The Representation of National Identity in Recent Literary Texts by Lithuanian Writers Living Abroad: Irena Mačiulytė-Guilford, "Glėbys", Antanas Šileika, "Bronzinė moteris" and "Pogrindis", and Valdas Papievis "Vienos vasaros eimigrantai" and "Eiti"
Bibliographic record
Abstract
The goal of this work is to analyse how identity is represented in recent novels by writers of Lithuanian origin living outside the homeland, using a methodology that combines literary, cultural and sociological approaches. With renewed independence in 1990, emigration has strongly increased, as have the number of literary works that refer to problems of identity. The object of the analysis is five novels by three writers: Irena Mačiulyte-Guilford‘s Glebys, 2003 ( The Embrace, l999), Antanas Šileika‘s Bronzinė moteris, 2009 ( Woman in Bronze, 2004) and Pogrindis, 2012 ( Underground, 2011), and Valdas Papievis‘ Vienos vasaros emigrantai, 2009 and Eiti, 2010. Papievis, who grew up in Soviet Lithuania, has continued writing in Lithuanian since settling in Paris in 1995, while the other two writers are second-generation Canadian Lithuanians writing in English. The protagonists of all the novels live between more than one identity. To understand their problems, in addition to postcolonial concepts like mimicry, hybridity and the in-between, and the narratological theory of possible worlds, sociological approaches to identity are also used: the imaginary community, identity negotiations, possible selves and social and collective memory. These help distinguish similarities and differences among the novels; their protagonists may be trapped by historical forces (Pogrindis) or feel they can never reconcile confronting identities (Glebys), or may find a creative solution (Bronzinė... [to full text]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".