Why this work is in the frame
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Bibliographic record
Abstract
Crimes are committed by uttering words or expressions, writing or signifying in a public way like insulting which is one of the crimes against public welfare. This crime has been dealt with and compared legally but its linguistic aspect has not been given much attention. This study tries to emphasize this crime pragmatically and contrastively in English and Arabic. No study has shed light on such aspects concerning the study under investigation. The researcher has not found any previous related study to get a benefit from about this topic. The aim of this study is to shed light on the points of similarity and difference in strategies of insulting in terms of speech act, implicature and impoliteness theories between English and Arabic. The present study hypothesizes the following: In terms of the three theories mentioned above, English and Arabic have points of similarities in strategies of insulting. To support or refute the hypothesis of the study, data consisting of 20 complaints in English and Arabic were collected from Courts of Appeal in Iraq, Britain and the United States. They are analyzed in terms of an eclectic model. The results arrived at are: English and Arabic are different in insulting in terms of the locutionary acts and illocutionary acts. Concerning impoliteness, the same strategies are applied to insulting in both languages. As far as implicature is concerned, the two languages are different in insulting.
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 | 0.011 |
| 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 | 0.000 |
| 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