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Record W2118313807

LONG RUN TRENDS IN INCOME INEQUALITY IN THE UNITED STATES, UK, SWEDEN, GERMANY AND CANADA: A BIRTH COHORT VIEW

2000· article· en· W2118313807 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEastern Economic Journal · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicIncome, Poverty, and Inequality
Canadian institutionsDalhousie University
Fundersnot available
KeywordsDecileInequalityEconomicsEconomic inequalityIncome distributionDemographic economicsPovertyIncome inequality metricsDistribution (mathematics)Household incomeCohortGeographyDemographyEconomic growthSociologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

This paper examines the level and distribution of equivalent after tax, after transfer money income in Canada, the United States, the UK, Germany and Sweden using micro-data from the Luxembourg Income Study from 1969/70 to 1994/95. It concentrates on inequality within and between birth cohorts. At any point in time, less than 11% of aggregate income inequality is due to intergenerational inequality. Although median income growth of different birth cohorts over the period has varied widely across countries, there has been a general trend to greater income inequality within cohorts since 1980. The five countries studied differ in the trends observed in aggregate income, poverty, polarization and income inequality. In the United States and the UK, the incomes of the top decile of each cohort have risen dramatically, but the incomes of the bottom quintile have stagnated. In Canada and Sweden both the top and bottom deciles of each cohort have experienced similar trends. Germany is an intermediate case.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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)0.0020.000

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 head0.028
GPT teacher head0.290
Teacher spread0.262 · 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