Are there lessons we can learn from the current response of service systems which have galvanized into action to meet the needs of children and families during the COVID-19 pandemic? How does the response of service systems affect our hypotheses about how change happens at scale?
In my professional role providing implementation support to public service systems, I’ve observed these systems responding to the COVID-19 pandemic with urgency and agility. The urgency is to be expected, but the agility has inspired me.
What can you do when a national funding umbrella organization asks you to add a new partner to a collaborative project, especially when that partner has a poor reputation for collaborating?
Here I share lessons based on my experience of leading a multi-million Euro grant, where two interdisciplinary language sciences laboratories, which had worked together successfully for 8 years, were preparing a bid for a 5-year continuation in funding. In the process of preparing that bid, our national umbrella organization suggested that a third language sciences laboratory that had strong links to neurosciences join the consortium.
By Steven Lam, Michelle Thompson, Kathleen Johnson, Cameron Fioret and Sarah Hargreaves
How can graduate students work productively with each other and community partners? Many researchers and practitioners are engaging in transdisciplinarity, yet there is surprisingly little critical reflection about the processes and outcomes of transdisciplinarity, particularly from the perspectives of graduate students and community partners who are increasingly involved.
Our group of four graduate students from the University of Guelph and one community partner from the Ecological Farmers Association of Ontario, reflect on our experiences of working together toward community food security in Canada, especially producing a guidebook for farmer-led research (Fioret et al. 2018). As none of us had previously worked together, nor shared any disciplines in common, we found it essential to first develop a guiding framework for collaboration. Our thinking combined the following key principles from action research and transdisciplinarity:
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.
There is considerable pressure on researchers to show that their work has impact and one area in which impact is valued is government policy making. But what makes for a successful government policy? What does it take to achieve striking government performance in difficult circumstances or the thousands of taken-for-granted everyday forms of effective public value creation by and through governments?
By Dan Stokols, Judith S. Olson, Maritza Salazar and Gary M. Olson
How can an ecosystem approach help in understanding and improving team science? How can this work in practice?
An Ecosystem Approach
Collaborations among scholars from different fields and their community partners are embedded in a multi-layered ecosystem ranging from micro to macro scales, and from local to more remote regions. Ecosystem levels include: