Dramatikk i Arktis – eller? En komparativ analyse av fremstillingen av Børge Ousland og Mike Horns polekspedisjon i nyhetsmediene.
Bibliographic record
Abstract
In the autumn of 2019, the polar explorers Børge Ousland and Mike Horn set out on an expedition that would take them from Hope in Canada to the North Pole, and further across the ice to the ice edge before Svalbard. Towards the end of the expedition, the news media more or less joined them, when it became clear that there were serious and possibly life-threatening challenges for the two polar explorers. In a short period from mid-November to new Year, the case received a lot of attention in the news media. This master's thesis aims to explore and shed light on the media coverage of this expedition in the Norwegian press, which has been the subject of several discussions. To investigate the topic, I answer the question:\nHow do the editors and interviewees involved assess the press coverage in Norwegian printed newspapers and online newspapers of Børge Ousland and Mike Horn's expedition to Antarctica?\nThrough the research design, I want to gain insight into what assessments are made in newsrooms when a case is under a dramatic development and is ongoing over a longer period of time¬¬. Several debates also arise in the wake of the coverage of the expedition, where both misinformation, over-coverage and overdramatization are highlighted. The thesis also looks at what makes an event like this interesting, how it becomes news, and how previous expeditions are covered through the news media. I do a thorough quantitative study of 611 articles about the expedition in the Norwegian media in the current period. This is used as a background for qualitative interviews with participants in the expedition, and with journalists and editors who wrote about the expedition. I use the findings from both surveys in a discussion relating to current theories, including both pseudo-events, agenda setting and framing. The findings of the study shed light into both the use of dramatic titles and introductions to the newspaper articles, how the choice of framework affects the perception of events, and how the editors themselves assess their own news coverage of this case set up against the expedition's experiences. My findings show that the concept of news is diverse, but what happens to journalism when there are more aspects than just the news criteria that decides what is prioritized in the newsrooms? I will discuss this towards the end of the study, and importantly, whether we can learn something from the coverage of this expedition to other comparable situations.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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".