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Record W4300671641 · doi:10.1353/wlt.2013.0195

Ending up with a Question Mark: An Interview with David Albahari

2013· article· en· W4300671641 on OpenAlexaboutno aff
Tamara Gosta, Tom Toremans

Bibliographic record

VenueWorld Literature Today · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsSerbianJudaismHistoryPopulationIdentity (music)Art historyArtClassicsLiteratureSociologyLinguisticsDemographyPhilosophyArchaeology

Abstract

fetched live from OpenAlex

Over the past four decades, Jewish Serbian-Canadian author David Albahari has produced a body of work that persistently questions matters of identity, language, and history. Until moving to Calgary in 1994, he spent most of his youth and adult life in Zemun and Belgrade. A prolific writer and translator (he has translated Beckett, Pynchon, Bellow, and others), Albahari also served as chair of the Federation of Jewish Communes in Yugoslavia in 1991, working closely on the evacuation of the Jewish population in Sarajevo. His 1996 novel Mamac (Eng. Bait, 2001), which partially draws on his experience of war-torn Yugoslavia, was awarded the NIN Award in 1997 and the Balkanica Award in 1998. For its translation, together with his translators Miryana and Klaus Wittman, Albahari received the Brücke Berlin Literature and Translation Prize. In 2003 Götz and Meyer, the English translation of Gec i Majer (1998), won the ALTA National Translation Award. Other works available in English include the novels Tsing (1997), Snow Man (2005), Leeches (2011), and the shortstory collection Words Are Something Else (1996). Albahari's works have been translated into more than sixteen languages, and in 2012 he received the Vilenica Prize, following in the footsteps of such writers as Milan Kundera and Claudio Magris. We caught up with Albahari in a quiet coffee shop in Zemun.

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 categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.760
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.239
Teacher spread0.230 · 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
GenreOther

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
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueWorld Literature TodaySame topicCanadian Identity and HistoryFrench-language works237,207