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Record W2127603603 · doi:10.1093/ije/dyh108

Commentary: The contingencies of income inequality and health: reflections on the Canadian Experience

2004· letter· en· W2127603603 on OpenAlexaffabout
N. A Ross

Bibliographic record

VenueInternational Journal of Epidemiology · 2004
Typeletter
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsMcGill University
Fundersnot available
KeywordsInequalitySocial inequalityEconomic inequalitySociologyHealth equityDemographic economicsPsychologyPublic healthMedicineEconomicsNursingMathematics

Abstract

fetched live from OpenAlex

In this issue of the International Journal of Epidemiology, Amir Shmueli recounts several health and economic indicators for Israel between 1979 and 2000.1 On the health side of things, life expectancy at birth increased by more than 5 years for both men and women as infant mortality declined precipitously. On the economic side of things, absolute wealth (measured in 1995 dollars per capita) rose from about 36 000 IS in 1979 to more than 54 000 IS in 2000. Inequality in the distribution of income also rose during the period, however, there were only modest increases in post-transfer and disposable income inequality. The most obvious increases in income inequality were to be found in the increasing gap in earned income. In other words, between 1979 and 2000 the gap created by polarized wages and returns from investment income was really quite significant. During the period, on average everyone was getting healthier and the Israeli economy was indeed growing but the health gains and growth appeared alongside increasingly polarized labour market opportunities and returns. In order to keep the post-transfer and post-tax (disposable) Gini coefficient fairly steady over time, it's clear in Shmueli's time series that the Israeli government had to up its involvement in terms of income transfers over the period.

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)0.007
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.167
Threshold uncertainty score0.416

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.003
Science and technology studies0.0160.009
Scholarly communication0.0050.006
Open science0.0070.002
Research integrity0.0500.041
Insufficient payload (model declined to judge)0.0090.002

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 head0.305
GPT teacher head0.510
Teacher spread0.205 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations3
Published2004
Admission routes2
Has abstractyes

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