Study of Factors Affecting Saudi-Iranian Relations and Conflicts and Their Resulting Behavior Pattern
Bibliographic record
Abstract
Relations between Tehran and Riyadh as two key players and two regional powers are of great importance. Special place of the two countries has caused relations between them to be very important in the formation of regional order in the Persian Gulf, the Middle East and Mediterranean area. Different behavior patterns in their relationship have taken place from the beginning of the relationship till now. After domestic, regional and international developments in 1999, Tehran and Riyadh went from divergence to the détente, coexistence and cooperation during the presidency of Hashemi Rafsanjani and Mohammad Khatami. However, since 2005 these two great neighboring countries again entered the competition, tensions and divergences. In this descriptive study, by using library method and reviewing online available resources conducted on Saudi-Iranian relations, our purpose is to investigate what were the effective factors in shaping the relations and conflicts between Iran and Saudi Arabia before the time Saudi Arabia cut diplomatic relations with Iran over the storming of the Saudi embassy in Tehran, and what behavior pattern these factors led to? According to results we found out that identical, geopolitical, and structural factors were the determinant factors in creating relations and conflicts between the two countries. Identity of Iran's political system is referred to Iranian-Islamic identity, while Saudi Arabia has Arabic-Islamic identity. Their geopolitical distinctions are related to Shiite and Sunni disciplines, and in terms of structure, rapprochement with U.S. and distribution of power in the Persian Gulf region are the most important indicators. These factors formed a “competitive conflict” behavior pattern among them.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".