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Record W2014015304 · doi:10.1163/1871191x-05010105

The External Relations of Tatarstan: In Pursuit of Sovereignty, or Playing the Sub-Nationalist Card?

2010· article· en· W2014015304 on OpenAlexaff
Elena Albina

Bibliographic record

VenueThe Hague Journal of Diplomacy · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Politics and Security
Canadian institutionsÉcole Nationale d'Administration Publique
Fundersnot available
KeywordsCONTESTNationalismSovereigntyInternational relationsPolitical scienceMainstreamPolitical economyEconomic systemSociologyLawPoliticsEconomics

Abstract

fetched live from OpenAlex

This article deliberates on the effects of sub-nationalism on the profile of a region in external relations. The questions under consideration in the present contribution are: (1) does nationalism make the external relations of a region conflictual vis-à-vis the federal centre?; and (2) to what extent can its alleged ill effect be counter-balanced by the well-elaborated mechanism of centre-regional coordination? This article aims to contest the assumptions of mainstream thinking in the literature on paradiplomacy, which suggests that sub-nationalism might have a negative effect and that strong institutions are indispensable for a positive outcome. Relying on an analysis of external relations in Tatarstan, a republic in the Russian Federation, this contribution illustrates the crucial role of the ‘manipulative’ form of nationalism as a key factor shaping the functional character of paradiplomacy.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.011
Scholarly communication0.0060.003
Open science0.0000.006
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.029
GPT teacher head0.330
Teacher spread0.302 · 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

Citations11
Published2010
Admission routes1
Has abstractyes

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