April 25 – April 29, 2022
The Social Science Methods Week (SSMW) is a series of workshops on methods with high potential to improve and advance research in the social sciences. Workshops are taught by expert methodologists drawn from departments across the social sciences. SSMW is an interdisciplinary forum where researchers can upgrade their methodological toolkit and build cross-disciplinary ties to like-minded scholars.
Registration is free, and open to graduate students, post-docs, staff, and faculty at the University of Toronto. Participants can register for as many workshops as they wish, though enrollment for each workshop is capped at 30 participants. Those wishing to be placed on a waitlist for a workshop should email their request to firstname.lastname@example.org.
Participants should have any necessary software pre-installed on their personal computers.
Questions can be directed to email@example.com.
Register for a workshop
Schedule of Workshops
|Monday, April 25||Tuesday, April 26||Wednesday, April 27||Thursday, April 28||Friday, April 29|
|Morning||9 am to 12 pm |
Introduction to R, the Tidyverse Way
|10 am to 12 pm|
Introduction to Python
|9 am to 12 pm |
(Fidan Elcioglu & Sophie Marois)
Studying the Social World in Situ: An Introduction to Ethnography
|Lunch Break||12 pm to 1 pm||12 pm to 1 pm||12 pm to 1 pm|
|Afternoon||1 pm to 3:30 pm|
GitHub as a Tool for Supporting Open Science: Version Control and Collaboration
|1 pm to 4 pm |
Pre-registration: A Tool for Improving Transparency and Replicability of our Science
|1 pm to 4 pm |
Digital Data Collection in Hard-to-Reach Settings: A Hybrid Remote-Participatory Approach
|1 pm to 4 pm |
Data Visualization and Data Exploration
|1 pm to 4 pm
(Alisha Stranges & Emily Mastragostino)
Digital Solutions for Qualitative and Archival Data Management
Introduction to R, the Tidyverse Way: R is now the lingua franca of programming in the social sciences. It is widely used in academia, public policy and business, for everything data science/analysis related. In this workshop, we will work through data cleaning, manipulation and basic statistical modelling and visualization. The workshop will allow participants to learn the fundamentals of R and the Tidyverse, a collection of R packages designed for data science and analysis, so participants can further pursue more advanced research in their area of interest. No prior experience with R or the Tidyverse is required for the workshop, but the attendees should have the latest versions of R and RStudio installed.
GitHub as a Tool for Supporting Open Science: Version Control and Collaboration: We’ve all experienced the massive headache of needing to sort through a folder of projects labeled “Version_1_31Mar_final _REALLYfinal_tara” or “Version_2_Mar29 _final_PIcomments” to find that specific version of a manuscript with comments from a collaborator. What if there was a software that can keep track of your team’s changes to code, data, and manuscripts! Enter Git and GitHub! GitHub is an internet hosting of the software, Git, used for tracking changes of any set of files and for coordinating work among programmers. Research communities use GitHub for its handy features in version control, collaboration, and storing public datasets and protocols. The goal of this workshop is to give a hands-on demonstration version control for text files and R scripts. This workshop will help you create your own GitHub profile, show you how to “push” versions of your work to GitHub in a private or public repository, and demonstrate how to use git and GitHub with R-studio. Lastly, we will discuss how GitHub is helpful tool for fostering collaboration and open science on your team and in academia. This workshop is open to all researchers who are interested in learning skills for managing and collaborating on databases, code, and manuscripts. Little coding experience is necessary although a portion of the workshop may focus on R and R-studio.
Introduction to Python: Python is a programming language. In the hands of social scientists, Python is a powerful tool for collecting, analyzing, and visualizing all kinds of data. This Intro to Python workshop is for both qualitative and quantitative researchers who have little or no experience with Python or any other programming language. We will introduce the basic elements of Python like syntax, data types, objects, and functions. We will learn how to get data into and out of Python by reading and writing files. We will learn how to access and manipulate data. Most importantly, we will introduce the active and exceptionally helpful online Python community, so that once the workshop is over everyone will be able to get good answers on their own to questions about how to do stuff in Python. By the end of this workshop, everyone will get this “joke”: Real programmers count from 0. Please install Anaconda, which includes the spyder application for using Python.
Link to Anaconda: https://www.anaconda.com/products/individual
Pre-registration: A Tool for Improving Transparency and Replicability of our Science: The replication crisis and the subsequent meta-science movement suggest that the replicability of published findings is not ideal. One of the key causes to the replication crisis is related to questionable research practices. For example, p-hacking, cherry-picking, and data dredging refer to practices where researchers selectively report significant results after conducting many statistical tests. To address this, meta-scientists have proposed pre-registration – the pre-specification of data collection and analytical plan prior to implementing a study – as a potential solution. In this workshop, I will overview the advantages of pre-registration, address common criticisms of pre-registration, introduce the components in a pre-registration, outline the steps to pre-register a study on Open Science Framework, and discuss how to write up a pre-registered study. To reach a wider audience, I will also discuss the different considerations in studies using primary data (i.e., data that your research team collects) and secondary data (i.e., existing data). Researchers at all levels who conduct studies using quantitative methods are welcome to attend. To get the most out of this workshop, you are especially encouraged to prepare a soon-to-be-implemented and original study idea so we can try pre-registering your study together!
