The U.S.–Iranian Rivalry in Iraq: The Impact of Cross-Influence on the State and Political Forces During 2019
Bibliographic record
Abstract
The year 2019 marked a turning point in the strategic rivalry between the United States and Iran in Iraq. This study examines how the cross-cutting influence of both powers deeply impacted Iraq’s political landscape during this pivotal year, particularly in the context of the October protest movement. It analyzes the tools—political, military, and diplomatic—employed by both actors to maintain and expand their leverage through local allies, while also assessing how these dynamics shaped internal divisions and state fragility. Special attention is given to the reactions of Iraqi political forces, the shifting alignments within Shi’a blocs, the cautious positioning of Sunni and Kurdish actors, and the role of the religious establishment in Najaf. The assassination of Qassem Soleimani and Abu Mahdi al-Muhandis is also addressed as a catalyst for internal polarization and a challenge to Iraq’s sovereign decision-making. The study concludes that, in the absence of a cohesive national project, Iraq remained a contested arena for external rivalries, with its sovereignty and institutional integrity repeatedly undermined by the conflicting agendas of foreign powers and their domestic allies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".