GEOPOLITICS AT THE WORLD'S PIVOT EXPLORING CENTRAL ASIA'S SECURITY CHALLENGES
Bibliographic record
Abstract
Central Asia’s five countries — the Republic of Kazakhstan, the Kyrgyz Republic, the Republic of Tajikistan, Turkmenistan, and the Republic of Uzbekistan — hold considerable geopolitical significance for global security. The Central Asian countries share borders with Russia, China, Iran and Afghanistan, and are rich in natural resources, including oil, gas, uranium, coal, gold, copper, aluminum and hydroelectric power. Central Asia’s unique geopolitical placement, valuable resources and the legacy left by the former Soviet Union have resulted in a host of complicated security challenges, including water security and transboundary water management; energy security; terrorism; narco-trafficking; migration and human trafficking; nuclear security; and border management. The issues transcend national boundaries and lend themselves to multilateral approaches. To date, regional cooperation has been piecemeal and stymied by the fact that many issues are inherently tangled with the others. Central Asia’s security challenges closely align with Canada’s national security and foreign policy priorities, as well as with Canada’s trade and investment interests, and thus suggest natural pathways for Canada to expand engagement in the region.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".