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Record W3033605207 · doi:10.1177/2158244020927414

Networks, Politics, and the Literary Public Sphere: The Foundation of Modern Democracy in Taiwan (1970s–1990s)

2020· article· en· W3033605207 on OpenAlexaff
Anson Au

Bibliographic record

VenueSAGE Open · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHong Kong and Taiwan Politics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPublic sphereIntelligentsiaPoliticsDemocracySociologySocial movementPolitical economySocial sciencePolitical scienceAestheticsLaw

Abstract

fetched live from OpenAlex

This article examines how literature is a networked social space of political repression and resistance, refracting broader contestations over national sovereignty, self-determination, and identity. Politicizing the traditionally apolitical “world of letters” in Habermas’s Structural Transformation of the Public Sphere, this article employs a novel analysis of the influence that the literary public sphere wields over political consciousness. Using the historical case of Taiwan’s literary networks from the 1970s to the 1990s, this article asserts that the literary public sphere produces a rational-critical generalization of knowledge and exposure to dissonant perspectives that invigorates civil society by creating intelligentsia. Through intelligentsia, ideas within the Taiwanese literary public sphere birthed powerful Dangwai parties that instituted democracy, informed their platforms, and ushered in a new wave of political elites. The Taiwanese case demonstrates how civic tasks can predict political tasks with enough force to stimulate a unique postcolonial political consciousness and spark a revolution.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.783
Threshold uncertainty score0.472

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.039
GPT teacher head0.305
Teacher spread0.266 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2020
Admission routes1
Has abstractyes

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