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Record W3091812787

ЯЗЫКОВЫЕ ТЕРРИТОРИАЛЬНЫЕ РЕЖИМЫ В ЭТНИЧЕСКИХ ФЕДЕРАЦИЯХ

2018· article· ru· W3091812787 on OpenAlexaboutno aff
Надежда Борисова Nadezhda Borisova

Bibliographic record

VenueВестник Пермского университета. Политология / Bulletin of Perm University. Political Science · 2018
Typearticle
Languageru
FieldArts and Humanities
TopicLinguistics, Language Diversity, and Identity
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupAutonomyLanguage policyPolitical scienceState (computer science)Territorial integrityFederal stateScope (computer science)GeographySociologyPublic administrationLawPolitics
DOInot available

Abstract

fetched live from OpenAlex

The struggle for a mother tongue as a medium is caused by the problem of survival of an ethnic group that perceives its language situation as discriminated. It politicizes language and refers us to the research problem of the balance between ethnic minority claims to the autonomy and territorial integrity of a state. In the case of an ethnic federation, the solution of this problem is to redesign the territorial and administrative structure by the separation of a new sub-federal state, transformation of internal boundaries or changing the capacity and scope of preferences for selected regions that get the status of an ethnic territorial autonomy. More often than not, the set of these measures includes language preferential policy. The institutionalized preferential language policy sets language territorial regimes various in their strength. The idea of classifying them into three types is verified by the example of eight ethnic territorial autonomies in five ethnic federations (Wallonia and Flanders in Belgium, Quebec in Canada, the Republika Srpska and the Federation of Bosnia and Herzegovina in Bosnia and Herzegovina, Andhra Pradesh and Telangana in India, and Jura in Switzerland DOI: 10.17072/2218-1067-2016-4-94-115

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)0.002
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.878
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.024
Scholarly communication0.0010.001
Open science0.0040.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0310.005

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 head0.016
GPT teacher head0.227
Teacher spread0.210 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueВестник Пермского университета. Политология / Bulletin of Perm University. Political ScienceSame topicLinguistics, Language Diversity, and IdentityFrench-language works237,207