Policy Trends of Major Overseas Countries in the US-China Technological Supremacy Competition and Korea's Plan to Build a Stable Global Supply Chain
Bibliographic record
Abstract
The development of high technology has even changed the traditional concept of security. As economic issues are included in the traditional concept of security, it has come to mean that securing competitiveness in advanced technology will take over economic security hegemony. Accordingly, the competition for hegemony between the United States and China is expanding from a trade war to a technology war and further to an all-out war over the legitimacy of values and systems. This competition for technological hegemony between the United States and China has a direct impact on Korea as well. Under these circumstances, this paper carefully examines the technology hegemony policies of the United States and China in Chapter Ⅱ, and reviews the response policies of major advanced countries such as the EU, Japan, and Canada among resource rich countries in Chapter Ⅲ. Then it derives implications for Korea to build a stable global supply chain in semiconductors, electric vehicles, batteries, and materials (including critical minerals) in Chapter Ⅳ, and finally presents countermeasures to the implications derived from the review and analysis above in Chapter Ⅴ.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".