The Global Economic Paradox: An Indigenous Philosophical Perspective
Bibliographic record
Abstract
The world economic order is facing a paradox, as liberalist principles promoting international open trade and multilateral cooperation are challenged by realist policies prioritizing competition and security. Central to this paradox is the tension between cooperation and competition in the U.S.-China relationship. Previous studies have primarily taken the U.S. perspectives and emphasized political and economic drivers of countries’ approaches to the paradox. However, they have neglected China’s viewpoints and the fundamental differences in the two nations’ philosophies regarding how to address paradoxes. These philosophies fundamentally influence their respective geopolitical decisions and, consequently, the world economic order. To address these gaps, we draw upon indigenous philosophical theories from both the West and the East to analyze the U.S. and China’s approaches to the cooperation versus competition paradox. Our analyses indicate that the world economy will likely be more complex than envisioned by prior studies, due to China’s situational approaches to adapt to geo-economic contingencies. We have also developed an analytical framework to examine the impact of the paradox at various levels of granularity—countries, MNEs, teams, and individuals—offering insights into geopolitical, geo-economic, and geo-cultural strategies for navigating the economic paradigm shift at these respective levels.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.023 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".