Synthesis of knowledge about participatory modeling: How a group’s perceptions changed over time

Community member post by Rebecca Jordan

Rebecca Jordan (biography)

How do a group’s perceptions change over time, when members across a range of institutions are brought together at regular intervals to synthesize ideas? Synthesis centers have been established to catalyze more effective cross-disciplinary research on complex problems, as described in the blog post ‘Synthesis centers as critical research infrastructure‘, by Andrew Campbell.

I co-led a group synthesizing ideas about participatory modeling as one of the activities at the National Socio-Environmental Synthesis Center (SESYNC). We met in Annapolis, Maryland, USA, four times over three years for 3-4 days per meeting. Our task was to synthesize what is known about participatory modeling tools, processes, and outcomes, especially in environmental and natural resources management contexts.

The group defined participatory modeling as a “purposeful learning process for action that engages the implicit and explicit knowledge of stakeholders to create formalized and shared representation(s) of reality” (participatorymodeling.org). In its idealized form, participatory modeling involves stakeholders in co-formulating the problem and the solution or decision-making outcomes. In some cases, stakeholders also co-generate – with expert modelers – the shared representation or model.

Here, I discuss two representations generated, respectively, at the first and last meetings and shown in the figures below. These representations are the result of combining models generated by the participatory modeling experts present at each meeting. Individuals were given the following prompt: “create a model using pen and paper that reflects the participatory modeling process”. The sheets of paper were then collected and aggregated, following which I created a digitized version.

Representation generated at the first meeting by the participatory modeling group (source: Rebecca Jordan)

Representation generated at the last (fourth) meeting by the participatory modelling group (source: Rebecca Jordan)

Comparing the figures generated at the first and last meetings, it can be seen that both feature models, cycles, multiple scales, inclusion, and exclusion of participants.

But there are four major differences. Compared to the last meeting figure, the first meeting figure:

  1. is process oriented, organized as steps,
  2. features explicit theories,
  3. lacks realistic pictures including people, and
  4. lacks explicit mention of researchers.

My impression is that these differences also framed the changes in group discussion during the meeting processes.

One change was that the participatory modeling experts became more comfortable with each other allowing for a more creative flow of ideas and a more comfortable discourse. They also became more familiar with the ideas being represented in the different disciplines and could talk more freely about these ideas.

If we take the two representations as indicative of the change in the way that participants viewed the participatory modeling process, then I suggest that the group became somewhat humbled by the limitations in the research about (and the institutions that house) participatory processes in general. Not only did we read about, and discuss at length, the processes and tools within multiple cases, but we also confronted the socio-economic and political challenges that people across the globe face. In addition, we recognized the complex layers of uncertainty embedded within natural and social systems. The figure from the final meeting depicts a more reflective and personalized perspective on the participatory process that encompasses a much greater scale.

What stood out to me was the increased appreciation for the multiple layers of the processes by which people gather information and learn. While the group began with discussions about the inherent complexity in governance processes and the extent of varying stakeholder needs, the group ended the series of meetings with greater recognition of neurology, cognition, identity, culture, and the researcher biases that are all part of participatory engagement.

While these are personal reflections, I am interested in what you see in the change across the two figures. For me, better capturing the complexity that arose in our discussions has great potential to improve participatory modeling and the research that uses it. What do you think?

Biography: Rebecca Jordan is Professor and Department Chair of Community Sustainability in the College of Agriculture and Natural Resources at Michigan State University, Michigan, USA. She devotes most of her research effort to investigating public learning of science through citizen science and participatory modeling. She was a co-Principal Investigator of the Participatory Modelling pursuit funded by the National Socio-Environmental Synthesis Center (SESYNC).

This blog post resulted from the Participatory Modeling pursuit which was part of the theme Building Resources for Complex, Action-Oriented Team Science funded by the National Socio-Environmental Synthesis Center (SESYNC).

Are more stakeholders better?

eleanor-sterling
Eleanor Sterling (biography)

Community member post by Eleanor Sterling

Participatory modeling, by definition, involves engaging “stakeholders” in decision making. But determining which stakeholders to involve, when, and how is a delicate balance. Early writings on stakeholder engagement methods represent engagement along a linear continuum from non-participatory to citizen-controlled decision making.

Non-participatory methods could include stakeholders passively receiving pre-set information, with no input to content or delivery (eg., public information campaigns). Fully collaborative partnerships (eg., participatory action research projects) involve co-creation of knowledge, co-identification of issues, and co-framing of and implementation of solutions. Continue reading

What’s in a name? The role of storytelling in participatory modeling

Community member post by Alison Singer

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Alison Singer (biography)

That which we call a rose,
by any other name would smell as sweet.

That Shakespeare guy really knew what he was talking about. A rose is what it is, no matter what we call it. A word is simply a cultural agreement about what we call something. And because language is a common thread that binds cultures together, participatory modeling – as a pursuit that strives to incorporate knowledge and perspectives from diverse stakeholders – is prime for integrating stories into its practice.

To an extent, that’s what every modeling activity does, whether it’s through translating an individual’s story into a fuzzy cognitive map, or into an agent-based model. But I would argue that the drive to quantify everything can sometimes make us lose the richness that a story can provide. Continue reading

Citizen science and participatory modeling

Community member post by Rebecca Jordan and Steven Gray

Rebecca Jordan (biography)

As investigators who engage the public in both modeling and research endeavors we address two major questions: Does citizen science have a place within the participatory modeling research community? And does participatory modeling have a place in the citizen science research community?

Let us start with definitions. Citizen science has been defined in many ways, but we will keep the definition simple. Citizen science refers to endeavors where persons who do not consider themselves scientific experts work with those who do consider themselves experts (around a specific issue) to address an authentic research question. Continue reading

Models as ‘interested amateurs’

Community member post by Pete Barbrook-Johnson

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Pete Barbrook-Johnson (biography)

How can we improve the often poor interaction and lack of genuine discussions between policy makers, experts, and those affected by policy?

As a social scientist who makes and uses models, an idea from Daniel Dennett’s (2013) book ‘Intuition Pumps and Other Tools for Thinking’ struck a chord with me. Dennett introduces the idea of using lay audiences to aid and improve understanding between experts. Dennett suggests that including lay audiences (which he calls ‘curious nonexperts’) in discussions can entice experts to err on the side of over-explaining their thoughts and positions. When experts are talking only to other experts, Dennett suggests they under-explain, not wanting to insult others or look stupid by going over basic assumptions. This means they can fail to identify areas of disagreement, or to reach consensus, understanding, or conclusions that may be constructive.

For Dennett, the ‘curious nonexperts’ are undergraduate philosophy students, to be included in debates between professors. For me, the book sparked the idea that models could be ‘curious nonexperts’ in policy debates and processes. I prefer and use the term ‘interested amateurs’ over ‘curious nonexperts’, simply because the word ‘amateur’ seems slightly more insulting towards models! Continue reading

Dealing with deep uncertainty: Scenarios

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Laura Schmitt Olabisi (biography)

Community member post by Laura Schmitt Olabisi

What is deep uncertainty? And how can scenarios help deal with it?

Deep uncertainty refers to ‘unknown unknowns’, which simulation models are fundamentally unsuited to address. Any model is a representation of a system, based on what we know about that system. We can’t model something that nobody knows about—so the capabilities of any model (even a participatory model) are bounded by our collective knowledge.

One of the ways we handle unknown unknowns is by using scenarios. Scenarios are stories about the future, meant to guide our decision-making in the present. Continue reading