For the British Sociological Association‘s 60th annual conference at LSE in April, I volunteered to present at the Postgraduate Forum on life as an early career sociologist working outside academia.
In it, I shared a brief summary of my career history to date, and offered a few hints and tips that I've picked up along the way that I hoped would prove useful for postgraduate students thinking about leaving academia. I've reproduced my presentation here, along with notes for further detail.
My career history in chronological order.
I graduated in 2005 from the University of York with a degree in Sociology. I like to think I gained quite a broad range of sociological theory and began to develop a ‘sociological imagination.’ For me, studying sociology gave me a new breadth of understanding of the world that studying sciences up to that point hadn't provided.
Data Analyst at Aviva
(Or Norwich Union as it was then known). After I graduated I worked for three years as a data analyst and coordinator for the IT division of Norwich Union. I would gather and analyse data and provide it in an accessible and readable format that could be used to make business decisions (typically to start, continue or stop a project). I enjoyed the methods and working with data, but wasn't satisfied as this was mostly superficial analysis and, essentially, made the company more efficient at selling or administering insurance premiums, something I could never get excited about.
MA Social Research
So I decided to return to York to study a postgraduate degree in social research. I wanted to learn more about social research methods—qualitative and quantitative—and sociological theory. It seemed like the natural way to bring together what I'd enjoyed about working in industry and my sociology degree that had largely been gathering dust since I graduated. I handed in my last pieces of work in September 2010 and graduated with distinction in January 2011. Along the way I completed an individual research project, exploring how people with visual impairments travel by train and manage travelling through railway stations and interactions with staff and other travellers.
Senior Research and Intelligence Officer
After handing in (but before formally graduating) I applied for, and got, a job at Lancashire County Council as a senior research officer. I was responsible for conducting and advising on primary research for the council. The research projects I worked on typically asked what services were being used, by whom, when and where, or gauged how Lancashire residents felt about a range of political issues or their area. With this information we could provide suggestions and recommendations to policy makers to meet these needs for services or improve areas. I thoroughly enjoyed the role and the projects I worked on, as it was a safe environment to practise and hone the research skills I'd learned during my course.
Hints and Tips
After that recap of my career to date, I'd like to offer some hints and tips I've picked up along the way.
I've relied on my knowledge of a number of theoretical sociological concepts when conducting and writing up research reports. In particular I have used Robert Putnam's theory of social capital; a broad range of socio-economic inequalities, but including health, employment and education; and adult social care policy. These are important to work with from the point of view of health and wellbeing, resilience, and community cohesion, among other effects.
I've used a range of qualitative and quantitative methods for a number of projects. In particular, I typically used an online or paper quantitative survey or focus groups for qualitative work.
Evidence-Based Policy Making
There is a move towards ‘evidence–based policy making’ in the large organisations for which I've worked. I don't intend to discuss its merits or faults. Instead, recognise this is the reality of working for these organisation and, in principle, it's a good thing. However, one of the effects of this movement is that there is a tendency to measure what's easy to measure, and not necessarily what's best to measure to answer your particular question. Often measuring these ‘wrong’ things is more damaging to the goal than measuring nothing, but so often this is done in ignorance and without proper thought. I see it as my role as a researcher and an ‘expert’ within the organisation to point these issues out and to encourage people to think about what they're measuring in the first instance and, if it becomes necessary, arguing the case that such measurements should not be taken and to suggest alternatives.
Learn to Love Numbers
Following on from this point, most of the evidence and measurements people take are quantitative, and so it is necessary to have a good understanding of numbers to properly analyse and evaluate them. Again, I'm not here to debate the merits of quants over quals (I think it's a shame quals aren't used more; I've seen projects use quants that would have got so much more with quals), this is just the reality. But don't panic. Most of what I do is percentages, tables, and averaging. I would suggest learn to be able to interpret chi–squared tests of statistical significance as the next most used technique. If you can already do this or regression and more advanced statistical analyses, then you have my permission to feel smug.