Belief in Miracles and the Presumed Requirement of Extraordinary Evidence
Bibliographic record
Abstract
In this paper, I criticize the commonly accepted view that belief in events plausibly viewed as miracles can only be justified if there exists extraordinarily strong evidence in their favour. Such a claim rests on the mistaken assumption that the evidence for such events must inevitably conflict with what is taken as evidence against their occurrence, such as the evidence for the laws of nature or the existence of evil. Given the arguments I develop that such presumed conflict is apparent rather than genuine, it cannot be urged that belief in events best understood as miracles requires extraordinarily strong evidence before it is justified. This being the case, John Henry Newman’s observation that “miracles differ from other events only when considered relatively to a general system … the same persons are competent to attest miraculous facts who are suitable witnesses of corresponding natural ones … a physician’s certificate is not needed to assure us of the illness of a friend; nor is it necessary for attesting the simple fact that he has instantaneously recovered” can be seen to be correct.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".