Dangerous bedfellows, industry and medicine : life savers or disease makers
Bibliographic record
Abstract
Advertising of products and services has become an accepted and integral part of everyday life, and advancements in mass media technology have made it easy to convey information to a large proportion of the population. However, when addressing health related services and products, the messages contained in today's advertisements have taken on a new purpose and tone. The healthcare industry in North America, especially pharmaceutical companies, and to a lesser extent the diagnostic imaging and the medical device industry, use direct-to-consumer (DTC) advertising to convey a message to a target population. On its face, the promotion of health awareness is an acceptable and worthy practice, but ethical concerns are raised when the health industry plays an instrumental role in creating "illnesses" or "conditions" for which they are providing treatments. At one time, to protect health consumers, legislation and regulations prohibited directly advertising of prescription healthcare products and services to consumers, since it was thought that physicians were the ones best equipped to deal with this information. However, times have changed, and DTC advertising now is openly allowed in some countries, and in others in some narrowly specific situations. This thesis examines the ethical and practical issues raised by this development, arguing that the negative consequences of permitting Direct-to-Consumer advertising far exceeds any positive benefits. If governments do not take an active role in preventing the further commercialization of medicine, Canada (and other countries as well) may be destined to become a nation of worried well.
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.
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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.034 |
| Scholarly communication | 0.019 | 0.019 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.011 | 0.015 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".