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A collaborative working group, under the auspices of Rice University's Baker Institute Center for the U.S. and Mexico, has conducted an in-depth analysis of the alliance structures within Mexican organized crime. The Baker Institute released a commentary titled "Unraveling Covert Networks: Analysis of Mexican Cartel Alliances" and summarized two research papers examining the alliance structure within Mexican organized crime.
The first paper, titled "Mexico’s 2021 Dark Network Alliance Structure: An Exploratory Social Network Analysis of Lantia Consultores' Illicit Network Alliance and Subgroup Data," analyzed cartel alliances in Mexico using data from Lantia Consultores. The study confirmed a bipolar structure in Mexico, with the Sinaloa Cartel and the Cártel de Jalisco Nueva Generación (CJNG) being the two central players. The Sinaloa Cartel and CJNG exhibited distinct approaches in organizing their alliances, with the Sinaloa Cartel adopting a more traditional approach and the CJNG pursuing a territorial and hierarchical organization. This diversity in alliance structures was attributed to a combination of factors, such as the Sinaloa Cartel's need to counter the CJNG's expansion.
The second paper, titled "The Use of Similarity-Based Algorithms to Predict Links in Mexican Criminal Networks," explored the use of predictive algorithms to forecast potential alliances within Mexico's criminal organizations. The paper highlighted the key themes of predictive algorithms in criminal networks, visualization of cartel alliance networks, capturing different forms of social capital, surmising existing relationships, challenges of studying dark networks, and practical applications. The study revealed that many of the predicted relationships likely already existed within criminal networks, suggesting that predictive algorithms can uncover both future potential alliances and previously undisclosed relationships. The paper also emphasized the practical applications of predictive algorithms in identifying and targeting criminal networks.
The research conducted by the collaborative working group provides valuable insights into the alliance structures within Mexican organized crime. The findings highlight the value of predictive algorithms in uncovering hidden connections within criminal networks and their potential to assist in law enforcement and security efforts. The analysis contends that by understanding the alliance structures and dynamics within Mexican organized crime, policymakers and law enforcement agencies can develop more effective strategies to combat criminal organizations.
