Bibliographic record
Abstract
This paper aims at examining the linguistic persuasiveness techniques based on Grice Maxims (1975) which are employed in Iraqi and Malaysian brochures, beside comparing the violations of Grice Maxims (1975) in Iraqi and Malaysian brochures. Beside that to verify a key hypothesis in this study that the violation of Grice Maxims is a basic pragmatic strategy in advertising to achieve persuasion. Qualitative method has been adopted while analyzing the data. The frequency of every violation has been counted and given a percentage. The results have shown a new dimension added to the previous literature, quantity maxim is frequently violated in Iraqi brochures. Quality maxim is the most violated maxim in Malaysian brochures. Furthermore ellipsis is highly used in Iraqi brochures while hyperbole is frequently used in Malaysian brochures to persuade the tourist. Furthermore the recent results confirm the key hypothesis through the instances of frequent violations of the maxims in both Iraqi and Malaysian brochures which persuade and tempt the reader to head to these destinations. The present study supports Leech’s (1966) goals of advertising. Memorability, Force and Participation exist in all the data in both contexts. Violations of Grice Maxims contribute to these goals. Simply because these violations strengthen the message of the brochures and give additional non-literal interpretation. The study suggests to carry out a further research on persuasion linguistic techniques used in tourism brochures about different cities and towns around the world adopting different theories.
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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 | 0.018 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".