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Individual and Neighborhood Vulnerability over the Latin American Immigrant Health Experience
Abstract: The state of Latino health seemingly defies the way in which the historical disadvantages faced by people of color in the United States get under the skin, and how place matters in reflecting or further reproducing these disparities. Hispanics –especially foreign-born individuals with lower socioeconomic statuses– have more favorable health than other race/ethnic groups –notably, U.S.-born non-Hispanic whites– in a limited but very important set of health outcomes such as cardiovascular function, some cancers and mortality across much of the life course.
In this talk, I discuss the mechanisms/phenomena driving the Hispanic immigrant health advantage, which is likely tied to processes of self-selection as well as to protection and resilience likely operating particularly well in heavily-concentrated Latino neighborhoods and enclaves. Throughout, I present my empirical research aimed at disentangling self-selection processes from the protection that immigrants might draw from fellow neighborhood and/or community members. I further discuss these findings in the context of how immigrants adapt in the longer term: these advantages and resilience eventually erode as immigrants spend more time in the United States –as well as across immigrant generations– through a series of processes by which immigrant and Latino vulnerability become somatized.
I conclude by speculating on the likely future of Latino and immigrant health, discussing how the resilience and vulnerability of Latino immigrants might evolve given recent major shifts U.S. immigration and social policies and practices, and due to important changes in the dynamics of migration between Mesoamerica and the United States.
Title: Grad Student Panel Discussing the Causal Toolkit Location: February 27, 2019, 2:00-3:30 PM 4240 Public Affairs Building CCPR Seminar Room Content: Focusing on the uses of the causal toolkit, several grad students will share a-ha moments and lessons learned from their own applied research. The target audience are grad students and researchers who wish to get a taste of how causal concepts are used. We will start with an open discussion (with audience Q+A) of introductory concepts in causation,…Find out more »
Small steps with Big Data: Using Machine Learning in Resource Economics
This talk looks at how recent developments in Big Data and Machine Learning are being used in conjunction with randomized controlled trials and large population level program evaluations to design, implement and measure efforts to change consumer behavior. We will explore the role played by very detailed consumption data (often at 15 minute intervals), as well as recent techniques such as deep learning to help us better understand individual and population behaviors, and which insights from behavioral sciences are effective at changing behaviors in areas such as energy conservation and efficiency.Find out more »
Population Vulnerability and Spatial Analytics
There has been a transition from population studies that were relatively data poor to the present day where digital data is plentiful on many fronts. The “Smart City” is fed by sources of information coming from all directions, where sensors observe things about the movement of vehicles and people, infrastructure conditions, air quality, weather, etc. The challenge is to make use of this digital data, and this is precisely the value added offered by a range of big data spatial analytics. This paper examines aspects of population vulnerability, focusing on particular types of risks and hazards in urban areas.Find out more »