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Record W4285063876 · doi:10.1515/9781503600560

The Long Afterlife of Nikkei Wartime Incarceration

2020· book· en· W4285063876 on OpenAlexaboutno aff
Karen M. Inouye

Bibliographic record

VenueStanford University Press eBooks · 2020
Typebook
Languageen
FieldSocial Sciences
TopicVietnamese History and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAfterlifeHistoryCriminologyPsychologyPhilosophyEpistemology

Abstract

fetched live from OpenAlex

The Long Afterlife of Nikkei Wartime Incarceration reexamines the history of imprisonment of U.S. and Canadian citizens of Japanese descent during World War II. Karen M. Inouye explores how historical events can linger in individual and collective memory and then crystallize in powerful moments of political engagement. Drawing on interviews and untapped archival materials—regarding politicians Norman Mineta and Warren Furutani, sociologist Tamotsu Shibutani, and Canadian activists Art Miki and Mary Kitagawa, among others—Inouye considers the experiences of former wartime prisoners and their on-going involvement in large-scale educational and legislative efforts. While many consider wartime imprisonment an isolated historical moment, Inouye shows how imprisonment and the suspension of rights have continued to impact political discourse and public policies in both the United States and Canada long after their supposed political and legal reversal. In particular, she attends to how activist groups can use the persistence of memory to engage empathetically with people across often profound cultural and political divides. This book addresses the mechanisms by which injustice can transform both its victims and its perpetrators, detailing the dangers of suspending rights during times of crisis as well as the opportunities for more empathetic agency.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.152
Threshold uncertainty score0.303

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.005
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.022
GPT teacher head0.229
Teacher spread0.207 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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Same venueStanford University Press eBooksSame topicVietnamese History and Culture StudiesFrench-language works237,207