Bibliographic record
Abstract
The level of change brought by science and technology in the 20th century has been unprecedented. Innovation across almost all sectors created a tremendous amount of prosperity, with states competing to get a share. The 21st century continues on this trajectory, albeit with an increased focus on innovation: as opportunities for growth in labour intensive industries decrease, innovation becomes even more central for creating economic development and security. At the same time, cutting-edge technologies have high risk, cost, and uncertainty, making the decision-making calculus for governments more complex. What is the role of the state in facilitating and driving the growth of cutting-edge technologies in the 21st century? The dissertation explores this key question, with a focus on biotech and specifically genomics. The story of the Human Genome Project demonstrates why and how a highly collaborative and decentralized culture was established internationally, while competition was fierce. The Chinese firm BGI and American Illumina are case studies that demonstrate how and why firms can collaborate and compete simultaneously. China and the USA, the two frontrunners in this field, are used as case studies, with a comparison of their developmental states from the 1940s until today revealing several surprising similarities. To approach the core research question, two frameworks are developed. The first compares three main approaches in literature as it relates to innovation and the state: liberalism, national innovation systems, and the developmental state. The argument is that the developmental state provides a stronger foundation for understanding how states facilitate and drive the growth of cutting-edge innovation. The second framework concerns the three dynamics that states need to manage and leverage to reap the benefits of cutting-edge innovation. Based on 32 interviews with policy and science experts in multiple countries, three dynamics are identified as key: collaboration and competition, centralization and decentralization, and techno-nationalism and techno-globalism. These three dynamics are often seen as opposites in a zero-sum game when, instead, they coexist and shape government decisions. As the cases of the USA and China demonstrate, developmental states have successfully leveraged these dynamics to benefit domestically. The dissertation makes several contributions, both theoretically and empirically. The theoretical contributions are around the relationship between globalization and the state, the role of developmental states in driving the growth of cutting-edge technologies, and the three dynamics identified key in this pursuit. In addition, the dissertation also contributes empirical knowledge through the comparative case studies of China and the USA, where several similarities between these two otherwise seemingly polar opposite cases emerge.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".