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Record W4403979895 · doi:10.1177/08883254221148489

Václav Havel: Posthumous Reclamation of a National Hero?

2024· article· en· W4403979895 on OpenAlexaff
Barbara J. Falk, Daniela Bouvier-Valenta

Bibliographic record

VenueEast European Politics and Societies and Cultures · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicEastern European Communism and Reforms
Canadian institutionsCanadian Forces CollegeRoyal Military College of Canada
Fundersnot available
KeywordsHEROLand reclamationEnvironmental ethicsArtPhilosophyArchaeologyHistoryLiterature

Abstract

fetched live from OpenAlex

A playwright, philosopher, and president, Václav Havel was well known at home and abroad for all his “careers” and contributions. This article compares and contrasts the recognition accorded to Havel at home and abroad, examining differing assessments and aspects of his legacy—his key contributions to politics, history, and the history of ideas. Within the Czech Republic, we refer to processes and types of memorialization such as local media, exhibitions, how Havel is and was referenced in protest, and more “official” memorials. This national process of reclaiming Havel increasingly brings his domestic profile into accord with his long-standing international stature—which was decidedly not the case while he was in political office. By following avenues of evidence and example from institutional and official levels to more decentralized, local, and unofficial initiatives, we explore which aspects of Havel’s own usable past are referenced, which in turn illuminates how collective memory is shaped. The process of memorializing Havel and paying tribute to his ideas and legacy is necessarily unfinished. Although he died in 2011, how Havel is remembered will continue to evolve, along with larger national and international discussions of dissidence and the impact of Charter 77, as both he and the Velvet Revolution continue to resonate in movements for political change in authoritarian regimes.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.852
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.021
GPT teacher head0.294
Teacher spread0.273 · 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.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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