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The image of batyr Suranshi in Zh. Zhabaev's poem and historical context

2023· article· en· W4387335152 on OpenAlexaboutno aff
S. S. Akhmetov

Bibliographic record

VenueEurasian Journal of Philology Science and Education · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSoviet and Russian History
Canadian institutionsnot available
Fundersnot available
KeywordsPoetryContext (archaeology)PhilologyPeriod (music)PoliticsQuarter (Canadian coin)LiteratureComparative historical researchHistoryNatural (archaeology)ArtSociologyAestheticsSocial scienceLawPolitical scienceArchaeology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.322
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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