Peculiarities of Using Stylistic Means in American Artistic Discourse
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
The article analyzes the use of stylistic means in contemporary American novels about the challenges of postmodern society, such as terrorist attacks, loneliness in digital reality, and digital technologies. Descriptive, continuous sampling, dictionary definitions, and contextual and component analysis methods were used to analyze the language material from novels by Douglas Coupland and Don DeLillo. The analyzed stylistic units were diverse and characterized by an emotional and evaluative component, with negative assessments being the most common. The units were divided into thematic groups, such as drugs, money, human behavior, and success/failure. The place and role of stylistic units in the novels were related to their content and stylistic features, with colloquial lexical items playing a significant role in creating a special atmosphere. The study also identified prospects for analyzing current trends in the development of English spoken language based on the works of contemporary American authors. The article concludes that excerpts from the analyzed novels can be used in the study of professional terminology and in seminars on the course "Features of literary translation" to help students compare online terminology and Internet jargon in English and Ukrainian. The Internet as an object of fiction and the use of these works of fiction in teaching English deserve further study.
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.
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 | 0.007 |
| 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 | 0.001 |
| 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