Scrutiny of E-Mail Discourse Features in an Organization Using Speech Act Theory
Bibliographic record
Abstract
Nowadays, most business communications and transactions are conducted via Computer Mediated Communication (CMC) and as email is the most familiar type of CMC.In reality email communication plays a vital role in establishing and maintaining business relationships, both within a company and with external contacts.This study investigates features of email discourse in workplace communication.Email exchanges are analyzed in order to clarify how members of an organization interact with each other using emails to achieve specific communicative needs of the organization.The data of this study consist of a corpus of email messages (N=112) which are exchanged among members of a selected Iranian organization and collected over a stipulated period.This study drew on the Speech Act Theory framework as the basis for analyzing and explaining the qualitative data.In addition, data was analysed using Nvivo.Finally, the study concludes that the employees in this Iranian organization adopted a variety of discourse and rhetorical strategies to achieve the specific communicative needs at the workplace.The selected strategies reflect the writer's interpersonal relationship with their email intractants.Finally, the findings clarified the features of email discourse.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".