This is the first post in what I hope will be an occasional series of posts on research broadly titled ‘Some thoughts on research’ in which I’ll draw on relevant literature and my own knowledge and experience. This initial post will draw on some ideas from philosophy of science.
An interesting starting point for this initial post is Richard Feynman’s famous assertion that “philosophy of science is as useful to scientists [or researchers, more broadly] as ornithology is to birds.” It’s not uncommon for practising researchers to effectively ask ‘Philosophy, who needs it?’.
This is a perspective I have often heard expressed and which I have some sympathy with. Sometimes people I’ve worked with have also expressed concerns about ‘analysis paralysis’ if we dwell on ‘philosophical’ complexities. It’s an understandable point. In one recent project I spent about 18 months grappling with the term ‘institution’ and what specific social entities or phenomena the term is meant to refer to in a study which sought to examine institutional decline. I’m not the only one struggling with this: philosophers of the social sciences are still arguing about the meaning of the concept of a social ‘institution’ and its referent (i.e. what real thing[s] it may, or may not, refer to). But in our empirical research and analysis we had to formulate or work with some provisional ideas and push on. I struggled with the conceptual and theoretical uncertainty and our need to operationalise vague concepts.
In my experience activists very often also have little time for philosophy, particularly philosophy of science. This is also somewhat understandable. To give one illustrative example, philosophers of biology are still arguing about the meaning of the term ‘species’ and what units of the natural world the term may refer to. One prominent philosopher of biology, Peter Godfrey-Smith, even argues that “species are not real units in the natural world”. Yet, at the same time, we are routinely exposed to statistics tracking the number of species extinctions and the number threatened with extinction (with such statistics presuming an unambiguous objective definition which can be tracked in the real world). Is it possible to combine a concern for, and/or an interest in, the problems and mysteries that animate philosophers whilst also being action oriented? Or is it necessary, in contrast, to “park” any such philosophical concerns in the context of activism?
I have more time than most for philosophy of science. I think there can be benefits from giving the ideas and worries of philosophers some more thought than we may initially be inclined to give them (though this may not always be practicable).
In the present post I mainly have in mind the context of empirical social research, but other forms of inquiry could also be considered. One idea is that philosophy of science can alert us to complexities and problems which might otherwise be given inadequate attention. As others have argued, it can be also a bulwark against unjustifiable certitude (which may be seen as a negative in some contexts) and a warning about the potential for harms fuelled by certitude. Philosophers of science sometimes also offer potential ‘solutions’ to the problems they highlight, though such problems may not be fully solvable (hence the inverted commas). These ideas may be useful either prescriptively or when evaluating practice. Finally, philosophers of science way into broader debates about knowledge and research which are relevant to social research (e.g. epistemological debates, etc.).
Below I’ll briefly consider one problem which is prominent in philosophy of science and ideas developed by a philosopher of science (Helen Longino from Stanford University).
The underdetermination problem
One version of the underdetermination problem has been mostly strongly articulated by Helen Longino. Her version of this problem is about the relations between theories and the evidence that’s available for them. The basic idea (or claim) is that – except in special cases (such as empirical generalisations) – data underdetermine hypothesis evaluation. A related claim is that there is no formal connection between theoretical hypotheses and the empirical data which gets brought forward as evidence (for the theoretical hypothesis).
More formally, she asserts that underdetermination is “the in-principle possibility of constructing multiple empirically equivalent, mutually inconsistent theories for any given body of evidence” (Longino 2002).
Longino argues that scientists (or researchers, more broadly) rely on background assumptions when dealing with the underdetermination problem. These assumptions are “beliefs in light of which one takes some x to be evidence for some h and to which one would appeal in defending the claim that x is evidence for h” (Longino, 1990). Longino further argued that these assumptions can be substantive (e.g. ontological assumptions, processual assumptions) or methodological. She is not the only philosopher to emphasise these assumptions: for example, philosophers of the social sciences have also emphasised the role of such background assumptions in empirical social research (e.g. link).
