Bibliographic record
Abstract
Bilingualism is today as much a topic of academic research and public debate as it has ever been in the period since the end of World War II, as globalization and the new economy, migration and the expanded and rapid circulation of information, keep the question at the forefront of economic, political, social and educational concerns. The purpose of this book is to explore one particular set of approaches to the topic which seems particularly useful for understanding what bilingualism might mean today, in this context of social change, and how new understandings of it, as ideology and practice, also contribute to linguistic and social theory. In particular, the book aims to move the field of bilingualism studies away from a ‘common-sense’, but in fact highly ideologized, view of bilingualism as the coexistence of two linguistic systems, and to develop a critical perspective which allows for a better grasp on the ways in which language practices are socially and politically embedded. The aim is to move discussions of bilingualism away from a focus on the whole bounded units of code and community, and towards a more processual and materialist approach which privileges language as social practice, speakers as social actors and boundaries as products of social action. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".