Shifting the Balance of Global Economic Power: the Sinosphere in Ascension Towards Dominance
Bibliographic record
Abstract
The Sinosphere is in ascension towards global economic dominance on both total and per capita bases, marking a fundamental shift in the balance of global economic and military power that is taking place absent any robust structural democratic and human rights reforms in this region. In contrast to comparisons during the 1980s of Japan potentially overtaking the United States as the world's largest economy, both purchasing power parity (PPP) and current United States dollar GDP metrics consistently project that China's gross domestic product (GDP) will exceed that of the United States sometime between 2015 and 2020. The Sinosphere's GDP-PPP passed that of The Commonwealth (including India) in 2011, The Commonwealth (excluding India) in 2005, the Francosphere member states in 2003, the Francosphere member and observer states in 2009 - subsequently widening the gap in all cases - and is predicted to surpass that of the Anglosphere by the early 2020s. China's military spending now exceeds that of all other nations bordering the East and South China Seas combined and the gap is widening rapidly. At current rates of increase, China's military expenditures may surpass those of the United States within the next decade. On a per capita basis, China's GDP-PPP is expected to overtake that of the United States and Canada by the early to mid-2030s, whereas Russia and the EU are projected to be surpassed by China in per capita GDP-PPP by the late 2020s.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.000 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".