Linguistic and Stylistic Features of English Public Speeches
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Political communication plays a special role in the life of modern society. Political speeches can be used to judge the direction of the development of political relations between states and the priorities of politicians in various spheres of social and political life. A political public speech is nothing but the interaction of a politician with the audience, a means of propaganda, a presentation of his position and views, a means of persuasion, and a tool for the power struggle. In political speeches, the important role of language as a means of struggle for power and a way to retain it is especially evident. This determines the relevance of studying the linguistic and stylistic features of political speech and identifying effective ways of linguistic influence on a wide audience. The scientific novelty of the article lies in the description of linguistic and stylistic means that contribute to the creation of an effective political speech in English on the example of the speeches of US President Donald Trump, whose speech style is of great interest to linguists. The article aims to describe the linguistic and stylistic means of creating expressiveness that Trump prefers in his speeches. An equally important objective is to determine the main functions of using linguistic and stylistic devices in a political speech.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it