Two cross-country skiers in the tabloids : - A study of the tabloids coverage of Charlotte Kalla and Marcus Hellner in the 2010 Olympics and the 2014 Olympics
Bibliographic record
Abstract
The purpose of this paper is to examine how the two Swedish cross-country skiers, Charlotte Kalla and Marcus Hellner are portrayed in the tabloids Aftonbladet and Expressen. The study is based on theories of sports journalism, media- and gender studies. Within these theories there are beliefs that men and women are portrayed differently in sports journalism. Sports journalism is described as a subject where there is a hierarchy in which the man is often framed as dominant in relationship to the woman. This study was made in an attempt to examine whether this was the case in the Swedish tabloid magazines Aftonbladet and Expressens coverage of the winter Olympics. Articles published about Charlotte Kalla and Marcus Hellner in the 2010 Vancouver Olympics, and the Olympic Games in Sochi in 2014 were analyzed by a quantitative content analysis. The two athletes were selected because they during the time of the study were prominent in their sport in which both achieved similar success. The results of the study showed that there were differences in Aftonbladet and Expressen’s media coverage of Charlotte Kalla and Marcus Hellner. Kalla appeared in more numbers of articles than Hellner but she was often described as weak and her physical appearance was often highlighted. Hellner was often described as strong and focused regardless of whether he had failed or was successful.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| 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".