The image of batyr Suranshi in Zh. Zhabaev's poem and historical context
Bibliographic record
Abstract
A worthy place among the historical figures of Kazakhstan is occupied by batyr and biy Suranshi. As one of the most famous military commanders, patriarchs, diplomats and political actors of his time, i.e. the second-third quarter of the 19th century, Suranshi-batyr attracted natural attention from the point of view of scientific and historical research. However, the artistic image of the batyr, created by akyn Zh. Zhabaev in the poem "Suranshi-batyr", is of no less interest. This article attempts to study the image of Suranshi-batyr in the context of comparison with historical material, as well as to compare the events described in the poem with actual historical phenomena confirmed by scientific sources. The akyn's poem is of interdisciplinary interest from both philological and historical points of view, as a work from the akyn's pre-revolutionary repertoire. Being a long-liver, Zh. Zhabaev in the first decades of his life was a contemporary of the batyr, which necessitates the analysis of the poem as a possible source of information about that period. Given the scientific interest on the part of the academic community, as well as the growing literary, artistic interest and demand for materials on the history of Kazakhstan on the part of artists and civil society, this article seems to be relevant and is an introductory part of subsequent research work on the study of the life and work of famous people of the middle second half of the 19th century.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".