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Record W3082953013 · doi:10.5509/2020933519

The Making of Post-Socialist Citizens in South Korea?

2020· article· en· W3082953013 on OpenAlexvenueno aff
Jaeyoun Won

Bibliographic record

VenuePacific Affairs · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Socioeconomic Reforms and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsDemocracyNormativePolitical economySociologyPolitical sciencePoliticsLaw

Abstract

fetched live from OpenAlex

This paper aims to capture the complex process through which former socialist North Koreans are remade as South Koreans. I argue that the process by which border crossers from North Korea are remade into post-socialist subjects is complex and multi-dimensional. I address the interlocked nature of institutions and subjectivities in citizen-making processes. On the one hand, it involves the institutionalizations of border crossers with the purpose of screening out "dangerous socialist subjects" for security reasons, followed by "post-socialist" education at Hanawon. On the other hand, it also entails the cultural dynamics of the citizen-making processes. Border crossers are taught not only about political democracy and the economic market, but the cultural learning of resilience to cope with hardship and uncertainty in South Korea. This paper finds two distinctive responses to the cultural learning of resilience—fear and rejection. In this sense, the institutionalizations and the cultural teaching of resilience have unintended consequences. These citizen-making processes raise the question of what characterizes normal subjectivity in a modern, marketized economy. Rather than accepting these normal assumptions as given and natural, this paper tries to uncover hidden assumptions and to problematize the arbitrariness of these normative assumptions. What appears normal, rational, free, and democratic can be actually accidental, temporary, absurd, and socially constructed. This paper attempts to challenge and demystify the meaning of rational, free, democratic, resilient, and normative citizenships that tend to be taken for granted.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.914
Threshold uncertainty score0.260

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.018
GPT teacher head0.260
Teacher spread0.242 · 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 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
Published2020
Admission routes1
Has abstractyes

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