Putting the Persian Back in “Magic”: Problems with Ignoring Ancient Ethnographic Discourses
Bibliographic record
Abstract
Abstract This paper calls for careful consideration of the ethnographic connotations of ancient phenomena often designated “magic” as performed by “magicians” (especially μάγος, μαγεία, μαγικός ) and for the retirement of English terms related to “magic” in the study of antiquity altogether. Deployment of such terms obscures precisely the ostensibly foreign and specifically “Persian” aura which attended references to Magians and Magian skill (better terms) as well as the commonly adopted ancient theory that Magian practices had disseminated throughout the ancient Mediterranean world (to Egyptians, Babylonians, and Syrians/Judeans) from the Persians themselves. I demonstrate this with reference to Greek ethnographic writing on Persian Magians and through a case study of Philo of Alexandria, Pliny the Elder, Apuleius of Madaura, Celsus and Origen, and pseudo-Clement.
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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 | 0.119 | 0.143 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.015 | 0.061 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".