Dynamics or Dilemma: Assessing the Innovation Systems of Three Satellite Platform Regions (Singapore, Dublin and Penang)
Bibliographic record
Abstract
This study attempts to put forward a quantitative assessment via patent-based indexes to frame the innovation dynamics of three highly acknowledged Satellite Platform regions – Singapore, Dublin and Penang. A Satellite Platform is generally viewed as a comparatively less sticky region hosting the operations of many different uncooperative multinationals. They faced a common dilemma, namely non-committal of MNCs in defining a local structure to generate knowledge and innovation. Nonetheless, we observed diverse intervention from different local governments to pivot away from the dilemma and compensate for the lack of patient capital from multinational firms. Divergent paths in terms of inventiveness were observed. Singapore stands out as a region obtaining indigenous patenting capabilities – achieving higher localization, de-concentration, diversification and university-industry linkage indexes. On the other hand, Dublin emerged to derive an exploitative patenting route – witnessing higher science-based linkage indexes. Meanwhile, Penang – as a region that has been focusing on upskilling its blue-collar population – is relatively behind in performance for almost all patenting indexes compared to the other two. The framing and findings of this paper are found instrumental in theorizing the divergence of interventions for knowledge-based economic development.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".