Genie Giaimo

Writing and Power
Power: who has it, who doesn’t, and what does it have to do with your writing? This course both instructs students in how to access power in academic contexts and to critique power structures. We’ll learn how power connects to literacy, and how it's shaped through rhetorical contexts. Students will explore their own power as writers and thinkers while engaging in meaningful personal, reflective and argumentative writing. The professor will work with each student extensively on their writing process and development, and we'll create a writing community. This course bears elective credit but does not fulfill the college writing requirement. 3 hrs. lect/disc

Labor Rhetorics: Work in the U.S. Imaginary
Recently, labor and work are everywhere in U.S. media and culture. From news articles and social media posts about “the great resignation” to anxieties about worker demands. In this course, we will use rhetorical analysis as both theory and research methodology to examine labor and work. Using a variety of cultural and public texts like non-fiction, literature, newspapers, television, and labor research, students will learn rhetorical concepts, interpret, and critically analyze the diverse messages about labor that surround us, and build skill in using written and oral communication to develop their own labor rhetorics and advocate for local workplace change.

The Art and Science of the Interview
Interviews are everywhere, from celebrity “freak-outs” to NPR’s StoryCorps to applying to your first job. We will use rhetorical and generic approaches to better understand the purpose and structure of the interview as it arises in different public and professional contexts. We will learn how to become better and more ethical interviewers, and we will conduct interviews on subjects that interest us. Along the way, we will write and reflect on the ethics, purposes, techniques, and psychosocial effects of interviewing. This course prepares students for the social-cultural and contextual nuances of conducting academic, activist, and personal interviews.

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, Linguistics, Political Science, or Writing & Rhetoric. This course will use the R programming language. No prior experience with R is necessary.

GEOG: Students will apply data science tools to explore the geography human-environment relationships around protected areas. We will use household survey and land cover data from locations across the humid tropics where the Wildlife Conservation Society has been tracking human wellbeing and forest resource use in high-priority conservation landscapes. Projects and visualizations will be presented back to WCS to inform their ongoing monitoring and management in these sites.

LNGT: In this section, we will learn how to collect and analyze Twitter data in R. We will focus on social metrics and geographical locations to examine language variation in online communities across the United States. While the emphasis will be placed on linguistics, the statistical and analytical tools will help you work with other types of Twitter corpora in the future.

PSCI: Students will use cross-national data to explore relationships between conflict events and political, social, and economic factors in each nation. What factors contribute to conflict and violence? Our focus will be to find patterns in the data using the tools in R and discuss what those patterns suggest for addressing rising conflict and resolving ones that have already experienced violence.

WRPR: Students will learn to conduct writing studies research through working with "big data” from a multiyear survey of first-year college students about their academic confidences, attitudes, and perceptions. We will explore how educational access, identity, and language background impacts survey responses. Using statistical analysis and data visualizations, as well as writing, we will report our findings.