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Record W2547937426 · doi:10.5817/cejcs2011-7-5

The representation of "home" : the novels of Vladimir Tasic

2011· article· en· W2547937426 on OpenAlexaboutno aff
Aleksandra V. Jovanović

Bibliographic record

VenueThe Central European journal of Canadian studies · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicDiscourse Analysis and Cultural Communication
Canadian institutionsnot available
Fundersnot available
KeywordsRepresentation (politics)HistoryArtPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

Vladimir Tasic is a professor of mathematics at the University of New Brunswick, as well as the author of several works of poetry, fiction and non-fiction. He writes in Serbian and English and publishes his work in Serbia and Canada. This article deals with his novels that were written in Serbian and translated into French and partially into English. The article tackles the theme of home in three of Tasic's novels Oproštajni dar (Farewell Gift), Kiša i hartija (Rain and Paper) and Stakleni zid (Glass Wall). The concept of home is discussed in the broader context of the Western literary tradition as well as its implications in the discourse of migrant writers like Salmon Rushdie, Homi Bhabha and V. S. Naipaul, along with the earlier manifestations of home in the writings of an older generation of exiled authors such as György Lukács, Ihab Hassan and Walter Benjamin. In his narrative world, Tasic establishes a perpetual dialogue between concepts of "home" on different levels of their fictional representation.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.980
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0190.020
Scholarly communication0.0090.003
Open science0.0010.005
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.171
GPT teacher head0.333
Teacher spread0.162 · 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 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
Published2011
Admission routes1
Has abstractyes

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