Bibliographic record
Abstract
Abstract This book proposes a new way of understanding augury, a form of Roman state divination designed to consult the god Jupiter. Previous scholarly studies of augury have tended to focus either upon its legal-constitutional aspects or upon its role in maintaining and perpetuating Roman social and political structures. This book contributes to the study of Roman religion, theology, politics, and cultural history by focusing upon what augury can tell us about how Romans understood their relationship with their gods. The current scholarly consensus holds that augury, like other forms of Roman public divination, told Romans what they wanted to hear. Modern scholars speak of augury as a way of gaining control over the gods, of priests and magistrates as ‘creating’ the divine will regardless of the empirical results of augural rituals, and of Jupiter as being ‘bound’ to actualize whatever signs human beings chose to report. This book challenges this consensus, arguing that augury in both theory and practice left space for perceived expressions of divine will which contradicted human wishes. When human and divine will clashed, it was the will of Jupiter, not that of the man consulting him, which was supposed to prevail. In theory as in practice, it was the Romans, not their supreme god, who were ‘bound’ by the auguries and auspices.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".