Using the Theory of Protracted Social Conflict and Structural Violence to Unravel the Tigray-Ethiopian War
Bibliographic record
Abstract
Ethiopia, Africa's oldest independent nation and a key player in the Horn of Africa’s security, has undergone significant political and economic transformations. Despite emerging as a regional powerhouse, Ethiopia faces a complex ethnic landscape with diverse demographic groups. The historically influential Tigray region, plunged into a civil conflict in November 2020, and involved ethno-regional militias, the federal government, and Eritrean forces. This conflict stems from historical tensions, including the autocratic rule of Meles Zenawi and the dominance of the Tigray People’s Liberation Front (TPLF). Prime Minister Abiy Ahmed Ali, who heralded for fostering unity, took office in 2018 but faced escalating ethnic tensions. Postponed elections and federal interventions fueled discontent, leading to the outbreak of the Tigray War in November 2020. Abiy's military offensive, initially portrayed as a targeted operation, escalated into a brutal conflict, drawing international concern. Accusations of civilian mistreatment and Eritrean involvement were initially denied but later acknowledged by the Ethiopian government. The Tigray War underscores the challenges of achieving ethnic harmony and political stability in Ethiopia. This paper analyzes the Tigray War in Ethiopia, tracing its origins from the 19th century to the present, examining its consequences. The article specifically employs the Protracted Social Conflict and Structural Violence Theories to explain the conflict. Received: 12-01-2024 Revised: 01-07-2024
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".