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Record W4210950833 · doi:10.4000/caliban.6523

Dwelling with the Land and in History: River Scenes and Cityscapes in Frances Itani's Requiem and Sachiko Murakami's Rebuild

2019· article· fr· W4210950833 on OpenAlexaboutno aff
Lara Okihiro

Bibliographic record

VenueCaliban · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicJapanese History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsHistoryArtGeography

Abstract

fetched live from OpenAlex

Le paysage est une partie importante de l'imaginaire social canadien et de l'histoire de l'exploitation du pays (des premiers colons européens au développement de l'oléoduc). Requiem, un roman de Frances Itani, et Rebuild, un recueil de poèmes de Sachiko Murakami, montrent tous deux la terre comme l'une des choses les plus précieuses prises aux Canadiens japonais pendant leur persécution par le gouvernement (1942-1949). Dans Requiem, le paysage est lié à l’histoire personnelle du protagoniste et conserve tout ce qui reste de tous les événements passés, ce qui en fait une source de réflexion et de guérison. Dans Rebuild, cependant, les tours en copropriété et les maisons construites pendant le boom immobilier de Vancouver ont pris le contrôle du paysage, effaçant l’histoire des peuples autochtones, et même des Canadiens d'origine japonaise, et engendrant une expérience de profonde désorientation et d'aliénation. Cet article analyse les expériences de la terre en tant que guérison et aliénation pour examiner ce que le roman et les poèmes nous disent sur notre relation contemporaine aux paysages : quelles sont les bonnes et les mauvaises manières de vivre sur la terre et comment devrions-nous vivre maintenant sur la terre ?

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.754
Threshold uncertainty score0.996

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 studies0.0000.001
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 head0.012
GPT teacher head0.211
Teacher spread0.199 · 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 designObservational
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
Published2019
Admission routes1
Has abstractyes

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