Bibliographic record
Abstract
In his seminal reflection on the badness of death, Nagel links it to the permanent loss “of whatever good there is in living.” I will argue, following McMurtry, that “whatever good there is in living” is defined by the life-value of resources, institutions, experiences, and activities. Enjoyed expressions of the human capacities to experience the world, to form relationships, and to act as creative agents are (with important qualifications) intrinsically life-valuable, the reason why anyone would desire to go on living indefinitely. As Nagel argues, “the fact that we will eventually die in a few score years cannot by itself imply that it would not be good to live longer. If there is no limit to the amount of life that it would be good to have, then it may be that a bad end is in store for all of us.” In this paper I want to question whether in fact there is no limit to the amount of life it would be good to have. My general conclusion will be that it is not the case that the eternal or even indefinite prolongation of any particular individual life necessarily increases life-value. Were death thus somehow removed as an inescapable limiting frame on human life, overall reductions of life-value would be the consequence. Individual and collective life would lose those forms of moral and material life-value that form the bases of life’s being meaningful and purposive.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.022 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".