Investigating Interdisciplinary
Practice: Methodological
Challenges (Introduction)
Miles MacLeod
University of Twente
Martina Merz
University of Klagenfurt
Uskali Mäki
University of Helsinki
Michiru Nagatsu
University of Helsinki
Interdisciplinarity (ID) is one of the most prominent ideas driving science
and research policy today.1 It is applied widely as a conception of what
particularly creative and socially relevant research processes should consist
of, whether in the natural sciences, the social sciences, the humanities, or
elsewhere. Its advocates, many of whom are located in current science and
research administration themselves, are using ideas of interdisciplinarity to
reshape university organization and research funding. For the last 40 years,
researchers studying interdisciplinarity have built up a substantial body of
literature constructing various visions of what it should be and how to tax-
onomize the different forms it can take, putting a distinct emphasis on a
theoretical approach to conceptualizing and understanding interdisciplin-
arity. However, the need for empirically substantiated knowledge has only
1.
See for instance high-level policy reports: National Science Foundation (2008),
Impact of Transformative Interdisciplinary Research and Graduate Education on Academic Institu-
tions, Workshop Report; National Academy of Sciences (2006), Facilitating Interdisciplinary
Research. Report; European Union Research Advisory Board (2004), Interdisciplinarity in
Research. Each report places a strong imperative on interdisciplinary research and promoting
the kinds of institutional regimes needed to support it. The European Research Council,
among others, explicitly targets its funding at interdisciplinary projects. In addition, count-
less papers have been written advocating the importance of interdisciplinarity (see partic-
ularly the notion of Mode 2 science, Gibbons et al. 1994; Nowotny et al. 2001).
Perspectives on Science 2019, vol. 27, no. 4
© 2019 by The Massachusetts Institute of Technology. Published
under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
doi:10.1162/posc_e_00315
545
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Introduction: Investigating Interdisciplinary Practice
recently attracted wider attention (see Huutoniemi et al. 2010; Klein
2000, 2017). Moreover, our understanding of what the critical constraints
on interdisciplinary interactions are is very limited, even though this
knowledge is very relevant to the rather strong expectations associated
with ID. Interdisciplinary approaches to knowledge production may
indeed be beneficial for tackling certain problems such as the systemic un-
certainties and ethical issues addressed within the realm of “Responsible
Research and Innovation,” which matches ID agendas in many ways (see
Wickson and Carew 2014). At the same time, it is far from clear whether
and to what extent the theoretical representations of ID given in inter-
disciplinary studies, science policy, and other areas of scholarship actually
match what is happening, or if they are even possible in practice (see
MacLeod and Nagatsu 2018).
Interdisciplinary interactions in science are challenging—in many cases
more situated, distributed, and dynamic than within-discipline inter-
actions. They take many forms and varieties, from the occasional transfer
of models and methods across disciplinary boundaries to the resources of
one field being used for criticizing assumptions in another (Mäki 2013,
2016). Interdisciplinarity can also be a matter of intensive ongoing collab-
oration addressing complex problems with novel approaches. This type of
collaboration requires negotiation of epistemic standards, trust and reliabil-
ity, the coordination of expertise, and the distribution of tasks. Interdisci-
plinarity is thus a multidimensional and multi-scale phenomenon
involving a rich interplay of established and novel scientific methodologies,
expert and social cognition, disciplinary preferences and values, academic
pecking orders and extra-academic pressures, historical relationships, and
institutional and policy frameworks. Understanding how these interactions
unfold does not seem to be based on strict regularities enabling reliable
anticipation in advance, but rather requires empirical investigation that
provides systematic ways of tracking various aspects of the process.
In this special issue2 we thus advocate a much more concerted effort to
empirically observe, document, and analyze interdisciplinary practices. We
believe that, at this point, it is important to step back and shine the torch
on the different approaches committed to such empirical analysis within
science studies of different orientation (History and Philosophy of Science,
Science and Technology Studies, and others). In particular, we ask what
different methodological perspectives have on offer, and what they each
2. This special issue builds on the Workshop “Investigating Interdisciplinary Practice:
Methodological Challenges” that we organized at the University of Helsinki 15–17 June
2015 with the financial support of the Academy of Finland. Earlier versions of two of the
three chapters were presented at the Workshop as invited lectures.
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Perspectives on Science
547
can contribute to our knowledge of ID, but also to our evaluations and
expectations of it. This is important insofar as there is evidence that many
interdisciplinary relationships fail (MacLeod 2018).
