Tag: social science

Some of the social research and evaluation papers I encounter include declarations of the authors’ metaphysical stance: social constructionist, realist (critical or otherwise), phenomenologist – and sometimes a dig at positivism. This is one way research and researchers are classified. Clearly there are different kinds of research; however, might it be easiest to see the differences in terms of research goals rather than jargon-heavy isms? Here are three examples of goals, to try to explore what I mean.

Evoke empathy. If you can’t have a chat with someone then the next best way to empathise with them is via a rich description by or about them. There is a bucket-load of pretentiousness in the literature (search for “thick description” to find some). But skip over this and there are wonderful works that are simply stories. Biographies you read which make you long to meet the subject. Film documentaries, though not fitting easily into traditional research output, are another. Anthologies gathering expressions of people’s lived experience without a researcher filter. “Interpretative Phenomenological Analyses” manage to include stories too, though with more metaphysics.

Classify. This may be the classification of perspectives, attitudes, experiences, processes, organisations, or other stuff-that-happens in society. For example: social class, personality, experiences people have in psychological therapy, political orientation, emotional experiences. The goal here is to develop patterns, whether from thematic analysis of interview responses, latent class analysis of answers on Likert scales, or some other kind of data and analysis. There’s no escaping theory, articulated and debated or unarticulated and unchallenged, when doing this.

Predict. Do people occupying a particular social class location tend to experience some mental health difficulties more often than others? Does your personality predict the kinds of books you like to read. Do particular events predict an emotion you will feel? Other predictions concern the impact of interventions of various kinds (broadly construed). What would happen if you funded national access to cognitive behavioural therapy or universal basic income? Theory matters here too, usually involving a story or model of why variables relate to each other. Prediction can be statistical or may involve gathering views on expert opinion (expert by lived experience or profession).

These goals cannot be straightforwardly mapped onto quantitative and qualitative data and analysis. As a colleague and I wrote (Fugard & Potts, 2016):

“Some qualitative research develops what looks like a taxonomy of experiences or phenomena. Much of this isn’t even framed as qualitative. Take for example Gray’s highly-cited work classifying type 1 and type 2 synapses. His labelled photos of cortex slices illustrate beautifully the role of subjectivity in qualitative analysis and there are clear questions about generalisability. Some qualitative analyses use statistical models of quantitative data, for example latent class analyses showing the different patterns of change in psychological therapies.”

What I personally want to see, as an avid reader of research, is a summary of the theory – topic-specific, substantive theory rather than metaphysical – that researchers had before launching into gathering data; how they plan to analyse the data; and what they think about the theory when they finished. Ideally I also want to know something about the politics driving the research, whether expressed in terms of conflicts of interest or the authors’ position on inequity or oppression investigated in a study. Reflections on ontological realism and epistemic relativity – less so.