This summer, I had the amazing opportunity to work alongside Prof. Dietlind Stolle on her two projects concerning the societal and political issues of political affective polarization in Europe, and vaccination polarization in Canada. For the former, I obtained and presented data concerning 17 European countries, on a variety of variables relating to political affective polarization. The second project incorporated many more steps in the academic research process. Dealing with a very recent survey administered in Canada by the CSDC, Prof. Stolle and I began our work to clean, manipulate, graph, and model the data to understand more about the causes and consequences of vaccination polarization. Vaccine polarization refers to the current social opposition between pro and anti vaccination groups, where the common ground between them seems to be thinning out. We study this phenomenon as it is new, and can have dire consequences, both socially and politically, namely regarding new grounds for discrimination and hate. This project was my favourite, as the topic of social polarization, especially regarding COVID vaccines, is very relevant to current events and even experiences of my own.
I was interested in ARIA because I am an avid academic and took great pleasure in completing political science research. When I discovered programming at McGill, I fell in love as well. Research was a clear way to unite these passions. Specifically, I was very intrigued by the realities of data analysis, making sense of thousands of survey responses and experimental results, creating comprehensible graphs and tables out of masses of information, and being able to extract logical conclusions—and even more questions—from it all. Once I realized that academic research ticked all the boxes, I was on a set path to be able to discover this world hands on. It was only natural, then, that I apply, and I was lucky enough to find Professor Stolle to complete this project with. Together, we discussed that I would work on data analysis, data visualization, and all the other components of writing an article, such as literature review, background research, interpretation, writing, and various other tasks.
Going into this program, my objectives were few, but clear. I wanted to gain experience within academic research, to understand the different pieces needed to complete a paper in full, and to learn more about coding in R, where I could be autonomous in dealing with large amounts of uncleaned data. During my internship, I was able to complete these two goals, and gain many skills beyond. I learned how to graph data efficiently, how to deal with missing data, and how to write a clean coding script that can be adapted and used throughout a study. I learned that after the collection of data, there are many important steps, such as viewing the data, its distributions, checking for missing or inaccurate responses, that come long before the first draft of a paper is even considered. I learned that there is a lot of work that goes into fitting one’s paper into its academic field, where previous research has already been done. I learned that a single model on the first try is usually not going to work, and there is a lot of rectifying, cleaning, fixing to do before the results are interpretable at all. These experiences were all extremely gratifying, especially seeing how the first draft of a paper I participated in is taking shape.
These successes could not have been possible, however, with challenges along the way. Fascinated by the coding aspect of research, I greatly struggled with the literary side. Researching articles, summarizing findings, regrouping papers was something I learned to do with great difficulty. Thanks to my supervisor, however, I was able to slowly progress, and am now confident in my abilities to write a literature review. Another part of this program I found challenging was adapting to a work environment where I held responsibilities. This was my first paid position where I needed to contribute intellectually, so I had trouble digesting feedback or constructive criticism. However, over these past few weeks, I learned that making mistakes is part of the process.
At the end of my internship, then, I was very pleased with the work I had put in, and the skills I had gained. I now have the amazing opportunity, thanks to ARIA, to continue working with my supervising professor on the paper on Canadian vaccine polarization. We may even wish to begin another project together in fall. I am very grateful to the generous donor of the Undergraduate Experiential Learning Opportunities Support Fund and ARIA that have given me the tools and the chance to set out on this path towards becoming a researcher. While I am still unsure of my future, I am certain that everything I have gained from this summer will shape my career path.
