Bibliographic record
Abstract
Many theists hold that for any world x that God has the power to actualize, there is a better world, y, that God had the power to actualize instead of x. Recently, however, it has been suggested that this scenario is incompatible with traditional theism: roughly, it is claimed that no being can be essentially unsurpassable on this view, since no matter what God does in actualizing a world, it is possible for God (or some other being) to do better, and hence it is possible for God (or some other being) to be better. In reply to an argument of this sort, Daniel and Frances Howard-Snyder offer the surprising claim that an essentially unsurpassable being could – consistently with his goodness and rationality – select a world for actualization at random. In what follows, I respond to the most recent contributions to this discussion. I criticize William Rowe’s new reply to the Howard-Snyders (but I endorse the spirit of one of his arguments), and I claim that Edward Wierenga’s new defence of the Howard-Snyders fails. I conclude that the Howard-Snyders’ argument fails to show that an essentially unsurpassable being could randomly choose a world for actualization. Accordingly, it fails to block an important argument for atheism.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.024 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".