Data Across the Curriculum: Using Geospatial Data to Illustrate Historical Change

History is a discipline that is founded on looking at changes over time, and for Sarah Purcell, Professor of History, data is an essential tool in measuring that change. More specifically, Purcell employs geospatial data to investigate historical change in both time and space for her Civil War & Reconstruction class, which focuses on the causes, progress, and consequences of the Civil War and Reconstruction with an emphasis on race, politics, economics, gender, and military conflict.

Purcell uses a stair-step approach in getting students exposed to geospatial data, first by using Google Maps to compare Civil War battleground locations to the locations of students’ hometowns, then investigating how other historians have used data, especially economic and demographic data, in tandem with historical narrative. Finally, Purcell has her students work with ArcGIS, an analytical map-making software, to visualize geographic trends in various historical data. For example, students in the class explore on black soldiers who enlisted in the U.S. Army during the Civil War in an in-class exercise (Figure 1) that encourages them to think critically about military data.

 

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To Sarah Purcell, data is important due to its wide applicability: using data in the context of history teaches a valuable lesson about how data can enhance just about any discipline. Moreover, in the history field, there exists a broad array of different types of data to be utilized, both qualitative and quantitative. While Purcell admits that some students have easier facility with working with data than others, she stresses that the struggle is important in internalizing quantitative literacy and getting accustomed to confronting data, an essential skill. The amount of involvement with data students get in her courses has impacted her students in a variety of ways: some students have gone on to get further training in ArcGIS via formal coursework, and others have been able to secure jobs, citing that employers are largely attracted to data skills in historical work.

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Mapping State Tax Expenditures to Demonstrate that All Else Really is Equal

Typically, when a business invests in a new piece of equipment, it cannot immediately deduct the full purchase price from its taxable income in the first year.  Instead, according to federal tax regulations, it deducts a percentage of the price in each of 2, 5, or 7 years depending on the type of equipment.  Businesses, of course, would prefer the tax deduction to happen in the first year so they have lower current taxes and therefore increased current cashflow which can be used to make additional investments that will pay off in the future.

In an effort to help small businesses, the federal government has long allowed for all investment costs below a specified threshold by any given firm to be immediately deducted.  This threshold, is specified in Section 179 of the tax code and is generally referred to as the Section 179 allowance.   For example, in 2002, all investment costs below $20,000 could be immediately deducted from taxable income but investment costs beyond $20,000 were subject to normal rules.

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Since 2003, the government has worked to encourage business investment by significantly increased this threshold (see figure 1). Interestingly, as the government has increased the threshold, many states have made equivalent alterations to their state tax policies.  Other states have increased their Section 179 allowance some.  Still others have not increased Section 179 generosity at all.  In new research, I attempt to use this state-level variation in Section 179 generosity to estimate how manufacturing investment and employment respond to state Section 179 conformity.

An important step in this research process has been demonstrating that states that do and do not conform to the federal threshold are not substantially different in other ways that would affect investment or employment trends.  One major concern, in particular, is that conforming states might be concentrated in a single region.  If investment and employment is changing in this region for reasons other than Section 179 conformity, then the research design, which compares conforming and non-conforming states, would inappropriately attribute investment and employment effects to state 179 conformity when, in fact, these effects are really due to regional trends.

To allay this concern, I enlisted the help of Bonnie Brooks in DASIL to create an interactive ArcGIS application which shows the evolution of state 179 conformity during the years 2000 to 2011.  From the application, it is immediately apparent that state conformity or non-conformity is not concentrated in any region.  Thus, the ArcGIS application simply and elegantly allays concerns that regional trends may undermine the key assumption in this and all applied microeconometrics research project: that all else really is equal.

To use the map:

  • Drag the second ticker to the beginning of the timeline to start the visualization from the year 2000

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Visualizing Mass Communications and State Institutions in Wartime China (1937-45)

In China, the study of history has always gone hand-in-hand with the study of geography. When studying China’s modern history, however, focus has shifted toward large-scale processes, such as revolution, and large-scale sociological transformations, such as changing class relations. More recently, however, some historians are starting to bring geography back in. Pathbreaking endeavors such as the China Historical GIS project and Harvard University WorldMap platform-based ChinaMap allow researchers to visualize the transformation of China across space and time. The result has been a new understanding of China and Chinese history highlighting the spatial distribution of ethnic and linguistic diversity, economic development, elite networks, and state institutions. One exciting result of this new understanding is that it allows students and researchers alike to visualize large-scale processes across time periods, which can in turn lead to new questions about how different places might have experienced the same era or event. Through the use of spatial approaches, we are challenged to rethink the applicability of national historical narratives to local human landscapes.

As a teacher and researcher of East Asian history, much of what I do focuses on how media, institutions, and person-to-person networks have connected the modern Chinese state to populations both inside and outside of China. Working in tandem with DASIL, I have begun to build and visualize datasets which describe how the “connective tissue” of state-building looked during the period of China’s War of Resistance to Japan (1937-1945)—a period of intense destruction and dislocation which some historians have also described as key period of modernization. This data is drawn from two editions of The China Handbook: a publication of the Chinese Ministry of Information released in 1943 and again in 1946. I discovered this publication quite by happenstance while searching the Grinnell College Library collections for local gazetteer data related to the period of China’s Republican Era (1911-1949). The value of The China Handbook is that it provides comprehensive provincial and urban data for a number of indicators of state development; here we (myself and DASIL’s outstanding post-bac fellow, Bonnie Brooks ’15) have focused on data concerning communications, education, and health care. To be fair, and as admitted by The China Handbook’s original editor, Hollington K. Tong, this data is not exhaustive, nor is it necessarily reliable given the rapidity of changes brought about by war and resulting partition of China into competing political zones. It does, however, represent at least a starting point for visualizing what China’s wartime states looked like “on the ground,” viewed through the lens of communications and other institutional infrastructure.

