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Record W2186967535 · doi:10.22215/cjers.v3i1.2429

Marginal Stories? The Perspectives on Citizenship of Multiple Citizens and Multicultural Persons of Estonia

2007· article· en· W2186967535 on OpenAlexvenueno aff
Leif Kalev, Rein Ruutsoo

Bibliographic record

VenueThe Canadian Journal of European and Russian Studies · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Politics and Security
Canadian institutionsnot available
Fundersnot available
KeywordsCitizenshipMulticulturalismEuropean unionPolitical scienceBottleneckSpace (punctuation)Public administrationSociologyGender studiesLawBusinessEconomicsLinguisticsPolitics

Abstract

fetched live from OpenAlex

This article focuses on practices of citizenship in Estonia by persons with multiple citizenship or multicultural background. In the previous stages of research on this topic primary attention was paid to national citizenship, multiple citizenship and European Union citizenship as institutions, as well as the role of citizenship in the construction of European space. Expected "configurations" of multiple citizenship as articulated in Marshallian (1992) terms, as well as linkages between different spaces of membership (national and not-national) of citizenship as perceived by the national decision makers, mapped both avenues and bottleneck s for the future. Our research raises questions and problems related to citizenship as both an essential tool of nation building and of EU integration (cf. Ruutsoo and Kal ev 2006, Ruutsoo and Kalev forthcoming). Full text available: https://doi.org/10.22215/rera.v3i1.181

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0170.023
Scholarly communication0.0110.007
Open science0.0010.011
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.048
GPT teacher head0.303
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2007
Admission routes1
Has abstractyes

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