She’s throwing her hat in the ring! Gendered mediation and the newspaper coverage of provincial leadership candidates Christy Clark and Alison Redford.
Bibliographic record
Abstract
In the past few years Canadians have witnessed a significant increase in the number of women holding premierships. One CBC journalist even dubbed 2011 “The Year of the Woman” in provincial politics, noting that four out of the thirteen provinces and territories were led by women: Alison Redford in Alberta, Christy Clark in British Columbia, Eva Aariak in Nunavut and Kathy Dunderdale in Newfoundland and Labrador (MacKinnon, 2011). Further to this, in 2012 Pauline Marois became the premier of Quebec, Kathleen Wynne was elected premier of Ontario in 2013, and Rachel Notley became the premier of Alberta in 2015. In light of this change in the political arena, and recent questions about whether, for example, media coverage of Christy Clark has been sexist (Hyslop, 2013; Orr, 2013) this thesis explores the key following question: How are Canadian female politicians running to become leaders of their provincial parties being represented in the news? Two case studies serve as the main focus of this research: Christy Clark’s leadership campaign in British Columbia in 2010/2011; and Alison Redford’s leadership campaign in Alberta in 2011. Using gendered mediation, representation theories, discussions of the public and private spheres, and with a focus on textual and framing analysis, this thesis looks at how the media focuses on gender differences, which may lead to explicit or implicit forms of sexism.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.008 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".