Bibliographic record
Abstract
Mary Talbot, Karen Atkinson & David Atkinson, Language and power in the modern world. Edinburgh: Edinburgh University Press, 2003. Pp. ix, 342. Pb £16.99. Centered on critical language study, Language and power in the modern world aims to “reveal and challenge aspects of the intense socialization to which we are all subjected, not only through language but also about language” (p. 4). The authors begin with a relatively brief introduction to the concept of power, leaning heavily on Foucault as interpreted by, especially, Norman Fairclough. The introduction, while focused on power, delves into Critical Discourse Analysis and the critical (socio)linguistics literatures to situate a quick overview of the book, which is organized around five chapters: “Language and the media,” “Language and organisations,” “Language and gender,” “Language and youth,” and “Multilingualism, ethnicity and identity.” In each chapter, the authors present an initial review essay of 11 to 20 pages, followed by an “activities” section, which typically presents two or three suggested tasks for students. The bulk of each chapter, however, is the set of four or five (edited) readings of primary sources relevant to the chapter's topic. The readings, regularly addressed in the earlier chapters as “Reading 1.2” or “Reading 2.3,” often with no title or author noted, are the best part of this book. The reading selections are quite recent, with only one title published before 1995, allowing the reader to catch up on some outstanding primary research that takes the five topic areas well beyond the classic studies of the 1970s and 1980s. The authors' choice of readings is well considered and fulfills their goal not to “promote one approach over another, [but] rather to illustrate a variety of approaches to the study of language and power” (4).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".