Peculiarities of Advertising Information Representation in the English-Language Mass Media Discourse
Bibliographic record
Abstract
The relevance of the study is driven by the role of advertising as a genre of mass media discourse in the formation of collective and individual conceptual and linguistic pictures of the world, the conceptual system of the subject of interpretation of the world around him, human consciousness, structuring, formation and transformation of knowledge about the world, and interpretation of knowledge. The research material was modern English-language advertising messages on the English-language Internet. The analysis of the practical material has shown that although the analyzed advertising messages do not directly indicate the evaluation of a product or commodity, it is still implicitly traced: some advertising messages advertise high-quality, new products, while others contain an appeal. It is concluded that the linguistic interpretation of advertising messages is represented by three types: selective, classifying, and evaluative. When interpreting an advertising message, a person, as a representative of a certain society, chooses in his or her mind those units of knowledge about an object of the surrounding world that he or she possesses. In other words, selective conceptualization takes place, which means that the selective function of interpretation is realized. The classifying type of linguistic interpretation implies an appeal to certain emotions and feelings of the subject of interpretation, as well as the division of goods into categories (tasty, useful, high-quality, new), which is evident in advertising messages. It has been proven that the implicit evaluation of goods and services as objects of interpretation indicates the evaluative type of linguistic interpretation.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".