"I saw what I saw": the media creates a miracle cure for anorexia
Bibliographic record
Abstract
This dissertation is a critical case study, which explores the role of the media from 1993 to 1997 in creating Peggy Claude-Pierre as an "angel on earth" and "the last hope" for anorexics. Claude-Pierre founded Montreux Counselling after curing her two daughters of anorexia nervosa. She was featured in a number of magazines, newspaper articles, radio programs, American talk-shows, ABC's 20/20, and NBC's Dateline, as well as programs in Germany, Australia, Canada and the UK. This dissertation further examines the period from 1997 to 2000 in which there was a contest of representations about whether Claude-Pierre was an "angel" or a dangerously charismatic leader of a "cult-like" facility. I approach this study from the perspective that Montreux cannot be understood outside of the common notions of gender, class, and race, nor outside the common understandings of illness, miracles, and science. I propose that the rise of Montreux to prominence within a short period of time is connected to the economic and ideological nature of the media and of professional culture--both maintain a mystique about their ability to "know" and tell the "truth." It is this paradigm of objectivity and progress from whence their knowledge is conveyed to the public. I argue that the media and professionals, in conjunction with discourses of both miracles and empiricism, were all integral to creating Montreux as a world-famous center. The media based their claims about Montreux on testimonials. They ignored their own role in creating Claude-Pierre; therefore, they left the role and responsibility of journalists and talk show hosts as the most powerful storytellers, unchallenged.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.019 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".