Current post
Implementing transdisciplinary research in post-Soviet Armenia and Georgia
By Tigran Keryan and Tamara Mitrofanenko
2. Tamara Mitrofanenko (biography)
What characterized the Soviet academic system and what is its legacy in two post-Soviet countries, Armenia and Georgia? What would it take for transdisciplinarity to flourish in those countries?
The Soviet academic system
During the Soviet era, the natural and technical sciences were prioritized, while the social sciences and humanities were marginalized. In addition, research functions were removed from the responsibilities of academic institutions and placed under the authority of the Academies of Sciences, which are central state-governed research institutes. Thus, the role of the universities was reduced to teaching, undermining the research capacity of higher educational institutions up to this day. The curriculum was centralized, focusing on Soviet propaganda and leaving little space for innovation. On the upside, this system ensured the absence of tuition fees in all universities and guaranteed employment for all graduates.
How can transdisciplinarity be implemented in the post-Soviet era?
Recent posts
Eleven success factors for transdisciplinary real-world labs
By Niko Schäpke, Oskar Marg, Matthias Bergmann, Franziska Stelzer and Daniel J. Lang
What is required for transdisciplinary real-world laboratories (labs) to successfully tackle and achieve long-term societal change? How can they make the change process transferable? What is required of the societal and scientific actors?
We discuss eleven success factors to facilitate successful transdisciplinary collaboration and to achieve desired societal effects. These are based on an accompanying research project, which supported and observed several real-world labs, aiming to develop overarching insights on methods and success factors.
Overcoming the mismatch between goals and outcomes in knowledge exchange
By Denis Karcher and Chris Cvitanovic
2. Chris Cvitanovic (biography)
How well do researchers achieve the research impacts they aim for? And if there is a mismatch, does it matter?
Together with colleagues (Karcher et al., 2021), we systematically searched for and reviewed nearly 400 studies that described goals and outcomes that were claimed for knowledge exchange at the science-policy interface. Although our focus was on the environmental sciences, the results may be more widely useful.
Big ambitions
The eight top goals that studies described for their knowledge exchange activities were:
1. Usability, eg., that the interaction with policy makers and/or the knowledge created were credible, legitimate, relevant, and timely (458 references).
Sixth annual review
By Gabriele Bammer
As the blog enters its 7th year, it is time for the annual review of how well it is meeting its aims of:
- sharing concepts, methods and other tools for tackling complex societal and environmental problems and acting as a repository of those tools
- being a global vehicle for exchange, discussion and network building to strengthen use of those tools.
All the trends are in the right direction, providing impetus to keep expanding the base of contributors and coverage of key topics. If you have developed a relevant tool or use an existing tool in a new way, I would love to hear from you. Comments on blog posts are always valuable. And, of course, feedback and suggestions are welcome.
This is the last blog post for 2021.
Stakeholder engagement primer: 10. Advanced skills
By Gabriele Bammer
Once researchers understand the basics of stakeholder engagement, what else is it useful for them to know? What additional concepts, methods and processes are helpful additions to their skill set so that they can engage more effectively?
Two areas for building additional skills are considered here:
- Understanding and managing power and control
- Working effectively with multiple stakeholders.
These areas are ripe for consolidation of existing knowledge and experience, as well as of useful tools. Here only some considerations are sketched out, drawing predominantly on key contributions to the i2Insights blog.
Understanding and managing power and control
Highlighted posts
Five lessons for early career researchers in interacting with policymakers
By Aparna Lal
How, as an early career researcher, can you get started in developing a working relationship with government policy makers? What do you need to be prepared for? What benefits can you expect?
Here I present five lessons from my first self-initiated engagement with policymakers. I am a computer modeller exploring the links between water-quality, climate and health. As such, my research sits at the crossroads of environmental science and public health. At the end of 2018, I decided to present some of my work to the Australian Capital Territory Environment, Planning and Sustainable Development Directorate.
Four patterns of thought for effective group decisions
By George P. Richardson and David F. Andersen
2. David F. Andersen (biography)
What can you do if you are in a group that is trying to deal with problems that are developing over time, where:
- root causes of the dynamics aren’t clear;
- different stakeholders have different perceptions;
- past solutions haven’t worked;
- solutions must take into account how the system will respond; and,
- implementing change will require aligning powerful stakeholders around policies that they agree have the highest likelihood of long-term success?
The fields of systems thinking and system dynamics modelling bring four important patterns of thought to such a group decision and negotiation:
Five principles of co-innovation
By Helen Percy, James Turner and Wendy Boyce
2. James Turner (biography)
3. Wendy Boyce (biography)
What is co-innovation and how can it be applied in practice in a research project?
Co-innovation is the process of jointly developing new or different solutions to a complex problem through multi-participant research processes – and keeping these processes alive throughout the research.
Our experience has been applying co-innovation as a research approach to address complex problems in an agricultural context, however, the principles apply well beyond agriculture.
How can we know unknown unknowns?
By Michael Smithson
In a 1993 paper, philosopher Ann Kerwin elaborated a view on ignorance that has been summarized in a 2×2 table describing crucial components of metacognition (see figure below). One margin of the table consisted of “knowns” and “unknowns”. The other margin comprised the adjectives “known” and “unknown”. Crosstabulating these produced “known knowns”, “known unknowns”, “unknown knowns”, and unknown unknowns”. The latter two categories have caused some befuddlement. What does it mean to not know what is known, or to not know what is unknown? And how can we convert either of these into their known counterparts?