Catching-up national innovations systems (NIS) in China and post-catching-up NIS in Korea and Taiwan: verifying the detour hypothesis and policy implications
Bibliographic record
Abstract
This study addresses the relationship between national innovation systems (NIS) and economic catch-up by latecomer economies, such as China, South Korea, and Taiwan. Contemporary China is found to also specialize in short cycle technologies, similar to Korea or Taiwan in the mid-1980s and 1990s, featuring opposite attributes from mature NIS. By contrast, Korea and Taiwan are moving away from short-cycle technologies into long cycle technologies-based sectors, and their NIS are becoming similar to those of advanced or mature NIS. Thus, this study verifies the so-called ‘detour’ hypothesis that a successful catching-up economy can follow a technological detour of first specializing in short cycle sectors and only later turning into more challenging or long cycle technology-based sectors. In addition, the linkage from such detour to economic growth performance is verified, confirming a positive relationship between moving into short cycle technologies and economic growth in China, and between going into long cycle technologies and economic growth in Korea and Taiwan for the post-catch-up stages or since the 2000s.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".