The Living Anonymous Kidney Donor: Lunatic or Saint?
Bibliographic record
Abstract
Studies indicate that 11% to 54% of individuals surveyed would consider donating a kidney, while alive, to a stranger. The idea of 'living anonymous donors' (LADs) as a donor source, however, has not been embraced by the medical community. Reservations focus on the belief that LADs might be psychologically unstable and thus unsuitable donors. Our goal was to inform policy development by exploring the psycho-social make up and motivations of the LAD. Ninety-three unsolicited individuals contacted our center expressing interest in living anonymous donation. Of these, 43 participated in our study, completing two extensive inventories of psychopathology and personality disorder and taking part in the Comprehensive Psycho-Social Interview (CPSI). From the Personality Assessment Inventory (PAI), the revised NEO Personality Inventory (NEO PI-R), and the CPSI, coders assessed psychological health, psycho-social suitability, commitment, and motivations. Twenty-one participants passed the stringent criteria to be considered potential LADs. Content analysis of motivations showed that potential LADs were more likely than non-LADs (those who did not pass the criteria) to have a spiritual belief system and to be altruistic. Non-LADs were more likely than potential LADs to use donation to make a statement against their families. The authors conclude with a preliminary outline of eight policy recommendations.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".