Teamwork

Six lessons for newly-forming large research consortia

By Daniel Black and Geoff Bates

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1. Daniel Black (biography)
2. Geoff Bates (biography)

What are some key tips for establishing new, large consortia to tackle complex global challenges? What are the best ways to coordinate large groups of researchers, practitioners and publics towards a shared goal?

Describing this type of research is cumbersome. As a shorthand we have started to use the terms ‘LMITs’ (pronounced ‘limits’) and ‘New LMITs’ to denote similarly characterised projects and teams that are: ‘Newly forming’, ‘Large-scale’, ‘Mission-orientated’, and ‘Inter- and Trans-disciplinary’.

Drawing on our own experience over the past three years of establishing a New LMIT, we suggest six primary inter-related recommendations for other New LMITs, and for those who fund or support such research groups:

1. Factor in (far) more time than you might expect
2. Seek out funders who understand

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An analytical framework for knowledge co-production

By Marianne Penker

Marianne Penker (biography)

How can students and academics starting out in transdisciplinary research begin to come to grips with knowledge co-production?

Colleagues and I developed a useful analytical framework comprising the following four elements:

  1. typology of actor roles (who?)
  2. research phases (when?)
  3. objectives and forms of actor integration (why?)
  4. types of knowledge (what?).

These four elements are illustrated in the figure below.

The development of the framework was based on the literature and our experiences in running a doctoral school on transdisciplinary sustainability research (see Enengel et al. 2012).

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Five core competency areas for participatory modeling

By Sondoss Elsawah, Elena Bakhanova, Raimo P. Hämäläinen and Alexey Voinov

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1. Sondoss Elsawah (biography)
2. Elena Bakhanova (biography)
3. Raimo P. Hämäläinen (biography)
4. Alexey Voinov (biography)

What knowledge and skills do individuals and teams need to be effective at participatory modeling?

We suggest that five core competency areas are essential for participatory modeling:

  1. systems thinking
  2. modeling
  3. group facilitation
  4. project management and leadership
  5. operating in the virtual space.

These are illustrated in the figure below.

These competency areas have naturally overlapping elements and should therefore be seen as a holistic and interdependent set. Further, while certain competencies such as modeling skills can be addressed by individual members of a participatory modeling team, the entire process is a team effort and it is necessary to also consider the competencies as a group skill.

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Wisely navigating knowledge co-production: Towards an ethics that builds capacities

By Guido Caniglia and Rebecca Freeth

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1. Guido Caniglia (biography)
2. Rebecca Freeth (biography)

How can I ensure that marginalized voices are heard in this project? Whom do I call on to offer the next perspective in this workshop and why? How can I intervene in this particular disagreement in a productive way? These are typical questions that researchers and practitioners involved in knowledge co-production processes ask themselves. They express deep ethical concerns, which also have epistemological and political implications, as they address the question: What should I do in this situation? What is right and wrong for me to do here?

We suggest that a perspective based on the ancient virtue of practical wisdom may help researchers and practitioners alike working in knowledge co-production to navigate the complexities of these questions.

Practical wisdom: An ancient virtue for wise navigation

Our answers to the deep ethical questions that emerge in collaborative and participatory research will vary depending on the specifics of the situation we are in, who is involved, as well as our own positionality and role in research projects or academic institutions. There is no formula to follow. 

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An effective way to organize research coordination meetings

By Gemma Jiang, Diane Boghrat and Jenny Grabmeier

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1. Gemma Jiang (biography)
2. Diane Boghrat (biography)
3. Jenny Grabmeier (biography)

How can large cross-disciplinary science institutes consisting of multiple teams working on multiple research projects overcome significant challenges to research coordination? Key aspects are:

  1. Visibility: how to keep different project teams informed of each other’s progress?
  2. Learning: how to support cross-project learning?
  3. Accountability: how to keep project teams accountable for their goals and deliverables?

Tackling these challenges requires a combination of asynchronous communications such as Slack, newsletters and emails, as well as synchronous communications such as research coordination meetings.

We describe an effective way of organizing weekly research coordination meetings in an institute bridging the gap between computer science and biology and share key reflections.

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Keyword quiz: an icebreaker method for interdisciplinary teams

By Sebastian Rogga and Anton Parisi

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1. Sebastian Rogga (biography)
2. Anton Parisi (biography)

How can members of interdisciplinary teams quickly gain a better understanding of each other’s thematic preferences and skills in a way that is also engaging and fun?

We have developed a “keyword quiz” icebreaker method to facilitate exchange between members of interdisciplinary teams, especially between people who are not complete strangers to each other but are collaborating in a project context for the first time.

In brief, the idea is to communicate each member’s scientific profile based on keywords from publications that the team members have published and that they have selected based on specific categories.

