Bibliographic record
Abstract
The American philosopher John Rawls describes a fair system of social cooperation as one that is both rational and reasonable. Is it rational and reasonable for societies that (1) are vulnerable to diverse risks of morbidity (e.g., cancer, heart disease) and mortality and (2) are constrained by limited medical resources, to prioritize aging research? In this paper I make the case for answering "yes" on both accounts. Focusing on a plausible example of an applied gerontological intervention (i.e., an antiaging pharmaceutical), I argue that the goal of decelerating the rate of human aging would be a more effective strategy for extending the human health span than the current strategy of just tackling each specific disease of aging. Furthermore, the aspiration to retard human aging is also a reasonable aspiration, for the principle that underlies it (i.e., the duty to prevent harm) is one that no one could reasonably reject.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.052 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.041 |
| Scholarly communication | 0.011 | 0.029 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.015 | 0.016 |
| Insufficient payload (model declined to judge) | 0.007 | 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".