A Contrastive Study into the Realization of Suggestion Speech Act: Persain vs English
Bibliographic record
Abstract
This study intends to conduct a contrastive analysis between English and Persian with regard to suggestion speech act. To this end, some Iranian university students were asked to complete a Discourse Completion Task (DCT) consisting of six situations in which their suggestion act was explored. The research data was analyzed using percentage and Chi-square test. The study findings were compared with the previous research carried out by Jiang (2006) exploring natives’ use of suggestion act in order to detect the similarities and variations between cultures. The results revealed the variations in almost most of the suggestion types. Furthermore, gender proved to be a significant factor in the production of suggestion strategies. Finally, pedagogical implications were discussed in the context of second language learning. Key words: Culture; Pragmatic competence; Speech act; Suggestion act Resume: Cette etude vise a effectuer une analyse contrastive entre l'anglais et le persain a l'egard de l'acte de parole suggestion. A cette fin, certains etudiants universitaires iraniens ont ete invites a remplir une tâche d'achevement du discours (DCT), compose de six situations dans lesquelles leur acte suggestion a ete exploree. les donnees de recherche a ete analysee a l'aide de pourcentage et de test du chi carre. les resultats de l'etude ont ete compares avec les recherches anterieures effectuees par Jiang (2006) explore indigenes utilisation de la suggestion agir afin de detecter les similitudes et les differences entre les deux cultures. les resultats a revele des variations dans la plupart des types presque suggestion. Par ailleurs, le genre s'est revelee etre un facteur important dans la production de strategies de suggestion. Enfin, les implications pedagogiques ont ete discutes dans le contexte de l'apprentissage des langues secondes. Mots cles: Culture; Competence pragmatique; Acte de parole; Agitationde suggestion
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".