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Record W2947618921 · doi:10.1515/iral-2018-0357

The refusal of request speech act in Persian, English, and Balouchi languages: A cross-cultural and cross-linguistic study

2019· article· en· W2947618921 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIRAL - International Review of Applied Linguistics in Language Teaching · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsCamosun College
Fundersnot available
KeywordsPersianLinguisticsPsychologySpeech actDescriptive statisticsRealization (probability)MathematicsStatistics

Abstract

fetched live from OpenAlex

Abstract The study examined the realization of refusal of request speech act in Persian, English, and Balouchi languages. 219 individuals participated in the study. Discourse completion task was employed to elicit the participants’ refusals. Descriptive statistics and Chi-square were used to analyze the data. The findings revealed the existence of statistically significant differences among the three groups of speakers concerning both the total frequencies and the frequencies of direct, indirect, and adjuncts to refusals strategies. Furthermore, concerning social status, no statistically significant differences were detected either for total number of strategies or for the number of strategies in main categories in each language, except for the indirect strategies among Persian speakers. In Persian language, with the increase in the interlocutors’ social status level, the increase in the number of indirect strategies was discerned. Likewise, the frequency differences of some semantic formulas were statistically significant regarding the social status in each language.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.810
Threshold uncertainty score0.635

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.389
Teacher spread0.362 · 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