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Record W4293228570 · doi:10.1177/0308275x221074828

Defying national homogeneity: Hidden acts of <i>Zainichi</i> Korean resistance in Japan

2022· article· en· W4293228570 on OpenAlexfundno aff
C Laurent, Xavier Robillard‐Martel

Bibliographic record

VenueCritique of Anthropology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicJapanese History and Culture
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsHegemonyDialecticSociologyPoliticsOpposition (politics)EthnographyColonialismCollective actionResistance (ecology)Gender studiesCultural hegemonyPolitical scienceEpistemologyLawAnthropology

Abstract

fetched live from OpenAlex

This article draws attention to the shifting dialectical relationship that exists between everyday acts of resistance and the forms of domination they seek to subvert. Using ethnographic data collected in Osaka’s Koreatown, we analyze some of the ways in which young Zainichi Koreans, the descendants of colonial subjects who migrated to Japan, use daily acts of self-preservation to chip away at hegemonic notions of Japanese national homogeneity. Seemingly trivial choices to dissimulate one’s identity, transmit cultural practices, and maintain historical memory constitute neglected forms of opposition that illustrate the contextual nature of Zainichi Korean resistance against marginalization and forced assimilation. These strategies offer a reservoir of resources that can be tapped into for collective political action, keeping the embers of resistance alive in between periods of open protest.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.014
Scholarly communication0.0050.004
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.339
Teacher spread0.311 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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