Healthy is the New Thin: The Discursive Production of Womenâ s Healthy Living Media
Bibliographic record
Abstract
This dissertation explores how food and fitness discourses are produced in the contemporary healthy-living mediascape for women. This is done through a content and discourse analysis of 640 blog posts from six foundational healthy living blogs and 230 articles from two high-circulation health and fitness magazines. In the first of three papers, I compare how food is framed in the magazines and blogs. I find that healthy-living magazines frame food as pathogenic, disease-promoting and dangerous in relation to body composition. In contrast, healthy living blog posts present food as a relatively “salutogenic” (Antonovsky 1996) force that promotes health and wellness. I argue that healthy living blog prosumers (who both produce and consume social media) are able to broaden the range of public health discourses, albeit without critiquing the moralization of health or thinness as an overarching goal. In the second paper, I use the analytical tool of biopedagogy to understand what bloggers are teaching readers about how to manage their bodies. I argue that, in order to generate the authority to disseminate health information bloggers, laypeople who are not health professionals must produce health media that includes a distinct knowledge base and evidence to support their recommendations. I offer the concept “blogspert” to describe the way in which bloggers’ authority to disseminate biopedagogy is produced through anecdotal evidence of successfully and intentionally cultivating bodily knowledge towards losing or managing weight. In the third paper, I study the construction of authenticity, a highly-valued trait in contemporary culture. I find that an authentic healthy persona is produced on healthy living blogs through “calibration” (Cairns and Johnston 2015) — a gendered self-presentation process whereby women continually work to position themselves away from pathologized extremes of feminine excess (e.g., obsessiveness perfectionism) and apathy (e.g., laziness, insufficient self-monitoring). Overall, in this dissertation I make the following conclusion: while healthy living bloggers remain compelled to navigate a broader context in which they are required to demonstrate self-regulation, they steer clear of restrictive and punitive discourses through presenting alternative logics of healthy living that reflect and reproduce the neoliberal fetishization of the individual and individual experience.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.010 | 0.030 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".