Bibliographic record
Abstract
Comparative work in the divinatory traditions of the Near East and the classical world, aside from the sub-discipline of astrology, has not been forthcoming. John Jacobs’s 2011 article, “Traces of the Omen Series Šumma Izbu in Cicero’s De divinatione,” is a notable exception. In this work, Jacobs compared Mesopotamian birth omens with those found in Graeco-Roman literature, and discovered a concordance in the category of lion births. This concordance, however, is not exclusive to omens concerning the birth of lions. Snake omens drawn from the Šumma Izbu, the Mesopotamian omen corpus of birth omens, focus on two portents: the rise of a powerful leader and a negative change in social status. When snake omens in Roman literature are examined alongside these Mesopotamian omens, it is evident that the apodoses of the Roman omens likewise portend either or both of these events. The secondary focus of this work is to provide a history of snake omens in Roman sources, and to that end, this work draws on virtually all snake omens in classical Roman literature, although some late sources may have escaped notice. Ultimately, this analysis of the Roman snake omens provides evidence that several ideas about snake omens—that they predict eminent people and social discord—migrated from Near Eastern omen literature and surfaced in Roman literature. While this investigation does not theorize the means of this transmission, it reaffirms the complex relationship Mesopotamian omen lore has with the classical world.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.111 | 0.041 |
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".