Sex, drugs, and rhetoric: The case of flibanserin for ‘female sexual dysfunction’
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In August, 2015, the US Food and Drug Administration approved Addyi (flibanserin) for the treatment of Hypoactive Sexual Desire Disorder in premenopausal women. Ten months before that, the FDA had held a Patient-Focused Drug Development Public Meeting to address the 'unmet need' for a pharmaceutical to treat that condition. I attended that meeting as a rhetorical observer. This essay is an account of persuasive strategies used on, and then by, the FDA, as it considered approving a drug that was not convincingly either safe or effective. The essay turns on three texts: the 'Even the Score' pro-drug campaign that informed the patient-focused meeting, the text of the meeting itself, and the FDA's own published report of the event. I describe how a pharmaceutical company (Sprout, then owners of flibanserin) recruited, and then ventriloquized, both health professionals and members of the public to pressure the FDA to approve a sex drug for women - claiming that not to do so was evidence of sexism. I argue, with rhetorical evidence, that the case for approving flibanserin had already been won before Sprout submitted its application.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Science and technology studies Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| gpt | Science and technology studies Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.011 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it