Commercialization of Space Systems: Policy Implications for the United States
Bibliographic record
Abstract
Commercialization of Space Systems is a topic of growing interest in national security and thus has significant implications for the government and commercial sector. Commercial industry, international consortia, and many nations such as India, China, Prance, Russia and Canada are now challenging the U.S. government preeminence in space. As U.S. capabilities and national dependence on space continue to increase, the commercial developers are finding new applications to market to government as well as private sector organizations. This study investigated how the military and government currently use commercial space systems to determine if the current policies are coherent and consistent, how the policies are being implemented, problems with policy implementation, and defining elements for a new policy. The findings of this study are that the U.S. needs more directive, active policies; the U.S. government should establish a commercial space systems czar to provide clear guidance and strong national leadership; the United States needs to develop a National Space Security Strategy; the United States must invest in critical technologies to maintain its space technology industrial base; the U.S. government must become a better consumer of commercial space systems by establishing a budget process that simplifies the ability to use these products and services; the U.S. government should establish and comply with standards and procedures for commercial space systems interoperability, export control, and licensing; and, finally, the U.S. government must decentralize how it controls the use of commercial space systems.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".