A Pragmatic Study on the Functions of Vague Language in Commercial Advertising
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
Vagueness is one of the basic attributes of natural language. This is the same to advertising language. Vague language is a subject of increasing interest, and both foreign and domestic studies have attained success in it. Nevertheless, the study on the application of vague language in the context of English commercial advertising is relatively sparse. Since the effectiveness of communication of commercial advertisements is one of the greatest concerns of advertisers, this paper is to demonstrate the functions of vague language in commercial advertising, which is a communicative factor in the effectiveness of advertisements, through analysis of vagueness in advertisements under the guidance of pragmatics, Grice’s Cooperative Principle and Conversational Implicature in particular. The paper shows that vague language in commercial advertising plays both positive and negative roles. Its positive functions include improving the flexibility of communication, enhancing the persuasiveness of communication and ensuring the accuracy of information whereas its negative functions cover misleading readers and making them subject to false understanding.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it