Jessica L'Roe

Land and Livelihoods - From Local to Global
How do flows of money, people, materials, and ideas connect local livelihoods to distant sites and global processes? How do geographers study patterns of poverty and inequality at different scales? How do we define human development and wellbeing, how do we determine who participates, and why does it matter? In this course we will draw from perspectives in fields ranging from development geography and political ecology to post-colonial studies to examine livelihood dynamics in the Global South. We will use texts, interviews, writing assignments, problem sets, and mapping exercises to explore relationships between economy, identity, and place in an increasingly connected world. 3 hrs. lect.

Seminar in Human-Environment Geography: Landscapes in Transition
What will Vermont look like in 100 years? What about the Brazilian Amazon, the Albertine Rift, or your home town? In this seminar, we will explore the ways that processes of change discussed in our thematic Geography classes like urbanization, climate change, gentrification, commoditization, 'globalization', and more may interact and play out in the future. We will discuss studies of historic and ongoing landscape transitions and conduct our own studies of student-selected places, focusing both on the changes most likely to occur given existing trajectories, and attempting to imagine and articulate what changes would be desirable. (Open to senior majors only; others by waiver) 3 hrs. sem.

Data Science Across Disciplines
In this course, we will gain exposure to the entire data science pipeline—obtaining and cleaning large and messy data sets, exploring these data and creating engaging visualizations, and communicating insights from the data in a meaningful manner. During morning sessions, we will learn the tools and techniques required to explore new and exciting data sets. During afternoon sessions, students will work in small groups with one of several faculty members on domain-specific research projects in Geography, Political Science, Restorative Justice, or Healthcare. This course will use the R programming language. No prior experience with R is necessary.

GEOG 1230: In this section, students will use data science tools to explore the ways migration systems in the United States changed during the COVID-19 pandemic. We will draw on data collected from mobile phones recording each phone’s monthly place of residence at the census tract level. The dataset includes monthly observations from January 2019 through December 2021 allowing the analysis to compare migration systems pre-pandemic with those during the pandemic.

INTD 1230A: Data is a powerful tool for improving health outcomes by making programmatic choices to support justice. In this afternoon section of Data Across the Disciplines, students will be working with Addison County Restorative Justice (ACRJ) on understanding patterns in the occurrence of driving under the influence. ACRJ has over 1,000 cases and would like to better understand their data and come up with ways to access information. We will explore how identity, geography, and support impact outcomes from DUI cases. Using statistical analysis and data visualizations, along with learning about ethical data practices, we will report our findings.

INTD 1230B: Let’s dive into the minutes and reports of local towns to develop an accessible news and history resource. Could this be a tool for small newspapers to track local news more easily? Can we map this fresh data for a new look across geographies? Do you want to help volunteer town officials make decisions and better wrangle with their town’s history and data?
In this course we will develop a focused database of documents produced by several municipal boards and commissions. We will engage in conversation with local officials, researchers, and journalists. This course aims to introduce students to making data from real world documents and the people that make them to generate useful information that is often open but frequently difficult to sift through.

MATH/STAT 1230: Students will explore pediatric healthcare data to better understand the risks correlated with various childhood illnesses through an emphasis on the intuition behind statistical and machine learning techniques. We will practice making informed decisions from noisy data and the steps to go from messy data to a final report. Students will become proficient in R and gain an understanding of various statistical techniques.

PSCI 1230: How do candidates for U.S. national office raise money? From whom do they raise it? In this section we will explore these questions using Federal Election Commission data on individual campaign contributions to federal candidates. Our analysis using R will help us identify geographic patterns in the data, as well as variations in funds raised across types of candidates. We will discuss what implications these patterns may have for the health and functioning of democracy in the U.S.