Bibliographic record
Abstract
In a recent article, Ireneusz Zieminski (2018) argues that the main goals of philosophy of religion are to (i) define religion; (ii) assess the truth value of religion and; (iii) assess the rationality of a religious way of life. Zieminski shows that each of these goals are difficult, if not impossible, to achieve. Hence, philosophy of religion leads to scepticism. He concludes that the conceptual tools philosophers of religion employ are best suited to study specific religious traditions, rather than religion more broadly construed. But it’s unclear whether the goals Zieminski attributes to philosophy of religion are accurate or even necessary for successful inquiry. I argue that an essentialist definition of religion isn’t necessary for philosophy of religion and that philosophers of religion already use the conceptual analysis in the way Zieminski suggests that they should. Finally, the epistemic standard Zieminski has in view is often obscure. And when it is clear, it is unrealistically high. Contemporary philosophers of religion rarely, if ever, claim to be offering certainty, or even evidence as strong as that found in the empirical sciences.
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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.029 |
| Scholarly communication | 0.007 | 0.022 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.020 | 0.044 |
| Insufficient payload (model declined to judge) | 0.004 | 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".