Uniformity and Diversity in Language Policy: Global Perspectives.
Bibliographic record
Abstract
Preface General Introduction Part I-Language Policy at the Official Level Introduction to Part I Chapter 1-Jane Warren and Leigh Oakes: Language Policy and Citizenship in Quebec: French as a Force for Unity in a Diverse Society? Chapter 2-Sally Boyd: Do National Languages Need Support and Protection in Legislation? The Case of Swedish as the 'Principal Language' of Sweden Chapter 3-Uldis Ozolins: Language Policy and Smaller National Languages: The Baltic States in the New Millennium Chapter 4-Paulin G. Djite: Language Policy in Australia: Does What Goes Up Have to Come Down? Chapter 5-Leigh Oakes: Regional Languages, the European Charter and Republican Values in France Today Part II-Language Policy in Practice: Indigenous and Migrant Languages in Education Introduction to Part II Chapter 6-Tadhg O Hifearnain: Breton Language Maintenance and Regeneration in Regional Education Policy Chapter 7-David Lasagabaster: Language Policy in Spain: The Coexistence of Small and Big Languages Chapter 8-Catherine E. Travis and Daniel J. Villa: Language Policy and Language Contact in New Mexico: The Case of Spanish Chapter 9-Gillian Wigglesworth and David Lasagabaster: Indigenous Languages, Bilingual Education, and English in Australia Chapter 10-Yvette Slaughter: Bringing Asia to the Home Front. The Australian Experience of Asian Language Education through National Policy Part III-Language Policy in Real and Virtual Worlds Introduction to Part III Chapter 11-Kerry Ryan and Tim Mcnamara: Testing Identity: Language Tests and Australian Citizenship Chapter 12-Diarmait Mac Giolla Chriost: Language as Political Emblem in the New Culture War in Northern Ireland Chapter 13-Claudia Maria Riehl and John Hajek: Language Policy and Reality in South Tyrol Chapter 14-Heinz l. Kretzenbacher: Addressing Policy on the Web: Netiquettes and Emerging Policies of Language Use in German Internet Forums Chapter 15-Catrin Norrby and John Hajek: Language Policy in Practice. What Happens When Swedish IKEA and H&M Take 'You' On? Chapter 16-Deborah Cameron: Regulating Language in the Global Service Industry
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.029 | 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".