Проблема Мухаджирства Из Российской Империи В Османскую Империю В Российкой Историографии/Rus Tarihçiliğinde Rusya İmparatorluğu’ndan Osmanlı İmparatorluğu’na Muhacirlik Sorunu
Bibliographic record
Abstract
The article analyzes the study of the problem of muhajirun movement of the Russian inhabitants of the North Caucasus after the Caucasian war in the Ottoman Empire. The author comes to the conclusion that the focus of attention of Russian historiography has been concentrated predominantly on the muhajirun movement of the third quarter of the 19th century. The article shows how the study of this problem was influenced by the political situation, what problems of the muhajirun movement attracted the attention of historians, and which, on the contrary, were ignored. The author proves the existence of two waves of politicization of the problem. The first wave took place after the end of the Great Patriotic war, and the second wave was in the late 1980s – the first half of the 1990s. The author traces the evolution of research approaches and the dynamics of assessments of the phenomenon of muhajirun movement. The special attention is paid to the latest works of Russian historians. The article deals with the issues that are currently the most interested for the Russian historians. It is concluded what problems of muhajirun movement have not yet received the adequate explanation in Russian historiography.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 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".