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Record W6996748605

Special Issue: Political and economic obstacles of minority language maintenance

2024· other· en· W6996748605 on OpenAlexfundno aff

Bibliographic record

VenuePublication Server of the Institute for German Language (Institute for German Language) · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersUniversity of TorontoMinistry of Education and Science of the Russian FederationUniversity of OklahomaSyracuse UniversitySmithsonian Institution
KeywordsMinority languagePoliticsCeltic languagesMinority rightsLanguage policyLanguage politicsMinority groupLanguage barrier
DOInot available

Abstract

fetched live from OpenAlex

This special issue of the Journal on Ethnopolitics and Minority Issues in Europe (JEMIE) brings together some of the participants of the symposium Political and Economic Resources and Obstacles of Minority Language Maintenance organized by the Language Survival Network ‘POGA’ at Tallinn University, Estonia, in December 2010. More than 20 scholars representing linguistics, anthropology, social sciences and law participated in the symposium, to present papers and discuss questions related to minority language loss, maintenance and revitalization. The six case studies contained in this special issue look at different minorities and regions in the European Union, Russia and the US. The linguistic communities discussed are the Russian-, Võru/Seto- and Latgalian-speaking minorities of Estonia and Latvia; the Welsh- and Breton-speaking communities of the Celtic language; the Russian Finno-Ugrian people with regional autonomies; and the native American groups of the Delaware/Cherokee and the Oneida. The reader will find articles relating to interdisciplinary research approaches in and on minority languages and minority language communities.

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.

How this classification was reachedexpand

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.262
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.015
GPT teacher head0.306
Teacher spread0.291 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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