Crisis and Adaptation in East Asian Innovation Systems: The Case of the Semiconductor Industry in Taiwan and South Korea
Bibliographic record
Abstract
In recent decades, both South Korea and Taiwan have made remarkable leaps in the development and production of semiconductors-the core element in burgeoning global telecommunications, computer, and computer equipment industries. Although many aspects of their sectoral industrial strategies have differed, both countries are now moving aggressively to adapt their semiconductor industries to turbulent global markets. In the wake of the severe regional financial crisis that began in 1997, this case study compares and contrasts continuing processes of adaptation among primary semiconductor manufacturers in the two countries. The crisis had observable effects, especially in Korea, but it was not deep enough to force fundamental adjustments in either country. In the early days of the industry in both places, a sense of vulnerability-the need to come from behind-gave rise to quite different corporate structures and attendant strategies. Remarkable differences persist in the ways in which the South Korean and Taiwanese semiconductor firms are seeking new advantages in rapidly changing regional and global markets. Strategic change and structural continuity mark the attempt of two relatively small countries to stay competitive in a key industry.
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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 | 0.002 |
| 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 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".