The Cognitive Illusion as a Mechanism of Communicative Accommodation (An Analysis of the English-Language Commemorative Discourse)
Bibliographic record
Abstract
Aim. To reveal means of verbalizing the cognitive illusion as a mechanism of social consolidation in commemorative discourse, i.e. a combination of language-mediated social practices of collective remembrance. Methodology. The research material is 800 small-format online texts of English-language commemorative discourse published from 2019 to 2024 by British, American, and Canadian politicians. The methods of the componential, conceptual, categorial, and cognitive-matrix analysis are used to model the “collective memory” as the central conceptual structure of commemorative discourse. The functioning of the mechanism of the cognitive illusion in commemorative discourse is described within the framework of Communication Accommodation Theory (CAT). Results. It is found that the cognitive illusion is the key mechanism of consolidation in commemorative discourse in that it helps to create and maintain a “virtual museum of collective memory” essential to the social group’s identity. The “collective memory” can be represented as a matrix centred around the “otherness – sameness” conceptual opposition. The matrix brings together two main cognitive contexts with a permeable boundary between them – that of “Past/Future” and that of “Present”. The cognitive illusion helps to transcend the boundary between the two cognitive contexts through a system of “biases” (perspectives of interpretation), whose functioning gets explained in terms of CAT, in particular convergence and divergence. Research implications. The article suggests a methodology for a joint cognitive-linguistic and communicative analysis and modeling of a virtual space which facilitates transmission of socially significant ideas in institutional discourse.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.003 |
| 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".