Medications as Social Phenomena
Bibliographic record
Abstract
This article discusses medications as socially embedded phenomena, using the class of psychoactive medications as a primary example. The analytical perspective is systemic, constructivist, and critical. We suggest that the ‘rational use of drugs’ paradigm fails to appreciate various legitimate rationalities motivating medication usages and is therefore inadequate to understand the place of medications in society. Medications have complex life cycles, with diverse actors, social systems, and institutions determining who uses what medications, how, when and why. Such understanding permits analyzing medications simultaneously as entities and representations. We outline recent changes in usage patterns of psychoactive medications (notably prescriptions to children), in pharmaceutical marketing practices (notably direct-to-consumer advertising), and in the construction of knowledge about drugs (notably the role of the Internet in legitimating consumers’ viewpoints). These changes indicate that medication life cycles evolve and mutate with social and technological change. These life cycles are viewed, then, as systems – part of other social, cultural, and economic systems, themselves in constant change. This perspective provides fertile ground to raise several research questions in order to understand better the nature of medications, their effects, and their place in society.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.035 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".