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Men, Women, and Money

2011· book· en· W2502755425 on OpenAlexaboutno aff
David R. Green, Alastair Owens, Josephine Maltby, Janette Rutterford

Bibliographic record

VenueOxford University Press eBooks · 2011
Typebook
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEmpireInvestment (military)Agency (philosophy)Financial marketCorporate governanceColonialismPopulationPolitical scienceFinanceBusinessSocial scienceSociologyLawPolitics

Abstract

fetched live from OpenAlex

Abstract The late nineteenth and early twentieth centuries witnessed significant developments in the structure, organization, and expansion of financial markets and opportunities for investment in Britain and its empire. But very little is known about how men and women engaged with these markets and with new opportunities for money-making. In what ways did the composition of personal fortunes alter in response to these developments? How did individuals make use of new financial opportunities to further their own priorities and ensure their families' well-being? What choices of securities did they make, and how did these reflect their attitudes to investment risk? What were the implications of a rapidly growing investor population for corporate governance and the regulation of markets? How significant is gender in understanding new patterns of wealth-holding and investment? This interdisciplinary book brings together a range of leading international scholars to answer these questions and to develop important new research agendas. Foremost among these is a concern for gender, with several of the chapters exploring the growing importance of women within investment markets. These findings open up dialogues between economic and financial historians with social, gender, and feminist historians and add a significant new dimension to existing research on women's economic agency. The volume also breaks fresh ground by analysing aspects of wealth-holding and finance in British colonial settings: Canada and Australia. Understanding the extent to which global financial processes shaped the economic lives of those on the ‘periphery’ as well as at the ‘heart’ of empire will offer new insights into the social and geographical diffusion of financial markets.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.927
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.035
GPT teacher head0.168
Teacher spread0.133 · 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

Citations20
Published2011
Admission routes1
Has abstractyes

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