Ethnic Divisions and the Onset of Civil Wars in Syria
Bibliographic record
Abstract
While most civil wars seem to have an economic basis, they are generally pushed by political, ethnic, and religious differences. This paper attempts to identify the drivers of the Syrian civil war of 2011 by investigating the role of ethnic divisions in starting a conflict. We integrate a variety of variables such as excluded population, power-sharing, anocracy, ethnic groups in addition to a number of economic factors. The main results indicate that ethnicity does not seem to be a very important factor in starting both the civil and ethnic conflict in Syria, but it shows that the lack of power-sharing to be the most significant factor. Therefore, where power in Syria was not inclusive and shared among different demographic segments, such as religious or urban groups, it created upheavals between different groups, as some groups disidentify with the state, paving the way to causing the conflict. Economic factors also provide an explanation of the onset of conflicts in Syria. The paper offers detailed policy suggestions that could serve as a recovery mechanism for the Syrian crisis and a preventive measurement for its reoccurrence.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".