Clinical Research in Context: Reexamining the Distinction between Research and Practice
Bibliographic record
Abstract
At least since the seminal work of the (US) National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research in the 1970s, a fundamental distinction between research and practice has underwritten both conceptual work in research ethics and regulations governing research involving human subjects. Notwithstanding its undoubted historical importance, I believe the distinction is problematic because it misrepresents clinical inquiry. In this essay, I aim to clarify the character of clinical inquiry by identifying crucial contextual constraints on justification constitutive of clinical science. This analysis shows that, from an epistemological point of view, clinical research and clinical practice are not sharply distinct but intimately intertwined. This result is important in its own right-an enriched understanding of the epistemology of clinical research is valuable in and of itself. But this result is also important because it has profound implications for the ethics of human subjects research.
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 | 0.072 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.013 | 0.154 |
| Scholarly communication | 0.033 | 0.041 |
| Open science | 0.004 | 0.021 |
| Research integrity | 0.015 | 0.025 |
| Insufficient payload (model declined to judge) | 0.002 | 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".