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Record W7137676581

World Literatures

2018· other· en· W7137676581 on OpenAlexfundno aff

Bibliographic record

VenueDirectory of Open access Books (OAPEN Foundation) · 2018
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersUniversity of OxfordQueen's UniversityMcGill University
KeywordsVernacularWorld literaturePrestigeFocus (optics)Chinese literatureDozen
DOInot available

Abstract

fetched live from OpenAlex

"Placing itself within the burgeoning field of world literary studies, the organising principle of this book is that of an open-ended dynamic, namely the cosmopolitan-vernacular exchange. As an adaptable comparative fulcrum for literary studies, the notion of the cosmopolitan-vernacular exchange accommodates also highly localised literatures. In this way, it redresses what has repeatedly been identified as a weakness of the world literature paradigm, namely the one-sided focus on literature that accumulates global prestige or makes it on the Euro-American book market. How has the vernacular been defined historically? How is it inflected by gender? How are the poles of the vernacular and the cosmopolitan distributed spatially or stylistically in literary narratives? How are cosmopolitan domains of literature incorporated in local literary communities? What are the effects of translation on the encoding of vernacular and cosmopolitan values? Ranging across a dozen languages and literature from five continents, these are some of the questions that the contributions attempt to address."

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)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.106
Threshold uncertainty score0.355

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.006
Science and technology studies0.0050.004
Scholarly communication0.0160.008
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1060.043

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 head0.092
GPT teacher head0.438
Teacher spread0.346 · 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
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
Published2018
Admission routes1
Has abstractyes

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