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Record W4381433619 · doi:10.7146/nts.v34i1.137924

How to Resolve the Trauma of Exile?

2023· article· en· W4381433619 on OpenAlexaboutno aff
Martin Nõmm

Bibliographic record

VenueNordic Theatre Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary, Security, and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeNegotiationGender studiesHistoryIdentity (music)Quarter (Canadian coin)World War IIThe artsPeriod (music)SociologyPolitical scienceAestheticsLiteratureArtLawSocial science

Abstract

fetched live from OpenAlex

The Estonians, Latvians, and Lithuanians who were forced to leave their respective homelands after World War II in the wake of Soviet occupation came to form exile communities across the world. These communities continued their cultural traditions and practices with the arts becoming a medium to reaffirm their identities in exile and narrate their experiences. But with a quarter of a century having passed since their migration, the 1970s became a period of re-evaluating this focus, often represented by topics of generational conflict or inability to change with the times. In North America, first generation Baltic exile playwrights Ilmar Külvet, Alfreds Straumanis, and Algirdas Landsbergis often scrutinized the condition of exile within their works. In this study, I will examine the Baltic narrative of exile as a cultural trauma and take into focus three works by these authors with representations reflecting on the changing times and crises of belonging and identity. The three plays also present a way out of these tensions and can be considered deliberate efforts by the authors to shift cultural discourse and explore other creative potentials of exile, best facilitated by negotiating between the old and the new, the traumatic past, and the ever-changing present.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.572
Threshold uncertainty score0.838

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.087
GPT teacher head0.376
Teacher spread0.289 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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