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Record W2806499209 · doi:10.16995/olh.202

Many a Footnote and Afterword: Dubravka Ugrešić and the Essay

2018· article· en· W2806499209 on OpenAlexafffund
Téa Rokolj

Bibliographic record

VenueOpen Library of Humanities · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicBalkans: History, Politics, Society
Canadian institutionsUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsPoliticsLiteratureContext (archaeology)RealmNationalismLiterary criticismAgency (philosophy)CriticismSociologyVariety (cybernetics)AestheticsCommunismHistoryPhilosophyArtLawSocial sciencePolitical science

Abstract

fetched live from OpenAlex

<p class="p1">A widely translated author, and a prominent voice from post-communist Europe, Dubravka Ugrešić has published a variety of literary forms in addition to literary criticism and translations. Playful experimentation with language, boundaries between texts, and literary conventions as well as an acute awareness of the contemporary socio-political context in which her own texts come to be are among the notable features of her writing. It is her essays, however, that invite a closer look at the interstices between the author and the narrator, the world and the text(s). From her early-1990s essays that were critical of the nationalist discourses of former Yugoslavia and which precipitated her exile through her more recent writing that engages with broader political and cultural questions, Ugrešić has come to embody a public intellectual and transnational writer. I argue that her choice of the essay as the literary form allows her to transcend these two identities, however fluid, and provides her with discursive authority and agency. Cognizant of its legacy and its expressive possibilities, Ugrešić continuously revisits the essay, and, at times, moves it into the realm of theoretical fiction. I shall focus on Ugrešić’s more recent work – the essays from <em>Karaoke Culture, Europe in Sepia </em>and<em> Peščanik</em>.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.824
Threshold uncertainty score1.000

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 studies0.0010.007
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.277
Teacher spread0.246 · 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 designTheoretical or conceptual
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
Published2018
Admission routes2
Has abstractyes

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