A Summer Country’s Coverage of a Winter Event: Australian Nationalistic Broadcast Focus of the 2018 Winter Olympic Games
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Broadcast commentary of sport programs often is seen as biased for the “home team.” This study sought to determine differences between how the media framed narratives of Australian and non-Australian Olympians by analyzing prime-time coverage of the 2018 PyeongChang Winter Olympic Games across all of Australia’s Seven Network channels. Because Australia is not a traditional powerhouse at the Winter Games, how the media portrays home team and foreign athletes is of interest in this summer sport country. Results revealed that overall, non-Australian athletes were covered and mentioned more frequently than Australian athletes. However, results found taxonomical differences in Seven Network’s depiction of Australian and non-Australian athletes’ successes—Australian success was attributed to athletic ability and courage, whereas non-Australians’ success was more frequently linked to intelligence, experience, and consonance. Differences in the attribution of failure by nationality were also found, with Australian’s failures more likely to be characterized by a lack of commitment and luck compared to their non-Australian counterparts. Athletes’ personalities also were described differently, with Australians receiving comments regarding their emotions, while non-Australians received either more neutral comments or had their appearance and body parts described more often. Theoretical and practical implications of this study are provided.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it