Eighth annual review

By Gabriele Bammer

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Gabriele Bammer (biography)

Which i2Insights contributions inspired you in 2023? What did you learn that was new and how did it help you in tackling the complex societal or environmental problems you focus on? What would you like to see in 2024 and beyond?

One of the delights of curating i2Insights is learning something from every blog post. Another is the personal interactions involved in broadening the global community of contributors, introducing fresh voices and fresh insights, alongside those who are more seasoned contributors.

In this last blog post for 2023, I survey three of the year’s many highlights and what they mean for the operation of i2Insights:

  • integration and synthesis as an emerging ‘hot’ topic
  • re-introducing “golden oldies,” ie. tried and tested tools
  • increasing the number of countries represented by contributors, with an accompanying focus on decolonisation.

i2Insights will be back on January 9, 2024 (Australian time) with our 500th contribution, which is also the first from Sri Lanka.

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The Strategic Choice Approach in shaping public policies

By Catherine Hobbs

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Catherine Hobbs (biography)

How can we be inspired, rather than overwhelmed, by differing perspectives in the inter-organisational planning required to more effectively address cross-cutting issues, or interacting areas of policy? How can we learn from the achievements of public policy action research, in the light of the local and global uncertainties of the 2020s?

Strategic Choice Approach was developed by John Friend with Allen Hickling, originating during the 1960s and 1970s. It emerged through a series of collaborative action research projects applied to public policy challenges in a number of countries, so that its origins are empirical rather than theoretical.

Friend described Strategic Choice Approach as being helpful as a practical approach to planning under pressure where “people of different outlooks and allegiances are working together with a shared concern to move rapidly towards commitments to action or to changes of policy on difficult issues of shared concern” (Friend, no date).

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Generating evidence using the Delphi method

By Dmitry Khodyakov

dmitry-khodyakov
Dmitry Khodyakov (biography)

What is Delphi? How has the Delphi method stood up over time? How can the best of Delphi be adapted to new circumstances and problems?

The Delphi method is a group-based process for eliciting and aggregating opinion on a topic with a goal of exploring the existence of consensus among a diverse group of handpicked experts. The Delphi method was developed at the RAND Corporation in the early 1950s to obtain a reliable expert consensus, which is often used as a substitute for empirical evidence when it does not exist.

The four key characteristics of the Delphi method are:

  1. anonymity, 
  2. iterative data collection,
  3. participant feedback, and
  4. statistical determination of group response.

As a result, Delphi has become best practice for quantifying the results of group elicitation processes.

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Making the Nominal Group Technique more accessible

By Jason Olsen

jason-olsen
Jason Olsen (biography)

Looking to gain real insights from those with lived experience about a specific topic? Interested in a low-cost method that fosters equal participation and discussion over participant domination in a research focus group? Want to know about modifications to make pan-disability (ie., working with participants with different impairments) research focus groups more inclusive?

The Nominal Group Technique developed by Ven and Delbecq (1972) has been used for more than 50 years. Key to its success is the posing of a single unambiguous and unbiased question about a problem that can generate a wide range of answers. The process structures the meeting to enable critical dimensions of the question to be identified, ranked and rated in a way that:

  • limits the influence of the researcher leading the project, as well as the influence of attendees,
  • allows participants to clarify the question’s dimensions and gaps,
  • increases the likelihood of equal participation for all group members,
  • affords equal influence to different, and potentially conflicting, values and ideas.

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Wisely navigating knowledge co-production: Towards an ethics that builds capacities

By Guido Caniglia and Rebecca Freeth

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1. Guido Caniglia (biography)
2. Rebecca Freeth (biography)

How can I ensure that marginalized voices are heard in this project? Whom do I call on to offer the next perspective in this workshop and why? How can I intervene in this particular disagreement in a productive way? These are typical questions that researchers and practitioners involved in knowledge co-production processes ask themselves. They express deep ethical concerns, which also have epistemological and political implications, as they address the question: What should I do in this situation? What is right and wrong for me to do here?

We suggest that a perspective based on the ancient virtue of practical wisdom may help researchers and practitioners alike working in knowledge co-production to navigate the complexities of these questions.

Practical wisdom: An ancient virtue for wise navigation

Our answers to the deep ethical questions that emerge in collaborative and participatory research will vary depending on the specifics of the situation we are in, who is involved, as well as our own positionality and role in research projects or academic institutions. There is no formula to follow. 

