Anonymity: What does it mean and why is it important to anonymous living liver donors?
Bibliographic record
Abstract
Anonymous living organ donation has recently become more common in select transplantation programs, with donors voluntarily offering a kidney or a lobe of their liver to those in need. These anonymous donations may be directed to a specific recipient or nondirected, and anonymity may be one way or reciprocal. Given their unique situation, we interviewed a cohort of anonymous living liver donors and explored their opinions surrounding anonymity and its implications in living liver donation. A total of 26 anonymous donors completed a semistructured qualitative interview consisting of questions regarding their experiences as a living liver donor. The interviews were audio-recorded, transcribed, and analyzed for common themes, specifically those pertaining to the donor's perceptions and experiences with anonymity. Five main themes related to anonymity were identified: (1) the moral importance of an unencumbered gift, (2) wanting internal satisfaction rather than seeking external accolades, (3) anonymity as a protection against potential negative outcomes in the recipient, (4) feelings of ambivalence toward meeting the recipient, and (5) concerns about negative perceptions among their own friends and family. These insights into the range of donors' attitudes toward anonymity will help improve awareness and provide the best possible mental and physical care for the anonymous donor.
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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 | 0.031 | 0.085 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.022 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".