The ‘science’ component of the social sciences is often the subject of jokes, with the idea that disciplines included in this label are not ‘real’ or ‘hard’ sciences. Their defenders are often quick to argue, however, that the quantitative tradition is a prevalent one among disciplines such as economics, demography, or political science.
In my own field – sociology – the scientific legacy has its roots in positivist thinking, most notably endorsed by pioneering figure Auguste Comte, who sought to provide a scientific way of explaining the social world. Arguably one of the ‘founding fathers’ of sociology, Emile Durkheim similarly pushed for society to be studied scientifically, and his Rules of Sociological Method were based on the measurement of ‘social facts’ existing independently and externally to individuals within society. Durkheim’s work was highly influential in studying sociological questions empirically, notably through the use of large-scale statistics to measure patterns of causality among different societies, a tradition which proved highly important in making generalizable claims.
While I do not deny the value of such methods, my point is that they do not and should not be perceived as the ‘gold standard’ in research methodology, while qualitative research is all-too-often set aside, seen as a less rigorous, second-order instrument
This empirical legacy still plays a major role today in sociology and other social sciences, and has produced a rich array of studies pointing to causal patterns in the so-called ‘soft sciences’. While I do not deny the value of such methods, my point is that they do not and should not be perceived as the ‘gold standard’ in research methodology, while qualitative research is all-too-often set aside, seen as a less rigorous, second-order instrument. Indeed, another pioneering figure in the discipline of sociology – Max Weber – formulated his own anti-positivist lens on sociological research, arguing for the value of interpretation or Verstehen of social phenomena. This interpretative tool provides richness to sociological inquiry, delving into a realm which by definition is unstable, unpredictable, and fluctuating.
While a ‘cultural turn’ has occurred in the field of British sociology in the past decades, away from detached numbers measuring social life and towards the study of experiences which give it colour and shape, statistics are still imbued with authority, treated as concrete, factual data. As good social scientists, our task should be to choose the appropriate methodology based on its suitability for a given research question, and de facto setting aside qualitative research as lacking in perceived value goes against this rigour.
The turn to figures and indicators can lead to the domination of expert knowledge over lay narratives, thus laying the terms for power relations favouring facts over experience.
Oxford is one such place, where the emphasis on causal mechanisms, analytical sociology, and econometric models, making it hard for qualitative researchers to feel at home, and in fact, very few students and faculty members choose this route. While I am glad to have deepened my understanding of statistics and quantitative methods, my own interests feel at odds with a department whose focus makes little room for interpretive sociology.
The seductive power of quantification, moreover, is not without its dangers, as the turn to figures and indicators can lead to the domination of expert knowledge over lay narratives, thus laying the terms for power relations favouring facts over experience. Beyond sociology, this is increasingly the case in the realms of human rights, global governance, and development, where economic and business models have crept into societal objects of study.
Quantification has also been charged with ‘making up’ the world it purports to measure, as people and things are placed into categories made in the process of labelling. To point out the philosophical and ontological questions triggered by quantification is not to say that qualitative research is devoid from such implications itself. In the social constructionist view, neither qualitative nor quantitative research – when employed to measure a field as complex and multifaceted as the social world – can claim to be fully objective. Rather than claiming a superiority of one type of research over the other, my aim is to outline the unique value of qualitative research, as a tool to explore those intricacies of human experience which cannot be captured by numerical measures.
For example, social class is a concept which can be measured in a number of ways. While quantitative researchers tend to favour economic and occupational dimensions, qualitative sociologists are more prone to examine cultural aspects of class identity. These axes may overlap to form a composite definition of social class, but choosing to focus on one or the other serves different purposes. While the former is useful if one’s aim is to measure social mobility, or occupational outcomes; the latter can inform us on the subjective experiences of living according to a class identity, and in Bourdieu’s terms (regarded with contempt by Oxonian sociologists) the habitus embodied by members of a given class.
While this may seem a futile exercise to researchers seeking to generalise concrete patterns to a given population, I would argue that qualitative research has its own distinctive purposes and worth. Identity forms a core component of our lived experiences, and in themselves are a worthy subject of study for the researcher seeking to understand the social world.
My point is that the social sciences deal with a domain which by definition cannot be detached from the nuances and experiences of the individuals that compose it. Quantifying ‘objective’ components of that world, therefore, paints only a partial portrait of the multidimensionality of human experience, ignoring the layered richness of the societies they seek to measure. Rather than disregard qualitative research as inferior to its quantitative counterpart, as good social scientists, we ought to recognise the value of both, and accept that each fits different purposes, and different research questions.
Picture Credit: Bill McConkey, https://www.europeana.eu/portal/en/record/9200579/kmtfzsvk.html?q=ideas#dcId=1552928982809&p=1
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