‘Taking charge of your health’: discourses of responsibility in English‐Canadian women's magazines
Bibliographic record
Abstract
This article presents an examination of the ways in which responsibility for health is constructed in popular English-Canadian women's magazines. Women's magazines are a unique media form, acting as guidebooks for women on matters relating to feminine gender roles and are important to examine as part of the corpus of societal discourses which frame our understandings of what it means to be healthy and how good health is achieved. Using discourse analysis several techniques were found which reinforce women's individual responsibility to create and maintain good health for themselves and their families. The magazines instruct women/readers directly about their health-related responsibilities and outline the negative consequences of inaction or incorrect action. The magazines also use the traditional discursive technique of women's personal accounts as both cautionary tales and inspirational stories to encourage readers to actively pursue healthy behaviours. Reflecting and reinforcing the discourse of healthism, women's magazines consistently present health as an important individual responsibility and a moral imperative which creates an entrepreneurial subject position for women. The article concludes by discussing the implications for women's magazine audiences within the ongoing feminist debate about this cultural industry.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.039 | 0.041 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| 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".