Bibliographic record
Abstract
Philosophical debate about the problem of evil derives, in part, from differing definitions of almighty power or omnipotence. Modern atheists such as John McTaggart, J. L. Mackie, Earl Condee, and Danny Goldstick maintain that an omnipotent God must be able to accomplish anything, even if it entails a contradiction. On this account, the Christian God cannot be omnipotent and benevolent, for a benevolent, omnipotent God would have forced free agents to desist from evil and this prevented the introduction of suffering into the world. It does not matter if the idea of creating free agents that were forced to be good entails a contradiction. On this account, a God who is truly omnipotent can perform contradictory feats. In this paper, I argue that the atheistic tradition is mistaken. In the first place, even an absolutely omnipotent God could, as an act of benevolence, create a world in which there is suffering. In the second place, I argue that the concept of absolute omnipotence is fatally flawed. An absolutely omnipotent God would lack, in a decisive sense, power. He would be weak rather than strong. So the atheist's argument fails when it is evaluated in light of a more rational account of omnipotence and when it is carefully considered on its own terms.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.035 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".