Bibliographic record
Abstract
I thank Jerome Gellman for his critique of my recent article "Ordinary Morality Implies Atheism." 1 In that article, I argued that traditional theism threatens ordinary morality by relieving us of any moral obligation to prevent horrifi c suff ering by innocent people even when we easily can.Gellman attempts to rescue that moral obligation from my charge that theism destroys it.I believe his attempted rescue fails.Gellman begins by quoting the main principle on which my argument depends, the principle sometimes called "theodical individualism" that I abbreviated with the initials "TI":(TI) Necessarily, God permits undeserved, involuntary human suffering only if such suff ering ultimately produces a net benefi t for the suff erer.He then correctly notes that theism-the proposition that God existsand TI together imply (to use Gellman's numbering) (3a) Necessarily, all undeserved, involuntary human suff ering ultimately produces a net benefi t for the suff erer.However, Gellman gives reasons to reject the claim in my argument that (3a) implies (again, his numbering) (3c) We never have a moral obligation to prevent undeserved, involuntary human suff ering.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.025 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.018 | 0.023 |
| Insufficient payload (model declined to judge) | 0.004 | 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".