Positioning Pharmaceuticals: The Emergence of Prescription Drug Advertising in Canada, 1987-2005
Bibliographic record
Abstract
This dissertation examines how the pharmaceutical industry in Canada used advertising to encourage Canadians to reimagine their relationship to prescription drugs between 1987 and 2005. During this period, drug companies stopped promoting products exclusively to physicians and began advertising directly to consumers. Using a strategy I call “pharmaceutical positioning,” the industry leveraged the communicative affordances of advertising to construct a new subjectivity— the “somatic consumer”—which is centred on the use of pharmaceuticals as technologies for self-actualization. Pharmaceutical positioning has five key aspects, each of which is explained in the dissertation. These include: the creation of a transformational consumer subject position (the somatic consumer); provision of authoritative health information in an otherwise information-scarce environment; access to non-traditional lifestyle expertise; the promise of biological indeterminacy; and an ethical orientation to body-centred consumption. This study analyzes representative pharmaceutical advertisements collected from three Canadian magazines: Chatelaine, Maclean’s, and Reader’s Digest. Using multimodal critical discourse analysis, I show how drug companies used advertisements as part of an effort to recontextualize access to prescription medicines as a consumer practice. The resulting analysis illustrates a convergence of pharmaceutical business interests with rising health consumerism and the “responsibilization” of health (Osborne, 1997, p. 185). By situating Canadian pharmaceutical advertising within communication studies, this dissertation expands the scope of existing analysis of the topic. It brings the object of analysis beyond the public health policy field, where it has received the lion’s share of attention. It argues the industry used advertising as a key mechanism to establish a direct relationship with consumers, thereby reshaping the way Canadians think about pharmaceuticals. The legacy of these efforts lives on today in the way we conceptualize about and relate to prescription drugs in this country.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.017 |
| Science and technology studies | 0.020 | 0.009 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".