Press Reports about Causes of Juvenile Crime and Associated Claims in the German Press
Bibliographic record
Abstract
This article examines the kinds of criminological knowledge and information that were considered in the press during the Hesse election campaign in 2007/2008, in which youth crime played a major role. The present study investigates the integration of information about the possible causes of youth crime into press articles, and examines to which extent information about these causes and motives for engaging in youth crime were considered by the press to be significant in the explanation of youth crime. The other aim of this study is to uncover which types of criminal policy and pedagogy had been reported about, and which of those measures had been regarded as meaningful. To this end, results of a content analysis of articles from two German daily newspapers—the Bild and the Süddeutsche Zeitung—are presented and compared. The differences between the two newspapers and their method of news construction are highlighted. The paper clarifies central concepts and discusses previous research in media crime and youth crime, as well as making methodological remarks. The results of the study indicate that only rarely was knowledge about the causes of juvenile crime published in the press; information about the individual itself was found to an even lesser extent. This was particularly true about the Bild. Claims for tougher methods of punishment dominated, whereas measures that aimed at crime prevention were seldom considered reasonable, and if so, were mainly included in the Süddeutsche Zeitung. These results in part reflect the importance of several news factors—notably consonance, personification, risk, and negativism—but also to a large extent reflect the political accentuation of the respective newspapers and their specific views of juvenile offenders.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.018 | 0.016 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".