Would a focus on ‘knowledge ecology’ provide a useful alternative to ‘knowledge integration’ in inter- and trans-disciplinary research?
My experience in bringing perspectives from the humanities, arts and social sciences (HASS) to projects led by researchers from science, technology, engineering and mathematics (STEM) has led me to agree with Sharp and colleagues (2011) that ‘knowledge integration’ is essentially a positivist concept, dependent on the idealist model of a unified field of scientific knowledge to which every bit of science contributed.
¿Cómo pueden los gobiernos, las comunidades y el sector privado efectivamente trabajar juntos para lograr un cambio social hacia el desarrollo sostenible?
En este blog describo los procesos claves que permitieron a Uruguay lograr uno de los regímenes más avanzados de protección del suelo de tierras de cultivo de secano en el mundo. Una explicación del proceso es la creación de una cultura pragmática de la complejidad, una cultura inclusiva, deliberativa que reconoce la naturaleza compleja del problema y abraza el potencial de lo posible.
Integration lies at the heart of inter- and transdisciplinarity. Klein & Newell (1996) call it the “acid test” of interdisciplinarity, and Pohl, van Kerkhoff, Hirsch Hadorn, & Bammer (2008) consider it “the core methodology underpinning the transdisciplinary research process.”
What exactly, though, is integration?
This blog post answers that question while identifying key resources.
Co-creation, and related terms like co-design, co-production, co-construction and co-innovation, are becoming increasingly popular. Upon closer scrutiny they share many characteristics with participatory processes. Is there a difference between the two – co-creation and participation – and if yes, what is it?
Let us first look at participation. Not all participatory processes are the same. They differ with regard to who is involved, who initiated the process and for what reason, the anticipated outcomes, the duration, the context in which it takes place, and who has control over the process and outcomes.
As scholars working within disciplines, we ascribe to certain theories, assumptions, and tools that position us within an intellectual community. As scholars working within fields, we focus our inquiry on specific interactions between the natural world and elements of human endeavor.
Being situated within these two spheres – as translational ecologists and other translational scientists are – carries with it certain tensions that can be challenging to navigate: Ultimately, who constitutes our target audience? How do we balance contribution to discipline through the development of theory with contribution to the field through recommendations for practice? Perhaps most importantly, how do we maximize our impact?
The term ‘translational ecology’ was coined by eminent natural scientist William Schlesinger in a 2010 editorial in Science magazine. He wrote, “Just as physicians use ‘translational medicine’ to connect the patient to new basic research, ‘translational ecology’ should connect end-users of environmental science to the field research carried out by scientists who study the basis of environmental problems.”
Further, Schlesinger posited that without such communication, ecological discoveries “will remain quietly archived while the biosphere degrades.” The editorial chafed some ecologists whose work is motivated by increasing our understanding of natural systems. Others, however, were inspired by this call to action and sought ways to (re)orient their careers from inquiry toward impact.
Our group, which includes natural and social scientists, educators, and practitioners from both academic and non-academic institutions, expanded Schlesinger’s vision of “two-way communication between stakeholders and scientists.”
What types of unknowns are tackled in interdisciplinary research? I draw on my experience directing a program of research on the feasibility of prescribing pharmaceutical heroin as a treatment for heroin dependence. Analysis of this case revealed six different types of unknowns:
What are the results of participatory modeling efforts? What contextual factors, resources and processes contribute to these results? Answering such questions requires the systematic and ongoing evaluation of processes, outputs and outcomes. At present participatory modeling lacks a framework to guide such evaluation efforts. In this post I offer some initial thoughts on the features of this framework.
A first step in developing an evaluation framework for participatory modeling is to establish criteria for processes, outputs, and outcomes. Such criteria would answer a basic question about what it means when we say that a participatory modeling process, output, or outcome is good, worthy, or meritorious.
When computer technology became available for developing and using graphics interfaces for interactive decision support systems, some of us got excited about the potential of directly involving stakeholders in the modeling and analyses of various water resource systems. Many of us believed that generating pictures that could show the impact of various design and management decisions or assumptions any user might want to make would give them a better understanding of the system being modeled and how they might improve its performance.
We even got fancy with respect performing sensitivity analyses and displaying uncertainty. Our displays were clear, understandable, and colorful. Sometimes we witnessed users even believing what they were seeing.
Participatory modeling has at its heart the goal of engaging and involving community stakeholders. It aims to connect academic environments and the communities we want to understand and/or help. Participatory modelling approaches include: use facilitators, provide hands-on experiences, allow open conversation, open up the modeling “black box,” look for areas of consensus, and “engage stakeholders” for their input.
One approach that has not been used to help translate and disseminate participatory models to non-modelers and non-scientists is something psychologists and anthropologists call “cultural models.” Cultural models are presupposed, taken-for-granted understandings of the world that are shared by a group of people.
1. The idea of “catching the rhythm” of the “patterns of movement” in our constantly changing world.
2. More effectively taking context into account.
3. “We cannot know the systems, but we can know more. We cannot perfect the systems, but we can do better.”
The challenge is to develop methods and processes to better achieve these goals. (Reblogged by Gabriele Bammer)
A key topic across disciplines is the authentic engagement and participation of key stakeholders in developing and guiding innovations to solve problems. Complex systems consist of dense webs of relationships where individual stakeholders self-organize through interactions. Research demonstrates that successful uptake of innovations requires genuine and meaningful interaction among researchers, service providers, policy makers, consumers, and other key stakeholders. Implementation efforts must address the various needs of these stakeholders. However, these efforts are described differently across disciplines and contexts – co-design, co-production, co-creation, and co-construction.
Developing consensus on terminology and meanings will facilitate future research and application of “co” concepts.