Vem är det ideala mordoffret? - En kvantitativ jämförande analys av hur kvinnliga mordoffer gestaltas och prioriteras i kvällspress
Bibliographic record
Abstract
Aim of thesis:\nThis study analyzes the difference in news framing and news selection of eight different cases of murdered women during the last ten years. Primarily we wanted to try to find a pattern between the women's personal aspects of age, ethnicity, and relationship to their murderer. The content we analyzed came from the two largest Swedish tabloid newspapers, Aftonbladet and Expressen (which included Kvällsposten and GT). The time span that we chose was three and a half months from the date the women were confirmed dead and their names was made public.\nTheoretical framework:\nThe framing of these were analyzed based on two different types of previous research. The Ideal Victim by Nils Christie (1986, 2001) and Det individuella brottet by Marie Demker and Göran Duus-Otterström (2011), who studied the theory of including framing.\nMethods(s):\nWe chose to use a quantitative analysis to make this study applicable to a larger amount of articles. We continue by breaking down our previously mentioned theories to be able to create an index of the articles and thereby try to distinguish differences between the cases.\nResults:\nThe results we found was that all these cases differentiate in both framing and news selection. Women of Swedish ethnicity got more attention than those of other ethnicity but were not presented with the same victim status or by an individually type of news framing.\nWomen who previously had a relationship with their murderer did not get as much coverage as those whose murderers were unknown to them, nor did they get the same type of victim status or including victim framing.\nThere were also patterns between the victims age and news selection. Younger women received more individual framing due to their relatives and/or friends being heard more than the older women, and they also appeared in more pictures in the articles.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".