Responding to stakeholders – lessons learnt

By Klaus Hubacek and Christina Prell

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Klaus Hubacek (biography)
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Christina Prell (biography)

Being responsive to stakeholder interests and suggestions is important for successful participatory modeling. We share lessons from an exciting, five year project in the UK entitled the Sustainable Uplands. The project sought to bring together a variety of groups ranging from academics, policy makers, residents, conservationists, and different ‘end user’ groups that all, in some way, held a stake in upland park areas in the UK.

Our process was iterative, tacking back and forth between field work, consultations among the research team, consultations with non-academic stakeholders, and modeling. Not only were our models heavily influenced by what stakeholders told us were important values and considerations regarding upland areas, but these also informed how we went about gathering the data.

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Modeling as empowerment

By Laura Schmitt Olabisi

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Laura Schmitt Olabisi (biography)

Who can make systems change? The challenges of complexity are intensely felt by those who are trying to make strategic interventions in coupled human-environmental systems in order to fulfill personal, societal, or institutional goals. The activists, leaders, and decision-makers I work with often feel overwhelmed by trying to deal with multiple problems at once, with limited time, resources, and attention. We need tools to help leaders cut through the complexity so that they can identify the most effective strategies to make change.

This is where participatory system dynamics modelers like myself come in.

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

By Pierre Bommel

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Pierre Bommel (biography)

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.

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Towards an evaluation framework for participatory modeling

By Miles McNall

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Miles McNall (biography)

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.

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Facilitating participatory modeling

By Rebecca Jordan

Rebecca Jordan (biography)

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?

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Modeling as social practice

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Jeremy Trombley (website and biography)

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.

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Why participatory models need to include cultural models

By Michael Paolisso

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Michael Paolisso (biography)

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.

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Modelling is the language of scientific discovery

By Steven Gray

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Steven Gray (biography)

Modeling is the language of scientific discovery and has significant implications for how scientists communicate within and across disciplines. Whether modeling the social interactions of individuals within a community in anthropology, the trade-offs of foraging behaviors in ecology, or the influence of warming ocean temperatures on circulation patterns in oceanography, the ability to represent empirical or theoretical understanding through modeling provides scientists with a semi-standardized language to explain how we think the world works. In fact, modeling is such a basic part of human reasoning and communication that the formal practice of scientific modeling has been recently extended to include non-scientists, especially as a way to understand complex and poorly understood socio-environmental dynamics and to improve collaborative research.

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