measures of journalist role perception. The following study addresses this gap by using Weaver, Beam, Brownlee, Voakes, and Wilhoit’s 2007 measure of journalists’ role perception to survey 116 American sports journalists working for daily, weekly, and biweekly newspapers throughout the United States and to determine how their perception of their journalism roles differs from their “news” colleagues. This study also examines the relationship between newspaper circulation size and perceived journalism roles, as well as determines if characteristics, such as sex, race, circulation size, and years at current news organization, can predict sports journalists’ perception of their professional roles.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".