photo of jess l'roe
Office
McCardell Bicen Hall 636
Tel
(802) 443-5387
Email
jlroe@middlebury.edu
Office Hours
Spring '24 Wed & Thurs 1:30-2:30pm and Fri 10:30 -11:30 am.

Office Address:

Middlebury College

Geography

McCardell Bicen Hall 636

Middlebury, VT 05753

Jessica L’Roe

Assistant Professor of Geography

Email: 
Phone: (802) 443-5387
Office Hours: Spring Term: Wed. & Thurs. 1:30 -2:30pm and Fri. 10:30 -11:30am
Office Location: McCardell Bicen Hall 636jlroe@middlebury.edu

I study human-environment relationships in forest landscapes undergoing rapid change. I focus on the intersection of conservation and development initiatives, with particular attention to land access, trends in inequality and well-being, and livelihood transitions. My field-research has been in the Amazon Basin and the highlands of East Africa, and I partner with organizations working on similar issues other parts of the world.

I attended graduate school at the University of Wisconsin-Madison where I received a Ph.D. in Geography, an M.A. in Agricultural and Applied Economics, and a M.Sc. in Conservation Biology and Sustainable Development. My undergraduate degree in Environmental Science is from the University of North Carolina, where I grew up. I enjoy natural history, gardening, making things, and raising a feisty little family.  

For more information, please visit my Website

Courses Taught

Course Description

Natural History of Addison County
In this course, we will forge a sense of place through attention and connection— learning to see the relationships within the region's ecological communities and cultivating relationships within its human communities. To this end, students will engage in a series of field trips in Middlebury and surrounding parts of Addison County. We will use Natural History as a structuring principle, building an understanding of the ways that current landscapes are shaped by influences from bedrock geology to human history to plant and animal assemblages. Our goal over the course of the semester is to help each other find our own places within the wider community, and by so doing, to help make Middlebury feel more like home. Be ready to venture outside. [One 50-min lec. + one 3 hrs. sem./lab]

Terms Taught

Fall 2023

Requirements

CW, PHL, SCI

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Course Description

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.

Terms Taught

Spring 2023, Spring 2024

Requirements

CMP, SOC

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Course Description

Environmental Change in Latin America
This course examines Latin America from a geographical perspective with emphasis on the social, political and ecological underpinnings of change in the region. Building upon the theme of global environmental change in the context of human-environment geography, we will explore urgent challenges linked to the agricultural and extractive industries, urban expansion, land grabs, land reform, indigenous rights, and rural and urban poverty. 3 hrs. lect.

Terms Taught

Spring 2020, Fall 2022, Fall 2023

Requirements

AMR, SOC

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Course Description

Placebased Data Analysis (formerly GEOG 0139)
Who migrates from urban areas during a pandemic? How are livelihoods distributed around protected areas in Central Africa? How much does location influence the price of a house? In this course students will discover ways to answer questions like these by introducing fundamentals for generating and analyzing data about people and the places they are connected to. Students will practice constructing datasets, visualizing relationships, formulating and testing hypotheses, modeling outcomes, and conveying results. We will cover descriptive and inferential statistics, focusing on geographic applications and the unique complexities of spatial data. Through cases and problem sets, students will explore complementarities between quantitative and qualitative analysis, emphasizing critical and reflexive approaches. Labs will build proficiency with software packages like R and GeoDa. The course aims to make students more savvy consumers of published work, to produce careful analysts, and to foster a deeper appreciation for the research process. No prior experience with Statistics or Geography is required; the course is designed to introduce students to approaches broadly relevant in Geography and allied social sciences. (DED) 3 hrs. lect./3 hrs. lab

Terms Taught

Spring 2024

Requirements

CW, DED

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Course Description

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.

Terms Taught

Spring 2022

Requirements

SOC

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Course Description

Independent Study
A one-credit intensive research project developed under the direction of a faculty member. Junior majors only. (Approval Required)

Terms Taught

Spring 2020, Winter 2021, Spring 2021, Winter 2022, Spring 2022, Fall 2022, Winter 2023, Spring 2023, Fall 2023, Winter 2024, Spring 2024, Fall 2024, Winter 2025, Spring 2025

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Course Description

Senior Research
A one-credit intensive research project developed under the direction of a faculty member. Senior majors only. (Approval Required)

Terms Taught

Spring 2020, Winter 2021, Spring 2021, Winter 2022, Spring 2022, Fall 2022, Winter 2023, Spring 2023, Fall 2023, Winter 2024, Spring 2024, Fall 2024, Spring 2025

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Course Description

Senior Thesis
Students with a departmental GPA of 3.3 or higher are eligible to complete a two-credit senior thesis. In order to complete a senior thesis, students must have a proposal approved by a primary thesis advisor and a secondary departmental reader prior to registering for the first 0701 credit. Upon completion of the thesis, thesis students will present their work in a public seminar and defend the thesis in front of the departmental faculty. Thesis presentations and defenses will typically take place during the final week of classes or the examination period. Upon completion of the presentation and defense, the primary advisor and secondary departmental reader will be responsible for evaluating and grading the thesis. It is strongly encouraged that students considering a thesis discuss their ideas with an advisor during the semester prior to registering for formal thesis credits. (Approval only)

Terms Taught

Spring 2020, Winter 2021, Spring 2021, Winter 2022, Spring 2022, Winter 2023, Spring 2023, Fall 2023, Winter 2024, Spring 2024, Fall 2024, Winter 2025, Spring 2025

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Course Description

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.

Terms Taught

Winter 2023

Requirements

DED, SOC, WTR

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