Transatlantic Environment and Energy Politics: Comparative and International Perspectives – Edited by Miranda A. Schreurs, Henrik Selin, and Stacy D. VanDeveer
Bibliographic record
Abstract
tance of national security imperatives in shaping S&T initiatives.One important episode was in 1965 following the PRC's detonation of its first atomic bomb.Greene does devote a few pages to examining the event, which she says is a turning point in the KMT's approach to S&T development, especially the emergence of a coordinated state effort to conduct nuclear-related S&T work.But there is only passing mention of the Chungshan Institute of S&T, one of the ROC's premier R&D facilities belonging to the Defense Ministry, and a major source of technological and industrial innovation in an otherwise barren landscape.Another surprising weakness is that the study ends in the early 1980s when Taiwan's S&T efforts begin to assume growing momentum and success.Although Greene does provide a concise summary of Taiwan's technological achievements in the 1980s and 1990s in the concluding chapter, it is an anticlimax compared with the careful and detailed examination in the preceding chapters of the previous 50 years of KMT approaches to S&T development.In the concluding chapter, Greene compares Taiwan's experience with the PRC's approach to S&T development in the post-1978 era.She declares that the PRC authorities are "following a very similar approach to what we have seen in the ROC" (p.163), pointing to the emphasis on science planning, science education, and state and private sector coordination of R&D.While Greene rightly points out that a scientific renaissance is currently under way in the PRC, she argues with little conviction that policy makers in Beijing had much to learn from their Taiwanese counterparts.In fact, the PRC has looked to the experiences of Japan, South Korea, Europe, and the United States for more relevant insights than Taiwan.This is because the huge size and organizational structure of the Chinese economy and its S&T establishment is very different from its much smaller Taiwanese counterpart.While Taiwan may have some useful lessons in S&T development to offer, especially its horizontal linkages with the global technology order, they are likely to be of limited value for the PRC.Despite these limitations, this book overall helps to provide new insights into understanding the critical factors required for latecomer developmental states to successfully utilize S&T policy in their modernization efforts.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.006 |
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".