A comparative analysis of this kind needs to begin by noting that meth-
odological approaches and the phenomena under investigation are not in-
dependent but shape one another, in different ways. Two directions in this
relationship can be identified. On the one hand, the selected methodolog-
ical approach and associated method(s) frame the phenomena under inves-
tigation in particular ways, rendering visible certain features while hiding
others. Consider an example. Reflecting on qualitative interviews, Lamont
and Swidler (2014) emphasize the merits of qualitative interviewing, e.g.
when compared to ethnographic approaches, while they also identify a
number of blind spots. In their view, qualitative interviews are less suitable
for in-depth consideration of the historical dimension and of limited use
only when analyzing institutional patterns (Lamont and Swidler 2014). In
similar ways, alternative methodological approaches each have their affor-
dances and limitations. An ethnographic approach to science is particularly
apt for in-depth exploration of embodied skills and step-by-step recon-
structions of knowledge generation (cf. the laboratory studies approach
in STS, e.g., Knorr Cetina 1995). Scientometric studies can trace large-
sized networks of ideas and researchers while being sensitive to change
in time as well as to the specificity of fields. Qualitative historical analyses
can counter premature claims to novelty, progress and singularity without
downplaying the specific features and affordances of different contexts
considered over time. In a similar vein, as this Special Issue will show, dif-
ferent methodological perspectives can and do generate distinct narratives
about interdisciplinarity and, in this process, configure the object of inves-
tigation in particular ways. Such narratives concern, among other things,
the development, type and role of ID in past and contemporary scholar-
ship, the social forms and epistemic features of interdisciplinary practice,
the practical problems encountered and solutions sought in specific local
contexts or epistemic cultures, and the development of new fields of schol-
arship in interdisciplinary boundary areas.
On the other hand, as a phenomenon of investigation, ID challenges
established methodological approaches and methods. One reason is that
it constitutes a rather ill-defined phenomenon, with its reference to “dis-
ciplines” and what happens between (“inter”) them. Another is that it
concerns a complex body of practices, cognitive structures, and social
forms, which vary widely from one case to another. This calls for a two-
fold reflection: First, what exactly is to be empirically investigated—where
and when is inter-disciplinarity? Second, which approaches are suitable for
addressing the selected “object”? Taking these two questions as guidance,
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Introduction: Investigating Interdisciplinary Practice
we have asked the authors of the three contributions to explicitly address
the methodological challenges raised within their respective empirical
studies and how these were handled, and to provide an insight into their
methods toolbox and methodological considerations.
Our selection covers a range of empirical methodologies, including both
quantitative (scientometric) and qualitative (cognitive-ethnographic, his-
torical) approaches. Each of these have the character of being outside most
of the mainstream discussion on interdisciplinarity in science policy, al-
though scientometric studies are sometimes relied on ( Yegros-Yegros
et al. 2015). But each does provide perspectives that can lead to genuine
novel insights into interdisciplinary practices. Each approach takes the
stance that a purely theoretical or intuitive account of ID is likely to fail
to understand the processes of interdisciplinary research and the outcomes
of funding policy interventions favoring ID. The approaches presented in
this Special Issue have the resources to illuminate at least some aspects of
the complex relationships between institutional contexts and goals, disci-
plinary methodological structures and standards, and problem-solving
environments, which emerge in day-to-day interdisciplinary activity, but
can remain impartial with respect to whether ID is necessary or desirable.
These approaches provide possible methodological options for those
seeking to study ID empirically and critically. To a large extent, they are
not rival options, they rather complement one another in asking different
questions about ID and highlighting different aspects. Our authors have
been asked to reflect on both the necessity and value, and limitations of their
respective methodological approaches for studying interdisciplinary research.
As such, the concept underlying the Special Issue is that of methodo-
logical pluralism (also see Kellert et al. 2006). We do not believe in the
existence of a royal road toward understanding interdisciplinarity, i.e., that
one particular methodological approach be much better suited than all
others for all purposes. At the same time, we are skeptical about the pros-
pects of triangulating methodological approaches in unproblematic ways
aiming at systematic integration of results. Instead, we side with the pic-
ture of a “collage” (Kalthoff 2010), i.e., the idea that the distinct ap-
proaches and corresponding methods “mobilize different relevancies”
(Kalthoff 2010, p. 363, our translation), with the potential of contradic-
ting or irritating one another in addition to complementing each other.
Thereby further investigation is stimulated and, as a consequence, a richer
understanding of interdisciplinary practice is engendered.
Our Contributions
The three papers have been selected to cover a spectrum of methods and
methodologies. The first from Nancy Nersessian introduces an ethnographic
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Perspectives on Science
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approach to the study of ID, in particular a cognitive-ethnographic approach.
