Living and Deceased Organ Donation Should Be Financially Neutral Acts
Bibliographic record
Abstract
The supply of organs—particularly kidneys—donated by living and deceased donors falls short of the number of patients added annually to transplant waiting lists in the United States. To remedy this problem, a number of prominent physicians, ethicists, economists and others have mounted a campaign to suspend the prohibitions in the National Organ Transplant Act of 1984 (NOTA) on the buying and selling of organs. The argument that providing financial benefits would incentivize enough people to part with a kidney (or a portion of a liver) to clear the waiting lists is flawed. This commentary marshals arguments against the claim that the shortage of donor organs would best be overcome by providing financial incentives for donation. We can increase the number of organs available for transplantation by removing all financial disincentives that deter unpaid living or deceased kidney donation. These disincentives include a range of burdens, such as the costs of travel and lodging for medical evaluation and surgery, lost wages, and the expense of dependent care during the period of organ removal and recuperation. Organ donation should remain an act that is financially neutral for donors, neither imposing financial burdens nor enriching them monetarily.
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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 | 0.015 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.032 | 0.027 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".