MétaCan
Menu
Back to cohort
Record W2328062071 · doi:10.1515/zaa.2011.59.2.109

‘And I Did Want to Pass’: Reading Canadian Second Generation Holocaust Memoirs as Migration Texts

2011· article· de· W2328062071 on OpenAlexaboutno aff
Nina Fischer

Bibliographic record

VenueZeitschrift für Anglistik und Amerikanistik · 2011
Typearticle
Languagede
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsMemoirThe HolocaustImmigrationHolocaust survivorsJudaismReading (process)SociologyTransgenerational epigeneticsAlienationHistoryIdentity (music)Gender studiesLiteratureAestheticsArtPolitical scienceArt historyLaw

Abstract

fetched live from OpenAlex

One aspect of post-Holocaust Jewish life to which little attention has been paid in the study of Holocaust literature is the experience of migration. This article examines three Canadian Second Generation Holocaust memoirs and their portrayal of migration. Memoirs by Jewish-Canadian authors prove to be particularly beneficial for analyzing aspects of migration because the immigration of Canada’s survivors often took place when their children were old enough to consciously experience it. Lisa Appignanesi’s Losing the Dead (1999), Eva Hoffman’s Lost in Translation (1989), and Elaine Kalman Naves’s Shoshanna’s Story (2003) all depict the challenges of the arrival to 1950s Canada. The memoirs explore the ways in which the young immigrants cope with dislocation, alienation, and belonging. Against the backdrop of a traumatic family history, they experience different forms of ‘cultural crossings’ - for instance, with regard to language, the immigrant’s body, or religious identity. The focus on migration in Second Generation memoirs highlights the transnational and transcultural rather than merely the transgenerational features of Holocaust memory.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.697
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.003

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 head0.261
Teacher spread0.239 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueZeitschrift für Anglistik und AmerikanistikSame topicCanadian Identity and HistoryFrench-language works237,207