Bibliographic record
Abstract
I defend the first premise of William Rowe’s well-known arguments from evil against influential criticisms due to William Alston. I next suggest that the central inference in Rowe’s arguments is best understood to move from the claim that we have an absence of evidence of a satisfactory theodicy to the claim that we have evidence of the absence of such a theodicy. I endorse the view which holds that this move succeeds only if it is reasonable to believe that (roughly) if there were such a theodicy, we would probably know it. After conceding that there may be modest prima facie support for this latter claim via the Principle of Credulity, I consider and reject four more ambitious arguments in its favour. I conclude that this necessary condition on Rowe’s crucial inference has not been shown to be satisfied.
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 | 0.035 | 0.184 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.063 |
| Scholarly communication | 0.011 | 0.031 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".