Scholarly Reflexivity, Methodological Practice, and Bevir and Blakely's Anti-Naturalism

ABSTRACT

Interpretive social science consists of researchers’ interpretations of actors’ interpretations. Bevir and Blakely’s anti-naturalist approach truncates this double hermeneutic, neglecting how researcher identity affects knowledge-making. Moreover, by disappearing methodology and treating methods as neutral tools, the authors miss the significance of methodological practice. In their treatment, an anti-naturalist philosophy is sufficient to produce high-quality interpretive research, even when the methods used are those of large-N statistics or other variables-based approaches. Unfortunately, then, the book is unlikely to create more space for research alternatives to the naturalism that the authors seek to unseat.

Keywords:

• anti-naturalism
• interpretivism
• methodology
• methods
• Mark Bevir
• Jason Blakely

Notes

1 As scholars can be positioned quite differently in disciplinary terms, it is important to recognize how exceedingly difficult it is for any one author or set of coauthors to understand the practices of other academicians across the multifaceted landscapes of the social sciences. For any piece of writing, authors must make decisions about what they include and omit. A common practice in book introductions is to discuss those choices, naming what they have not taken up and why. Bevir and Blakely do not include such a section, so I have no way of knowing whether the failure to include feminist philosophers of science was an oversight or a deliberate decision. I’m not sure which would be worse.

2 The point about interpretations of interpretations has been made by many theorists, among them Alfred Schütz, (1967), Clifford Geertz (1983), Anthony Giddens (1984), and Patrick Jackson (2014).

3 For their historical discussion of naturalism, see pp. 3-8. On pp. 6 and 7, Bevir and Blakely use the terms positivist and positivism in their description of the behavioral revolution in social science.

4 Bevir and Blakely use “anti-naturalism” to refer to “interpretivism.” Even though they draw on widely known works that endorse an “interpretive social science” (e.g., Taylor 1971, Hiley et al. 1991, and Rabinow and Sullivan [1979] 1987), and despite the presence of that phrase in the main title of the book, Bevir and Blakely eschew that legacy, insisting, instead, on anti-naturalism as the preferred term. They are aware of the potential confusion from that choice of label, citing Lincoln and Guba’s (1985) influential methodological treatise, Naturalistic Inquiry, in which “naturalistic” means beginning social scientific research from the everyday lives of the social actors studied—as opposed to its use in the philosophical literature, where it refers to the “overriding authority of the natural sciences over the social ones” (Bevir and Blakely 2018, 19). What Bevir and Blakely do not consider are the implications of the “anti.” In a contemporary context it is awkward—a bit like defining “woman” as “not a man,” telling us what Bevir and Blakely oppose, not what they favor. More important, the “anti” seems inconsistent with the potential fruitfulness of their project, which asks us to ponder: What would our social science and public policy look like with a robust, widespread use of interpretivist practices of research that center on hermeneutical and historical contexts of meaning making?

5 It is a category error to include rational choice theory in this list. Case studies, large-N statistics, surveys, Q-methodology, and ethnography are some of the methods of empirical research that Bevir and Blakely take up. Rational choice theory is, as they recognize, a “heuristic” for theorizing. But a heuristic is not a method of data generation of or from the social world. Like simulations, the “evidence” heuristics provide is about theoretical connections and possibilities. For a contrasting view of rational choice that avoids committing this category error, but also discusses the possibilities of treating rational choice in ideal-typical terms, see Jackson 2011.

6 Here are some of these caveats, emphases added:

… to clarify how social scientists should use these methods [ethnography, mass surveys, and census data] while also remaining cautious of the possibility of naturalist vitiation. (Bevir and Blakely 2018, 89)

But there is nothing about the degree of structuring of an interview that forces researchers to treat reality in a naturalist way. To the contrary, staying aware of the interpretive features of the meanings gathered allows researchers to decide how much or how little to structure their interviews on a purely pragmatic basis. (Ibid., 96)

Both concept formation and explanatory forms [referencing mass survey research and structured interviewing] must remain anti-naturalist, but the method for generating information need not necessarily be rejected even if some caution of use is in order. (Ibid.)

Social scientists are thus free to make use of whatever data analysis tools they choose so long as they guard themselves against naturalist tendencies. (Ibid., 97)

… provided researchers [using random sampling and statistical inference] keep clear of the temptation to impose mechanistic explanations between atomized, essentialized, or reified variables. (Ibid., 99)

[Random sampling and statistical inference can be] accepted as a powerful tool provided social scientists do not mistakenly begin to atomize and correlate such findings. (Ibid., 100)

… under the spell of naturalism, researchers might start treating coded terms like reified, essentialist, or atomistic objects. … Researchers can correct this mistake by always remaining aware of the way their coded categories should be derived from. … (Ibid., 102)

There is no reason why interpretive social scientists cannot make careful and selective use of Q methodology if it helps them … [but they] must also be philosophically cautious and resist the temptation to atomize. … (Ibid., 103)

7 “By itself, the qualitative-quantitative terminology erroneously suggests that researchers using the former ‘don’t count,’ while those using the latter ‘don’t interpret’ their data. As we have pointed out, however, researchers in both philosophical traditions constructing, say, a case study would count and interpret, but with different understandings of what they are doing and what this means for the knowledge they produce. The more appropriate taxonomy today would be one that reflects differences in ontological and epistemological presuppositions, rather than the false and misleading opposition between qualitative and quantitative research” (Schwartz-Shea and Yanow 2002, 480).

8 Bevir and Blakely’s inadequate treatment of this matter may be due to inattentiveness to how the quantitative-qualitative dichotomy gets understood in various disciplines. In some, such as education (e.g., Creswell 1998), “qualitative research” or the “qualitative approach” are used synonymously with interpretivism. John W. Creswell, for example, does not recognize the possibility of positivist qualitative research. For a recent critique of representations of “qualitative research” that fail to acknowledge that it may be based not only on interpretivist presuppositions but also on positivist ones, see Berkovich 2018.

9 They also claim, contra Jackson’s discussion of method and methodology, that “all methods are compatible with one another” (Bevir and Blakely 2018, 94).

10 On the European continent, graduate education takes quite different forms than in the United States. In a number of countries there, interpretivism has been more widely accepted, although the standardization and quantification trends are operative there as well.