An Analysis on Teachers’ Politeness Strategy and Student’s Compliance in Teaching Learning Process at SD Negeri 024184 Binjai Timur Binjai –North Sumatra-Indonesia
Bibliographic record
Abstract
This study aims to find out the politeness strategies used by the teachers and how the politeness affects to the student’s compliance. The focus is on directive and expressive speech acts. The subjects of this study were two teachers and the students of class II-A and II-B at SD 024184 Binjai Timur Binjai. The data was gathered by video audio recording the teachers’ utterances and the students’ compliances to the teacher, in order to find the teacher’s politeness principles and the students’ compliances to the teachers’ utterances. In the data analysis, it is found that 1) the teachers used four maxims in their communication to the students. They are tact maxim, generosity maxim, approbation maxim and agreement maxim. It is not found that the teachers used modesty maxim and sympathy maxim. 2) The teachers were dominantly used tact maxim in their directive speech acts to the students. 3) Children pragmatic competence and positive emotions were the factors that affected the students’ compliances to the teachers’ politeness utterances.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".