Dataset 1: Chinese Mass Communications State and City Data
Download: Shape files (2.82MB)
Dataset 2: Aggregated File
Excessive use of force by law enforcement is by no means a novel phenomenon in the United States. However, with high-profile cases like Michael Brown, Eric Garner, and most recently Greg Gunn, fueling national movements such as #BlackLivesMatter, race-related incidences of police brutality are receiving worldwide media attention.
I investigated geographic trends in reported police brutality, using Los Angeles County at the census tract level and data from The Guardian’s project “The Counted,” a comprehensive dataset that records all people killed by police and other law enforcement agencies in the US, for the year 2015.
To measure the effect of location on incidences of police brutality, I conducted a hot spot analysis, which identifies statistically significant spatial clusters of high (hot spots) and low police brutality (cold spots). Essentially, the hot spots/cold spots indicate whether observed spatial clustering of police brutality events is more pronounced than if the values were randomly distributed. We specified the spatial relationship for the analysis as Contiguity Edges, meaning that census tracts that share a boundary or overlap with a census tract that contains a police brutality event will be weighted more that those that don’t in the analysis.
Below is a map depicting the results of the hot spot analysis.
The hot spots depicted in the map reveal the relationship between location and the occurrence of police brutality. The neighborhoods enveloped in hot spots are those with an abnormally high number of police brutality events, indicating that these areas may be disproportionately affected by excessive use of force by law enforcement.
Looking demographically at both the incidences themselves and these hot spot neighborhoods can shed some light on why these areas have abnormally high police brutality. Right off the bat, the number of blue and green dots (Hispanic/Latino and black victims, respectively), dominates the map. Breaking down by race, there were 30 victims of Hispanic/Latino descent, 11 black, 4 Asian/Pacific Islander, 7 white, and 1 Arab-American. In addition, most of the incidences with blacks as victims happen in LA neighborhoods that have a large population of blacks, such as Willowbrook and Westmont. The same trend also appears when focusing on Hispanic/Latino victims: most Hispanic/Latino victims died in neighborhoods with large populations of Hispanics/Latinos, such as Los Angeles proper and Eastern LA County (Baldwin Park, Irwindale, West Covina).
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The field of geography is split into two camps: critical scholars, who are skeptical of data because they believe it silences certain voices within society and fails to explain process and context, and empirical scholars, who incorporate data to create empirical models that explain geographic concepts and trends. Leif Brottem, Assistant Professor of Political Science with a PhD in Geography, is a firm believer in the importance of both critical and empirical approaches. Data analysis can compensate for and expand upon the limits of text and qualitative evidence. His focus on data analysis as a tool that illustrates narrative is evident in the work of each of his three classes, Introduction to Global Development Studies (GDS), Introduction to Geographical Analysis and Cartography, and Climate Change, Development, and Environment.
In his Introduction to Global Development Studies, for instance, Brottem utilizes infographics & charts to explain basic concepts, and utilizes data tools such as GapMinder to illustrate change over time and regional differences pertaining to a variety of development indicators. His students also complete two data analysis exercises as a part of the class: one exercise asks students to study the relationship between economic development and social development indicators, and the second has students explore different aspects of population dynamics such as carrying capacity, limits to growth and the determinants of population growth.
In Brottem’s Introduction to Geographical Analysis and Cartography course, students learn both the basic critical perspectives on how to evaluate maps and understand their overt and covert messages and practical techniques for making maps using Geographical Information Systems software. Students complete in-class exercises and take-home labs that require creating data and using data to solve problems.
Finally, in Climate Change, Development, and Environment, Brottem utilizes data analysis in the form of topic-modeling: students investigate textual trends in various sources, from tweets to scholarly articles, using the MALLET topic model package. In addition, his students also work with Nvivo to conduct further qualitative analysis, and GIS to visualize spatial trends.
Working with data builds data literacy, a marketable and necessary skill in the real world that Brottem says isn’t typically developed in a liberal arts settings. Building data literacy is especially important in his introductory classes, because he has students who wouldn’t otherwise be exposed to data, and aims to get them comfortable with using data and reduce their fears of data, numbers, and data analysis. Brottem strongly believes that data is a powerful explanatory tool that helps students think of different ways to look at the world and their studies, beyond theory.
