A Quarter Century of NBC's Prime-Time Summer Olympics: A Sex-Based Analysis of the Network's Coverage
Bibliographic record
Abstract
Abstract: The Olympics offer female athletes the opportunity to shine on the biggest stage, and media tend to cover women's sports more and better during those events. This report is a sex-based quantitative content analysis of NBC's U.S. prime-time broadcast coverage of the 1996, 2000, 2004, 2008, 2012, 2016, and 2020 Summer Olympic Games. It focuses on two main aspects: (1) coverage of men's and women's events and (2) the sex of sources and speakers featured. Results indicate that while NBC's coverage prominently features female athletes, men's sports were still overrepresented during the Tokyo 2020 coverage compared to American men's success in the competition, and the coverage of both the latest Summer Games in Japan and the previous six editions include hegemonic masculinity cues. Primarily, women's coverage became increasingly less diverse over time, focusing mostly on a few major sports, all deemed "socially acceptable" per stereotypical gender norms (gymnastics, track and field, beach volleyball, and swimming and diving). Meanwhile, women involved in physical-power or hard body-contact sports are almost never featured in prime time, despite their successes in competition. Regarding sources and speakers, men have almost always been seen and heard (either working for NBC or being interviewed) more often than women.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".