The Motivations behind China's Government-Initiated Industrial Investments Overseas
Bibliographic record
Abstract
Over twenty years' openness has made mainland China (PRC) (hereafter called China) one of the world's major destinations for foreign investment!. Indeed, by the mid-1990s, China became the world's second largest host nation to foreign direct investment (FDI).2 Foreign-funded enterprises have played a catalytic role in the process of a market-based economy, contributing about half of China's foreign trade since the mid-1990s.3 By 1999, China held over US$15 billion in foreign exchange reserves, which was the second largest in the world. These statistics, however, showjust one side of China's open door policy. High levels of inward FDI have over-shadowed increasing levels of outward investment, which is the subject of this paper.4 Since the late 1980s, the Chinese government has not simply put its effort into exporting made-in-China products to earn foreign currency or into encouraging foreign inward capital. In fact, it has actively encouraged its manufacturers to invest overseas, and has deliberately and strategically organized Chinese transnational activities.5 Throughout the last
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".