Bibliographic record
Abstract
In 1660 a thirty-five-year-old Mennonite minister, Thielemann van Braght of Dordrecht in the Netherlands, completed the immense task of publishing a 1,500-page martyrology, the Martyrs Mirror. The book, whose featured martyrs are mostly Dutch Mennonites, marked the zenith of various collections of martyr stories published in the Netherlands shortly after the onset of religious freedom following William of Orange’s rebellion against the Spanish during the 1570s. In Martyrs Mirror: A Social History, David L. Weaver-Zercher argues that the Martyrs Mirror did more than report on a historic fact: true, with some 2,500 victims, persecution of Anabaptists “outpaced” that of all other Christian groups combined during the Reformation (16). But for Weaver-Zercher the original Martyrs Mirror is more than an archival record; it marks a cultural creation set in a shifting and complex social context, as do its many editions over the centuries. Indeed, its immense staying power—with thousands of copies still sold each year to both the “tradition-minded . . . and assimilated” (xvi) branches of the Mennonite world—reveals a text that has taken on disparate meanings. The result of Weaver-Zercher’s approach sheds significant new light on evolving ethnoreligious identities at the heart of Mennonite history.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 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".