Bibliographic record
Abstract
The purpose of Diachronic Pragmatics is to exemplify historical pragmatics in its twofold sense of constituting both a subject matter and a methodology. This book demonstrates how diachronic pragmatics, with its complementary diachronic function-to-form mapping and diachronic form-to-function mapping, can be used to trace pragmatic developments within the English language. Through a set of case studies it explores the evolution of such speech acts as promises, curses, blessings, and greetings and such speech events as flyting and sounding. Collectively these “illocutionary biographies” manifest the workings of several important pragmatic processes and trends: increased epistemicity, subjectification, and discursization (a special kind of pragmaticalization). It also establishes the centrality of cultural traditions in diachronic reconstruction, examining various de-institutionalizations of extra-linguistic context and their affect on speech act performance. Taken together, the case studies presented in Diachronic Pragmatics highlight the complex interactions of formal, semantic, and pragmatic processes over time. Illustrating the possibilities of historical pragmatic pursuit, this book stands as an invitation to further research in a new and important discipline.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.029 |
| Scholarly communication | 0.009 | 0.015 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".