Bibliographic record
Abstract
The future of economic growth is projected by solving differential equations describing growth rate.Analysis was carried out for 12 countries representing the leading economies responsible for around 70% of the global economic output.Out of all these countries, the most secure and stable economic growth is in Japan, Germany and France.In contrast, economic growth in China, India and Brazil is strongly insecure and potentially leading to the economic collapse.Economic growth in the United States, United Kingdom, Canada and Australia is on the border line.It also might become unsustainable.Economic growth in the remaining two countries, Italy and Russian Federation, is unpredictable.As for the preventive measures, for Japan, Germany and France, growth rate should be, if possible, maintained at a small value below 1%.Economic growth in these countries is described by logistic trajectories.Their asymptotic approach to a maximum value is hard to control but the growth rate should not be allowed to be substantially increased.For China, India and Brazil, growth rate should be now decreasing sufficiently fast to avoid the potential economic collapse.For the USA, UK, Canada and Australia, it would be also advisable to decrease their growth rate faster than in the recent years.For two countries, Italy and Russian Federation, it is essential to stabilise, if possible, their economic growth.
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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 | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".