Interdisciplinarity and evil – Understanding incommensurability

By J. Britt Holbrook

J. Britt Holbrook (biography)

Incommensurability is a recognized problem in interdisciplinary research. What is it? How can we understand it? And what can we do about it?

What is it?

Incommensurability is best illustrated by a real example. I once co-taught a class with a colleague from another discipline. Her discipline depends on empirical analysis of data sets, literally on counting things. I, on the other hand, am a philosopher. We don’t count. One day she said to our students, “If you don’t have an empirical element in what you’re doing, it’s not research.” I watched the students start nodding, paused for half a beat, and volunteered, “So, I’ve never done any research in my entire career.” “That’s right!” she replied, immediately, yet hesitating somewhere between a discovery and a joke.

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CoNavigator: Hands-on interdisciplinary problem solving

By Katrine Lindvig, Line Hillersdal and David Earle

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1. Katrine Lindvig (biography)
2. Line Hillersdal (biography)
3. David Earle (biography)

How can we resolve the stark disparity between theoretical knowledge about interdisciplinary approaches and practical applications? How can we get from written guidelines to actual practices, especially taking into account the contextual nature of knowledge production; not least when the collaborating partners come from different disciplinary fields with diverse expectations and concerns?

For the past few years, we have been developing ways in which academic theory and physical interactions can be combined. The result is CoNavigator – a hands-on, 3-dimensional and gamified tool which can be used:

  • for learning purposes in educational settings
  • as a fast-tracking tool for interdisciplinary problem solving.

CoNavigator is a tool which allows groups to collaborate on a 3-dimensional visualisation of the interdisciplinary topography of a given field or theme.

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Ten steps to make your research more relevant

By Christian Pohl, Pius Krütli and Michael Stauffacher

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1. Christian Pohl (biography)
2. Pius Krütli (biography)
3. Michael Stauffacher (biography)

Interdisciplinary and transdisciplinary research often aims at broader impact in society. But, how can you make such impact happen?

A researcher might face a number of questions (s)he was not necessarily trained to address, such as:

  • How can I be sure that my research question will provide knowledge relevant for society?
  • Who in this fuzzy thing called society are my primary target audiences anyway?
  • Are some of them more important for my project than others?

Over the last several years, we developed 10 steps to provide a structured way of thinking through how to improve the societal relevance of a research project, as summarised in the table below.

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Recognising interdisciplinary expertise

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Gabriele Bammer (biography)

By Gabriele Bammer

Could we overcome the challenges of embedding interdisciplinarity in the academic mainstream if relevant expertise were defined and recognized as a new discipline? What is this relevant expertise?

Here I consider team-based interdisciplinarity addressing complex societal and environmental problems and argue that it needs specific expertise over and above that contributed by disciplines. This set of knowledge and skills is currently poorly defined and recognized.

If contributing such know-how was an established role, it could provide a way of more adequately integrating interdisciplinary researchers into academic institutions. Furthermore, the time is ripe to codify that expertise by pulling together lessons from decades of experience.

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Epistemological obstacles to interdisciplinary research

By Evelyn Brister

evelyn-brister
Evelyn Brister (biography)

What causes interdisciplinary collaborations to default to the standard frameworks and methods of a single discipline, leaving collaborators feeling like they aren’t being taken seriously, or that what they’ve brought to the project has been left on the table, ignored and underappreciated?

Sometimes it is miscommunication, but sometimes it is that collaborators disagree. And sometimes disagreements are both fundamental and intractable.

Often, these disagreements can be traced back to different epistemological frameworks. Epistemological frameworks are beliefs about how particular disciplines conceive of what it is they investigate, how to investigate it, what counts as sufficient evidence, and why the knowledge they produce matters.

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Promotion and tenure policies for interdisciplinary and collaborative research

By Julie Thompson Klein and Holly J. Falk-Krzesinski

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1. Julie Thompson Klein’s biography
2. Holly J. Falk-Krzesinski (biography)

Expanding interest in interdisciplinary and collaborative research across universities, funding agencies, professional organizations, and science-policy bodies has prompted growing attention to the academic reward system. Promotion and tenure loom large in this discussion. The acronym “P&T” in this blog is the customary abbreviation for “promotion and tenure” in North America, but the practices are international. All collaborative research is not interdisciplinary, and all interdisciplinary research is not team based. However, they are coupled increasingly in order to address complex scientific and societal problems, while also fostering innovation and partnerships bridging the academy and industry.

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Sharing mental models is critical for interdisciplinary collaboration

By Jen Badham and Gabriele Bammer

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1. Jen Badham (biography)
2. Gabriele Bammer (biography)

What is a mental model? How do mental models influence interdisciplinary collaboration? What processes can help tease out differences in mental models?

Mental models

Let’s start with mental models. What does the word ‘chair’ mean to you? Do you have an image of a chair, perhaps a wooden chair with four legs and a back, an office chair with wheels, or possibly a comfortable lounge chair from which you watch television?

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Productive multivocal analysis – Part 2: Achieving epistemological engagement

By Kristine Lund

kristine-lund
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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Productive multivocal analysis – Part 1: Avoiding the pitfalls of interdisciplinarity

By Kristine Lund

kristine-lund
Kristine Lund (biography)

Many voices are expressed when researchers from different backgrounds come together to work on a new project and it may sound like cacophony. All those voices are competing to be heard. In addition, researchers make different assumptions about people and data and if these assumptions are not brought to light, the project can reach an impasse later on and much time can be wasted.

So how can such multivocality be positive and productive, while avoiding trouble? How can multiple voices be harnessed to not only achieve the project’s goals, but also to make scientific progress?

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Learning from Google about inter- and transdisciplinary leadership

By Janet G. Hering

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Janet G. Hering (biography)

Like most engineers, the Google leadership had assumed that the leader of an engineering team must be at least as competent technically as the members of the team. As Laszlo Bock described in his 2015 book Work Rules!, however, a data-driven assessment disproved this assumption. The counter-intuitive result of “Project Oxygen” was that having “important technical skills that help advise the team” only ranked number eight in the list of key attributes differentiating the most from the least effective managers.

This is very good news for leaders of inter- and transdisciplinary synthesis projects since it’s highly unlikely that these leaders could have all the subject expertise relevant to their projects. If subject expertise is not the most important characteristic of leadership, then what kind of expertise should leaders have and what kind of roles do they play? How important are leaders and leadership in such synthesis projects?

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A guide to ontology, epistemology, and philosophical perspectives for interdisciplinary researchers

By Katie Moon and Deborah Blackman

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1. Katie Moon (biography)
2. Deborah Blackman (biography)

How can understanding philosophy improve our research? How can an understanding of what frames our research influence our choices? Do researchers’ personal thoughts and beliefs shape research design, outcomes and interpretation?

These questions are all important for social science research. Here we present a philosophical guide for scientists to assist in the production of effective social science (adapted from Moon and Blackman, 2014).

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Pro-active learning to improve interdisciplinary processes

By Laura R. Meagher

Member of Board of Governors
Laura R. Meagher (biography)

I am a firm believer in looking at interdisciplinary collaboration and knowledge exchange – or impact generation – as processes. If you can see something as a process, you can learn about it. If you can learn about it, you can do it better!

I find that this approach helps people to feel enfranchised, to believe that it is possible for them to open up what might have seemed to be a static black box and achieve understanding of the dynamics of how nouns like ‘interdisciplinarity’ or ‘knowledge exchange’ or ‘research impact’ can actually come to be.

In addition to using sources such as master classes, briefing guides or articles, individuals involved in interdisciplinary work can take several (inter-related) pro-active approaches to learning about interdisciplinary processes:

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