Studying the Social World in Situ: An Introduction to Ethnography: Join Sociology Professor Emine Fidan Elcioglu and Ph.D. student Sophie Marois in a conversation about ethnographic methods in the social sciences. Their workshop will build on Fidan’s ethnographic research about race and immigration politics at the US-Mexico border (2011-2012; 2017), as well as Sophie’s participation in a collective ethnography of the trial for the Québec City mosque shooting at the Superior Court of Québec (2018-2019). The workshop will follow the trajectory of both research projects, from gaining access to the field to writing and publishing ethnographic work—with a common focus on participant observation in politically contentious settings. Comparing and contrasting these research experiences will shed light on different ways to approach and design ethnographic fieldwork, illustrating the strengths and challenges of this form of data collection.
Digital Data Collection in Hard-to-Reach Settings: A Hybrid Remote-Participatory Approach:
Part 1: Presentation & Q&A (1 hr)
This workshop will engage participants in the growing domain of digital data collection methods in qualitative research, with a focus on hard to reach settings. The workshop will open with a presentation on a recent research project based in the Dzaleka Refugee Camps in Malawi. Project data collected was conducted entirely through a hybrid remote and participatory approach, also adopting and adhering to anti-oppressive methodologies. The focus of the study is on the role of technology in the lives of refugees in Dzaleka, with a focus on teaching and learning environments. The project team included two Canadian Faculty, two doctoral students, and six community researchers – men and women who live as refugees in Dzaleka. The presentation will outline in some detail the process of building a project like this, training community researchers, managing data collection and storage, and critically considering the various moments when power dynamics infiltrate team dynamics and the research agenda.
Part 2: Research Case Studies (1.5 hrs)
Participants will be provided with case study scenarios derived from the study and put into small groups/breakout rooms to discuss how to proceed through the challenges of the study contexts. In doing so, small groups will be asked to present their solutions, debates, and considerations to the full workshop. These case studies are designed to open what are always difficult discussions about power, privilege, coloniality, and oppression in this type of global research study, further complicated by digital data collection and remote team building.
Data Visualization and Data Exploration using R: This course is about visualizing data. There are three main reasons for visualizing data: exploring, understanding, and explaining. This course is for anyone working with data, whether a little or a lot of it. We will be using the programming language R and the ggplot package, familiarity with R will be helpful. We will learn about different types of plots and what each are good for displaying. We will learn about the ways to include more variables in the same plot as well as using grids of multiple plots. We will focus on exploring data but also talk about visually presenting analysis results.
Digital Solutions for Qualitative and Archival Data Management: Data management and organization is an integral but often overlooked component of any qualitative or archival research project. As data accumulate, research files become numerous, excessively large, disorganized, and burdensome, which complicates research production, analysis, and publication. Drawing on techniques used in the organization and analysis of an oral history project currently in progress, team members from the LGBTQ Oral History Digital Collaboratory will demonstrate digital solutions for qualitative data management in two parts: 1) a universal, step-by-step guide for file management that prioritizes quick retrieval and ease of access for research conducted independently or collaboratively; 2) an introduction to NVivo, a qualitative data management software that extends data organization toward collective file analysis. The strategies and tools covered in this workshop will support file management for those starting data collection or those retroactively managing unruly file sets. Bring your data for an opportunity to experiment with these techniques. Participation does not require access to, or previous experience with, NVivo.
Dr. Felix Cheung, Canada Research Chair in Population Well-being, seeks to promote a satisfying, purposeful, and engaging life (i.e., subjective well-being) based on sound empirical research. The first line of his research examines the determinants, consequences, and policy relevance of subjective well-being across diverse populations, with a focus on addressing pressing global issues (e.g., sociopolitical unrest, income inequality, and terrorism). His studies involve over 8 million participants based on large international datasets (e.g., Gallup World Poll) as well as diverse representative samples of participants (e.g., Syrians living in Syria during the civil war). His second line of research focuses on meta-science (the scientific study of science) and examines how the reliability of scientific findings can be potentially improved by ‘Big Science’ (i.e., studies done by large collaborative teams), open science practices (e.g., pre-registration and data sharing), and research incentives. Dr. Cheung has more than 10 years of experience with pre-registration, including a large-scale collaboration that results in a publication in Science that estimated the replicability of psychological research with a collection of 100 pre-registered replications.
