Business writing on the go
Bibliographic record
Abstract
Purpose– The purpose of this paper is to investigate how business executives perceive and account for their use of paratextual cues as a means of managing their professional impressions in business e‐mails on their smartphone (i.e. BlackBerry, iPhone, etc.) and office computer.Design/methodology/approach– Semi‐structured, audio‐recorded telephone interviews were conducted with a representative sample of 60 business executives from various sectors in Canada. The interviews examined executives' typical ways of writing e‐mails for business purposes, both on their smartphone and office computer. All interviews were transcribed and then analyzed using a mix of quantitative and qualitative analyses.Findings– This study shows how organizational leaders vary their ways of opening and closing business e‐mails when comparing their smartphone to their office computer communication. To account for these differences, they routinely use folk categories that suggest distinctions between formal and informal relationships, internal and external communication, as well as the recipient's identity and their own. Hence, executives are aware of the social meanings inscribed in paratextual cues and even the absence of these cues is frequently used as a cue in itself.Originality/value– E‐mailing is a crucial part of contemporary corporate communications, yet few studies have examined organizational leaders' e‐mail writing practices on their smartphone in relation to their office computer. While executives might seem very task‐oriented in their communication, this study shows that their everyday e‐mail‐writing practices play an important role in the co‐construction of professional identities and relationships.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.418 | 0.266 |
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".