MétaCan
Menu
Back to cohort
Record W2995749511 · doi:10.35998/ejm-2019-0013

German Mononational Federalism and the Sorbian Quest for Territorial Autonomy

2019· article· de· W2995749511 on OpenAlexaff
Jean-Rémi Carbonneau

Bibliographic record

VenueEuropäisches Journal für Minderheitenfragen · 2019
Typearticle
Languagede
FieldSocial Sciences
TopicHistorical Geopolitical and Social Dynamics
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsFederalismAutonomyGermanPolitical sciencePluralism (philosophy)Political economyState (computer science)Cooperative federalismRegional autonomyPublic administrationSociologyLawHistoryPolitics

Abstract

fetched live from OpenAlex

If Germany became something close to a “mononational” state, this is not due to the historical absence of national minorities but to the fact that federalism never was intended to empower them, as the case of the Lusatian Sorbs clearly demonstrates. The present article stresses the importance of territorial autonomy and federalism for national minorities. It proposes an institutional analysis centered on the historical path taken by the Sorbs with special emphasis on the critical junctures and the windows of opportunity they opened for their territorial demands in the 20th and the 21st centuries. This article contributes to the comparative literature on federalism and territorial pluralism by providing a counterfactual analysis where a national minority could not achieve accommodation on a territorial basis despite the existence of a federal tradition. It offers an original case study of the challenges faced by a national minority very little known outside East and Central Europe.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.013
Scholarly communication0.0030.002
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.302
Teacher spread0.287 · 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 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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueEuropäisches Journal für MinderheitenfragenSame topicHistorical Geopolitical and Social DynamicsFrench-language works237,207