Moabite women, Transjordanian women, and incest and exogamy: The gendered dimensions of boundaries in the Hebrew Bible
Bibliographic record
Abstract
Building on the work of David Jobling (who suggests there is a structural coding of the Cisjordan as male and the Transjordan as female) and Rachel Havrelock (who suggests the Transjordan and Moab are places of gender deviancy), this article explores issues of geographical, ethnic, and gender identity in stories of Moabite and Transjordanian women. Particular attention is given to the twin tropes of incest and exogamy and how this relates to the pattern of anxiety and lost identity in the Transjordan. Analysis begins with the story of Lot’s daughters, who serve as archetypal and paradigmatic Moabite women, and moves on to include the Moabite women in Numbers 25, Zelophehad’s daughters, Jephthah’s daughter, and Ruth.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".