Bibliographic record
Abstract
Sh.Marjani Institute of History, Academy of Sciences of the Republic of Tatarstan, 5 entrance Kremlin, Kazan 420014, Russian Federation E-mail: dilnur1976@mail.ru The author of this article points out that although the Golden Horde was cre-ated as the result of conquests that terminated the existence of such Muslim states as the Khwarazmian Empire and Volga Bulgaria, nevertheless Muslims perceived the territory of the Golden Horde as “Dar al-Islam”, that is the “territory of Mus-lims”. In the author’s view, the reasons for this lie in the fact that Jochi himself and Batu were in close contact with the Baghdad Caliphate, whence the first Sufi missionaries came, who together with the Central Asian missionaries engaged in spreading Islam among the population of the Golden Horde, and especially among the Tatar elite. Particularly successful in this were Qalandars, Sufis from Anatolia. Islamization took place not only among the sedentary and, first of all, urban population, but the similar transformations happened also among nomadic population of the Golden Horde. Even during the reign of non-Muslim rulers in the Golden Horde, who came to power after khan Berke, the process of Islamization was not interrupted. The author believes that Sufis had been active from the first days of the Golden Horde, and they documented their vision of the Golden Horde history. In the author’s opinion, the history outlined in original Turkic-Tatar sources, for example written by Otemish Hajji and Abdulgaffar Kyrymi, transmit exactly this “Islamized” history of the Jochids. When the story concerns Muslim khans, such as Berke and Uzbek, it accentuates the role of sheikhs. Data from the theological work the “Qalandar-name”, created in the Golden Horde, provides much new factual material on the issue of spread of Islam. The Qalandars were very knowledgeable about Islam and they were prac-ticing Sufis who devoted themselves to proselytizing Islam. They distinguished themselves from other missionaries through their appeal, first of all, to the rulers. Therefore, their activities were clandestine and secret. The author connects their appearance in the Golden Horde with khan Berke’s activities, because he married to a Seljuk princess and rescued the last Seljuk princes from Byzantine captivity. According to the “Islamized” history of the Golden Horde, khans Berke and Uz-bek as well as Janibek were pious Muslim rulers, who possessed all the best Mus-lim qualities, and absolutely the most important, they also participated in spread-ing of Islam as disciples of one or another sheikh. It is known that, for example, khans Janibek and Berdibek were raised by atalyks, that is by Sufi mentors. The
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".