Transforming Canadian Women on the Road to Modernity: A Frame Analysis of Feminisms in Chatelaine (1928-2010)
Bibliographic record
Abstract
Chatelaine, Canada’s longest running women’s magazine (1928-present), has seen various changes in relation to women’s presence in society, specifically women’s health and bodies. The purpose of this study is to investigate the framing methods employed in the presentation of health content in relation to the evolution of feminism throughout this publication’s existence. Drawing upon Michel Foucault’s (1979; 1980) investigation of power, the body, and sexuality; Susan Bordo’s (1993b) feminist theorizing on the cultural meanings of the female body; Erving Goffman’s (1974) Frame Analysis; and further theoretical foundations of frame analysis by scholars in media and communication studies, this thesis examines the ways which health knowledge in Chatelaine aids in the empowerment and modernization of women. The research design of this thesis employs a quantitative media content analysis and qualitative semi-structured in-depth interviews to explore the presence and production of health content in this publication between 1928 and 2010. Findings demonstrate Chatelaine’s interaction with the feminist movement in Canada—as feminist initiatives and activism in Canada flourish, Chatelaine covers an increasingly broad and diverse body of health topics. The analyses reveal the sophistication in Chatelaine’s health content, which is evidenced in the employment of various journalistic techniques that aid in the development of an increasingly pervasive media text. In doing so, Chatelaine demonstrates its ability to empower women through current, clear, and concise health knowledge.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.033 | 0.022 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".