China and the United States in Civil-Commercial Air and Space: Specialist cultures and international relations in high-technology sectors
Bibliographic record
Abstract
Why are some high-technology sectors trans-nationally integrated while others are sites of interstate competition? This dissertation explores this question through a comparison of China-U.S. relations in two strategic, high-technology sectors: civil-commercial aircraft manufacture and civil-commercial spacecraft manufacture. Between 1989 and 2009, China-U.S. relations took strikingly different trajectories in these two sectors. In the aircraft sector, the two countries’ industries traded and integrated their activities and their civil agencies cooperated. By contrast, in the space sector, their industries did not trade or integrate, their civil agencies did not cooperate, and the two countries engaged in a form of technological competition. The divergent trajectories taken by China-United States relations in these two sectors are puzzling because both sectors present similar incentives and disincentives for both transnational integration and interstate competition. Theories of international relations do not fully explain this sectoral variation. This research indicates that this variation is traceable to underlying differences in how specialists in each sector, including technical and policy experts, implicitly reason about and represent technologies in general. In both countries, the air and space specialist communities each hold distinct understandings of the relationship between humans and technology. Performing representational practices that reflect these distinct assumptions, aeronautic and space specialists discursively constitute each sector and its technologies as distinct objects of policy, requiring different forms of state action. In air, these include policies adopted by both countries to enhance bilateral trade, industrial partnership, and technical cooperation. In space, these include measures to inhibit bilateral trade and cooperation while preparing for a coming bilateral confrontation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".