The Most Good You Can Do with Your Kidneys: Effective Altruism and the Organ-Shortage Problem
Bibliographic record
Abstract
Effective altruism is a growing philosophical and social movement, whose members design their lives in ways aligned with doing the most good that they can do. The main focus of this paper is to explore what effective altruism has to say about the moral obligations people have to do good with their organs, in the face of an organ-shortage problem. It is argued that an effective altruism framework offers a number of valuable theoretical and practical insights relevant to ongoing debate about how to resolve the organ-shortage problem. Its recommendations constitute a plausible and promising strategy for increasing the supply of, and decreasing the demand for, human organs, in a way that protects (rather than ignores, or preys upon) the global poor. And, many of its recommendations can be implemented into policy without requiring that citizens actually become effective altruists themselves.
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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 | 0.022 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.050 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.010 | 0.011 |
| 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".