Dr. Negin Dahya is Assistant Professor at The Institute of Communication, Culture, Information, and Technology (ICCIT). She is the appointment Special Advisor for Equity, Diversity and Inclusion, Office of the Dean, University of Toronto Mississauga. Dahya’s research focuses on refugee studies and migration, women, and technology in the context of learning. She adopts postcolonial theory and feminist science and technology studies to understand the social and cultural complexities of women’s lived experiences with technology. Dahya’s decade of experience working with refugees in camps has focused on sub-Saharan Africa, particularly in the Dadaab, Kakuma, and Dzaleka refugee camps. In addition, Dahya has worked extensively with girls and women of colour, and recently with incarcerated youth, in the context of youth media education research. Dahya has published in American Educational Research Journal, Comparative Education, Information, Communication and Society, Journal of Documentation, among other venues. More information about her work can be found at www.negindahya.ca.
Dr. Alicia Eads is Assistant Professor in the Department of Sociology and is cross-appointed with the University of Toronto’s Centre for Industrial Relations and Human Resources. She received PhD in Sociology from Cornell University and a BA in Sociology and Psychology from the University of Iowa. Her research uses computational and qualitative methods to understand how cultural meaning affects economic and political processes, particularly within the context of organizations. Recent work has focused on the policy response to the housing market collapse in the United States.
Dr. Emine Fidan Elcioglu is Assistant Professor of Sociology at the University of Toronto. She is the author Divided by the Wall: Progressive and Conservative Immigration Politics at the U.S.-Mexico Border (University of California Press, 2020), a finalist for the Society for the Study of Social Problem’s prestigious 2020 C. Wright Mills Award. At the intersection of political sociology and migration studies, Professor Elcioglu’s research examines how citizens make sense of non-citizenship and national gatekeeping.
Tara Henechowicz is a Ph.D. candidate in Music and Health Science and in the Collaborative Program in Neuroscience at the University of Toronto. Tara is an interdisciplinary researcher has experience in using various statistical softwares (primarily R) to work with a variety of data including but not limited to behavioural data, surveys, clinical research, and genomics.
Sophie Marois is a Ph.D. student in Sociology at the University of Toronto. Her research interests are situated at the intersection of political sociology, race studies, and the sociology of punishment. She holds a Master’s degree in Sociology from Laval University (Québec City), as well as a Bachelor’s degree in Sociology from the same university. She has experience with a variety of qualitative methods, including in-depth interviews, documentary research, and ethnographic fieldwork.
Emily Mastragostino is a PhD student in Counselling and Clinical Psychology at the Ontario Institute for Studies in Education (OISE) in the University of Toronto. From a positive psychology lens, Emily’s research focuses on investigating the ways in which marginalized communities cultivate wellbeing, despite institutional and social barriers. Currently, Emily is coding 30+ narrative interviews for the LGBTQ Oral History Digital Collaboratory’s Pussy Palace Oral History Project. Through the coding process, she identifies and organizes themes in the lived experiences of organizers, patrons, and community members involved in the police raid of the 2000 Pussy Palace bathhouse event. She holds an MA in Counselling and Clinical Psychology from the University of Toronto and a BA (Hons) double major in Psychology and Humanities, with a research background spanning classic quantitative methods to participatory, arts-based, qualitative approaches.
Justin Savoie is a PhD candidate in Political Science at the University of Toronto. His current work uses models of natural language to examine how politicians and citizens talk about political matters, with a particular focus on the Canadian context. He has co-authored peer-reviewed work on public opinion, political behaviour, and citizen forecasting; more broadly his areas of interests include computational social science and Canadian politics. In addition to his academic work, Justin has worked as Data Science Lead with Vox Pop Labs, a social enterprise that builds survey-based applications organizing political and social data in meaningful ways. At Vox Pop Labs, he was leading all data science activities for projects such as Vote Compass, Australia Talks, and the COVID-19 Monitor.
Alisha Stranges is the Research Manager for the LGBTQ Oral History Digital Collaboratory, UTM Historical Studies. She holds an MA in Women & Gender Studies (2020) from the University of Toronto, with a collaborative specialization in Sexual Diversity Studies and a Diploma in Theatre Performance (2006) from Humber College. In January 2021, Alisha joined the LGBTQ Oral History Digital Collaboratory as the Project Manager and Co-Oral Historian for the Pussy Palace Oral History Project. As lead interviewer, Alisha has collected 36 narrator accounts surrounding the September 2000 police raid of the Pussy Palace bathhouse events. She supervises a 5-member team in the preservation and creative activation of these interviews and is responsible for organizing and managing all research data and archival materials that accumulate throughout the life cycle of the project. Currently, Alisha also serves as the Collaboratory’s Research Manager, supporting Collaboratory director Dr. Elspeth Brown in the planning, development, and execution of concurrent projects.
Catherine Yeh is a PhD student in Sociology at the University of Toronto. Her research interests are in the areas of the sociology of culture, gender, and economic sociology. She is currently working on a project that analyzes economics and sociology journal text data; this project was what motivated her to learn Python. Through her own experience of learning Python, she understands the challenges of learning coding as a non-coder as well as how Python can be useful to social scientists specifically.