MétaCan
Menu
Back to cohort
Record W2560231664

Europe’s changing lessons from the past

2016· article· en· W2560231664 on OpenAlexaff
Aline Sierp

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Geopolitical and Social Dynamics
Canadian institutionsMontreal Council on Foreign Relations
Fundersnot available
KeywordsDictatorshipDisciplineSociologyPoliticsOppressionMeaning (existential)LawSocial sciencePolitical scienceMedia studiesDemocracyEpistemology
DOInot available

Abstract

fetched live from OpenAlex

This special issue brings together scholars who concentrate on the way ‘lessons from the past’ have been framed in different national contexts in Central and Eastern Europe. In the wake of crisis in Europe, bits and pieces of the past are being resurrected as a means of understanding the present and imagining the future. References to historical experiences and lessons from the past have started to reappear in public and private discourse. Most allusions go back to the first half of last century and the experience of war, oppression and dictatorship that have marked the beginning of European cooperation within a fixed institutional framework. ‘Lessons from the past’ have always played a considerable role in EU integration history. But how has their meaning changed over time? Which role do references to WWII, Nazism and Fascism, Civil War and the Holocaust still play in today’s debates on further integration? How is their relevance to the present disputed? What is the process through which they are revived and reanimated in contemporary debates? By gathering scholars from different universities in the Netherlands, Denmark, Belgium, Poland, Germany and the US with different disciplinary backgrounds (political science, anthropology, history, sociology, law, cultural studies) and from different generations, this special issue examines the topic from the widest possible angle. In addition to detailed empirical discussions covering diverse national settings across Central and Eastern Europe, the different contributions and the introduction by the guest editor discuss and offer a variety of conceptual and methodological approaches within the inter-disciplinary study of memory and identity in the context of socio-economic and political crises.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.931
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.286
Teacher spread0.256 · 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 teacher head, not a consensus.

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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueData Archiving and Networked Services (DANS)Same topicHistorical Geopolitical and Social DynamicsFrench-language works237,207