Negative impact of democracy on GDP annual growth rate in 2001-2019 and 2020 and mortality rate due to COVID-19 in 2020
Bibliographic record
Abstract
The study examines the negative impact of democracy on the GDP annual growth rate in 2001-2019 and 2020 and the morality rate due to COVID-19 in 2020. Whether democracy has deteriorated in the first 20 years of the 21st century in terms of annual gross domestic product (GDP) growth rate and the mortality rate due to COVID-19 was investigated. Using various statistical data and by applying instrumental variable analysis with three instrumental variables. The negative correlation between democratic maturity and GDP growth rate and positive one between democratic maturity and COVID-19 mortality rate in 2020 were found. The same relationships were observed even when the data of China and the United States or those of China and G7 countries were deleted and even when only G20 countries were considered, indicating that this is a common phenomenon in the world. We also proposed that these relationships were casual. The decline in the growth of capital formation, the accompanying decline in the growth of value added in all three sectors, and the decline in the growth of international trade were suggested as the causes of democracy’s deterioration. Negative effects of democracy were also observed when GDP per capita growth rate was used, when democracy indicators proposed by different institutions were used, or when the Great Recession was considered. We confirmed the same negative effect of democracy by considering covariates and using the GDP growth rate in 2021, following the pandemic. This strengthened the conclusion that democracy in the first 20 years of the 21st century has deteriorated in terms of annual GDP growth rate and mortality rate due to COVID-19 in 2020.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".