How (not) to be rude: Facilitatingthe acquisition of L2 (im)politeness
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
Abstract This article argues for frequent targeted teaching of relational language use or (im)politeness in the L2 classroom. The approach presented here draws on authentic data in the target language and in the language of instruction, which are readily available online. It encourages the learner to make use of their multilingual resources and is exploratory in nature, allowing for a deep engagement with (im)politeness, viz., an extensive array of semiotic features invested in the co-construction of social relations in every social interaction. Working at the interface of (im)politeness studies, intercultural pragmatics, interlanguage pragmatics, and language pedagogy, and undertaken from the perspective of interpersonal pragmatics and relational work, the qualitative analysis focuses on the collaborative work products from participatory learning activities of intermediate to advanced learners of German at a large North-American university. Results show the learners’ raised awareness and broadened knowledge. In particular, learners became aware that what is judged as (im)polite is dependent on the relationship of the interactants, the gender of the interactants, the sociocultural background, norms, values, and believes of the interactants, the context of the interaction, the affiliations of the evaluator, the sociocultural background, norms, values, and believes of the evaluator, etc. Results also suggest that some of the learners need to develop their pragmalinguistic skills further to fully participate in the evaluation of pragmatically rich target language discourse. Additional studies are needed to explore the impact on the learners’ interactional competence.
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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it