The Pragmatic Aspect of Modality in the English Mass-Media Discourse
Bibliographic record
Abstract
The article is devoted to the pragmatic aspect of modality representation in the English mass-media discourse. The categorial status of modality, typology of modal meanings and their interaction have been examined from the viewpoint of historical perspective. The research is aimed at revealing the pragmatic characteristics of subjective-interpersonal (author-recipient) modality, which reflects the author's intentions to describe the world (epistemic modality), change the world (deontic modality), evaluate the world (axiological modality). The four factors of internet communication - the addresser, the addressee, the text, the objective reality - are studied within the framework of communicative-pragmatic approach to modality. The discourse-analysis and pragma-stylistic analysis have been applied to depict language means representing modality in the English mass-media Internet discourse, in the article on political issues. It has been revealed that the author of the article may act differently in accordance with the roles he assumes - of an informer, of an expert-analyst, of a consultant-adviser; his task is to attract the readers and involve them in discussion in the comments section. The expression of authorship is principal here and the author's modality is always explicit. The comments following the text of an article are distinguished by a variety of the authors' communicative strategies and modal meanings.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.015 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".