Perfect amount of generalization

Luker’s section on generalization was very helpful in shedding some light on how to eventually make claims based on research findings. While writing my SSHRC proposal (which was based on my MI Thesis proposal), I found myself panicking over whether I was moving off-track with my suggested method of conducting email interviews of a handful of people. I decided on the number of people to interview based on various papers written about the ‘ideal’ number of interviews/the perfect sample size etc. However, when I finally sat down and wrote my proposal, I suddenly became unsure of how I would eventually make sense of the data I had collected. Would it really represent a real-world phenomenon? How would I differentiate my research findings as a real description of something that really happens vs my personal opinion/perspective about something that happens? Essentially, I was worried about convincing people that I had enough evidence to ‘generalize’ and describe something as a real-world situation.

I thought Luker’s explanation about situating research findings at the same level of abstraction with other comparable studies very helpful in addressing my concerns about generalizing and making sense of the data collected. Luker’s final remark essentially summed it up for me – I learned that I need to generalize ‘theoretically”... “ to see how our findings illuminate, contradict, extend, or amplify existing theory.” This idea helped me  realize that I don’t necessarily need to explain everything about my little area of research – rather focus on explaining ‘what’ is happening, and ‘how’ it is happening. Within the limited scope of the research questions I tend to answer through my Master’s thesis, I don’t necessarily have to try to explain ‘why’ things happen in a certain way – I can instead focus on choosing a level of abstraction already explored and situate my ‘what’ and ‘how’ on that level of comparison.