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Loyalty in Context

2014· book-chapter· en· W2503511997 on OpenAlexaboutno aff
Marcus Klamert

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEuropean Union Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsLoyaltyGermanSolidarityPolitical scienceFidelityContext (archaeology)FaithLawFederal lawEuropean unionGood faithPublic administrationInternational tradeEconomicsEngineeringGeographyLegislation

Abstract

fetched live from OpenAlex

Abstract Chapter 2 discusses various concepts related to Union loyalty, such as constitutional and federal loyalty, federal fidelity (Bundestreue in German law), the Union law principle of solidarity, and the public international law principles of pacta sunt servanda and good faith. It explores whether Union loyalty is distinct from solidarity, to which it is often compared in the literature, and to what extent it shares features with the German and Austrian variants of federal fidelity, as well as with good faith in public international law in general and World Trade Organization law in particular. Case studies on national federal systems such as the US, Canada, and Australia examine the correlation between the absence of a clear division of competences in federal systems and the strength of the respective principles of fidelity.

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)0.002
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 score0.016
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.017
Scholarly communication0.0100.006
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0160.001

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 head0.034
GPT teacher head0.288
Teacher spread0.254 · 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
Published2014
Admission routes1
Has abstractyes

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