Bibliographic record
Abstract
The increasing importance of emerging markets has broad implications for the world’s allocation of consumer goods, investments, and environmental resources.In fact, the U.S. and China are the dominant leaders in the top 10 largest economies. The others include2019 Japan at $5.2 trillion and an estimated $5.4 trillion, Germany at $4.2 trillion and an estimated $4.5 trillion, The United Kingdom at $3 trillion and an estimated $3.2 trillion, India at $2.9 trillion and an estimated $3.3 trillion, France at $2.9 trillion and an estimated $3.1 trillion, Italy at $2.2 trillion and an estimated $2.3 trillion, Brazil at $2.1 trillion and an estimated $2.2 trillion, Canada at $1.8 trillion in 2019 and an estimated $1.9 trillion. The rising importance of emerging market economies in 2020 will have broad implications for the world’s allocation of consumer goods, investments, and environmental resources. India is at a tipping point, both in terms of economic growth and in the human development of its more than one billion citizens. The country is the sixth largest economy in the world, with a GDP of $2.6 trillion in 2017.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".