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Record W2090882351 · doi:10.5539/elt.v6n10p188

Politeness in Interlanguage Pragmatics of Complaints by Indonesian Learners of English

2013· article· en· W2090882351 on OpenAlexvenueno aff
Agus Wijayanto, Malikatul Laila, Aryati Prasetyarini, Susiati Susiati

Bibliographic record

VenueEnglish Language Teaching · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsnot available
FundersUniversitas Muhammadiyah Surakarta
KeywordsPolitenessPsychologyPoliteness theoryIndonesianPragmaticsComplaintInterlanguageLinguisticsSocial psychology

Abstract

fetched live from OpenAlex

Complaint is intrinsically an abusive act which tends to offend the complainees. In spite of this complainers could consider politeness when they still intend to maintain a good relationship with the complainees. This paper investigated politeness strategies involved in complaints relating to different social status levels and social distances. The data of the complaints were elicited through oral discourse completion tasks from 50 Indonesian learners of English consisting of 25 males and 25 females. The findings indicated that most complaints sounded very direct, particularly those addressed to lower-unfamiliar interlocutors. Four politeness strategies of Brown and Levinson (1987) were employed by the learners. Bald on record and Positive politeness were the most pervasive strategies used across status levels and social distances. Negative politeness was comparatively high, but it was not as high as Bald on record and Positive politeness. Off-record was rarely phrased across status levels and social distances.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.254
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations27
Published2013
Admission routes1
Has abstractyes

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