Integration and Implementation Insights
A community blog providing research resources for understanding and acting on complex real-world problems
Three points in this blog post by Nora Bateson resonate:
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)
By Alexey Voinov
Science is getting increasingly bureaucratized, more and more driven by metrics and indices, which have very little to do with the actual scientific content and recognition among peers. This is actively supported by the still dominant for-profit publication mechanism, which harvests products of scientific research for free, processes, reviews and edits them using voluntary work of scientists themselves and then sells the resulting papers back to the scientific community at obscene costs. The original ideals of scientific pursuit of truth for the sake of the betterment of humanity are diluted and forfeited in the exhausting race for grants, tenure, patents, citations and nominations. Something has to change, especially in the era of post-normal science when so much is at stake, and so little is actually done to address the mounting problems of the environment and society.
By Allison Metz
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.
By Steven Gray
Modeling is the language of scientific discovery and has significant implications for how scientists communicate within and across disciplines. Whether modeling the social interactions of individuals within a community in anthropology, the trade-offs of foraging behaviors in ecology, or the influence of warming ocean temperatures on circulation patterns in oceanography, the ability to represent empirical or theoretical understanding through modeling provides scientists with a semi-standardized language to explain how we think the world works. In fact, modeling is such a basic part of human reasoning and communication that the formal practice of scientific modeling has been recently extended to include non-scientists, especially as a way to understand complex and poorly understood socio-environmental dynamics and to improve collaborative research.
By Gabriele Bammer
In a recent special issue of the journal Nature on interdisciplinarity (17 September 2015, p313-315), Rick Rylance criticised “arcane debates about whether research is inter-, multi-, trans-, cross- or post-disciplinary”, opining “I find this faintly theological hair-splitting unhelpful.” Does he have a point?
By Gabriele Bammer
The aim of this site is to host a global conversation about… well one of the challenges is that we don’t yet have an agreed name for our topic.
This is a conversation for you if your research does some of the following:
I think about these practices as integration and implementation sciences. You might call them systems thinking, action research, interdisciplinarity or transdisciplinarity, implementation science, post-normal science, mode 2 research, project management, complex systems science or a host of other terms.