This document presents the methodological framework for analyzing the impact of targeted assassinations on Iranian nuclear scientists’ research output through bibliometric analysis.
| Metric | Value |
|---|---|
| Total Scientists | 17 |
| Time Span | 2007-2025 (18 years) |
| Event Types | Confirmed & suspected assassinations |
| Source | Table 7 |
Scope: All Iranian nuclear scientists who were assassinated with definitive confirmation or strong international consensus attributing responsibility to foreign government agents.
The initial dataset includes:
To ensure analyzable cases with sufficient data, we applied two key filters:
| Scientist | Year | Expertise | Institution |
|---|---|---|---|
| Ardeshir Hosseinpour | 2007 | Electromagnetism | Shiraz University |
| Masoud Ali-Mohammadi | 2010 | Quantum Physics | University of Tehran |
| Majid Shahriari | 2010 | Neutron Transport | Shahid Beheshti University |
| Fereydoon Abbasi-Davani | 2010 (survived) | Nuclear Physics | Shahid Beheshti University |
To identify the primary institutional home for each scientist:
Table 10 shows the distribution of 403 Iranian institutions in OpenAlex: - Ranges from 106,779 works (University of Tehran) to smaller institutions - Top 30 institutions account for majority of Iranian scientific output
| Institution | Scientist | Field | Total_Works | Note |
|---|---|---|---|---|
| Shiraz University | A. Hosseinpour | Electromagnetism | 35,722 | |
| University of Tehran | M. Ali-Mohammadi | Quantum Physics | 106,779 | |
| Shahid Beheshti University | M. Shahriari + F. Abbasi-Davani | Nuclear Physics | 35,830 | ⚠ ‘Double-Hit’ Scenario |
Unique “Double-Hit” Scenario: - Two scientists (Shahriari and Abbasi-Davani) targeted at same institution on same day (Nov 29, 2010) - Shahriari was killed; Abbasi-Davani survived - Creates conditions that might simultaneously amplify and attenuate disruption
How it works: - Each work assigned up to 3 topics by algorithm - Topics determined from: title, abstract, citations, journal name - Hierarchical structure: Topic → Subfield → Field → Domain - Accuracy: ~53% for top-1 prediction; ~73% for top-10
Result: Complete map of each scientist’s research domains
| Scientist | Unique Topics | Example Topics |
|---|---|---|
| A. Hosseinpour | 9 | Magnetic Properties of Ferrites, Electromagnetic wave absorption |
| M. Shahriari | 44 | Radiation Effects and Dosimetry, Nuclear Physics and Applications |
| M. Ali-Mohammadi | 46 | Black Holes and Theoretical Physics, Quantum Information |
| F. Abbasi-Davani | 109 | Particle accelerators, Gyrotron Research, Nuclear reactor physics |
Note: Lower topic counts (e.g., Hosseinpour’s 9) create greater variance and less precise model estimates. Larger portfolios (e.g., Abbasi-Davani’s 109) enable more robust statistical analysis.
For each case study, we defined which topic areas were “exposed” to assassination (treated) and which were not (control).
| Case | Institution | Treated | Definition | Treated_Works | Control_Works |
|---|---|---|---|---|---|
| Cases 1 & 2 | Shahid Beheshti University | Core Nuclear Physics Areas | INTERSECTION of Shahriari ∩ Abbasi topics | 1,240 | 33,750 |
| Case 3 | University of Tehran | Quantum Physics Areas | All Ali-Mohammadi topics | 3,450 | 100,834 |
| Case 4 | Shiraz University | Electromagnetism Physics Areas | All Hosseinpour topics | 217 | 34,807 |
Since two scientists were targeted at Shahid Beheshti on the same day, we used a stricter definition:
Summary (Table 5): All treated vs. control definitions established to enable within-institution comparisons that control for institutional variance.
| Element | Description |
|---|---|
| Unit of Analysis | Topic-Month-Year |
| Time Window | 10 years: 5 years pre + 5 years post assassination |
| Outcome Variable | Publication counts per topic-month-year |
| Model Type | Difference-in-Differences (Poisson regression) |
Two complementary approaches:
Model Specification:
\[Y_{it} = \beta_0 + \beta_1 \cdot Treatment_i + \beta_2 \cdot Post_t + \beta_3 \cdot (Treatment \times Post)_{it} + \varepsilon_{it}\]
Where: - \(Y_{it}\) = publication count for topic \(i\) at time \(t\) - \(Treatment_i\) = indicator for treated topic areas - \(Post_t\) = indicator for post-assassination period - \(\beta_3\) = differential effect of assassination on treated vs. control areas
Key Features: - Accounts for baseline growth rates across all fields - Isolates effect of external shock (assassination) - Can detect subtle slowdowns or plateaus, not just absolute decreases - Standard errors clustered by topic
| Step | Input | Output | Key_Decision |
|---|---|---|---|
|
All assassinations | 17 scientists | Historical records |
|
17 scientists | 4 scientists | Pre-2021 + ≥5 pubs |
|
4 scientists | 4-26 profiles | Manual verification |
|
Author profiles | 3 institutions | Frequency |
|
3 institutions | 9-109 topics each | OpenAlex algorithm |
|
Topic portfolios | Treated/Control | Intersection for SBU |
|
4 case studies | DiD estimates | 10-year windows |
Systematic Selection
Rigorous filters ensure analyzable cases with sufficient data for robust
analysis
Robust Disambiguation
Manual verification + expert validation prevents false matches and
ensures accuracy
Multiple Comparisons
Within and between-institution designs triangulate effects and control
for confounds
Controlled Analysis
Accounts for institutional factors, topic-specific trends, and baseline
growth rates
Transparent & Reproducible
All decisions documented, open-source data, replicable methods
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