Bibliographic record
Abstract
On what basis does God choose a possible world to make actual? Theists typically claim that God freely selects exactly one world on the basis of its axiological characteristics. But suppose that there are infinitely many unsurpassable worlds from which to choose; or else that there are no unsurpassable worlds, but instead an infinite hierarchy of increasingly better worlds. On each of these scenarios, philosophers have alleged that God is unable rationally to choose a world for actualization. In the former case, God lacks sufficient reason to select any particular world, since there are infinitely many other equally good candidates. In the latter case, God lacks sufficient reason to select any particular world, since for any world there are infinitely many better candidates. These considerations generate arguments for atheism, as follows. On theism, God is supposed to be the explanation for this world ’s being actual, and God requires sufficient reasons for action. So on either scenario or, since there is an actual world, and since God could not have had a sufficient reason for selecting it, this world was not actualized by God. In response, defenders of theism have urged that God need not have sufficient reason for choosing a world on or : God may defensibly choose a world at random. In what follows, I evaluate this reply. I conclude that it succeeds only on the enormously implausible assumption that there is exactly one randomizer available to God Like Recommend Bookmark Cite Options
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 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".