“Sverige ska bli bra igen” : en analys av högerpopulistiskt uppträdande i svensk kvällspress
Bibliographic record
Abstract
During the 21st century, right wing populist parties (RPP:s) all over Europe have started entering the political parliaments. The Sweden Democrats have, like few others, had a fast growing political success in Sweden, growing from about 7% in the 2010 election to about 20% in the 2022 election. With their success, it is inevitable that the sociocultural and sociopolitical discourse has changed. This means that, according to media logic, the traditional mass media has had to adjust. The relationship between RPP:s and mass media have a history of being antagonistic, in regards to ideals and policies. How does the success of the Sweden Democrats affect the news reporting made by Swedish media? In this study, we examine the differences between the news reporting made by Aftonbladet in the month leading up to the 2010 election and the 2022 election in Sweden. The study is made up of both a quantitative and qualitative part, both complementing each other, and is theoretically based on previous research on the right wing populist performance, radical rhetorics and traditional media. The results indicate that the Sweden Democrats have gained political legitimacy through the traditional media over the past 12 years, partly by exploiting certain political topics and using sensationalist and populist rhetoric. But also by affecting socio-political discourse and therefore becoming central in mass media's report on political events and/or subjects
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".