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Record W2015333635 · doi:10.1093/cww/vvp012

Entangled Genealogies: White Femininity on the Threshold of Change in Andrea Levy's Small Island

2009· article· en· W2015333635 on OpenAlexaffabout
Sarah Brophy

Bibliographic record

VenueContemporary Women s Writing · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicEcocriticism and Environmental Literature
Canadian institutionsMcMaster University
Fundersnot available
KeywordsFemininityWhite (mutation)Art historyArtGenealogySociologyHistoryGender studiesBiology

Abstract

fetched live from OpenAlex

Isolation is the hallmark of male migrant narratives of 1950s London. Consider V. S. Naipaul's depiction of the city as a “conglomeration of private cells” (The Mimic Men 22); or George Lamming's image of embittered black nightclub owners who, believing they “have no people” in the metropolis, violently force new migrants who arrive in search of lodging out into the street's lonely “cul-de-sac” (The Emigrants 278–81).1 Andrea Levy's historical novel Small Island (2004) brings into view what her predecessors saw in rare glimpses, but ultimately judged next to impossible in postwar Britain: possibilities for intimacy, community, and a multiracial future. Writing as the daughter of Jamaican-born parents (her father landed at Tilbury, UK on the SS Empire Windrush in 1948), Levy premises Small Island's account of the postwar period on a concept of encounter gleaned from conversations with her mother: Immigration is a very complex process – it doesn't just change the people who come, it changes the people they come to … . Whenever my mother spoke about coming to this country, she always spoke about the white people she met too. I am fascinated by the point of contact where two ways of viewing things, black and white, meet. (“After the Windrush” 23)

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.044
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.018
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.124
GPT teacher head0.244
Teacher spread0.121 · 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 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

Citations11
Published2009
Admission routes2
Has abstractyes

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