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Record W3027880885 · doi:10.1111/1758-5899.12816

Power versus Leadership?

2020· article· en· W3027880885 on OpenAlexaff
Ann Fitzgerald, Andrew S. Thompson

Bibliographic record

VenueGlobal Policy · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Relations and Foreign Policy
Canadian institutionsBalsillie School of International Affairs
Fundersnot available
KeywordsChinaPower (physics)Soft powerPolitical scienceOrder (exchange)Construct (python library)Corporate governanceWorld orderHard powerGlobal governancePolitical economyEuropean unionWorld War IIDevelopment economicsEconomyInternational tradeEconomicsLawManagementPolitics

Abstract

fetched live from OpenAlex

Abstract European power in the 21st century is not what it was in the 20th century. The rules‐based liberal international order that Europe helped to construct after the Second World War is under threat, and arguably in decline. As this ‘order’ diminishes, so too does Europe’s ability to influence world events. While Europe will never command either the military or economic hard and ‘sharp’ power of the United States or China, it remains an important international actor with considerable soft power, even with the United Kingdom’s recent departure from the union. Although we question some of the assumptions and priorities identified by the authors of ‘Enhancing Europe’s Global Power’, we share their view that a united and strong Europe has a great deal to offer to the world, particularly in the areas of data governance and tertiary education.

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)0.007
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.032
Scholarly communication0.0120.011
Open science0.0010.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0200.002

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 head0.122
GPT teacher head0.389
Teacher spread0.267 · 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 designTheoretical or conceptual
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
Published2020
Admission routes1
Has abstractyes

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