STS scholars, by applying an ethnographic perspective, have helped to unpack
many aspects of interdisciplinary relationships (see e.g., Rhoten 2003; Barry
et al. 2008; Haapasaari et al. 2012; Merz 2015). But, typically, such studies
have put aside the nature and structure of the cognitive problem-solving sys-
tems that individuals and groups build out of the background institutional,
material, and epistemological resources they operate with. Studying these cog-
nitive systems requires one to ask questions about the reasoning processes and
practices of individuals, and the role of often distributed representations in
those processes and practices. Cognitive ethnography provides a methodology
and conceptual framework (relying on concepts like distributed cognition and
model-based reasoning) for a fine-grained analysis of such problem-solving
practices. This empirical work seems especially important in the context of
ID, as Nersessian suggests, since it is the coordination or integration of dif-
ferent situated cognitive processes and practices through the construction of
shared representations that characterize interdisciplinary relationships, con-
tributing significantly to their success or failure. In her analysis, Nersessian
discusses examples of interdisciplinary integration in bio-medical engineering.
A second paper from Alan L. Porter and his co-authors proposes an
approach to the analysis of interdisciplinary practice that combines biblio-
metrics with tech mining. The notion of ID underlying such quantitative
analysis refers to the integration of knowledge (bodies of specialized
knowledge, research practices) with a focus on how knowledge is being
interchanged between research fields. Quantitative analyses of interdisci-
plinary research come with a number of methodological challenges and
choices. A first challenge points to the necessity of explicitly addressing
discipline as a precondition for identifying, and thus being able to inves-
tigate, interdisciplinary research. Categorizing disciplinarity of research output
(e.g., a journal article) can be done in several ways. For example, an article
can be assigned a disciplinary category in view of its content (e.g., con-
cepts) or, instead, of its source (e.g., journal). Each level of categorization
has its own benefits and weaknesses, as the authors discuss in detail. A
second challenge concerns the issue of how (the degree of ) interdisciplin-
arity is to be measured in view of particular research concerns. Scores of
integration, specialization or diffusion, for example, each measure changes
in ID in distinct ways. Devising a bibliometric study of this kind thus
requires one to make difficult choices: “The upshot is that the researcher
should not simply apply a standard set of metrics and visualizations to ad-
dress all interdisciplinary research (IDR) questions; rather the data treat-
ment/methods/metrics/visualizations should be tailored to the study’s
research questions” (Porter et al. 2019, p. 600 in this volume). While
the research design needs to be adapted to the particular case addressed, this
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Introduction: Investigating Interdisciplinary Practice
methodological approach has the benefit that it affords wide comparison—
across time and across fields—while addressing the integration of knowl-
edge at different levels of granularity.
The third contribution from Mitchell Ash provides a historical analysis
of interdisciplinary practices. One drawback of current discussion is the
lack of historical perspective on ID, treating disciplines as somehow stable
structures, rather than moving entities. “It should be clear that institution-
alized practices of ID cannot be taken as given, but also need to be histor-
icized. This means that they need to be queried as to the circumstances in
which they came into being, are or are not stabilized, and pass away or
develop in new directions” (Ash 2019, p. 622 in this volume). Taxonomies
or definitions of interdisciplinarity in this regard, which lump together
cases of ID across time, have little analytic use. Disciplines are not perma-
nent structures, but have constantly shifted, and this implies changes to
what counts as interdisciplinary practices and the motivation for it. It
should be noted however that much writing on ID seems to imply that
ID is a new development in science, associated with the Mode 2 knowl-
edge movement that emerged in the mid-nineties in response to modern
environmental and social problems. This feeds the impression that ID
must be singular and transformative. But Ash argues that interdisciplinary
practices as well as policies favoring interdisciplinarity are much older than
this. Historical institutions have favored problem-centered research since
the early twentieth century, the Manhattan project being a major example,
and science has seen plenty of interdisciplinary practice since. Critically, Ash
notes that modern policy movements appear not only to encourage, but to
mandate problem-oriented inter- and multidisciplinarity, with the aim of
shifting funding priorities toward perceived policy imperatives without
asking whether such work actually produces better science or scholarship.
He therefore asks whether such policies have actually produced epistemically
better science or scholarship, or rather created incentives for scientists to
simulate interdisciplinary practices in order to get funding, without engag-
ing in substantive interdisciplinary work. Historical comparison helps to
reveal such disjunctions between modern and historical practices, and helps
to make visible that the shape that ID takes depends very much on context-
specific forces.
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