Five lessons for early career researchers in interacting with policymakers

Community member post by Aparna Lal

Aparna Lal
Aparna Lal (biography)

How, as an early career researcher, can you get started in developing a working relationship with government policy makers? What do you need to be prepared for? What benefits can you expect?

Here I present five lessons from my first self-initiated engagement with policymakers. I am a computer modeller exploring the links between water-quality, climate and health. As such, my research sits at the crossroads of environmental science and public health. At the end of 2018, I decided to present some of my work to the Australian Capital Territory Environment, Planning and Sustainable Development Directorate.

My anticipated outcomes from this presentation were to start a conversation around water and health in the Australian Capital Territory and to leave the meeting with new insights. I also learnt the following lessons: Continue reading

Five principles of co-innovation

Community member post by Helen Percy, James Turner and Wendy Boyce

Helen Percy (biography)

What is co-innovation and how can it be applied in practice in a research project?

Co-innovation is the process of jointly developing new or different solutions to a complex problem through multi-participant research processes – and keeping these processes alive throughout the research.

James Turner (biography)

Our experience has been applying co-innovation as a research approach to address complex problems in an agricultural context, however, the principles apply well beyond agriculture. Co-innovation is most suited to hard-to-solve technical, social, cultural and economic challenges. Such challenges have no obvious cause and effect relationships, as well as many different players with a stake in the research problem and solution. These include policy makers, industry, community members, first nations representatives and others who are involved in the research as partners and stakeholders. Continue reading

How to support research consortia

Community member post by Bruce Currie-Alder and Georgina Cundill Kemp

Bruce Currie-Alder (biography)

A research consortium is a model of collaboration that brings together multiple institutions that are otherwise independent from one another to address a common set of questions using a defined structure and governance model. Increasingly consortia are also being joined in cross-consortia networks. How can connections be made across the institutions in individual consortia, as well as in cross-consortia networks, to ensure that such collaborations are more than the sum of their parts? Continue reading

Designing scenarios to guide robust decisions

Community member post by Bonnie McBain

Bonnie McBain (biography)

What makes scenarios useful to decision makers in effectively planning for the future? Here I discuss three aspects of scenarios:

  • goals;
  • design; and,
  • use and defensibility.

Goals of scenarios

Since predicting the future is not possible, it’s important to know that scenarios are not predictions. Instead, scenarios stimulate thinking and conversations about possible futures. Continue reading

Agent-based modelling for knowledge synthesis and decision support

Community member post by Jen Badham

Jen Badham (biography)

The most familiar models are predictive, such as those used to forecast the weather or plan the economy. However, models have many different uses and different modelling techniques are more or less suitable for specific purposes.

Here I present an example of how a game and a computerised agent-based model have been used for knowledge synthesis and decision support.

The game and model were developed by a team from the Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), a French agricultural research organisation with an international development focus. The issue of interest was land use conflict between crop and cattle farming in the Gnith community in Senegal (D’Aquino et al. 2003).

Agent-based modelling is particularly effective where understanding is more important than prediction. This is because agent-based models can represent the real world in a very natural way, making them more accessible than some other types of models. Continue reading

Funding transformative research: 10 key stages

Community member post by Flurina Schneider

Flurina Schneider (biography)

How can funding programmes maximize the potential of transformative research that seeks to make a real difference? How can funders support a more hands-on approach to societal challenges such as ecological crises? A group of Swiss transdisciplinary researchers and funding-agency staff identified 10 overlapping stages and their key ingredients. The stages are also described in the figure below. Continue reading