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Record W4220666279 · doi:10.1017/s0008938921001734

Negotiating Sovereignty in German History—Historiographical Challenges

2022· article· en· W4220666279 on OpenAlexaff
Rüdiger Graf, Heidi Tworek

Bibliographic record

VenueCentral European History · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicEuropean Political History Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSovereigntyPopular sovereigntyHistoriographyGermanPoliticsPolitical scienceColonialismLawPower (physics)NegotiationAutonomyPolitical economyInternational relationsSociologyHistory

Abstract

fetched live from OpenAlex

Abstract This article introduces a special issue on the politics of sovereignty in German history. Historical work provides an important corrective to understand the current discursive resurgence of sovereignty. Historians (and other scholars) should treat sovereignty not as a factual description of the world, but rather analyze it as a rhetorical claim to assert power in territorial, political, economic, legal, and cultural disputes. Much of the power of sovereignty lies in the power to define its boundaries, whether geographical or conceptual. German history offers a particularly fruitful route to historicize the concept, as Germany is arguably both a paradigmatic and a special case in the history of sovereignty. From late-nineteenth-century colonialism to contemporary disputes around gambling restrictions, German discourse on sovereignty has intertwined with and challenged international understandings of sovereignty together with neighboring concepts, such as independence, autonomy, supreme authority, and control. In the twentieth century, perhaps no country experienced stronger affirmations of both sovereignty and the necessity to integrate into inter- and supranational structures than the country at the center of the two world wars and subsequently divided during the Cold War.

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)0.004
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.020
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0040.022
Scholarly communication0.0100.009
Open science0.0010.003
Research integrity0.0020.002
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 head0.056
GPT teacher head0.202
Teacher spread0.146 · 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
Published2022
Admission routes1
Has abstractyes

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