The Book of Samuel: Studies in History, Historiography, Theology and Poetics Combined. Part Two: A Study of the Narratives Depicting Four National Leaders and Their Dynasties. By Moshe Garsiel
Bibliographic record
Abstract
Seldom in publishing do the words ‘Part Two’ carry so much weight. Readers of this volume need to know that Garsiel’s first volume (which was published in 2018 and covers 1 Samuel 17–2 Samuel 20) is effectively assumed knowledge for understanding this one. Fortunately, Garsiel provides a brief introductory chapter which situates this study, so that readers starting here will at least have some orientation to his approach to Samuel, but the reality is that a much richer reading of this volume is achieved through knowing the first part. Indeed, Garsiel urges readers to begin with the introductory chapter to the previous volume if possible. This volume covers 1 Samuel 1–16 and 2 Samuel 21–1 Kings 4:6, with Garsiel providing a close reading of various passages, starting with 1 Kings 1:1–4:6 (divided into two chapters) before returning to 2 Samuel 21–24 and then 1 Samuel 1–16 (divided into five chapters). The order is important for Garsiel as it provides him with a means of highlighting his main argument, which is that the earliest form of the Samuel corpus was composed by a follower of Nathan in the early years of Solomon’s reign. Although there was some editing to link everything, the material covered here is largely what was composed by the second author, probably about 30 years later, who was opposed to Nathan.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".