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Record W2051846499 · doi:10.1017/s026841600900719x

Lives in the balance? Gender, age and assets in late-nineteenth-century England and Wales

2009· article· en· W2051846499 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueContinuity and Change · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsYork University
Fundersnot available
KeywordsEstateDemographic economicsBalance (ability)DutyPopulationBalance sheetHistorical demographyComposition (language)Perspective (graphical)DemographyEconomicsSociologyPolitical scienceDeveloped countryFinancePsychologyLaw

Abstract

fetched live from OpenAlex

Abstract Studies of wealth-holding in nineteenth-century Britain focus either on establishing aggregate measures or on individual case studies. These do not allow for a comparative analysis of the way that the composition of wealth was influenced by age and gender. This article explores the importance of these factors using both a case-study approach and a more comprehensive analysis of wealth left at death for a sample of 1,444 individuals. By establishing the age at death for 1,274 of these individuals, together with evidence from a series of death duty records, it is possible to determine the composition of assets by age and gender. For both men and women, shares became more important over the life course. Real estate was more important for men of all ages compared to women, for whom safe investments in government securities assumed greater significance with age. These findings confirm that both age and gender influenced the amount and composition of wealth and demonstrate that these factors need to be taken into account in any model that seeks to make generalizations about the pattern of wealth-holding in the population at large. Emphasizing these demand-side factors provides a different perspective on the rise of Britain as a ‘nation of investors’.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.346

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 science0.0000.000
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 head0.056
GPT teacher head0.228
Teacher spread0.172 · 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