Direct to consumer advertising is medicalising normal human experienceFor
Bibliographic record
Abstract
# Direct to consumer advertising is medicalising normal human experience {#article-title-2} In direct to consumer advertising, drug companies target advertisements for prescription drugs directly at the public. Barbara Mintzes argues that this type of advertising risks medicalising normal human conditions, with the drug companies raking in increasingly healthy profits. Silvia N Bonaccorso and Jeffrey L Sturchio argue that, through advertising, drug companies can enable patients to make better informed choices about their health and treatment # For {#article-title-3} In October 2001, GlaxoSmithKline ran an advertisement in the New York Times Magazine for paroxetine (known as Paxil in the United States). A woman is walking on a crowded street, her face strained, in a crowd otherwise blurred. The headline reads, “Millions suffer from chronic anxiety. Millions could be helped by Paxil.” No doubt many New Yorkers felt anxious in the aftermath of the attack on the World Trade Center, experiencing symptoms highlighted in the advertisement, such as worry, anxiety, or irritability. At what point does an understandable response to distressing life events become an indication for drug treatment—and a market opportunity? Kawachi and Conrad describe medicalisation as a “process by which non-medical problems become defined and treated as medical problems, usually in terms of illnesses and disorders,” decontextualizing human problems and turning attention from the social environment to the individual.1 They point out the negative consequences, chiefly the extension of the sick role and diversion from other solutions. Does direct to consumer advertising of prescription …
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How this classification was reachedexpand
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 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; both teacher heads agree on what is shown here.
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".