Bibliographic record
Abstract
The article deals with the linguocognitive aspects of commemorative discourse. Commemorative discourse is understood here as a combination of language-mediated social practices of preservation, promotion and transfer of the heritage of the past. The topicality of the present paper is determined by the need to expand the knowledge of commemorative discourse as an object of linguocognitive study. The aim of the article is to reveal and describe the ways of verbalizing the linguocognitive grounds of English-language commemorative discourse. The material is 570 English-language small-format texts published online by British, American, and Canadian politicians from 2018 till 2024. The research was conducted with general scientific methods (analysis, synthesis, description, etc.), types of analyzing language phenomena (conceptual, categorial, contextual analysis, discourse analysis) and techniques of material selection and systematization (continuous sampling, fixation of language phenomena). Having analyzed the empirical material, the author finds the principal types of knowledge represented in English-language commemorative discourse – language, intuitive, and scientific, and describes means of their verbalization. The basic linguocognitive mechanisms of meaning-making, which facilitate (re)interpretation of the past, get revealed, cognitive illusion being the most prominent of them. Cognitive illusion is serviced by mechanisms like fusion, analogy, reification, recontextualization, grounding, perspectivization, vantage point, subjectivization, and intersubjectivization.
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 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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.033 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".