Pedagogical reflections on <i>New Testament Apocrypha: More Noncanonical Scriptures</i> , volume 2
Bibliographic record
Abstract
In this review article, the author makes the case for Tony Burke’s recent second volume of New Testament Apocrypha: More Noncanonical Scriptures (Eerdmans, 2020) as a publication that can help historians and scholars of religion navigate the convoluted warrens of ancient Christian literature. Adopting a pedagogical lens, the author argues that this volume goes deeper than standard tomes like Marvin Meyer’s Nag Hammadi Scriptures (HarperOne, 2007), offering its audience a more rigorously up-to-date picture of the state of Apocrypha research. The level of rigour and detail on display here might also make the volume more suitable for graduate or upper-level undergraduate courses. In order to support his presentation of the pedagogical value of Burke’s work, the author draws on specific examples rooted in several primary sources contained therein, from the Old Uyghur Adoration of the Magi to the Byzantine Life of Mary Magdalene.
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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 | 0.003 | 0.009 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".