Export Controls: Observations on Selected Countries' Systems and Proposed Treaties
Bibliographic record
Abstract
A letter report issued by the Government Accountability Office with an abstract that begins "The U.S. government annually controls billions of dollars worth of U.S. arms and dual-use items exported to its allies and partners through a system of laws, regulations, and processes. Weaknesses in this system led GAO in 2007 to include export controls as part of a high-risk area and called for a reexamination, including evaluating alternative approaches. Increasing international collaboration on defense programs also makes it important to understand how other countries control exports. Proposed treaties would change the process for the export or transfer of certain U.S. arms to the United Kingdom and Australia. Based on a request to review allies' export control systems and the proposed treaties, this report (1) identifies how selected allies' systems differ from the U.S. system, and (2) assesses how the proposed treaties will change controls on arms exports. To conduct its work, GAO selected six countries--Australia, Canada, France, Germany, Japan, and the United Kingdom--based on factors such as whether they were major destinations for U.S. goods or significant arms exporters; conducted site visits in four countries; analyzed agency documentation on the foreign and U.S. systems and treaty related documents; and interviewed officials."
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 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".