Bibliographic record
Abstract
Abstract Consensus is lacking among research ethicists on the question of how broadly to understand the requirements of non‐exploitation in international clinical research. Two types of principles have been proposed, minimalist and non‐minimalist, grounded in two opposing conceptions of exploitation, transactional and systemic. Transactionalists have offered principles, which, it has been argued, are satisfied by minimal gains to vulnerable subjects measured against an unjust status quo. Systemicists have advanced principles with decidedly non‐minimal mandates but only by conflating the obligations of clinical research with those of First World citizenship. My aim here is to break this deadlock by offering grounds for a non‐minimal requirement of international research ethics grounded in a transactional conception of exploitation. I do this by arguing that a subject's gains must be measured not only within the transaction, relative to her own starting point and to the share of gains enjoyed by her co‐transactor, but also across transactions, so as to ensure parity of benefit to trial participants whenever, and wherever, parity of burden is assumed.
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 | 0.154 | 0.171 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.083 |
| Scholarly communication | 0.015 | 0.017 |
| Open science | 0.003 | 0.025 |
| Research integrity | 0.006 | 0.009 |
| 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".