Verbal Politeness as an Important Tool of Diplomacy
Bibliographic record
Abstract
This article examines the notion of diplomatic courtesy and analyzes the ways of its language expression in Russian diplomatic discourse on the example of the speeches delivered by the Minister of Foreign Affairs of the Russian Federation Sergey Lavrov. Diplomatic courtesy is considered by the authors as an integral part of the diplomatic language, which, being a component of the official business style, is characterized by standardization, normalization, lack of emotionality and neutrality. At the same time, the diplomatic language allows the use of language means that are not regulated by the diplomatic protocol, which act as euphemisms and allow expressing opinions on acute political problems without violating the existing rules of diplomatic communication. The success of diplomatic communication is achieved with the help of universal speech formulas that serve as a means of manifesting courtesy and correspond to the standards of diplomatic communication. Such speech formulas themselves do not have legal force, but they have great moral and political power, since they contribute to the regulation of the nature of relations between countries. The article shows that diplomatic courtesy can be both positive and negative. The degree of courtesy in a diplomat's speech may depend on a wide range of various factors conditioned by the dependence of diplomatic etiquette on the specifics of interaction between communicants. Based on the results of the conducted research, the authors came to the conclusion that during various meetings the Minister of Foreign Affairs uses the following verbal means - speech formulas of greeting, address, compliment, invitation, gratitude, condolence, farewell. The frequency of such speech formulas is explained by the need of abidance of an international protocol that prescribes to diplomatic staff a certain sequence of verbal and non-verbal actions.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".