A quick guide to post-normal science

By Silvio Funtowicz

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Silvio Funtowicz (biography)

Post-normal science comes into play for decision-making on policy issues where facts are uncertain, values in dispute, stakes high and decisions urgent.

A good example of a problem requiring post-normal science is the actions that need to be taken to mitigate the effects of sea level rise consequent on global climate change. All the causal elements are uncertain in the extreme, at stake is much of the built environment and the settlement patterns of people, what to save and what to sacrifice is in dispute, and the window for decision-making is shrinking. The COVID-19 pandemic is another instance of a post-normal science problem. The behaviour of the current and emerging variants of the virus is uncertain, the values of socially intrusive remedies are in dispute, and obviously stakes are high and decisions urgent.

In such contexts of policy making, normal science (in the Kuhnian sense, see Kuhn 1962) is still necessary, but no longer sufficient.

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Combining and adapting frameworks for research implementation

By Kirsty Jones and Sara Bice

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1. Kirsty Jones (biography)
2. Sara Bice (biography)

How can combining frameworks help plan a research implementation process? What specific contributions can different frameworks make?

In our research with industry, we found combining three frameworks to be an effective way to get handles on a complex implementation landscape and to design the necessary steps to systematically work our way through it. The frameworks we found useful were: a logic model, a pathway to impact and the Consolidated Framework for Implementation Research, which we adapted to our context.

We provide four figures to show how we used each framework and briefly describe the benefits we derived from each of them. Although fully understanding the detail in the figures requires familiarity with the specifics of our research, we trust the figures provide insight into how each framework was used.

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Five questions to understand epistemology and its influence on integrative research processes

By Katie Moon, Chris Cvitanovic, Deborah A. Blackman, Ivan R. Scales and Nicola K. Browne

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1. Katie Moon; 2. Chris Cvitanovic; 3. Deborah A. Blackman; 4. Ivan R. Scales; 5. Nicola K. Browne (biographies)

How can we reduce the barriers to successful integrative research processes? In particular, how can we understand the different epistemologies that underpin knowledge?

Epistemology is the branch of philosophy that asks: how do we know what we know? It is concerned with how we can ensure that knowledge is both adequate and legitimate, by considering:

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A tool for transdisciplinary research planning and evaluation

By Brian Belcher, Rachel Claus, Rachel Davel, Stephanie Jones and Daniela Pinto

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1. Brian Belcher; 2. Rachel Claus; 3. Rachel Davel; 4. Stephanie Jones; 5. Daniela Pinto (biographies)

What are the characteristics of high-quality transdisciplinary research? As research approaches increasingly cross disciplinary bounds and engage stakeholders in the research process to more effectively address complex problems, traditional academic research assessment criteria are insufficient and may even constrain transdisciplinary research development and use. There is a need for appropriate principles and criteria to guide transdisciplinary research practice and evaluation.

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Principles for welcoming all voices

By Keith McCandless

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Keith McCandless (biography)

Which principles would allow us to manage and lead groups that aspire to include all voices in shaping next steps and the future?

Liberating Structures is an approach to working together that puts innovative and facilitative power in the hands of everyone. It does this through 33 adaptable microstructures that allow groups of people of any size to be all-inclusive and to unleash everyone’s power.

Liberating Structures is based on ten principles that help guide choices and keep a community together while moving toward their set purpose.

Liberating Structures practice and principles come alive through active engagement. The path is co-evolving, iterative, and mutually shaped. As shown in the table below, each principle is couched as follows: When Liberating Structures are part of everyday interactions, it is possible to…

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A Partnership Outcome Spaces framework for transdisciplinary student-staff partnerships

By Giedre Kligyte, Mieke van der Bijl-Brouwer, Jarnae Leslie, Tyler Key, Bethany Hooper and Eleanor Salazar

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1. Giedre Kligyte; 2. Mieke van der Bijl-Brouwer; 3. Jarnae Leslie; 4. Tyler Key; 5. Bethany Hooper; 6. Eleanor Salazar (biographies)

How can universities leverage students’ perspectives to create pathways towards lasting organisational change in higher education? How can we conceptualise institutional impact and outcomes of transdisciplinary student-staff partnerships?

