Integration and Implementation Insights

La modélisation participative, un lieu privilégié pour l’interdisciplinarité? / Participatory modeling: An ideal place for interdisciplinarity?

September 5, 2024April 7, 2016

By Pierre Bommel

An English version of this post is available

La modélisation participative cherche à impliquer un groupe de personnes dans la conception et la révision d’un modèle. L’objectif à terme consiste à mieux caractériser les problèmes actuels et imaginer collectivement comment tenter de les résoudre. Dans le domaine de l’environnement en particulier, il apparaît nécessaire que les acteurs concernés se sentent impliqués dans la démarche de modélisation, afin qu’ils puissent exprimer leurs propres points de vue, mais aussi pour mieux s’engager dans des décisions collectives. De ce fait, pour aborder la gestion intégrée des ressources, il est nécessaire de mettre les acteurs au centre des préoccupations de recherche, à la fois lors de la phase la conception du modèle mais aussi pour l’exploration de ces scénarios.

Should researchers be honest brokers or advocates?

September 5, 2024April 5, 2016

By John Callewaert

When to advocate and when to be an honest broker is a question that deserves serious attention by those working on collaborative and engaged research initiatives. In my role as the Integrated Assessment director at the University of Michigan’s Graham Sustainability Institute I facilitate a wide array of collaborative research efforts. For most of our initiatives we strive to work within an honest broker frame. Following the work of Pielke (2007), the honest broker engages in decision-making by clarifying and sometimes expanding the scope of choice to decision-makers. Our recent analysis of options for High Volume Hydraulic Fracturing in Michigan^[1] (fracking) and outlining sustainability goals for our Ann Arbor campus^[2] are two examples which involved teams of faculty, students, practitioners and decision-makers.

The honest broker approach was particularly important for the project on fracking given the polarized views that can sometimes be associated with this topic.

Towards an evaluation framework for participatory modeling

September 5, 2024March 31, 2016

By Miles McNall

What are the results of participatory modeling efforts? What contextual factors, resources and processes contribute to these results? Answering such questions requires the systematic and ongoing evaluation of processes, outputs and outcomes. At present participatory modeling lacks a framework to guide such evaluation efforts. In this post I offer some initial thoughts on the features of this framework.

A first step in developing an evaluation framework for participatory modeling is to establish criteria for processes, outputs, and outcomes. Such criteria would answer a basic question about what it means when we say that a participatory modeling process, output, or outcome is good, worthy, or meritorious.

Research impact: Six kinds of change

September 5, 2024March 29, 2016

By Gabriele Bammer

What kinds of change can implementation of research findings contribute to? Sometimes the aim is to make change happen, while at other times research implementation is in response to particular proposed or ongoing change.

Making change happen

Two ways of making change happen that are important for research impact are: 1) contributing to the on-going quest for improvement and 2) combatting practices or behaviours that have negative outcomes for individuals or society.

Examples of contributing to the quest for ongoing improvement include technological research such as invention of thinner lenses to revolutionise cameras and social research such as development and implementation of a disability insurance scheme.

Moving from models that synthesize to models that innovate

September 11, 2024March 24, 2016

By Pete Loucks

When computer technology became available for developing and using graphics interfaces for interactive decision support systems, some of us got excited about the potential of directly involving stakeholders in the modeling and analyses of various water resource systems. Many of us believed that generating pictures that could show the impact of various design and management decisions or assumptions any user might want to make would give them a better understanding of the system being modeled and how they might improve its performance.

We even got fancy with respect performing sensitivity analyses and displaying uncertainty. Our displays were clear, understandable, and colorful. Sometimes we witnessed users even believing what they were seeing. We occasionally had to remind users that our models were, and would continue to be, approximations of reality, at best. It was fun developing and using such tools, and indeed today most models that are used to analyze river basins, groundwater, and coastal zones incorporate interactive, graphics-based, decision support frameworks.

The knowledge practice paradox

March 3, 2026March 22, 2016

By Robert Duiveman

Both researchers and politicians frequently claim that the interactions between science and public policy need reform and improvement: an agenda actualized by people all over the world by engaging in new collaborative knowledge practices. But a closer relationship doesn’t necessarily equal a better one; it depends on the design of the collaboration as well as the choices made along the way.

Given the societal and scientific importance attached to new knowledge practices, there is a striking lack of insight into what is actually done within them. There seems to be what I label a knowledge practice paradox. In order to ensure that an experimental collaborative knowledge practice gets its results accepted and implemented ‘in real world circumstances’ it needs to be presented as scientifically sound, politically adroit and deliberatively legitimized.

Yet – as those involved know – research methods and design alone are usually insufficient to get there. It’s the practical wisdom (phronèsis) applied along the way that is key to real success.

Facilitating participatory modeling

September 5, 2024March 17, 2016

By Rebecca Jordan

Facilitate: “To help (something) run more smoothly and effectively” (Merriam-Webster online dictionary).

