On Reconstructing the Shorter Edition of the Book of Jeremiah: A Review of Michael B. Shepherd’s <i>A Commentary on Jeremiah</i>
Bibliographic record
Abstract
Abstract In his recent commentary on the book of Jeremiah, Michael B. Shepherd has made a novel contribution by basing his translation and exegesis on the shorter edition of Jeremiah reflected by the Old Greek (OG) translation and two witnesses from Qumran (4QJerb, d). Giving preference to the Hebrew source behind OG as the more original form of the book of Jeremiah, he argues that the MT presents a systematically revised edition of Jeremiah reflecting a historization of the prophetic material, which stands in contrast to the more open-ended, eschatological version of the shorter edition. Alongside his translation and commentary, Shepherd provides a reconstruction of the entire Hebrew Vorlage behind OG-Jeremiah. This review engages critically with Shepherd’s contribution as it relates specifically to textual scholarship on the book of Jeremiah and other attempts at reconstructing either the Vorlage of OG-Jeremiah or the shorter Hebrew edition of Jeremiah. Attention is given to key methodological questions that must be accounted for in both retroverting OG and reconstructing Jeremiah’s shorter edition, as well as to the importance of a nuanced and comprehensive account of OG-Jeremiah’s translation technique. It is concluded that despite its ingenuity and many commendable features, Shepherd’s work is hindered by numerous shortcomings and does not achieve a definitive reconstruction of the shorter edition of Jeremiah upon which future scholarship can build without extensive revision.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".