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Participatory scenario planning

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1. Maike Hamann (biography)
2. Tanja Hichert (biography)
3. Nadia Sitas (biography)

By Maike Hamann, Tanja Hichert and Nadia Sitas

Within the many different ways of developing scenarios, what are useful general procedures for participatory processes? What resources are required? What are the strengths and weaknesses of involving stakeholders?

Scenarios are vignettes or narratives of possible futures, and when used in a set, usually depict purposefully divergent visions of what the future may hold. The point of scenario planning is not to predict the future, but to explore its uncertainties. Scenario development has a long history in corporate and military strategic planning, and is also commonly used in global environmental assessments to link current decision-making to future impacts. Participatory scenario planning extends scenario development into the realm of stakeholder-engaged research.

In general, the process for participatory scenario planning broadly follows three phases.

1. Identifying stakeholders and setting the scene

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Why complex problems need abductive reasoning

By Mariana Zafeirakopoulos

mariana-zafeirakopoulos
Mariana Zafeirakopoulos (biography)

How does the way we approach complex problems differ from how we approach problems that are familiar or obvious?

In this i2Insights contribution, I explore four kinds of reasoning:

  • Deduction
  • Induction
  • Abduction
  • Design abduction.

Design abduction is the brain-child of Professor Kees Dorst (2015). In simplified terms, these different kinds of reasoning can be compared as follows (Watson and Dorst, 2022, p. 3; taken from Dorst, 2015, pp. 46-49):

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Five lessons to improve how models serve society

By Andrea Saltelli

andrea-saltelli
Andrea Saltelli (biography)

Models are mathematical constructs better understood by their developers than by users. So should the public trust models? What insights can help society demand the quality it needs from modeling?

Mathematical modelling is a multiverse, where each scientific discipline adopts its own styles of modeling and quality control. Very little in the way of ‘user instructions’ is available to those affected by modeling practices.

This blog post presents five lessons to improve modelling that were developed as a manifesto by a cross-disciplinary group of natural and social scientists (Saltelli et al., 2020).

Lesson 1: Mind the assumptions

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Judgment and decision making with unknown states and outcomes

By Michael Smithson

Michael Smithson
Michael Smithson (biography)

What issues arise for effective judgments, predictions, and decisions when decision makers do not know all the potential starting positions, available alternatives and possible outcomes?

A shorthand term for this collection of possible starting points (also known as prior states), alternatives, and outcomes is “sample space.” Here I elucidate why sample space is important and how judgments and decisions can be influenced when it is incomplete.

Why is sample space important?

When it comes to dealing with unknowns, economists and others traditionally distinguish between “risk” (where probabilities can be assigned to every possible outcome) and “uncertainty” (where the probabilities are vague or unknown). Both of those versions of unknowns assume that decision makers know everything about the sample space.

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Stakeholder engagement primer: 8. Generating ideas and reaching agreement

By Gabriele Bammer

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What skills for generating ideas and reaching agreement should every researcher involved in stakeholder engagement seek to cultivate? What key methods and concepts should they be familiar with?

The focus in this blog post is on generating ideas and reaching agreement, as well as recognising the “groan zone” between these two phases in a group process. Researchers will have diverse attributes and not everyone will be well-placed to cultivate the skills described here. Having an understanding of the skills can help in choosing the researchers best placed to undertake the stakeholder engagement.

Generating ideas: Brainstorming

For brainstorming to work well, it requires rapid-fire contributions, no holding back or self-censoring of ideas, and no discussion or criticism of the ideas proposed. It often involves a group of stakeholders (or stakeholders and researchers) sitting around a flipchart or whiteboard, with one person writing down the ideas as members of the group say them.

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A tool for transforming resistance to insights in decision-making

By Gemma Jiang

author_gemma-jiang
Gemma Jiang (biography)

Do you encounter resistance from your team members, especially in regard to difficult decisions? How might decision-making processes be better facilitated to generate insights instead of resistance?

I describe a conceptual framework and an accompanying practical tool from Lewis Deep Democracy (2021) that can transform resistance to insights in decision-making processes.

The conceptual framework: Understanding how decision making generates resistance

It is important first to understand the consciousness of a team. If you think of a team’s consciousness as an iceberg, the ideas and opinions that are expressed are the conscious part above the waterline, while those that are not expressed are the unconscious part below the waterline. If decisions are made based only on the team’s expressed ideas and opinions, those below the waterline will likely form resistance. This is often what happens with “majority rules” democracy.

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A quick guide to post-normal science

By Silvio Funtowicz

silvio-funtowicz
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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