Barth, Origen, and Universal Salvation: Restoring Particularity. By TOM GREGGS.
Bibliographic record
Abstract
As is immediately apparent from the title, this book, a revised Cambridge doctoral thesis, is something of a novelty. It is not often, if ever, that Origen and Barth have been brought into conjunction with each other in a sustained way for theologically constructive purposes. This Greggs readily acknowledges, but he maintains that such a comparison is not as odd as one might at first think. The two authors had a great deal in common: both were church theologians, but both in some ways were outsiders in the church (Greggs cites the church’s response to their respective unconventional—and contrasting!—sexual expressions as part of the evidence for this), both lived in times of persecution, both were biblical in their approach to theology, both lived in periods when Christianity was not dominant, and both appear to have adhered to a belief in universal salvation. The basic premiss of the book is...
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".