ADDRESS FORM AS A REFLECTION OF ETHNO-CULTURAL STYLE OF COMMUNICATION (based on British and Canadian English)
Bibliographic record
Abstract
Culture and the process of communication are interrelated, since culture not only indicates between which members of the society a communication act is possible, but also helps to decode correctly the meaning of the message that was encoded, and also according to what conditions the message would be correctly interpreted by the interlocutor. The historically established ethno-cultural style of communication (T. Larina) reflects the communicative peculiarities of people’s behavior when choosing verbal and non-verbal means in the process of communication. The article is devoted to sociocultural features that influence the choice of language means for expressing an initial speech formula. The aim of our research is to examine address forms in the boundaries of one language but in two different countries (Canada, Great Britain) with their historical and cultural background. We draw on Cultural Dimensions of G. Hofstede (1991), the Theory of Politeness (Brown & Levinson 1987, Leech 2014), the background of Intercultural Pragmatics (A. Wierzbicka 2003, I. Kecskes 2014), Speech Accommodation Theory (Giles 1977) and etc. The article presents the results of the study on the usage of address forms among the representatives of British English (BrE) and Canadian English (CanE) in order to identify similarities and differences and to explain the results according to cultural characteristics.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".