“tsɑrɑŋ?” - Telephone Conversation Openings in the Rushani Language
Bibliographic record
Abstract
This paper uses conversation analysis (CA) to examine telephone conversation openings in an unwritten and understudied language, Rushani, spoken primarily in remote, mountainous areas of Tajikistan and Afghanistan. In a sample of three telephone conversations, examples are sought of the four opening sequences of telephone calls originally identified by Schegloff (1986): summons-answer; identification-recognition; greetings; and initial inquiries. At first glance, telephone conversation openings in Rushani appear to skip over the greeting stage and move directly into an extended exchange of initial inquiries. However, upon closer analysis, it is argued that a Rushani word that translates as “How are you” is in fact used by conversation participants as a greeting. The paper concludes with an argument that the study supports a “universalist” position of CA as applied to calls conducted in languages other than English (Luke & Pavlidou, 2002). Despite their apparent form as initial inquiries, greetings in telephone conversations in Rushani serve precisely the same function and resolve the same “interactional issues” as greetings in other languages (Schegloff, 1986).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".