Bibliographic record
Abstract
Telling the story of how Christians learned to stop worrying and embrace the probable, this chapter considers how thinkers evaluated the certainty and truth of Jesus revelations, both canonical and contemporary. The latter included revelations made to women, with gender rendering their accounts especially unreliable, or, in the plain ken, especially trustworthy. Some writers used Jesus as a tool to demolish the claims of reason; others found in Jesus the compelling certainty they sought. Throughout the East, from Greece to Russia, hesychasts combined the Jesus prayer with breathing techniques to compensate for the instability of knowledge. Jean Gerson raised a difficult question: Should a priest celebrate the eucharist—that is, affect the presence of the body and blood of Jesus—after a nocturnal emission? His investigations led to the development of a plain-ken approach that celebrated a messy probabilism as an acceptable answer to uncertainty, first in ethics, and later more generally. In these ways a plain-ken vision of history, a messy world of contingency, arose between what was necessarily true and what was impossible.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.040 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 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 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".