Bibliographic record
Abstract
The article is dedicated to the analysis of the verbal influence (also known as suggestion) realization phenomenon in political discourse, which is usually understood as a holistic combined image of the text (be it an advertisement slogan, a political program, a speech, or an interview) itself and the emotions of its recipient and addressee. and is aimed at a a political subject’s (politics, political force, power) influencing a political object (audience, electorate, voter). The political discourse is studied from the standpoint of Psychology, Communicative Linguistics, Sociolinguistics, Speech Acts Theory, Advertisement Theory, PR / GR, Political Linguistics and other related sciences, but it is the involvement of such new methods of studying the linguistic and extralinguistic implementation of suggestion in political discourse, influence being its basic function, that emphasizes the relevance of the work, aimed at studying the manifestations of suggestion in political discourses with the help of NLP’s Milton-model analysis. Contemporary political discourse as an array, which, given the specificity of its functioning in today's information society, is characterized by immanent suggestogenicity is the object of the research; while the essential linguistic features of political discourse as a tool for the realization of its programmed suggestibility are the subject. The factual data of the research is represented by recorded media speeches, political advertisement, political programs and press conference speeches of the politicians heading the governments of Ukraine, USA, France, Spain, Italy, Canada, Germany (about 200 items of each class). The author involves the meta- and Milton-model analysis of the text having been researched and developed in the NLP paradigm in order to isolate the actual linguistic influential patterns (markers of language metamodeling processes, simple, complex and indirect inductions). The linguistic algorithm of Milton-model analysis of political discourses having been researched and visually illustrated with relevant examples combines a complex scientific approach within such multisubstrate science as NLP, and thus it will allow not only to single out dominant strategies of constructing texts and mechanisms of these discourses, but also to highlight the ways to counteract their negative effect, as well as serve in the construction of appropriate planning decisions in the field of optimizing the effectiveness of political communication, emphasized the prospects of the research having been presented in the article, as well as its essential practical value.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".