The keywords of a publication are presented visually to the whole group and the team members then guess, in the form of a quiz, which team member published the associated publication.

After the author has been revealed, they share the reasons for choosing the publication.

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Externalizing implicit expectations and assumptions in transdisciplinary research

By Verena Radinger-Peer, Katharina Gugerell and Marianne Penker

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1. Verena Radinger-Peer (biography)
2. Katharina Gugerell (biography)
3. Marianne Penker (biography

How can implicit expectations and assumptions of team members in transdisciplinary research collaborations be identified?

We used Q-methodology as a tool to make diverse expectations and perceptions of transdisciplinary research collaborations tangible and thus negotiable.

Q-methodology is an established explorative, semi-quantitative method for investigating distinctive viewpoints of a given population based on inverted factor analysis. While we do not explain Q methodology here, it is increasingly used and we refer those who want to find out more to Watts and Stenner (2012).

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Improving cross-disciplinary collaboration with strategy knotworking and ecocycle planning

By Nancy White

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Nancy White (biography)

How can cross-disciplinary teams improve their project results and cross-team learning, especially when they are part of a portfolio of funded projects?

I have worked with cross disciplinary teams in international agriculture development, ecosystems management and mental health. For the most part, these are externally funded initiatives and have requirements both for results (application of the work) and for cross-team learning. Often there is not useful clarity about how funder and grantee agendas work in sync. And there is rarely opportunity or support for shared optimization and exploration across different portfolios of funded work.

I have used the six knotworking questions plus ecocycle planning from Liberating Structures to make it possible for a group to look back critically, assess the current state, and prospectively generate options to move forward.

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Dealing with differences in interests through principled negotiation

By Gabriele Bammer

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Gabriele Bammer (biography)

How can the interests of a diverse group of researchers and stakeholders tackling a complex societal problem be understood and managed?

Interests arise when a person has a stake in something and stands to gain or lose depending on what happens to that something:

  • researchers commonly have a stake in advancing their work and careers,
  • stakeholders affected by a societal problem generally have a stake in improving the problem, and
  • stakeholders in a position to do something about a problem generally have a stake in improving outcomes for the problem through their sphere of influence.

Interests relate not only to personal conditions or stakes (self-interest), but also to principles such as reducing inequities and promoting justice.

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Resolving disagreements by negotiating agreements in the right way

By Lawrence Susskind

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Lawrence Susskind (biography)

How can interdisciplinary teams avoid getting stuck on questions like:

  1. What kinds of data do we need to collect?
  2. What methods or techniques should we use to analyze our data?
  3. How should we handle gaps or incongruities in our findings?
  4. What are the policy implications or prescriptions that follow from our findings?

I want to share some lessons I’ve learned about handling disagreements on these four questions.

Research Design

One interdisciplinary project I worked on many years ago involved trying to assess the feasibility of burying nuclear waste in the ocean floor.

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Advancing considerations of affect in interdisciplinary collaborations

By Mareike Smolka, Erik Fisher and Alexandra Hausstein

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1. Mareike Smolka (biography)
2. Erik Fisher (biography)
2. Alexandra Hausstein’s biography

Have you ever had a fleeting impression of seeing certainty disrupted, the impulse to laugh when your expectations were broken, or a startling sense of something being both familiar and foreign at the same time?

As social scientists engaged in collaborative studies with natural scientists and engineers, we have had these experiences repeatedly while doing research. Whenever we recognized that our social science paradigm was confronted with a different approach to knowing the world, unsettling experiences of difference emerged, which we later analyzed as moments of disconcertment.

In a comparative analysis of the affective substrates of interdisciplinary collaboration (Smolka et al., 2020), we found that attending to disconcertment facilitated collaborative knowledge production.

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Collaboration agreement template

By L. Michelle Bennett, Edgar Cardenas and Michael O’Rourke

1. L. Michelle Bennett (biography)
2. Edgar Cardenas (biography)
2. Michael O’Rourke (biography)

As scientific research continues to move towards collaborative knowledge production, scientists must become more adept at working in teams. How can teams improve their chances of collaboration success? What is a good way to facilitate dialogue about shared values, norms and processes of collaboration? Are there ways of anticipating, identifying, and addressing obstacles as they arise?

We have designed a collaboration agreement template to assist teams in:

  • Making explicit and therefore transparent important aspects of their approach to collaboration
  • Ensuring they have a shared vision for their work together
  • Recognizing that their working relationships are dynamic, individually and as a team, and will require flexibility and a willingness to adapt over time
  • Establishing expectations for working together, including what they do and say
  • Preparing for disagreements and even conflicts, especially in the early stages and along the way when there are changes in team composition.

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