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Record W4309572881 · doi:10.1515/9783110740301

Global Literary Studies

2022· book· en· W4309572881 on OpenAlexaff
Diana Roig-Sanz, Neus Rotger

Bibliographic record

Venuenot available
Typebook
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsECW Press (Canada)
FundersEuropean Social FundAgencia Estatal de InvestigaciónUniversitat Oberta de CatalunyaUniversitat de les Illes BalearsMinisterio de Ciencia e InnovaciónEuropean Commission
KeywordsLiterary criticismArtLiterature

Abstract

fetched live from OpenAlex

While the very existence of global literary studies as an institutionalised field is not yet fully established, the global turn in various disciplines in the humanities and the social sciences has been gaining traction in recent years. This book aims to contribute to the field of global literary studies with a more inclusive and decentralising approach. Specifically, it responds to a double demand: the need for expanding openness to other ways of seeing the global literary space by including multiple literary and cultural traditions and other interdisciplinary perspectives in the discussion, and the need for conceptual models and different case studies that will help develop a global approach in four key avenues of research: global translation flows and translation policies, the post-1989 novel as a global form, global literary environments, and a global perspective on film and cinema history. Gathering contributions from international scholars with expertise in various areas of research, the volume is structured around five target concepts: space, scale, time, connectivity, and agency. We also take gender and LGBTQ+ perspectives, as well as a digital approach.

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)0.002
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: Other · Consensus signal: Other
Teacher disagreement score0.035
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.006
Science and technology studies0.0040.007
Scholarly communication0.0100.005
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0350.006

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 head0.054
GPT teacher head0.263
Teacher spread0.210 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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