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Record W2100859191 · doi:10.1017/s0047404505230117

<i>Language and power in the modern world</i>

2005· article· en· W2100859191 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLanguage in Society · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsWestern University
Fundersnot available
KeywordsReading (process)Power (physics)LinguisticsSociologyIdentity (music)MultilingualismOn LanguagePhilosophy

Abstract

fetched live from OpenAlex

Mary Talbot, Karen Atkinson &amp; 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).

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.415
Teacher spread0.389 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it