Bibliographic record
Abstract
В центре внимания статьи — апологетическое сочинение африканского ритора кон. III ‑ нач. IV вв. н.э. Арнобия «Против язычников». Апология была написана Арнобием после принятия им христианства для обоснования своих взглядов и содержит обширный материал по греко-римскому язычеству. Известно негативное отношение языческого населения к распространению христианства в Римской империи. Зачастую последователи новой религии объявлялись суеверными и безграмотными варварами, скудоумными неучами, не знакомыми с достижениями античной философии и риторическими приемами. Арнобий, по сведениям Иеронима Стридонского, блестяще образованный учитель риторики из города Сикка. Используя все свои познания по философии, риторике и греко-римскому пантеону, Арнобий бьет противника его же оружием, обличая в варварстве религиозные представления язычников. Такой прием носит в неориторике название «возвратный удар» или «принцип бумеранга». The article focuses on the apologetic composition of the African rhetorician of the 3rd — 4th centuries AD Arnobius “Adversus nationes”. The apology was written by Arnobius after he adopted Christianity to substantiate his views and contains extensive material on Greco-Roman paganism. The negative attitude of the pagan population towards the spread of Christianity in the Roman Empire is known. Often the followers of the new religion were declared superstitious and illiterate barbarians, not familiar with the achievements of ancient philosophy and rhetoric. Arnobius, according to Hieronymus of Stridon, is a brilliantly educated rhetoric teacher from Sicca Veneria. Using all his knowledge of philosophy, rhetoric and the Greco-Roman pantheon, Arnobius hits the enemy with his own weapons, exposing the barbarism of pagan religious ideas. Such a technique is called in neo-rhetoric “recoil strike” or “boomerang principle”.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 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 | 0.012 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".