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A Poetics of the Writers' Conference: Literary Relation in the Cold War World

2021· article· en· W3194462978 on OpenAlexfundno aff
Adhira Mangalagiri

Bibliographic record

VenueComparative Literature Studies · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicPostcolonial and Cultural Literary Studies
Canadian institutionsnot available
FundersMcGill University
KeywordsPoeticsRelation (database)DiplomacyState (computer science)Literary criticismColonialismLiteratureHistoryCold warMedia studiesChinaPolitical scienceSociologyPoetryArtLawPolitics

Abstract

fetched live from OpenAlex

Abstract This article offers a poetics of the writers' conference as conducted via channels of Cold War–era cultural diplomacy through a reading of the Asian Writers' Conference (New Delhi, 1956), a largely forgotten predecessor of the better-known Afro-Asian Writers' Conferences. Focusing particularly on the Chinese writers in attendance, I read the conference literarily, with an eye to its aesthetics and the particular performance of transnational literary relation that it engendered. The Conference's fortuitous confluence with the Hundred Flowers Campaign in China unexpectedly made possible an approach to transnational literary exchange that actively eschewed and rebelled against state intervention in the literary sphere. As such, the Asian Writers' Conference effected a form of transnational literary relation that thrived in its self-avowed uselessness to mandates of diplomacy. The Conference warns against the tendency in South–South studies to valorize the decentering of colonial powers as cultural mediators without a critical engagement with the nation-state's overseeing presence once it occupies that agential role in transnational literary exchange.

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)0.005
metaresearch head score (Gemma)0.007
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0210.030
Scholarly communication0.0170.005
Open science0.0020.007
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0070.001

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 head0.100
GPT teacher head0.306
Teacher spread0.206 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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