Word Order in the War Scroll (1QM) and Its Implications for Interpretation
Bibliographic record
Abstract
Abstract In studies of Qumran Hebrew, syntax has been somewhat neglected. The present study attempts to help fill in our understanding of QH syntax, and word order specifically. The data of 1QM can best be explained using a Subject-Verb model. However, the model is not perfect. Consideration of the strange word order patterns of and leads to a revision of the SV model, which is better able to account for all the word order phenomena in 1QM. The basic word order of 1QM is best described as Subject-Verb, with inversion triggered by the fronting of a non-subject element or by the use of an intransitive main verb. A robust understanding of word order carries important ramifications for interpretation. In 1QM 1:1‐3, for example, word order supports an identification of the sons of Levi, Judah, and Benjamin as “violators of the covenant.”
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.010 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".