By Dena Fam, Julie Thompson Klein, Sabine Hoffman, Cynthia Mitchell and Christian Pohl
The concept of integration is widely regarded as the crux of transdisciplinary research, education, and practice. However, there is no one-size-fits-all approach or methodology. Projects and programs vary in purpose, scale and scope, problem focus, research question, mix of expertise, degree of coordination and communication, timing, and responsibility for integration. Based on findings in a study of integration we conducted (Pohl et al., 2021), we address four common questions to provide insights into transdisciplinary integration as a multidimensional interactive process.
How can local knowledge be effectively and fairly incorporated in transdisciplinary projects? How can such projects avoid “knowledge mining” and “knowledge appropriation” that recognize marginalized knowledge only where it is convenient for dominant actors and their goals? In addition, how can knowledge integration programs avoid being naive or even harmful by forcing Indigenous people into regimes of knowledge production that continue to be dominated by the perspectives of external researchers?
As we enter a new decade with numerous looming social and environmental issues, what are the challenges and opportunities facing the scientific community to unlock the potential of socio-environmental systems modeling?
What is socio-environmental systems modelling?
Socio-environmental systems modelling:
involves developing and/or applying models to investigate complex problems arising from interactions among human (ie. social, economic) and natural (ie. biophysical, ecological, environmental) systems.
can be used to support multiple goals, such as informing decision making and actionable science, promoting learning, education and communication.
is based on a diverse set of computational modeling approaches, including system dynamics, Bayesian networks, agent-based models, dynamic stochastic equilibrium models, statistical microsimulation models and hybrid approaches.
How can academic researchers working in transdisciplinary teams establish genuine collaborations with people who do not work in academia? How can they overcome the limitations of their discipline-based training, especially assigning value and hierarchy to specialized forms of knowledge production that privileges certain methodologies and epistemologies over others?
We argue that to truly engage in collaborative work, academics need to participate in deliberate processes of critical unlearning that enable the decentering of academia in the processes and politics of transdisciplinary knowledge production and knowledge translation. What we mean by this is that academics have to be willing to acknowledge, reflect upon, and intentionally discard conventional avenues of designing and conducting research activities in order to be authentically open to other ways of exploring questions about the world in collaboration with diverse groups of social actors.
How can we distinguish between knowledge and ignorance and our meta-knowledge of these – that is, whether we are aware that we know or don’t know any particular thing? The common answer is the 2×2 trope of: known knowns; unknown knowns; known unknowns; and unknown unknowns.
For those interested in helping people navigate a complex world, unknown unknowns are perhaps the trickiest of these to explain – partly because the moment you think of an example, the previously “unknown unknown” morphs into a “known unknown”.
My interest here is to demonstrate that this 2×2 division of knowledge and ignorance is far less crisp than we often assume.
This is because knowledge is not something that exists in the world but rather in individual minds. That is, whether something is ‘known’ depends not on whether someone, somewhere, knows it; but on whether this person, here-and-now does.
What makes interdisciplinary and transdisciplinary research challenging? What can go wrong and lead to failure? What has your experience been?
Modes of research that involve the integration of different perspectives, such as interdisciplinary and transdisciplinary research, are notoriously challenging for a host of reasons. Interdisciplinary research requires the combination of insights from different academic disciplines and it is common that these:
bear the stamp of different epistemologies; and,
involve different types of data collected using different methods in the service of different explanations.
Can a dive into the philosophical depths of transdisciplinarity provide an orientation to the fundamental purpose and need for transdisciplinarity?
The earlier philosophers of transdisciplinarity – such as Erich Jantsch (1980), Basarab Nicolescu (2002), and Edgar Morin (2008) – all aim to stretch or transcend the dominant Western paradigm, which arises in part from Aristotle’s rules of good thought. Aristotle’s rules of good thought, or his epistemology, state essentially that to make meaning in the world, we must see in terms of difference; we must make sense in terms of black and white, or dualistic and reductive thinking.
How might the environmental humanities complement insights offered by the environmental sciences, while also remaining faithful to their goal of addressing complexity in analysis and searching for solutions that are context-dependent and pluralistic?
There is a long and rich tradition of scholarship in the humanities addressing environmental problems. Included under the term ‘environmental studies’ until recently, fields such as the arts, design, history, literary studies, and philosophy are now gathering under the new umbrella of the ‘environmental humanities’.
Can philosophical insights be useful for interdisciplinary researchers in extending their thinking about the role of values and knowledge in research? More broadly, can a model or heuristic simplify some of the complexity in understanding how research works?
It’s common for interdisciplinary researchers to consider ontology and epistemology, two major arms of philosophical inquiry into human understanding, but axiology – a third major arm – is oft overlooked.
I start by describing axiology, then detail work by Michael Patterson and Daniel Williams (1998) who place axiology alongside ontology and epistemology. The outcome herein is to cautiously eject and then present a part of their work as a heuristic that may help interdisciplinary researchers to extend understanding on philosophical commitments that underlie research.
What causes interdisciplinary collaborations to default to the standard frameworks and methods of a single discipline, leaving collaborators feeling like they aren’t being taken seriously, or that what they’ve brought to the project has been left on the table, ignored and underappreciated?
Sometimes it is miscommunication, but sometimes it is that collaborators disagree. And sometimes disagreements are both fundamental and intractable.
Often, these disagreements can be traced back to different epistemological frameworks. Epistemological frameworks are beliefs about how particular disciplines conceive of what it is they investigate, how to investigate it, what counts as sufficient evidence, and why the knowledge they produce matters.
In a previous blog post I described multivocality – ie., harnessing multiple voices – in interdisciplinary research and how research I was involved in (Suthers et al., 2013) highlighted pitfalls to be avoided. This blog post examines four ways in which epistemological engagement can be achieved. Two of these are positive and two may have both positive and negative aspects, depending on how the collaboration plays out.
Once a team begins analyzing a shared corpus from different perspectives — in our case, it was a corpus of people solving problems together — it’s the comparison of researchers’ respective analyses that can be a motor for productive epistemological encounters between the researchers.