เปรียบเทียบวิธี
ดูวิธีที่เลือกเทียบกันแบบเคียงข้าง แถวที่ต่างกันจะถูกเน้นไว้
| Militarized Interstate Dispute Analysis× | Alliance Network Analysis× | |
|---|---|---|
| สาขาวิชา | International Relations | International Relations |
| ตระกูล | Process / pipeline | Process / pipeline |
| ปีกำเนิด≠ | 1996 | 2012 |
| ผู้ริเริ่ม≠ | Daniel Jones, Stuart Bremer & J. David Singer (Correlates of War project) | Skyler Cranmer, Bruce Desmarais & Elizabeth Menninga |
| ประเภท≠ | Coding and statistical analysis of interstate militarized confrontations | Network analysis and inferential network modeling of interstate alliances |
| แหล่งต้นตำรับ≠ | Jones, D. M., Bremer, S. A., & Singer, J. D. (1996). Militarized interstate disputes, 1816–1992: Rationale, coding rules, and empirical patterns. Conflict Management and Peace Science, 15(2), 163–213. DOI ↗ | Cranmer, S. J., Desmarais, B. A., & Menninga, E. J. (2012). Complex dependencies in the alliance network. Conflict Management and Peace Science, 29(3), 279–313. DOI ↗ |
| ชื่อเรียกอื่น | MID Analysis, Militarized Dispute Coding, Correlates of War Dispute Analysis, Dyadic Conflict Onset Analysis | International Alliance Networks, Alliance Portfolio Network Analysis, Network Models of Alliance Formation, Interstate Alliance Graph Analysis |
| ที่เกี่ยวข้อง | 3 | 3 |
| สรุป≠ | Militarized interstate dispute (MID) analysis is the coding and quantitative study of confrontations in which one state threatens, displays, or uses military force against another. Built on the Correlates of War project's MID dataset and the coding rules codified by Jones, Bremer, and Singer (1996), it provides the standard observational measure of interstate conflict short of and including war, structured as dyad-years so that the onset, escalation, and outcomes of disputes can be modeled statistically across two centuries of the international system. | Alliance network analysis studies international alliances as a graph of states linked by formal security commitments, and models how that network forms and evolves. Rather than treating each alliance dyad as independent, it uses network science and inferential models such as the exponential random graph model (ERGM) — applied to alliance data by Cranmer, Desmarais, and Menninga (2012) — to capture the complex dependencies, such as a state's tendency to ally with its allies' allies, that ordinary dyadic regression assumes away. |
| ScholarGateชุดข้อมูล ↗ |
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