DYNAMICS OF THE SEMANTIC COMPLEX OF DOMINANT UNITS IN POETIC TEXT: INTERTEXTUAL ASPECT (a Case Study of L. Cohen’s Poem ‘Elegy’)
Bibliographic record
Abstract
The article deals with the dynamics of the semantic complex of dominant units in poetic text. Units of poetic text are divided into constant and dominant ones. Constant units realize the function of the context formation. They have one clear meaning. Dominant units realize the function of semantization. They are poly-interpretative. The methodology of the work is based on the theory of intertextuality which is viewed from the position of structural, interpretative and lingua-cultural approaches. The brief typology and characteristics of intertextual relations are given: auto- (self-quotations, self-allusions), in- (quotations, allusions), para- (structural and compositional units of a text such as a title, an epigraph, etc.) and arch-textuality (genre imitation; referring to well-known artistic images or cultural phenomena). The paper presents the model of analysis of dominant units in poetic text. The analysis is carried out in five steps: fragmentation, contextual analysis, search and determination of intertextual relations between the analyzed unit and units of address texts, contextual analysis of address texts, synthesis of the obtained contextual meanings. The practical material under study is the poem Elegy by the Canadian poet L. Cohen. The unit of analysis is the personal pronoun he in the given poetic text. The paper establishes intertextual relations between Elegy and texts from Greek mythology, the Holy Bible, Christian culture, and other works by L. Cohen. The conducted analysis shows that intertextual relations between the studied units initiate exchange and superimposition of their context meanings. As a result, the studied unit can have several meanings (some of which are not present in dictionaries but unique for the given author) within the same context. In this way, the dynamics of the semantic complex of the studied units and poetic text is realized.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.016 | 0.029 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".