Bibliographic record
Abstract
To the Editor: The recent editorial by B. Kaplan and R. Williams (1Kaplan B Williams R Organ donation: The gift, the weight and the tyranny of good acts.Am J Transplant. 2007; 7: 497-498Abstract Full Text Full Text PDF PubMed Scopus (6) Google Scholar) in response to the cry of anger from N. Scheper‐Hughes (2Scheper‐Hughes N The tyranny of the gift: sacrificial violence in living donor transplants.Am J Transplant. 2007; 7: 1-5Abstract Full Text Full Text PDF PubMed Scopus (131) Google Scholar) brings the debate back to the ordinary patient's bedside. As a practicing transplant surgeon, I admit that cases of real abuse of live donations by families and/or physicians exist. However, this does not allow Scheper‐Hughes' blunt conclusion that the social and familial conundrums caused by donation ‘fall outside the view of transplant professionals’ (2Scheper‐Hughes N The tyranny of the gift: sacrificial violence in living donor transplants.Am J Transplant. 2007; 7: 1-5Abstract Full Text Full Text PDF PubMed Scopus (131) Google Scholar). As Kaplan and Williams write, ‘pure altruism does not exist’. Paradoxically, this may be one of the reasons of the increasing popularity of live donations as, in most situations, the gift relieves a whole family, not just a recipient, from the tyranny (ignored by Scheper‐Hughes) of recurrent hospitalizations, dialysis, unemployment, problematic traveling and impaired social life. It follows that in the vast majority of cases, live donor transplantation is to be viewed as a family therapy rather than a predatory aggression.
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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 | 0.007 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.020 | 0.041 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".