Approaches to Transparency in Arms Control and Verification - A Canadian View of Chinese Perspectives
Bibliographic record
Abstract
China and Canada represent nearly two opposite ends of a continuum starting with near-total secrecy and ending at near-total transparency in matters of state. Canada advocates transparency, and China opposes it - or at least is extremely cautious in cooperating unless some vital interests are served. China is increasingly drawn into processes of transparency and verification, but the prevailing view is that transparency is only possible between states of equal power; otherwise, the weaker are at a disadvantage in revealing their weakness. It can be argued that Chinese reluctance to increase transparency only fuels suspicions about its intentions. China regards secrecy to be an essential element of statecraft, and will not modify it simply to mollify critics, or to surrender it for access to more sophisticated Western technology. Greater availability of timely and accurate information can have positive benefits for international peace and security, but it is the imbalance between democratic and authoritarian habits of information control that differing notions of transparency emerge. Transparency is not merely a technical problem, but one which derives from the nature of the political system.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.018 | 0.041 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".