Investigating the Military Intervention Project Dataset: Patterns in the United States' expanding use of military force from 1776 to 2019, from displays and threats of force to covert operations and actual war.
Purpose: For my final Advanced GIS project during fall 2023, I chose to explore the Military Intervention Project dataset from researchers at Tufts. I came across MIP through a Data is Plural newsletter, serendipitously after just listening to an investigatory podcast on the history of the U.S. CIA and former OSS agencies. With this newfound interest in the U.S.'s long history of covert operations and global conflict intervention, I realized that my knowledge of this topic was relatively lacking. With that, I decided to take the MIP researchers up on their mandate for other scholars to investigate and explore their work further.
Research Questions: According to this dataset, what has the scope of US intervention with other states looked like over its history as a nation? Where and against which states has the US intervened the most and the least? When and at what significant time periods has the US intervened the most and the least between 1776 to 2019? Why and in what manner has the US gotten involved in conflict with other states? Has this shifted over time and/or region?
Results: This was primarily an extensive exploratory data project where I highlighted different ways to visualize various combinations of variables from the dataset. Because the MIP data crucially did not include spatial data -- though it does use country codes from another Correlates of War (COW) dataset, which MIP built upon -- I individually geocoded each row of the data by matching those countries to ESRI polygons and latitude/longitude points of country capitals. I then transformed the data into a series of maps and visualizations in an ArcGIS StoryMap in order to demonstrate a broad base of mapping skills, including interactive and static maps, a map tour, and an interactive dashboard.
Major Takeaways Included: Identifying eras with the highest number of interventions (Post WWII and Cold War, Turn of the Century until 1917, Post 911 or Colonial/Civil), eras with the lowest number of interventions (WWI and II Years, 1990s/Post Cold War Years), and regions with the highest number of interventions (Latin America and the Caribbean, followed by Asia, which includes the Middle East). I was also able to visualize and identify regional shifts in focus in U.S. military interventions towards Asia (especially the Middle East) and Africa over time, particularly in the 1990s through the latter post 9-11 years. Longer-lasting interventions generally began between the Post Civil War/Turn of the Century and Post 9-11 periods, however, the highest frequency of individual interventions by start year is found during the Post WWII/Cold War Years. In terms of presidencies involved in interventions, I was able to show how the launch and long duration of the War in Afghanistan acts as an outlier relative to other interventions, skewing the data heavily towards George W. Bush's administration.
Methods: Data cleaning and manipulation (Python, Excel); Spatial Analysis (ArcGIS); Visualization, design & data storytelling (ArcGIS Online, Tableau). More on each step of the methodology can be found in the StoryMap below.
Skills: Data cleaning, Spatial data analysis, Exploratory data analysis, Data storytelling
Tools Used: Excel, GitHub, Python, Tableau, ArcGIS Pro and ArcGIS Online
For the full Jupyter notebooks with Python code for data cleaning and joining, visit my GitHub repository.
Learning Outcomes: Research, Communication, Technology, Critical Perspectives
Sources
Journal of Conflict Resolution (2023): "Introducing the Military Intervention Project: A New Dataset on US Military Interventions, 1776-2019." https://journals.sagepub.com/doi/10.1177/00220027221117546.
MIP Dataset, Center for Strategic Studies at Tufts, https://sites.tufts.edu/css/mip-research/mip-dataset/.