British and Australian Corporate Communication: A Socio-Linguistic Perspective
Bibliographic record
Abstract
In this study, the corpora of British and Australian corporate communications were compared with the aim of specifying their sociolinguistic features in the context of five lexical and stylistic markers: professional jargon, as well as expressive, colloquial, uncodified and evaluative lexis. Lexical and stylistic characteristics of corporate communication from the point of view of a sociolinguistic approach were analyzed using transcripts of British and Australian communicative corporate interactions. The methods of continuous sampling, comparative, lexical-stylistic and sociolinguistic analysis were implemented to process an assembled corpus of 158 authentic transcripts. Based on the results of the analysis, quantitative data were compared, reflecting the volume of use of the indicated lexical-stylistic markers in the two samples. Quantitative data were subsequently analyzed to determine sociolinguistic characteristics that can be assessed as specific features of the communicative behavior of British and Australian superiors in dealing with subordinates. For each of the markers of lexical-stylistic differentiation under consideration, the two samples analyzed in the work showed differing results of a varied and at the same time exponential degree of discrepancy.
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 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 | 0.044 |
| 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) | 0.001 | 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 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".