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Record W2755693168 · doi:10.1215/03335372-4166647

Narrative Tradition on the Border: Alexander Veselovsky and Narrative Hybridity in the Age of World Literature

2017· article· en· W2755693168 on OpenAlexaff
Kate Holland

Bibliographic record

VenuePoetics Today · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicRussian Literature and Bakhtin Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHybridityNarrativePoeticsLiteratureLiterary criticismHistory of literatureHistorySociologyArtPoetry

Abstract

fetched live from OpenAlex

The idea of narrative hybridity was central to the work of the Russian literary theorist Alexander Veselovsky (1838 – 1906), particularly to his unfinished work Historical Poetics. For Veselovsky and the Russian theorists who followed him, including Mikhail Bakhtin and Yuri M. Lotman, the boundary rather than the center is the site of hybridization and thus literary and cultural transformation. This article argues that this model of hybridization on the border can point in the direction of a synthesis between the theoretical impulse of contemporary attempts to conceive of a world literary system, with their scale and their concern with models of circulation, and those of postcolonial criticism and creolization theory, with their focus on hybridization and literary and cultural transformation on the periphery and mistrust of centripetal accounts of literary and cultural history. The article examines how Veselovsky's account of the role of narrative tradition and narrative hybridization on the periphery demonstrates the potential of geographic borderlands and periods of historical transition and borderline genres and is a useful touchstone for the work of scholars arguing for the redefinition of traditional understandings of center and periphery in literary history.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.020
Scholarly communication0.0070.008
Open science0.0010.005
Research integrity0.0010.002
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 head0.036
GPT teacher head0.336
Teacher spread0.301 · 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 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

Citations3
Published2017
Admission routes1
Has abstractyes

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