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Record W2778391255 · doi:10.25336/p60g7g

Inequality in mortality decreases with age: Evidence from developing countries using census data

2017· article· en· W2778391255 on OpenAlexvenueno aff
Rubén Castro, Eduardo Fajnzylber, Andrés Fortunato

Bibliographic record

VenueCanadian Studies in Population · 2017
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsnot available
Fundersnot available
KeywordsMicrodata (statistics)Sierra leoneSocioeconomic statusDeveloping countryCensusDemographyGeographyInequalityPopulationSocioeconomicsEconomicsEconomic growthSociologyMathematics

Abstract

fetched live from OpenAlex

With some exceptions, studies consistently find that mortality rate ratios between the highest and lowest socioeconomic status (SES) groups are substantially larger among the young-age population, rather than the old one. This pattern is relevant for policy and research, but it has seldom been explored in populations of developing countries. In this study, eight samples in the Integrated Public Use Microdata Series (IPUMS) that contain mortality data (El Salvador 1992, Rwanda 2002, Senegal 2002, Sierra Leone 2004, Uganda 2002, Malawi 2008, Brazil 2010, and Zambia 2010) and information about household assets are analyzed, and, using SES of equal relative size, results in seven out of eight cases are the same as those in developed societies: ratios are larger among the young age group and among men. Therefore, the ratio of mortality by relative-SES also decreases with age in several developing ones.

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)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.709
GPT teacher head0.617
Teacher spread0.092 · 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 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

Citations2
Published2017
Admission routes1
Has abstractyes

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