О ВАРВАРАХ И ТИРАНАХ: СКРЫТОЕ ВАРВАРСТВО КАК ЭЛЕМЕНТ ПОЛИТИЧЕСКОЙ КРИТИКИ В ПОЗДНЕЙ РИМСКОЙ ИМПЕРИИ
Bibliographic record
Abstract
В статье анализируется использование дискурса скрытого варвара в политической пропаганде IV столетия на примере анализа биографий императоров Галерия и Максимина Дазы, представленных в труде христианского ритора Лактанция «De mortibus persecutorum». Делается вывод, что свидетельства церковного историка о характере вышеназванных императоров прямо опровергаются данными менее ангажированных авторов. Выдвигвается предположение, что, создавая образы гонителей, Лактанций использовал традиционный для римской литературы набор топосов, принятых для характеристики «тиранов», и усиливал свои обвинения, подчеркивая их варварское происхождение. Делается предположение, что основная часть описания Галерия была заимствована Лактанцием из сделанной веком ранее историком Геродианом характеристики императора Максимина Фракийца. The article analyzes the use of discourse of the hidden barbarian in political propaganda of the 4th century on the example of the biographies of emperors Galerius and Maximinus Daza, presented in the work by Lactantius «De mortibus Persecutorum». It is concluded that the testimony of the historian on the character and ethnic origin of the aforementioned emperors is directly refuted by the data of less engaged authors. The assumption is made that while creating the image of the persecutors, Lactantius utilized a set of traditional topoi used to characterize the «tyrants» and enforced his accusations by stressing their barbaric origin. It is assumed that the main part of the Galerius’ description was borrowed by Lactantius from the characteristics of the emperor Maximinus Thracius made a century earlier by the historian Herodian.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.007 |
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".