20 Years of Olympic Media Research: Trends and Future Directions
Bibliographic record
Abstract
The Olympic Games is the largest multisport event in the world, regularly drawing global audiences in the billions to watch coverage of athletes from hundreds of nations. It has received a great deal of scholarly attention, especially in terms of media coverage, consumption, and co-creation. As coverage has the ability to impact media consumers' perceptions of nations, cultures, and issues, it is important to develop an understanding of research trends relating to the Olympic Games and media in order to uncover gaps in the literature which may be filled by future scholarly work. Therefore, in order to highlight trends in the established literature and uncover areas for development, a systematic literature review was conducted to examine the state of Olympic media research over a 20-year time period (1999-2018). A total of 221 articles were examined, revealing insights into the types of research being produced from theoretical, methodological, and contextual perspectives. Results revealed a significant proportion of scholarship focused on the Summer Olympic Games, the United States, newspaper accounts of the Games, and utilized media framing and agenda setting frameworks and the content analysis methodology. Just over half of the studies utilized a theoretical or conceptual framework, the prevalence of which increased over time. Core areas for continued development in the Olympic media space include embracing and grounding research in theory, diversification in research context, and expanding upon the definition of the Olympic Games within the greater Olympic Movement.
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 | 0.020 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.017 | 0.029 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.011 | 0.018 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".