A critique of the moral economy of pharmaceutical development
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
Drug development is widely recognized as risky, time consuming, and costly for pharmaceutical firms. Less widely appreciated is the fact that nonhuman animals and patients also bear risks and costs for pharmaceutical development. I argue that by participating in studies, nonhuman animals and patients commit some (or for nonhuman animals, all) of their welfare and labor to drive this process forward. I further argue that this commitment of welfare and labor is rendered invisible by discourses that present trial participation to patients as medical opportunity, despite evidence and principled reasons suggesting the contrary. This subsidy of welfare and labor, though nominal to moderate on a per patient basis, is significant when aggregated across patients and clinical trials and considered alongside nonhuman animal use. I close by arguing that this subsidy is grounded on defective consent, and that it generates two strong claims on researchers and states overseeing the research. The first is an obligation to economize on nonhuman animal and patient welfare and labor by conducting research efficiently. The second is an obligation to align drug development and policy with the aspirations that motivate the use of nonhuman animals and the motivations of patients in this endeavor.
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.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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