Interdisciplinary Studies in Social Sciences and Humanities (INSH)
INSH 1000. Social Sciences and Humanities at Northeastern. 1 Hour.
Intended for freshmen in the College of Social Sciences and Humanities. Introduces freshmen to the liberal arts in general. Offers students an opportunity to become familiar with their major, to develop the academic skills necessary to succeed (analytical ability and critical thinking), to become grounded in the culture and values of the university community, and to develop interpersonal skills—in short, to become familiar with all the skills needed to become a successful university student.
INSH 1102. Food in Contemporary Context. 4 Hours.
Covers a multidisciplinary set of perspectives on an intrinsic part of daily life—food. Food is not just about survival—it is about being human. Producing it, making it, eating it, obsessing about it is woven throughout our lives. It defines, and is defined by, culture. It is the basis of economies, has produced great fortunes, defines entire communities, and is the cause of conflicts. It is at once natural and artificial, grown and manufactured. It nourishes us, and it makes us sick. It is the source of sublime pleasure and no small anxiety. Food defines us, as much as we define it. With these considerations, this course uses food as a lens into contemporary life.
INSH 1300. Introduction to Health and Humanities. 4 Hours.
Explores the ways in which narrative and other forms of creative and cultural expression help shape conceptions of illness, healing, and the body. Offers students opportunities to consider the health and humanities through a variety of interdisciplinary perspectives and genres. Includes small-group and classwide experiential field outings. Culminates in the composition of reflective responses, a medical ethics/medical journalism piece, and a team-based experiential e-portfolio project. Course objectives include differentiating between healing and curing; knowing how to elicit, listen to, and analyze stories to determine how participants in the healthcare system experience illness and healing; being able to articulate the ways health is a cultural construct; and using this analysis to identify an empathic response as a future professional.
INSH 1500. Digital Methods for Social Sciences and Humanities. 4 Hours.
Introduces programming skills and computational methods through application to topics in the social sciences and humanities. Methods include computational text analysis, network analysis, mapping software and analysis, computational approaches to data, big data, and/or social simulation. Offers students an opportunity to develop an understanding of the use and significance of computational tools for social sciences and humanities. No previous programming experience required.
INSH 1990. Elective. 1-4 Hours.
Offers elective credit for courses taken at other academic institutions. May be repeated without limit.
INSH 2101. Love and Hate: Social, Psychological, and Literary Approaches. 4 Hours.
Studies materials that define and describe love and hate from the fields of literature and literary criticism, social psychology, and criminology and criminal justice. “Love” and “hate” are small words describing powerful emotions with profound effects on individuals and on social groups. Focusing largely on contemporary examples, offers students an opportunity to analyze the differences and areas of overlap in the above fields’ approaches to love and hate, to discuss societal responses to these emotions, and to apply the methodologies of each field to research questions of their own. INSH 2101 and PSYC 2101 are cross-listed.
INSH 2102. Bostonography: The City through Data, Texts, Maps, and Networks. 4 Hours.
Uses Boston as a case study for integrating computational methods with the social sciences and humanities to provide new insights into major cultural, historical, and societal questions as they relate to and extend beyond the city of Boston. Through lectures, discussions, and labs, the course examines a variety of data sets that measure geographic, historical, literary, political, civic, and institutional landscapes. Offers students an opportunity to combine analytical tools, such as geospatial mapping, data visualization, and network science, with readings, hands-on class activities, and museum or site visits, enabling a comprehensive view of complex cultural and social phenomena.
INSH 2990. Elective. 1-4 Hours.
INSH 3990. Elective. 1-4 Hours.
INSH 4990. Elective. 1-4 Hours.
INSH 6300. Research Methods in the Social Sciences. 4 Hours.
Surveys methods of social research, including field study and participant observation techniques, survey techniques, interviewing and questionnaire construction, sampling procedures, experimental design, content analysis, and use of available data.
INSH 6302. Qualitative Methods. 4 Hours.
Introduces the principles and use of common qualitative methods with a particular focus on their application in the social sciences. Offers students an opportunity to engage in primary data collection and to learn how to use a variety of analytic techniques, including transcription, field-note preparation, memos, development of coding schemes and conceptual frameworks, and data-verifying techniques.
