Tertullian of Carthage and the Fantasy Life of Power: On Martyrs, Christians, and Other Attachments to Juridical Scenes
Bibliographic record
Abstract
Scholars have read Tertullian of Carthage, especially his obsessions with Roman officials and juridical procedures, as a window into early Christian martyrological discourses and the concerns of real Christian communities. Conversely, this article argues that Tertullian is better understood as an unexceptional part of a larger cultural phenomenon of fantasies of Roman power and juridical scenes. The Roman Empire took hold in the minds of its provincial subjects through its curious combination of symbolic presence and concrete administrative absence. Various geographic and genre-specific examples suggest a prevalence of fantasy life around certain articulations of Roman power, as colonial subjects tried to make sense of intensified social change. Juridical scenes in particular promised truth, resolution, and clarity where there was little to be found. This article situates Tertullian within such social ambiguities, ones that defined life in Roman Carthage, and demonstrates that Tertullian's stark renditions of Roman authorities in confrontation with Christians are largely fabricated from literary sources. This context and Tertullian's writings paint a historical picture of the emergence of the term "Christian" (as epithet and then self-identification) as simply one concentrated instance of such fantasies and juridical attachments.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.049 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".