Attempting to draw some lines in the academic sphere, within which I can get cozy, dive deeper, attempt to keep up with everything within those bounds, largely to stop myself from pursuing every shiny object.
This writing exercise is going to sound unusually precise for such an early-career researcher, but I have enough professional experience that “early-career” doesn’t strictly apply to me. My approach to building a research career is naturally going to be different from that of a twenty year old who’s going straight from high school to college to grad school. For one, I’m going to be aggressively focused on what I want, and may not be as interested in exploratory experiences. There’s a trade-off, but I’m working with limited time resources, so I know exactly what type of researcher I want to be in a few years from now. In other words, I don’t have the luxury of not knowing.
In terms of methods, I’ve learnt very quickly that I cannot rely on fieldwork being a core part of my work. I live in the US, and my interests are all in South Asia. Unless I work with local partners (funding?) I have to be careful not to make this central to my research. Luckily, I have strong computational and data skills, and now need to hone my statistical skills to potentially be a quantitative researcher with qualitative interpretive skills.
Quant was generally not so exciting to me because I as expecting this path to lead to lots of empirical work, and not enough strength in theory-building. Or perhaps I was looking in the wrong circles. I have since come to understand that quantitative researches in the social sciences are given an extra touch of credibility in their theoretical interpretations because their ideas are oh-so-empirical. From where I stand, I may as well recognize the playing ground and prepare to leverage it.
So far, this means my methods scope is limited to quantitative methods. Great to have this clarity. I can spend a lot of time learning more about the nuances of quant methods in the social sciences.
There are many other parameters of scope definition I’m going to find useful to put in place earlier than later. I’m interested in anything technology x society, and excited by the effects on gender, labour, economics. Particularly, I’m drawn to studying the extent and limits of government power to regulate tech, not to mention how governments themselves leverage or weaponize tech policy.
The fascinating thing about sociology is that you get to study the intra-personal, inter-personal, micro, meso and macro dimensions of nearly any phenomenon, and they’re all going to enrich theory-building. Here, I enjoy making connections across the whole range, and don’t necessarily want to pick a specific scale, but if I had to, I’d pick international relations. What is that, more macro than macro?
Restating these thoughts in more material terms in the next section:
I want to study how digital technologies reshape economic life and institutional power, particularly in the majority world. My current focus is on India, though I’m drawn to comparative global work that puts different contexts in conversation. It’s very clarifying for me to explicitly call out where I want to develop scholarship.
Substantive areas: platform labor and algorithmic management, fintech and the digitization of financial services, government technology and citizen-state relations, the political economy of automation. I’m especially interested in how regulatory frameworks struggle to keep pace with technological change, and who wins and loses in that gap.
Methods: I’m comfortable with computational approaches (working with large datasets, building scrapers, quantitative analysis) and spend a lot of time thinking about how to pair these with interpretive frameworks. I can work with qualitative data, but I’m not currently doing ethnographic fieldwork. Open to online interviews and remote methods when human subjects research is needed.
What I want to learn more about: comparative institutional analysis, deeper engagement with STS and economic sociology theory, sharper quantitative skills for causal inference, and how to write for both academic and public audiences without losing rigor in either.
What I bring: twelve years of industry experience (fintech, edtech, design leadership), fluency in moving between building things and critiquing them, and a genuine obsession with understanding how systems actually work beneath the surface.
I didn’t know what I’d get out of this writing exercise, but looks like I’ve just written myself a scope document for doctoral studies, or a research manifesto, if you’ll permit me some romanticism.