Ethical Issues in Dialysis Aaron SpitalSeries Editor: Soliciting Kidneys on Web Sites: Is it Fair?
Bibliographic record
Abstract
The Internet serves as a meeting place where people in need of kidney transplants can find strangers willing to donate. While Good Samaritan donors located via the Internet increase the number of kidneys available for transplantation, they also raise ethical issues. This practice alters the pattern for distributing kidneys from unrelated living donors and raises questions of justice in the allocation of organs. It is unclear if commercial forces are at play in the arrangements made between potential donors and recipients via the Internet. While it is unfair that some recipients do not have suitable willing living donors, Web sites help to balance the inequity by increasing the opportunity to find a living donor; they also benefit other potential recipients by reducing the waiting list. However, although these Web sites are probably here to stay, Internet donor-recipient matches can have negative consequences that we need to minimize. Suggested strategies include regulated, monitored Web sites and the development of more anonymous organ donor programs.
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How this classification was reachedexpand
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".