INSH 6404. Computational Social Science. 4 Hours.
Introduces the fundamental techniques of quantitative data analysis, ranging from foundational skills—such as data description and visualization, probability, and statistics—to the workhorse of data analysis and regression, to more advanced topics—such as machine learning and networks. Emphasizes real-world data and applications using the R statistical computing language. Offers students an opportunity to finish the course ready to apply a wide variety of analytic methods to data problems, present their results to nonexperts, and progress to more advanced course work delving into the many topics introduced here.
INSH 6406. Analyzing Complex Digitized Data. 4 Hours.
Introduces cutting-edge ways of structuring and analyzing complex data or digitized text-as-data using the open-source programming language Python. Scholars across multiple disciplines are finding themselves face-to-face with massive amounts of digitized data. In the humanities and social sciences, these data are often in the form of unstructured text and un- or under-structured data. Encourages students to think about novel ways they can apply these techniques to their own data and research questions and to apply the methods in their own research, whether it be in academia or in industry.
INSH 6500. Statistical Analysis. 4 Hours.
Studies the use of social science quantitative techniques, emphasizing applications of value to public-sector analysts and scholars alike. Introduces probability and statistical analysis. Topics include measures of central tendency and dispersion, probability and probability distributions, sampling distributions and hypothesis testing, bivariate correlation, regression, and forecasting. Examines how to generate and interpret statistical analyses.
INSH 6864. Experiential Integration. 1 Hour.
Offers an integration course providing an opportunity for students on experiential placement to connect conceptual course material to experiential components. Students are expected to: interact with students from other disciplines, apply knowledge and skills across educational and experiential contexts; connect experiential components to different disciplines and domains of knowledge; and situate experiential components in the context of their own field and beyond. Requires department signature.
INSH 6964. Co-op Work Experience. 0 Hours.
Provides eligible students with an opportunity for work experience. May be repeated once.
INSH 7400. Quantitative Analysis. 4 Hours.
Studies the use of social science quantitative techniques and how to generate and interpret statistical analyses. Topics include measures of central tendency and dispersion, probability and probability distributions, sampling distributions and hypothesis testing, bivariate correlation, regression, and forecasting. Builds upon the concepts of correlation and inference to present analytic procedures involving several variables (including multiple regression, logistic regression, causal analysis, and multiway ANOVA) and introduces more advanced multivariate analytic methods.
INSH 7500. Advanced Quantitative Analysis. 4 Hours.
Designed to build upon the foundations provided by INSH 6404, INSH 6500, or an equivalent introductory statistics course with the goal of students becoming proficient with selected quantitative multivariate analysis techniques. Covers the ordinary least squares (OLS) regression model and the assumptions underlying it in detail, as well as the techniques for analyzing data when OLS assumptions do not apply, such as simultaneous equation models, time-series models, and maximum likelihood techniques for limited and discrete dependent variables. Requires prior completion of INSH 6404, INSH 6500, or an equivalent introductory statistics course. PhD students only or by permission.
INSH 7600. Advanced Methodological and Quantitative Techniques. 4 Hours.
Builds upon the foundations provided by INSH 7400 and INSH 7500 (and their equivalents) with the goal of students becoming proficient with selected advanced specialized quantitative analysis techniques or platforms. Taught throughout the semesterby different faculty members with expertise in particular statistical methods. Example modules include hierarchical linear modeling, structural equation modeling, path analysis, and time-series analysis.
INSH 7910. NULab Project Seminar. 2 Hours.
Offers students an opportunity to learn and use digital humanities methods with others in groups and across disciplines in the collaborative space of the NULab seminar. May be repeated up to three times.
INSH 9980. Experiential PhD Research Residency. 0 Hours.
Comprises a research residency experience in an organization whose mission and activities are aligned with the College of Social Sciences and Humanities PhD programs. The research residency is designed to help develop dissertation ideas or research papers or to obtain access to resources helpful to dissertation development or research. A faculty member serves as an advisor for the residency experience, but individuals within the organization in which the student is working are asked to serve as formal mentors for the student residency experience.