The goal of this project is to a) describe the dynamics of violence in Mexico; b) the evolution of criminal groups, their dynamics across time, and map their territorial presence; and c) identify the way organize criminal groups (OCGs) “rule” the territories they control, including how they relate state officials and the communities where they operate.
To do so, PovGov is using text analysis (on different sources, printed and digital), GIS, Neural Networks, and several data processing techniques.
Mexicans and Central Americans are estimated to account for roughly 7.6 million (around 67%) of the unauthorized immigrants in the United States. Many of them migrate to escape violence. This kind of migration brings a myriad of risks as migrants face dangerous environments as well as predation by organized crime groups and rent-seeking government officials. Upon arriving in the United States, they are at risk of deportation at any moment, thus exposing them to the risk of being returned to the environment that sent them abroad in the first place. Additionally, deportations impose stresses on families, inflict childhood traumas, and may themselves involve human rights violations.
We seek to explore the ways in which legally sponsored temporary migration can serve as an alternate approach to addressing the social problems that often motivate this form of immigration. We are particularly interested in understanding the effects of large increases in family monthly incomes (an average of US $3,000, which places the household in the top decile of the Mexican income distribution) on household poverty, human capital, health, and other family-level outcomes. We also want to understand how this large increase in household income can be mobilized to create local public goods and increases in political accountability. Finally, we are particularly interested in understanding ways to insulate these resources from predation by organized criminal groups.
As of this year, the United States operates one of the largest immigration court systems in the world, with an estimated 830,000 cases pending in 68 courthouses across the country. As immigration court judges are often the deciding actors separating a foreign national's admission to or removal from the U.S., their decisions are frequently matters of life or death. Against the backdrop of a rapidly changing immigration landscape, Povgov seeks to better understand 1) the legal and non-legal considerations that enter into judicial decision-making, and 2) the long-term consequences of immigration court decisions on migrants’ well-being and home countries.
Disparities in adjudicative outcomes across the U.S. immigration courts are well-documented—while some judges exhibit asylum grant rates of over 90 percent, others have grant rates in the single digits. These variations have led some scholars to conclude that asylum and removal outcomes are less dependent on the legal facts of the case in question and more on the identity of the presiding immigration judge. While present research has extensively documented these discrepancies across time and space, they provide little insight intowhy such disparities exist in the first place. To shed light on this question, we conduct a sentiment analysis of immigration court transcripts to determine whether recurrent themes and the manner in which they are considered in the courtroom setting vary according to judge-specific characteristics. This analysis will be combined with additional statistical approaches—such as predictive modeling and machine learning—to address other relevant considerations, including whether judges’ language usage during hearings can predict case outcomes. Given how powerful nationality is as a determinant of asylum and removal decisions, we also examine how immigration court outcomes can affect migrants’ home countries and long-term well-being.
Despite the epidemiological transition, which has shifted the burden of public health in Mexico from infectious to chronic diseases, conditions of poverty, insecurity and a failure to establish a more effective governance in the fragmented and decentralized health systems have meant that many preventable deaths in Mexico continue occurring. This challenge has only been exacerbated by the COVID-19 crisis, which will result in a significant death toll and have long lasting effects on the health of all Mexicans. Inequality in access to care, failures in supplies, facility and equipment maintenance, and nurse and doctor absenteeism, as well as insufficient funding and other inefficiencies in clinics and hospitals within the public health care systems have resulted in the premature loss of life.
The goal of this project is to understand the burden of disease and the governance conditions that may enable the public health system in Mexico to produce more equitable outcomes and save lives. The study builds upon the analysis of more than ten million death certificates from 1998 to 2018, coupled with the analysis of the institutional response to the COVID-19 crisis by the various public health providers in Mexico. By better understanding the disease profiles and the public health responses and governance we may empower patients, health providers and policymakers to adjust their interventions to better serve the majority of Mexicans, and target specific attention to those living in indigenous communities and under conditions of extreme poverty.
How can gender inequitable attitudes, norms and behaviors that lead to gender-based violence be altered? We seek to answer this question through an intervention targeting Mexican middle- and high school students in one of the most violent municipalities in the Greater Mexico City Metropolitan Area.
Based on Cognitive Behavioral Therapy, the intervention provides students with tools of emotional regulation, identification of biases and stereotypes, and prosocial behavioral strategies that can diffuse otherwise violent attitudes and behaviors. The intervention also explores the potential of well connected students acting as social vehicles for positive changes to gender inequitable norms at the school level.
Why have institutional anti-corruption reforms largely failed in Latin America? To answer this question, we propose a research agenda that identifies micro-dynamics linking institutional anti-corruption efforts with populism and citizen corruption perceptions, attitudes, and behavior. Using Mexico as our case study, we first wish to understand to what extent citizen perceptions of corruption are culturally or institutionally rooted. Then, we wish to uncover under what conditions institutional vs. populist frameworks deter citizens’ willingness to engage in bribery.
Our research agenda is composed of two separate but interlinked interventions. First, our research sets out to understand whether the failure of institutional anti-corruption reforms can be attributed to citizens’ perceptions of corruption and attitudes towards corruption being culturally embedded, rendering the impact of institutional measures negligible. For this purpose, we rely on a unique randomized control trial that leverages migration as a vehicle to disentangle culture and institutions in understanding attitudinal outcomes. Second, we seek to understand whether the failure of institutionalized anti-corruption efforts can be linked to anti-corruption populism movements. For this purpose, we rely on a lab-in-the-field experiment that examines how institutional vis-à-vis populist “anti-corruption” payoffs affect behavioral propensities of engaging in bribery along the US-Mexico border.
We will be developing a satellite monitoring system that enables policymakers and humanitarian aid organizations to track the progression of the Rohingya refugee crisis from 1980 to the present. We will conduct participatory mapping workshops in Kutupalong Refugee Camp to capture the oral and visual histories of life before, during, and after the refugees’ expulsion. We will then tie these histories to remote sensing analyses that map landscape changes indicating mass violence, such as forest regrowth following village destructions. Using architectural 3D modeling techniques, we will create digital visualizations of our Rohingya participants’ home villages, providing them with ‘digital capsules’ of their cultural histories from before the atrocities. This project will revolutionize our ability to transparently monitor mass violence while empowering refugees to preserve their histories using cutting-edge modeling technologies. Liza Goldberg is responsible for this project.
PovGov collaborated with the Instituto Tecnológico Autónomo de México (ITAM), a leading university in Social Sciences in Mexico, supported by the US Embassy in Mexico and the Mexican Association of Universities (ANUIES). Together, we initiated a summer program, sponsored for four years, and virtually during the pandemic, bringing together ten indigenous students from various Mexican communities with counterparts from a prestigious Mexican institution. The immersive experience at Stanford covered Global Risks in citizen security, governance, and the environment in Mexico, integrating extracurricular activities in Silicon Valley. This initiative not only provided access to cutting-edge research and sophisticated methodologies but also fostered continued engagement, with many students participating in research teams and internships, particularly focusing on indigenous governance and the impact of COVID-19 on indigenous communities in Mexico.
