Mythical Cognition and Artistic Method
Bibliographic record
Abstract
The aim of the study is to research mythical cognition, which is of particular importance for deep understanding of the issue of mythologism, mythopoetics in literature, and world literary science. The leading research methods for this issue is the analysis method. The specifics of using the mythopoetic method in poetry was given by the poetry of Tynyshtykbek Abdikakimov, the artistic and aesthetic value of mythical knowledge was revealed. The article also analyses the differences between mythological and poetic cognition and proves the value and power of the mythopoetic method in fiction. The system of mythological thinking of a mythological worldview not only determines Kazakh national worldview, but also transfers the fruits of mythical consciousness to the visual system, forming a huge channel of artistic approach. The novelty of the study is determined by the fact that the actual problem of literary criticism was analysed, which is a spiritual value, the transformation of mythological consciousness into poetic consciousness in the poems of the poet, into the basis of images and poetic expressions formed in the system of modern literary thinking. The practical significance of the study is determined by the necessity to study the activity of mythical knowledge in poetics.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".