English-Language Media Discourse and its Psycholinguistic Functioning in the First Quarter of the 21st Century
Bibliographic record
Abstract
The purpose of this study is to evaluate the degree of influence of the English-language media discourse on the consciousness of a secondary linguistic personality (i.e., a person who speaks English as a foreign language) interacting with English-language electronic media on the Internet at present. The research material included a variety of media resources from leading English-language information platforms in the USA, Great Britain, Canada, etc. The key research method applied in this study is a psycholinguistic associative experiment, which made it possible to empirically assess the impact level of the English-language media discourse on individuals who are not native speakers of English (young people aged 18 to 30 years, receiving basic and specialized higher education in leading Russian universities), but who are active users of English-language information resources, thereby directly or indirectly becoming the object of influence of the English-language media discourse space. As a result of the experimental work, it was possible to establish the presence of positive or neutral reactions to the words — stimuli characterizing English-language media discourse among the respondents of this study. This may indicate the desire of the respondents to remain in continuous interaction with the media reality of the English-language digital media, the information content of which is attractive by representing current social problems, challenges and new opportunities facing human civilization today and in the future.
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.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".