The Why and the How of Renewal in Philosophy of Religion
Bibliographic record
Abstract
Recently, we co-edited a volume of essays (Draper & Schellenberg 2017) dedicated to the proposition that our field, the philosophy of religion, is not all that it could be. The new set of essays we’re joining here shows that this sentiment is, at the least, not going away. That’s encouraging, but how can we get beyond sentiment? In this our own essay we hope to do so by focusing very precisely and persuasively on problems and solutions: on why our field needs renewal and how to achieve it. More specifically, we hope to get every reader to recognize and accept at least one problem from the range of problems in the field as it exists today that we propose to identify, and to select for special thought and supportive effort at least one solution from the range of solutions we’ll be promoting. Let’s adjust that slightly: one extra problem and one extra solution – for we’re going to start by setting the right mood with some thoughts about a very basic problem/solution pair that we should all be able to recognize/support.
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 | 0.003 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".