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Record W4319345585 · doi:10.7765/9781526162397.00005

Acknowledgements

2023· book-chapter· en· W4319345585 on OpenAlexafffund
Erin Silver

Bibliographic record

VenueManchester University Press eBooks · 2023
Typebook-chapter
Languageen
FieldSocial Sciences
TopicWorld Wars: History, Literature, and Impact
Canadian institutionsOntario College of Art and Design
FundersUniversity of British Columbia
KeywordsMemoirNorwegianNarrativeHistoryPerformance artPaintingArt historyMedia studiesArtGender studiesLiteratureSociology

Abstract

fetched live from OpenAlex

This book can be described as an 'oblique memoir'. The central underlying and repeated themes of the book are exile and displacement; lives (and deaths) during the Third Reich; mother-daughter and sibling relationships; the generational transmission of trauma and experience; transatlantic reflections; and the struggle for creative expression. Stories mobilised, and people encountered, in the course of the narrative include: the internment of aliens in Britain during the Second World War; cultural life in Rochester, New York, in the 1920s; the social and personal meanings of colour(s). It also includes the industrialist and philanthropist, Henry Simon of Manchester, including his relationship with the Norwegian explorer, Fridtjof Nansen; the liberal British campaigner and MP of the 1940s, Eleanor Rathbone; reflections on the lives and images of spinsters. The text is supplemented and interrupted throughout by images (photographs, paintings, facsimile documents), some of which serve to illustrate the story, others engaging indirectly with the written word. The book also explains how forced exile persists through generations through a family history. It showcases the differences between English and American cultures. The book focuses on the incidence of cancers caused by exposure to radioactivity in England, and the impact it had on Anglo-American relations.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.467
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.048
GPT teacher head0.248
Teacher spread0.200 · 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.

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
Published2023
Admission routes2
Has abstractyes

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