Like many practices in life, there is an art and a science to facilitation. Certainly, best practices in facilitating processes within participatory modeling mirror many of those practices highlighted in guides to other participatory approaches. It is of critical importance that the expectations around the word “effective”, as taken from the definition above, are identified and negotiated. How can an individual or team of individuals help the process if expectations are unmatched?

Given that resources exist to encourage facilitation, the question that I struggle with is how is participatory modeling different? What does the addition of a model (i.e., an abstract representation) mean for facilitating participation? I argue that the benefits of using a model as a boundary object (i.e., a static representation that is jointly created but differently interpreted) about which stakeholders can discuss, are manifold.

Working together for better outcomes: Lessons for funders, researchers, and researcher partners

September 5, 2024March 15, 2016

By Kit Macleod

As a community of interdisciplinary practice we need to share our collective knowledge on how funders, researchers and wider research partners can work together for better outcomes to address pressing societal challenges.

Funding interdisciplinary research: improving practices and processes

Seven key challenges to funding interdisciplinary research include:

No agreed criteria defining ‘excellence’ in interdisciplinary research.
Poor agreement of the benefits and costs of interdisciplinary ways of working.
No agreement on how much or what kind of additional funding support is required for interdisciplinary research.
No consensus on terminology.
No clearly delineated college of peers from which to select appropriate reviewers.
Limited appropriate interdisciplinary peer review processes.
Restrictions within funding organisations concerning budget allocations and support for interdisciplinary research.

A guidance note for research funders then suggests ways forward from the pre-call stage to evaluation of completed research projects.

Modeling as social practice

September 5, 2024March 10, 2016

By Jeremy Trombley

Modeling – the creation of simplified or abstract representations of the world – is something that people do in many different ways and for many different reasons, and is a social practice. This is true even in the case of scientific and computational models that don’t meet the specific criteria of “participatory” or “collaborative.” Scientists and modelers interact with one another, share information, critique and help to refine one another’s work, and much more as they build models.

Furthermore, all of these activities take place within broader social structures – universities, government agencies, non-government organizations, or simply community groups – and involve resources – funding sources, technologies – that also have social factors that are both embedded within and emerging from them. Understanding the relationship between all of these social dimensions as well as those of the problems that modeling is being used to address is an important task, particularly in participatory modeling projects.

Ten dimensions of integration: Guidelines for modellers

September 5, 2024March 8, 2016

By Serena Hamilton and Tony Jakeman

authors_mosaic_serena-hamilton-tony-jakeman — 1. Serena Hamilton (biography)
2. Tony Jakeman (biography)

Why Integrated Assessment and Integrated Modelling? In our highly connected world environmental problems have social or economic causes and consequences, and decisions to assist one segment of a population can have negative repercussions on other parts of the population. It is broadly accepted that we require integrated, rather than piecemeal approaches to resolve environmental or other complex problems.

Integrated Assessment and its inherent platform, Integrated Modelling, bring together diverse knowledge, data, methods and perspectives into one coherent and comprehensive framework. This process of organizing and synthesizing multiple forms of information across disciplinary and conceptual boundaries allows us to explore linkages and feedbacks between different parts of the system, as well as the trade-offs involved with alternative management interventions on different socioeconomic and environmental criteria.

Why participatory models need to include cultural models

September 5, 2024March 4, 2016

By Michael Paolisso

Participatory modeling has at its heart the goal of engaging and involving community stakeholders. It aims to connect academic environments and the communities we want to understand and/or help. Participatory modelling approaches include: use facilitators, provide hands-on experiences, allow open conversation, open up the modeling “black box,” look for areas of consensus, and “engage stakeholders” for their input.

One approach that has not been used to help translate and disseminate participatory models to non-modelers and non-scientists is something psychologists and anthropologists call “cultural models.” Cultural models are presupposed, taken-for-granted understandings of the world that are shared by a group of people.

Cognitive anthropologists, including those who focus on human and environment interactions, developed the theory and method of cultural modeling in order to understand the cultural knowledge and values that individuals use to “make sense,” understand, and evaluate the world around them.

Do we need to discipline interdisciplinarity?

September 19, 2024March 2, 2016

By Gabriele Bammer

Imagine a team of researchers tackling global health inequalities, with a focus on sanitation. The team comprises epidemiologists and biostatisticians interested both in measuring the extent of the problem and designing intervention trials, engineers investigating a range of sanitation options, anthropologists examining the cultural aspects of sanitation, economists and political scientists documenting the economic benefits and looking for policy levers to assist in making change happen.

The team is working at national policy levels and with a range of target communities seeking to engender small business interest in promoting new sanitation options, as well as individual and community behaviour change. There is collaboration with major international donors and non-government organisations. The team has a talented and charismatic leader.

What the team does not have is access to the full array of theory and methods for synthesising the input of the different disciplines, along with all the relevant stakeholder knowledge. Nor does it have the ability to bring to bear all the different ways of teasing out and taking into account the knowledge gaps – the unknowns. Finally the team cannot tap into the wealth of information about how to provide effective integrated research support for policy and practice change.