“Let us cast lots, so that we may know” (Jonah 1:7): Oracle of Lot as a Ritual-like Activity in Ancient Jewish Texts
Bibliographic record
Abstract
Abstract This article seeks to push further scholarly interest and discussion about the ancient Jewish use of the oracle of lot, which has historically been hindered by its categorization as a divinatory method, by including ritual into its categorization. This article explores the ways in which the oracle of lot, as portrayed in Jewish literature, can be categorized under Catharine Bell’s description of ritual-like activity. First, the article gives a general overview of the methods, materials, and functions that the oracle of lot had in the ancient world. Following this discussion, we move on to four case studies where we examine the ritual-like characteristics of the oracle of lot as attested in four Jewish texts: 1 Samuel 14, Jonah 1, Esther 3, and the Community Rule (1QS).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".