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The start of the school year is a time many students start putting thought into what disciplines to study for the remainder of their collegiate careers. Many on-campus resources such as the Center for Careers, Life, and Service are already in the full swing of advising students, such as the “Choosing Your Major” info session on Sept 21st from noon to 1 in the Joe Rosenfield Center. Here in DASIL, we thought it would be fun to investigate what Grinnell College students majored in over the years to illustrate the transformation of student academic patterns. Using data from the Office of Academic Affairs, Office of the Registrar, and the Office of Analytic Support and Institutional Research, we created two interactive graphics. One is a line graph presenting the number of declared majors over time from 1991 to 2015 by major and rank compared to other majors. Our second visualization is a geographic map with two layers: the US layer breaks down the proportion of students by state and major from 1985 to 2015, while the world layer illustrates the proportion of international students by country and major.
Click on the Details button below to find out more about the data for each visualization.
For the map:
For the line graph:
The Biology major holds the record for most students declared within this time frame, at 53 students for the Class of 1995. Since its creation, the number of students who major in Biological Chemistry increased leaps and bounds, ranking as the second most-declared major in the Class of 2015, tied with Psychology. Economics shows a general increasing trend over time, while majors like English and Sociology show erratic variability throughout.
American Studies majors appears to be representing the South and Southwest regions of the US, while Sociology is prominent in states located in the Midwest and, similarly, the South. A large proportion of students hailing from California study the hard sciences, especially Biological Chemistry. Surprisingly, there is a significant proportion of biology majors represented in most of the states.
Scoping out, the social sciences and hard sciences are popular disciplines among international students. Economics, Biological Chemistry, and Math are popular, especially in countries like China and India. Several humanities majors are not well-represented by international students, such as Theatre and Gender, Women, & Sexuality Studies.
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In the Fall 2014 semester, students in History 214: The American Civil War and Reconstruction class got help from DASIL to explore data about black soldiers who enlisted in the U.S. Army during the Civil War. Where did black soldiers come from? What kinds of economic and social factors influenced their experiences? Students read an article by the very creative economic historians Dora L. Costa and Matthew E. Kahn, “Forging A New Identity: The Costs and Benefits of Diversity in Civil War Combat Units for Black Slaves and Freemen” (2004),” which used a variety of census, enlistment, and pension data to examine some of the effects of serving in the military on the almost 200,000 black men who enlisted in the U.S. Army after 1862. Students had also read several articles that used Geographic Information Systems to do spatial analysis, and I was interested in doing an in-class exercise to help them think critically about military data and to introduce them to using the GIS technology.
DASIL Director Kathy Kamp, Post-Baccalaureate Fellow Sara Sanders, and DASIL student Harry Maher worked with me to design an exercise that could help students to visualize data about black soldiers for themselves and to think about the effects of geography on black enlistment. We used a dataset on “Union Army Recruits in Black Regiments in the United States Army 1862-1865” compiled by Jacob Metzger and Robert A. Margo available through the ICPSR as a starting point.
The DASIL staff created tables that contained the Metzger and Margo data, along with 1860 census information on population and agricultural production and some tables on black enlistment from Freedom’s Soldiers: The Black Military Experience in the Civil War (Berlin, Reidy, and Rowland, 1998). We worked together to create a GIS exercise based on the data that could whet the students’ appetites for working with spatial data in just one class period.
The in-class exercise had two points: to get the students thinking about the nature of the datasets and to have them use ArcGIS software to create maps that showed the relationship between the proportion of black soldiers enlisted in relation to the total population by state and cotton production by county. The Metzger and Margo dataset is based on a judgment sample, so students were able to examine the dataset alongside census records to appreciate how judgment samples do not include comprehensive data. Nor do they represent a random, representative sampling of black soldiers. But used alongside the census data and the tables from Freedom’s Soldiers, the data were still able to help them form some useful conclusions.