MétaCan
Menu
Back to cohort
Record W2067733164 · doi:10.2307/27694419

Women on Their Own: Interdisciplinary Perspectives on Being Single. Ed. by Rudolph M. Bell and Virginia Yans. (New Brunswick: Rutgers University Press, 2008. viii, 273 pp. $49.95, ISBN 978-0-8135-4210-2.)

2008· article· en· W2067733164 on OpenAlexaboutno aff
M. G. O’Brien

Bibliographic record

VenueJournal of American History · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicAmerican Constitutional Law and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsSubject (documents)HistoryMedia studiesGreat DepressionClassicsArt historySociologyLibrary scienceArchaeology

Abstract

fetched live from OpenAlex

On the whole, it is encouraging to see from this interdisciplinary collection of essays that the historical subject of single women is becoming more complex. Once, it was no subject at all, then it acquired some standing as the study of what was once called spinsters, and now the historical study of single women has proliferated. This book, for example, arises from a year-long seminar in 2003–2004 at the Rutgers Center for Historical Analysis, whose Web page now offers a bibliography on works that deal with this subject (http://www.scc.rutgers.edu/rcha) and links to related resources, notably the Scholars of Single Women Network (http://medusanet.ca/singlewomen/resources/bib_main.htm). The essays in Women on Their Own range widely, at least on topics since the early nineteenth century. Widows loom large: they vote in Montreal in 1832, run businesses in Albany from 1813 to 1885, give away millions of dollars in the person of Olivia Sage, and weep decorously for Confederate heroes. Women who never married are conspicuous, too: in Victorian and Edwardian Britain, the American depression of the 1930s, contemporary Ireland, the recent United States, and the modern Caribbean. There is even an essay on how blind women considered the business of not marrying, an essay in which Helen Keller is significant.

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), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.524
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.232
Teacher spread0.219 · 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
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
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueJournal of American HistorySame topicAmerican Constitutional Law and PoliticsFrench-language works237,207