I Am a Christian: The Nun, the Devil, and Martin Luther
Bibliographic record
Abstract
I am close to a US Federal Agent and we have remarked more than once that my job as an historian is not entirely different from the job of a detective.We are both trying to solve mysteries or explain events.Carolyn Schneider's new book is a prime example of history as detective story.The sermon illustration that provokes this mystery is common.I first heard it during one of my father's sermons in the early 1980s.It records the experience of a woman who when confronted by the devil repelled him with a simple declaration of her faith, "I am Christian." Since that sermon thirty years ago, I have heard it retold a number of times, sometimes with water signifying baptism being thrown at the devil for good measure.Sometimes, it is Luther himself who is the focus of the story rather than the woman about whom he spoke.It is true that Luther seems to have used her as an exemplum for his own bouts with the devil.This book, Schneider tells us, began as a "quest to uncover the identity of Luther's faithful woman, " (1).The book ends with a theological investigation into the continuing usefulness of the story for pastoral care today.The first chapter opens the mystery by discussing the many and various ways and contexts within which Luther retold the story of a faithful woman and her encounter with the devil.The illustration can be found in his writings as early as 1520 and as late as 1544.They stretch across sermons, formal essays (like Babylonian Captivity -the first recorded use of the story), lectures, commentaries, and not-surprisingly the Table Talk.The story's contours change and the main character goes through some transformations -from a holy virgin, to nun, or a girl, or even sometimes she is given the name Mechthild.As Schneider guides the reader through these changes in Chapter Two, she carefully highlights how the story was changed to accommodate Luther's changing theological vision.As his theology evolved, so too did the story.In Chapter Three, we arrive at the center of the mystery.Who was the faithful woman?Discovering her identity is far more difficult than Schneider had first thought it might be.She posits a number of possibilities including Mechthild of Hackeborn (d.1298) and Mechthild of Magdeburg (d.1285).In the end, it
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".