Longino further asserts the following about background assumptions used by researchers: 1) assumptions-in-use are a function of consensus in a particular community; 2) background assumptions are typically learned by researchers during their apprenticeship; and 3) background assumptions tend to be largely invisible to practitioners.
My own experience suggests that researchers don’t need to go through a formal apprenticeship to pick up such assumptions. In my own doctoral research I didn’t receive or undertake an apprenticeship. Instead, my assumptions were learned as I read widely and gradually internalised background assumptions from material I’d read. For example, I read about causal inference and ideas about causality in the social world (e.g. I read work by Daniel Little and others on causal mechanisms theory) and identified some prevailing ideas in social research which gradually got incorporated into my guiding conceptual framework. I learned about what might be considered “paradigm examples of successful research” (Little, 2015) and I tried to figure out ways of emulating them that made sense in my own research project. This was a highly stressful process to go through as a novice researcher: a formal mentor-apprentice style relationship in which I was inducted into particular mode/form of research would have been a better process (or, at least, far less stressful).
Longino draws on her arguments about underdetermination when making claims about the deep sociality of scientific knowledge and proposing an epistemological theory she calls critical contextual empiricism. Critical contextual empiricism acknowledges social forces, emphasises the roles of social processes, and notes the ways that scientists inherit methods, concepts, and standards from a community. I’ll note a few ideas below.
Longino’s critical contextual empiricism
Interestingly, Longino doesn’t think that objectivity is impaired by social influence. Instead, she contends that social forces and interaction assists with ‘securing firm, rationally based knowledge’ (Longino, 2002) – rather than being a cause of bias or irrationality – and she terms her social epistemology perspective ‘critical contextual empiricism’. Some of the arguments in my thesis are contrary to this, but she does emphasise particular conditions on such social interactions which may have been missing in the focal case I studied.
In particular, Longino strongly emphasises the importance of critical discursive interactions in justification, thereby making epistemology much more social. Related to this, she is well-known for specifying a set of norms that she believes are important for knowledge-producing communities such as having recognised avenues for criticism and related agreed venues for critical interaction.
Three related claims are that:
- background assumptions must be subject to broad critical debate;
- assumptions shared by all members of a community will be shielded from criticism (a point that suggests a necessary role for outsiders, in some instances); and
- justification requires critical discursive interaction (in addition to other element such a logical relations) examining key assumptions structuring the reasoning or inferences being made.
Philosophers like Longino try to elaborate formal conditions on social interaction which they argue are necessary for performing such epistemic work (see her related books such as Science as Social Knowledge [Longino, 1990] and Fate of Knowledge [Longino, 2002]).
Heady, complicated stuff (that I’ve only just vaguely outlined)! But it is interesting to think about regarding solutions to the underdetermination problem (including how these are formed or used), and regarding knowledge-producing communities and activities.
Related thoughts on research (including my own)
When I was doing my doctoral research and preparing my dissertation I didn’t explicitly think about the transformation of data in the ways I’ve outlined above, nor did I fully appreciate the potential centrality of background assumptions during this process and the defence of claims (I hadn’t read Logino’s works on the underdetermination problem). The texts on qualitative data analysis I reviewed also didn’t critically discuss the processes by which data is given a new status as evidence nor the relations between theories and the evidence that is available for them. Material that I read tended to be handwavy.
Nonetheless, I did come to see some of the data I had collected as relevant evidence for specific explanatory claims. However, I largely fumbled my way towards these interpretive decisions and related justificatory reasoning via a highly iterative process and I expected to receive criticism. (To my great surprise none was forthcoming in the thesis examination, so perhaps my justificatory reasoning was judged to be sufficiently persuasive).
Related to this, two potential benefits of philosophy of science are that it can help to make what we’re doing implicitly much more explicit and it can problematise these activities. In doing so it makes arguments about what it means to do such things well (or poorly) which can be drawn upon when managing and evaluating knowledge practices.
Additionally, epistemological theories and frameworks like Longino’s ‘critical contextual empiricism’ can point us towards deeper consideration the constitutive roles of social interaction and necessary conditions on (potentially) generative interaction.