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Record W3004873870 · doi:10.1111/roiw.12453

Long Run Canadian Wealth Inequality in International Context

2020· article· en· W3004873870 on OpenAlexaffabout
James Davies, Livio Di Matteo

Bibliographic record

VenueReview of Income and Wealth · 2020
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsLakehead UniversityWestern University
Fundersnot available
KeywordsInequalityEconomicsContext (archaeology)Distribution of wealthWealth distributionReal estateDemographic economicsDistribution (mathematics)Economic inequalityEstateDevelopment economicsGeographyFinance

Abstract

fetched live from OpenAlex

A gap in estimates of the personal distribution of Canadian wealth between 1902 and 1970 is partly filled, using estate multiplier estimates for 1945–1968. The historical record is extended by adjusting the upper tail in survey results since 1970 to make it consistent with respected journalists’ “rich lists.” Top wealth shares decline from 1892 to 1902 and from 1945 to the late 1960s, consistent with the downward trend in most advanced western countries over much of the 20th century. Since 1984 there has been a clear upward trend in wealth inequality in Canada, as in many other countries, and in the United States. Currently, wealth inequality is higher in Canada than in the U.K. and much of continental Europe, somewhat lower than Austria or Germany, and distinctly lower than the U.S. Contrasts between Canada and the U.S. in wealth inequality trends are discussed.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.058
Threshold uncertainty score0.421

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.018
Science and technology studies0.0040.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.070
GPT teacher head0.452
Teacher spread0.383 · 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 designObservational
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

Citations15
Published2020
Admission routes2
Has abstractyes

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