Regional Security Arrangements and Foreign Policy of the Islamic Republic of Iran Case Study: Shanghai Cooperation Organization
Bibliographic record
Abstract
In international system scene, interests and strategies for ensuring these interests are among key strategies of powerful countries. Therefore, super powers, organize security in different geographical areas through competition in order to challenge competitors and threaten them. Shanghai cooperation organization (SCO), as the most important security measure, has been developed by influence of competitive atmosphere in international system by help of Russian, China and some other important regional allies in response to transatlantic actions. As a result, this security measure could control peripheral threats in the region. In this regard, Islamic Republic of Iran, has considered emergence of this regional security measure as a serious threat for its national and regional interests and has acted to suppress them in the framework of its defense diplomacy. Considering this, authors try to answer this question that how Shanghai cooperation organization as security measure can influence the foreign policy behavior of Islamic Republic of Iran? By studying and analyzing how and why Shanghai cooperation organization (SOC) around Islamic Republic of Iran and determining foreign policy of super powers in establishing this organization, its effect on the foreign policy behavior of Islamic Republic of Iran is considered.
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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 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".