Eight grand challenges in socio-environmental systems modeling

By Sondoss Elsawah and Anthony J. Jakeman

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Sondoss Elsawah (biography)

As we enter a new decade with numerous looming social and environmental issues, what are the challenges and opportunities facing the scientific community to unlock the potential of socio-environmental systems modeling?

What is socio-environmental systems modelling?

Socio-environmental systems modelling:

  1. involves developing and/or applying models to investigate complex problems arising from interactions among human (ie. social, economic) and natural (ie. biophysical, ecological, environmental) systems.
  2. can be used to support multiple goals, such as informing decision making and actionable science, promoting learning, education and communication.
  3. is based on a diverse set of computational modeling approaches, including system dynamics, Bayesian networks, agent-based models, dynamic stochastic equilibrium models, statistical microsimulation models and hybrid approaches.

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Productive multivocal analysis – Part 2: Achieving epistemological engagement

By Kristine Lund

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Kristine Lund (biography)

In a previous blog post I described multivocalityie., harnessing multiple voices – in interdisciplinary research and how research I was involved in (Suthers et al., 2013) highlighted pitfalls to be avoided. This blog post examines four ways in which epistemological engagement can be achieved. Two of these are positive and two may have both positive and negative aspects, depending on how the collaboration plays out.

Once a team begins analyzing a shared corpus from different perspectives — in our case, it was a corpus of people solving problems together — it’s the comparison of researchers’ respective analyses that can be a motor for productive epistemological encounters between the researchers.

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Overturning the design of outcome measures

By Diana Rose

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Diana Rose (biography)

Outcome measures in research about treatment and service provision may not seem a particularly controversial or even exciting domain for citizen involvement. Although the research landscape is changing – partly as a result of engaging stakeholders in knowledge production and its effects – the design of outcome measures has been largely immune to these developments.

The standard way of constructing such measures – for evaluating treatment outcomes and services – has serious flaws and requires an alternative that grounds them firmly in the experiences and situations of the people whose views are being solicited.

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