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Record W2121413986 · doi:10.1093/ije/dyi224

Impact of economic crisis on cause-specific mortality in South Korea

2005· article· en· W2121413986 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.

Bibliographic record

VenueInternational Journal of Epidemiology · 2005
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsMcGill University
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsDevelopment economicsGeographyEnvironmental healthSocioeconomicsMedicineEconomics

Abstract

fetched live from OpenAlex

BACKGROUND: Economic changes can be powerful determinants of health. In the late 1990s, South Korea experienced a steep economic decline. This study examines whether the massive economic changes affected trends in all-cause and cause-specific mortality in South Korea. METHOD: Mid-year population estimates of 5 year age groups (denominators) and death certificate data (numerators) from the National Statistical Office of Korea were used to compute cause-specific age-standardized mortality rates before and after the economic crisis. RESULTS: All-cause mortality continued to decrease in both sexes and all age groups during the crisis. Cerebrovascular accidents, stomach cancer, and liver disease contributed most to this decline. A remarkable decrease in transport accident mortality rates was also observed. The most salient increase in mortality was suicidal death. Mortality from homicide, pneumonia, and alcohol dependence increased during the economic crisis, but these accounted for a small proportion of total mortality. CONCLUSIONS: Short-term mortality effects of the South Korean economic crisis were relatively small. It appears that any short-term effects of the economic decline were overwhelmed by the momentum of large declines in causes of death such as stroke, stomach cancer, and liver disease, which are probably related to exposures with much longer aetiological periods. However, this study focused on rather immediate mortality effects and follow-up studies are needed to elucidate any longer-term health effects of the South Korean economic crisis.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.025
Threshold uncertainty score0.942

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.227
GPT teacher head0.529
Teacher spread0.302 · 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