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Record W4404884928 · doi:10.1177/17506980241300610

Authenticity, absence, and pedagogy on a historical injustice bus tour

2024· article· en· W4404884928 on OpenAlexafffundabout
James Miles

Bibliographic record

VenueMemory Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicAsian American and Pacific Histories
Canadian institutionsUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsInjusticeSociologyAestheticsEpistemologyPedagogyHistoryPolitical scienceLawArtPhilosophy

Abstract

fetched live from OpenAlex

This article explores how memory practices at sites of historical injustice are shaped by authenticity and absence. It explores a case study of a weeklong bus tour which visited over 15 historic sites dedicated to memorializing the internment of Japanese Canadians during the Second World War. Drawing on the concept of dark tourism, this article explores how the bus tour was simultaneously a planned pedagogical experience, and part of a larger and sustained set of memory practices dedicated to maintaining and cultivating the cultural memory of injustices faced by Japanese Canadians. The article illustrates how these memory practices helped establish a pedagogical authority for some attendees and facilitated certain ethical engagements with the difficult past while avoiding and excluding others. It also demonstrates how the practice of dark tourism is implicated in larger conversations about the erasure of settler colonialism at sites of memory in Canada.

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)0.003
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 score0.181
Threshold uncertainty score0.360

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.020
Scholarly communication0.0050.002
Open science0.0010.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.048
GPT teacher head0.376
Teacher spread0.328 · 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

Citations1
Published2024
Admission routes3
Has abstractyes

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