Eglon’s Fat and Ehud’s Oracle: A Reconsideration of Humour in Judges 3.12–30
Bibliographic record
Abstract
Judg. 3.12–30 details the assassination of King Eglon of Moab by the Benjaminite Ehud ben Gera. Many scholars insist that the story was originally meant to be funny, contending that the text casts Eglon (i.e. ‘Little Calf’) humorously as a slaughtered bovine. Indeed, some regard the text as ‘satire’, though there remains no consensus as to what, exactly, constitutes the butt of the joke. In this article, I argue that Eglon’s fat and Ehud’s feigned oracle work together to form a comical critique of foreign rulers and their reliance on divination. The argument draws on Victor Raskin’s semantic theory of verbal humour along with a re-examination of fat on elite male bodies in the Hebrew Bible and the practice of ancient oracle giving, as reflected in cuneiform sources. I thus aim to elucidate ways the text would have registered as humorous and meaningful for an ancient West Asian audience.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.046 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| 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 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".