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Record W2886243230 · doi:10.5771/0947-9511-2018-1-143

Does the EU Have a Past? Narratives of European Integration History and the Union’s Public Awareness Deficit

2018· article· en· W2886243230 on OpenAlexaff
Kiran Klaus Patel, Alexandros Sianos, Sophie Vanhoonacker

Bibliographic record

VenueJournal of European Integration History · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Geopolitical and Social Dynamics
Canadian institutionsMontreal Council on Foreign Relations
Fundersnot available
KeywordsEuropean unionNarrativeEuropean integrationPolitical scienceHistoryInternational tradeLiteratureArtBusiness

Abstract

fetched live from OpenAlex

The history of the European Union suffers from a public awareness deficit. 1 Partly, this has to do with the fact that, until recently, European integration has remained a rather small and self-contained field of historiography, while scholars of collective memory and political narratives have only of late commenced examining historical narratives and the politics of remembrance in an EU context. 2 More importantly, political initiatives have failed to nurture public interest in the topic, so that most citizens in the member states and beyond know little about the process that led to the creation of today's European Union.Even if the EU's importance for economic and other issues in our times is hardly doubted, Europeans themselves rarely feel the urge to study this chapter of history.Recent initiatives, such as the House of European History museum in Brussels and the multi-volume project of a history of the European Commission, try to bring about change, but remain projects that only reach small sections of the population.3 In a time of Euroscepticism, neo-nationalism and populism, this lack of knowledge is problematic.This article aims to make an initial contribution to furthering our understanding of the public visibility and media salience of European integration history since the 1.This article results from the work of the Jean Monnet Centre for Excellence HOMER -From History to Memory Culture: Narratives of the European Council Summits from The Hague (1969) to Maastricht (1991) and Lisbon (2009) which Kiran Klaus Patel and Sophie Vanhoonacker have co-directed between 2014 and 2017.We are grateful to our other two co-directors, Wolfgang Wessels (University of Cologne) and Jürgen Mittag (German Sport University), to our students from the three participating universities, to Hartmut Marhold and to the Erasmus+ programme of the European Union.See also: https://www.dshs-koeln.de/en/institute-of-european-sport-development-and-leisure-studies/re-search-projects/ongoing-projects/homer-from-history-to-memory-culture-narratives-of-the-european-council-summits/(last accessed 5 October 2017).2. See, as recent contributions,

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)0.009
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0150.026
Scholarly communication0.0190.015
Open science0.0010.008
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.035
GPT teacher head0.266
Teacher spread0.231 · 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

Citations14
Published2018
Admission routes1
Has abstractyes

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