THE USAGE OF SPORT NEWS SERVICE OF CZECH NEWS AGENCY FROM THE OLYMPIC GAMES IN VANCOUVER 2010 IN NEWSPAPER SPORT
Bibliographic record
Abstract
The bachelor thesis "The usage of sport news service of Czech News Agency from the Olympic Games in Vancouver 2010 in the newspaper Sport" deals with a media coverage of extraordinary important sport event aiming to find out the extend of today's dependence of print newspapers on the service of the press agency. The research is based on the example of the Olympic Winter Games in Vancouver, one of the most important sport events of 2010, and it surveys the production of sport section of Czech News Agency and the only Czech newspaper focused on sport. The thesis is focused on comparison of the Olympics' news service in the agency and in the newspaper and it covers the period beginning one week before the start of the Olympics and ending one week after the end of the Olympics. It traces the amount of agency's news used by Sport and it finds out whether the newspaper regularly adopted specific kind of news. The thesis also explores whether the journalists in Sport somehow worked more on the agency news or left them in their original form. In the times of on-line media expansion when the on-line news servers use the service from agencies very frequently, the newspaper should not just copy the news from the Czech News Agency. Consequently, the thesis focuses on the approach of the newspaper to agency's...
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".