Just the Facts? Media Coverage of Female and Male High Court Appointees in Five Democracies
Bibliographic record
Abstract
In this article, we examine gender differences in news media portrayals of nominees to high courts and whether those differences vary across country and time. Although past research has examined gender differences in news media coverage of candidates for elective office, few studies have looked at media coverage of high court nominees. As women are increasingly nominated to courts around the world, it is important to examine how nominations are covered by the news media and whether there is significant variation in coverage based on gender. We analyze media coverage of high court justices in five democracies: Argentina, Australia, Canada, South Africa, and the United States. We compare coverage of women appointed to the highest court with coverage of the most temporally proximate male nominees. We also compare coverage over time within each country as well as between countries that nominated women early with those that did so more recently. We find some evidence of gendered coverage, especially with regard to the attention paid to the gender of the women appointees.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".