Below the level of national boundaries, modern China is divided into numerous separate administrative units known as provinces. However, the number of provinces has changed with time and successive governments, which poses a challenge for those seeking to visualize data at the province level for eras during which the number of these units was larger than it is today—as was the case during the latter half of the Republican Era, which witnessed a proliferation of efforts to tame China’s restive and geopolitically fragile borders through the process of province-building. A key part of Bonnie’s contribution, then—the results of which will hopefully be used and refined by other researchers working at the intersection of geographic information systems (GIS) and modern Chinese history—was the creation of new shapefiles corresponding to each province that existed during the 1937-1945 period. The resulting maps are thus entirely new creations, and will hopefully serve to help bridge the current gap which lies between geospatial research on imperial China and research on contemporary China after Mao.  The shapefiles are available for download in DASIL’s Downloadable Data section.

For the map:

    • The Contents button(contentsbutton) will display all layers. Unclick the checkbox next to the layer name to hide the layer. To view the legend, click on the “Show Legend” icon (contentsbutton) below the layer name.
    • To examine other variables, find the “Change Style” button (contentsbutton) below the layer name you wish to view, then select the desired variable from the “Choose an attribute to show” drop-down menu.  You may alter the map with colors, symbols or size. You may also alter variables (e.g. normalize variables by population).
    • Click on an individual Chinese province to see available data.
    • The shapefiles featured in the map are available for download on the DASIL website. Click here for the download.

 

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Data Across the Curriculum: Integrating Data Analysis with Narrative in Political Science

From a pedagogical standpoint, Danielle Lussier, Assistant Professor of Political Science, stresses data as a tool for helping students approach problems from multiple perspectives. Working interactively with data allows them to better compare narratives and better understand the research process in both lower-level and upper-level material.

Political science is both a quantitative and qualitative field, so students at all levels of Lussier’s political science classes delve into both data types extensively and build data analytic skills as students progress in the major. Every class taught by Lussier involves data labs that draw on both cross-national data with countries as the unit of measure and on data with individuals as the unit of measure. The labs directly relate to readings, concepts, and/or countries that students study.

At the 100-level, students gain both an introduction to fundamental data concepts such as the construction and measurement of variables and to analytical computer programs like STATA, a statistical package, and ArcGIS, which analyses spatial data. The image below is of a GIS map her introductory political science students make in a data lab.

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At the 200-level, Lussier’s students delve into applied data analysis and write in-depth data reports that compare data analyses from the course readings to data analyses that students reconstruct and update from the readings.

At the 300-level, students get the opportunity to pose questions about class readings and use lab time to test their inquiries with actual data from the readings. In addition, Lussier assigns students research modules that allow them to create their own qualitative variables from cross-national data that they then transform into quantitative data, giving students the opportunity to apply the data skills they’ve accumulated in each course level.

The positive impact of incorporating data into classroom work is not lost on students. Students in all levels of her courses are widely receptive to data in coursework and have viewed working with data in her classes as an integral stepping stone to both academic and professional pursuits. Adam Lauretig ’13, the first Post-Baccalaureate Fellow for DASIL, was inspired by Lussier’s data-driven coursework to pursue more advanced courses in spatial statistics, and subsequently created visualizations like the interactive timeline map of historical coups d’etat. Additionally, many of her students have cited the research and data skills developed in her class work as marketable to employers and graduate programs.

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Exploring Racial Disparities in New York City’s Stop-and-Frisk Policies

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A comparison of the two maps above yields a surprising conclusion: African-Americans are much less likely to be arrested in areas with higher African-American populations!

One of the best examples of the use of statistics in policy research is in the controversy about New York City’s Stop-Question-and-Frisk policies, which give police officers the right to stop, search, or arrest any suspicious person with reasonable grounds for action. These policies were an effort to reduce crime rates, under the philosophy that stopping suspicious persons will prevent smaller crimes from escalating into more violent ones. In recent years, the NYPD had been under fire for alleged racial discrimination in their stops. Research on approximately 175,000 stops from January 1998 through March 1999, for example, showed that Blacks and Hispanics represented 51% and 33% of the stops, while only representing 26% and 24% of the New York City population respectively. The NYPD defended their practices, saying that since crimes mostly happen in black neighborhoods, it is natural that more black people would be found suspicious of crimes.

Using the stop-and-frisk dataset provided by the NYPD and 2010 census data, numbers were compiled into an interactive heat map of arrests directly related to the stop-and-frisk policy in New York City, as an aid to visualizing this disparity in race.

For each precinct, the visualization allows you to compare the racial make-up of the population with the proportion of arrests by race. For instance, this shows that in Precinct 104 while less than 2 % of the population in this precinct is African-Americans, over 15% of the arrests were of African-Americans.

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Evidence of racial disparity is clear.  African-Americans are consistently overrepresented in arrests compared to the population in each precinct.

The exception to this trend which was alluded to at the beginning of the post:  in areas with high African-American populations, the disparity disappears, and even reverses in a few precincts! Thus African-Americans are much less likely to be arrested in neighborhoods with high African-American populations.

Use this visualization to explore the trends in arrests due to the stop-and-frisk policies in New York:

Another visualization on stops and arrests in New York City can be accessed here. You can also go here for more information on these data visualizations.  These visualizations were created as part of a Grinnell College Mentored Advanced Project with Ying Long and Zachary Segall under the direction of Shonda Kuiper.

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