On sin-based responses to divine hiddenness
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract While sin-based responses to divine hiddenness arguments are a road less travelled, they do nonetheless have a number of defenders in the contemporary divine hiddenness literature. I begin this article by exploring the various strategies that have been employed to attempt to motivate such accounts. What none of these strategies seem to take into account, however, is a cluster of facts about the correlation (or lack thereof) between a person's propositional attitudes about God and the degree to which that person displays the relevant moral and intellectual virtues. This article aims to fill this lacuna by mapping out the options available to defenders of sin-based responses in trying to cope with this cluster of facts. I argue that there may be resources available for preserving some aspects of the sin-based approach, but that taking stock of the aforementioned facts will ultimately require the positing of causal factors besides sin in order to generate a sufficient explanation of the phenomenon of non-belief.
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.
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 | 0.000 | 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 | 0.000 |
| 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 | 0.003 |
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 it