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Record W3156898303 · doi:10.22148/001c.22333

Feminist Bestsellers: A Digital History of 1970s Feminism

2021· article· en· W3156898303 on OpenAlexvenueno aff
Michelle Moravec, Kent K. Chang

Bibliographic record

VenueJournal of Cultural Analytics · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicCultural History and Identity Formation
Canadian institutionsnot available
Fundersnot available
KeywordsFeminismMainstreamHistoriographyGender studiesSociologySalientMedia studiesPolitical scienceLaw

Abstract

fetched live from OpenAlex

Feminism of the 1970s remains among the most influential social movements within the United States. Bestselling texts played a crucial role in spreading feminism beyond early activists into the mainstream of American society. Contemporary scholars of feminism continue to rely on these works as pivotal historical sources. This paper utilizes quantitative methods to compare six feminist bestsellers from 1970. Our data consists of three subcorpora of digitized books published in 1970 found in the Hathi Trust: six feminist bestsellers, a sample of non-fiction, and a sample of writing about women. Computational textual analysis identifies each bestselling title's salient features and the contributions each text made at this key moment in the development of feminist thought. These results led us to propose a historiographical intervention that credits one bestseller, The Black Woman, with a more prominent role in the development of 1970s feminism.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.008
Science and technology studies0.0040.005
Scholarly communication0.0050.004
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.056
GPT teacher head0.232
Teacher spread0.175 · 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
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

Citations3
Published2021
Admission routes1
Has abstractyes

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