Reporting Germany's 2005 Bundestag Election Campaign: Was Gender an Issue?
Bibliographic record
Abstract
Research conducted in the United States and Canada shows that female candidates for political office are covered differently in the news than their male counterparts: Female candidates receive less coverage, their electoral prospects are more negatively assessed, and the focus of reporting is often on “soft” issues compared with coverage of male candidates. We examine reporting during the 2005 Bundestag election campaign to assess the degree to which findings can be extended from North American and European contexts. Germany's first female chancellor candidate, Angela Merkel, and her male opponent, incumbent Chancellor Gerhard Schröder, were the main focus of campaign news. Drawing on an analysis of the four main evening national television newscasts and the most widely read newspaper in the six weeks prior to Election Day, we show that while the two candidates were rather equal in terms of visibility in the news, and did not differ substantially in terms of the issues on which they were reported, gender did play a considerable role in framing certain stories.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".