MétaCan
Menu
Back to cohort
Record W4387735412 · doi:10.5195/jll.2023.333

Epitaphs to Empire: On Abe Kōbō and the (Un)Making of the Repatriation Narrative

2023· article· en· W4387735412 on OpenAlexaff
Christina Yi

Bibliographic record

VenueJapanese Language and Literature · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicJapanese History and Culture
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRepatriationNarrativeHomecomingHistoryReading (process)LiteratureContext (archaeology)ArtPolitical scienceLawArt historyArchaeology

Abstract

fetched live from OpenAlex

This article considers some of the dynamics of movement and non-movement in the context of East Asia through an examination of the repatriation narrative. By “repatriation narrative,” I refer to a postwar Japanese form of testimonial interlocution which features a first-person returnee narrator/author who explicitly or implicitly addresses a national audience that does not share the experience of repatriation; and which temporalizes repatriation as a memory reconstructed in the present, marked on one end by the end of the war and on the other by the returnee’s “homecoming” to Japan. This article considers the discursive limits of the repatriation narrative by reading Abe Kōbō’s 1948 debut work Owarishi michi no shirube ni (The Signpost at the End of the Road) and 1957 novella Kemonotachi wa kokyō o mezasu (The Beasts Head for Home) in relation to Fujiwara Tei’s 1949 paradigmatic repatriation narrative Nagareru hoshi wa nagarete iru (The Shooting Stars are Alive), focusing in particular on the various literary and geopolitical displacements in all three texts. In reading Abe's works against the larger discursive history of the repatriation narrative, I aim to show how both texts evince a preoccupation with narrative form that is itself a critique.

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: none
Teacher disagreement score0.015
Threshold uncertainty score0.029

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 studies0.0130.014
Scholarly communication0.0060.006
Open science0.0010.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.279
Teacher spread0.271 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJapanese Language and LiteratureSame topicJapanese History and CultureFrench-language works237,207