The Closing Sequences and Ritual Expressions of Informal Mobile Phone Calls Between Saudis: A Conversational Analysis
Bibliographic record
Abstract
Although much work has been conducted on studying conversational openings of telephone and ritual expressions, conversational closings and ritual expressions have received less attention by researchers due to the complexity and difficulty of identifying the beginning of closings in telephone conversations. The parts of closing and ritual expressions on telephone have been examined in some languages, but Arabic has not been studied in landline telephone or mobile phone. Therefore, this study seeks to identify the sequences and ritual expressions between Saudi friends and relatives to explore the strategies of closing informal mobile phone calls by using a conversation analysis approach. Thirty audio-recorded and transcribed mobile phone conversations served as the data source for this study. The results found that the majority of mobile phone closing conversations include three parts: pre-closing, leave taking, and terminal exchange that are similar to many languages such as English, Japanese, and German. Also, various expressions were used in pre-closing and leave taking sequences, but the expressions of using prayers were used more frequently in the sequences. Finally, closing conversation is affected by various external and internal social factors in the sequences and the use of ritual expressions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".