Working Paper Series Talking Tough: Gender and Reported Speech in Campaign News Coverage
Bibliographic record
Abstract
Reported speech represents an important means of analyzing how party leaders ’ messages are mediated by the masculine norms of political reporting. Building on the notion of “gendered mediation”, we argue that conventional news frames construct politics in stereotypically masculine terms and we examine the implications of these news frames for the coverage of female leaders. Content analysis of reported speech in television news coverage of the 1993 Canadian election, combined with the results of an experiment, reveals that the speech of the two women leaders was subject to more interpretation by the media and was reported in more negative and aggressive language. The study concludes that gendered mediation serves to hinder women’s chances of electoral success. 1 “X makes statements and I make outbursts” (female British MP quoted in Sreberny-Mohammadi and Ross 1996) Female politicians world wide have criticized the media for coverage which is more negative than their male colleagues’, which focuses more on appearances than on issues and which reinforces masculine and feminine stereotypes (Kahn 1996; Herzog 1998; Robinson and
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".