The Other Languages of Europe(Demographic, Sociolinguistic and Educational Perspectives)
Bibliographic record
Abstract
Part I Regional language in Europe: Basque in Spain and France, J. Cenoz Welsh in Great Britain, C. Williams Scottish Gaelic in Great Britain, B. Robertson Frisian in the Netherlands, D. Gorter, A. Riermersma and J. Ytsma Slovenian in Austria with a focus on Charinthia, B. Busch Swedish in Finland A-L Ostern national minority languages in Sweden, L. Huss. Part II Immigrant languages in Europe: Immigrant languages in Sweden, S. Boyd immigrant languages in Germany, with a focus on Hamburg and Hessen, I. Gogolin and H. Reich immigrant languages in the Netherlands, T. van der Avoird, P. Broeder and G. Extra community languages in Great Britain, V. Edwards and E. Reid immigrant language in France, D. Caubet and G. Vermes Arabic in Spain, B. Lopez Garcia and L. Mijares Molina Roma in Europe, P. Bakker. Part III Outlook from abroad: multingualism and multiculturalism in Canada, J. Edwards Spanish in the USA, with a focus on California, R. Macias majority and minority languages in South Africa, N. Alexander immigration and language policy in Australia, U. Ozolins and M. Clyne linguistic minorities in India, A. Choudhry languages in Turkey, K. Yamur languages in Morocco, J. Saib.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".