MétaCan
Menu
Back to cohort
Record W4401479883 · doi:10.1111/ajes.12600

Political democracy, economy, and cancer risk: A comparative analysis of 170 countries

2024· article· en· W4401479883 on OpenAlexaff
Andrew C. Patterson

Bibliographic record

VenueAmerican Journal of Economics and Sociology · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsMacEwan University
Fundersnot available
KeywordsDemocracyPoliticsPolitical sciencePolitical economyDevelopment economicsEconomicsLaw

Abstract

fetched live from OpenAlex

Abstract Much literature acknowledges the importance of political systems for population health. People living in democratic countries tend to have higher life expectancies and lower rates of infant mortality compared to those in other countries. However, few quantitative comparative studies explore the political origins of chronic disease. To address this gap, this study examines the impact of political democracy on cancer risk. Using data from the Global Cancer Observatory (GLOBOCAN), regression models test differences in age‐adjusted cancer rates across 170 countries. Counter to study hypotheses, overall incidence of cancer is not any lower in democratic countries. This is evident even when removing the confounding influence of economic and several other factors. However, among children and adolescents, cancer mortality rates and leukemia incidence are exceptions since these are lower in democratic countries in some models. Results otherwise do not support the view that political regime type alone prevents cancer. Overall findings appear robust to threats of endogeneity, higher average age in developed countries, comparative differences in the ability to diagnose cases, and several other threats. The broader literature indicates that democratic countries have better health overall. However, findings are that democratic countries have higher cancer incidence on average, which is likely due to having higher levels of economic prosperity compared to more autocratic countries. Economic policy is likely to be an important consideration for preventing cancer. Longitudinal analysis was not possible for these data, which is reason for caution when interpreting these findings.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.744
Threshold uncertainty score0.924

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.027
GPT teacher head0.327
Teacher spread0.301 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Economics and SociologySame topicGlobal Public Health Policies and EpidemiologyFrench-language works237,207