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Record W2031206414 · doi:10.3138/ijcs.48.33

Subversive Middlebrow: The Campaigns to Ban Kathleen Winsor’s <i>Forever Amber</i> in the US and Canada

2014· article· en· W2031206414 on OpenAlexvenueaboutno aff
Lise Jaillant

Bibliographic record

VenueInternational Journal of Canadian Studies · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicLiterature: history, themes, analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMiddlebrowBoycottHighbrowArt historyResistance (ecology)ArtMedia studiesSloganHistoryPolitical scienceSociologyLawLiteraturePolitics

Abstract

fetched live from OpenAlex

In 1944, Macmillan launched Kathleen Winsor’s racy first novel Forever Amber with an advertising budget of nearly $27,000. Forever Amber can be seen as an example of “the feminine middlebrow novel” (Humble), a kind of commercial fiction largely written and consumed by middle-class women. The immense success of both the novel and the $6,375,000 movie adaptation met with active resistance from conservative groups in the US and in Canada. In 1946, Winsor’s novel went on trial in Boston for obscenity. Moreover, the appeals to boycott movie theatres that played Forever Amber triggered similar campaigns in Canada. The Catholic press in Quebec endorsed the boycotts, and the Toronto politician David A. Balfour demanded a ban on “salacious literature.” Drawing on extensive archival research in the Macmillan collection at the New York Public Library and the Annie Laurie Williams papers at Columbia University Library, this article shows that a “middlebrow” bestseller such as Forever Amber played an important role in the fight against censorship in the US and in Canada. Yet the cultural impact of Forever Amber has been largely neglected, in part because scholars have focused on controversial “highbrow” fiction such as Ulysses and Lady Chatterley’s Lover.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.247
Threshold uncertainty score0.280

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.020
GPT teacher head0.213
Teacher spread0.194 · 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 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

Citations1
Published2014
Admission routes2
Has abstractyes

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