Why student-staff partnerships?

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Navigating intercultural relations in transdisciplinary practice: The partial overlaps framework

By David Ludwig, Vitor Renck & Charbel N. El-Hani

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1. David Ludwig (biography)
2. Vitor Renck (biography)
3. Charbel N. El-Hani (biography)

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?

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Core competencies for implementation practice

By Sobia Khan and Julia E. Moore

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1. Sobia Khan (biography)
2. Julia E. Moore (biography)

How can implementation practitioners – those who are implementing in practice rather than for research – become more effective? How can the pragmatism required to apply implementation science principles to practice be taught and fostered? What are the core competencies of implementation practice?

We conducted a scan of the literature and grey literature and then consolidated six existing core competency documents, covering implementation practice, knowledge translation, and knowledge mobilization. The core competencies outlined across these six documents required some synthesis and re-framing in order to really make sense and resonate with practitioners, particularly to address differences across settings.

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Three types of knowledge

By Tobias Buser and Flurina Schneider

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1. Tobias Buser (biography)
2. Flurina Schneider (biography)

When addressing societal challenges, how can researchers orient their thinking to produce not only knowledge on problems, but also knowledge that helps to overcome those problems?

The concept of ‘three types of knowledge’ is helpful for structuring project goals, formulating research questions and developing action plans. The concept first appeared in the 1990s and has developed into a core underpinning of transdisciplinary research.

The three types of knowledge, illustrated in the first figure below, are:

1. Systems knowledge, which is usually defined as knowledge about the current system or problem situation. It is mainly analytical and descriptive. For example, if you think of water scarcity, systems knowledge refers to producing a holistic understanding of the relevant socio-ecological system, including aspects like water availability, water uses, water management, justice questions, and their interrelations.

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Three complexity principles for convergence research

By Gemma Jiang

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Gemma Jiang (biography)

How can principles adapted from complexity thinking be applied to convergence research? How can such principles help integrate knowledge, methods, and expertise from different disciplines to form novel frameworks that catalyze scientific discovery and innovation?

I present three principles from the complexity paradigm that are highly relevant to convergence research. I then describe three types of transformative containers that I have developed to create enabling conditions for applying complexity principles to convergence.

1. Ecosystem consciousness: An inversion of perspectives

Ecosystem consciousness is necessary because in complex systems the whole (ecosystem) is bigger than the sum of its parts; the wellbeing of the whole and the parts are interdependent and mutually reinforcing.

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Integration: The IPO model

By Stephen Crowley and Graham Hubbs

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1. Stephen Crowley (biography)
2. Graham Hubbs (biography)

How can we improve our understanding of knowledge integration? What are the elements of integration?

Sometimes what gets integrated are products of science, such as data sets or scientific models. Sometimes it is not the products that are integrated but instead the methods, as can happen on interdisciplinary teams. On these teams, scientists work together, so sometimes it is the people themselves (scientists are people!) or their disciplinary cultures that get integrated.

These are only some of the possible elements of integration. There is just as wide a variety of processes and products of integration as there are elements. The process of integrating data sets might be a sort of analysis, and the result might be a table or graph that displays the results of research in a conspicuous manner. Integrating diverse scientists into an interdisciplinary team, by contrast, is a matter of people working together, and the result of the integration is not a table or a graph but the team itself.

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Considering uncertainty, awareness and ambiguity as a three-dimensional space

By Fabio Boschetti

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Fabio Boschetti (biography)

The concept of unknown unknowns highlights the importance of introspection in assessing knowledge. It suggests that finding our way in the set of known-knowns, known-unknowns, unknown-knowns and unknown-unknowns, reduces to asking:

  1. how uncertain are we? and
  2. how aware are we of uncertainty?

When a problem involves a decision-making team, rather than a single individual, we also need to ask:

  1. how do context and perception affect what we know?

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