Discourse: Register, Genre, and Style
Bibliographic record
Abstract
Chapter 8 provides a select introduction to register, genre, and style. The multidimensional analysis of style reveals a gradual drift from “literate” to “oral” over time. Attention is given here to the news and religious registers. The news register has seen the rise of the newspaper, leading to the introduction of new publication types, such as television, radio, and internet news, and new genres, such as editorials, obituaries, or weather forecasts. The religious register has a long history and has been remarkably stable. Two religious genres, prayers and sermons, have changed little in respect to function, structure, and linguistic characteristics. The function of recipes remains constant (i.e., instructions on how to prepare or do something), thus accounting for the imperative as the defining linguistic form, but we find differences in the content of recipes (medicinal vs. culinary), in the audience of recipes (e.g., the professional vs. the amateur cook), in the structural elements found in recipes (e.g., separation of the ingredients and the procedural steps), and in characteristic linguistic features (e.g., the introduction of null objects and telegraphic style).
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".