Bibliographic record
Abstract
Central Eurasia has long been an area that occupies utmost geostrategic importance inthe international system. Scholars throughout the 20th century identified Central Eurasia as the singlemost pivotal area for powerful states to gain influence and control. Their theories were based upon the fact that the region contained vast natural resources, a large population, high economic potential, and was geographically situated in a location strategically important for all world powers. As aresult, Central Eurasia’s importance in international affairs influenced geostrategic thinking during the inter-war years into WWII, the Cold War, and the post-Cold War era. Yet the shift in power that has occurred globally in recent years has caused scholars to signal the emergence of a new multipolar world. Some scholars have additionally hypothesized that there will be new geostrategic pivot states and regions located outside of Central Eurasia as a result. This study uses both historical and contemporary literature from the field of geopolitics to construct a list of potential pivots in the current international system. It then compares potential new pivot areas to the traditional Central Eurasian region using the variables listed above. The study finds that there are in fact comparable geostrategic pivots located outside of the Central Eurasian region in the contemporary international system. The implications of these findings are then discussed in the context of geostrategy and international security.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".