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Record W2416956333 · doi:10.25336/p6vp5j

Epidemiologic Transition in Australia – the last hundred years

2016· article· en· W2416956333 on OpenAlexvenueno aff
Heather Booth

Bibliographic record

VenueCanadian Studies in Population · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicInsurance, Mortality, Demography, Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsLife expectancyDemographyEpidemiological transitionDemographic transitionMortality ratePandemicCause of deathGerontologyMedicineCoronavirus disease 2019 (COVID-19)PopulationDiseaseFertilitySociologyPathology

Abstract

fetched live from OpenAlex

Mortality change in Australia since 1907 is analysed in the light of Epidemiologic Transition theory. Trends in life expectancy by sex and the sex difference, are examined at ages 0, 50, 65 and 85 years. Trends in mortality by major cause of death are broadly related to the stages of the Epidemiologic Transition, and a decomposition of changes in life expectancy by age and cause of death is used to further elaborate on the progression through three stages, the Age of Receding Pandemics, the Age of Degenerative and Man-Made Diseases and the Age of Delayed Degenerative Diseases. A consideration of temporal changes in age patterns of mortality decline includes a focus on infant mortality, the accident hump and mortality at older ages. In the early decades of the twentieth century, Australia was a leader in the Epidemiologic Transition, but had lost this advantage by 1950. Differentials by state/territory, indigeneity and socio-economic factors identify the leaders and laggards in the transition.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.120
GPT teacher head0.390
Teacher spread0.270 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

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