Concepts – Page 13 – Integration and Implementation Insights

What motivates researchers to become transdisciplinary and what are the implications for career development?

June 8, 2022November 12, 2019

By Maria Helena Guimarães, Olivia Bina and Christian Pohl

authors_mosaic_maria-helena-guimarães_olivia-bina_christian-pohl.jpg — 1. Maria Helena Guimarães (biography)
2. Olivia Bina (biography)
3. Christian Pohl (biography)

If disciplines shape scientific research by forming the primary institutional and cognitive units in academia, how do researchers start being interested in and working with a transdisciplinary approach? How does this influence their career development?

We interviewed 12 researchers working in Switzerland who are part of academia and identify as ‘transdisciplinarians’.

They described seven types of motivations:

Participatory research and power

August 11, 2023October 15, 2019

By Diana Rose

Can even the most well-designed participatory research really level the power relations between researchers and the relevant community? The key issues are who sets the research agenda, who drives the research process and governs it, and who interprets information. In all these aspects of research, the aim is for the community to no longer be ‘subjects’ but equal partners.

In this blog post, I outline challenges to achieving this mission, so that we can be realistic about what’s involved in trying to achieve equal partnerships. The difficulties identified are not proposed as tensions to be ‘solved’ but as dilemmas that can be articulated so as better to facilitate good practice, not reach an unattainable perfect state.

In my research on mental health services, my team and I are mental health service users ourselves and are therefore more intrinsically part of the community being researched.

What do you know? And how is it relevant to unknown unknowns?

August 11, 2023September 24, 2019

By Matthew Welsh

Author - Matthew Welsh — Matthew Welsh (biography)

How can we distinguish between knowledge and ignorance and our meta-knowledge of these – that is, whether we are aware that we know or don’t know any particular thing? The common answer is the 2×2 trope of: known knowns; unknown knowns; known unknowns; and unknown unknowns.

For those interested in helping people navigate a complex world, unknown unknowns are perhaps the trickiest of these to explain – partly because the moment you think of an example, the previously “unknown unknown” morphs into a “known unknown”.

My interest here is to demonstrate that this 2×2 division of knowledge and ignorance is far less crisp than we often assume.

This is because knowledge is not something that exists in the world but rather in individual minds. That is, whether something is ‘known’ depends not on whether someone, somewhere, knows it; but on whether this person, here-and-now does.

Using discomfort to prompt learning in collaborative teams

August 15, 2022September 3, 2019

By Rebecca Freeth and Guido Caniglia

authors_rebecca-freeth_guido-caniglia — 1. Rebecca Freeth (biography)
2. Guido Caniglia (biography)

We know that reflecting can make a marked difference to the quality of our collective endeavour. However, in the daily busyness of inter- and trans- disciplinary research collaborations, time for reflection slides away from us as more immediate tasks jostle for attention. What would help us put into regular practice what we know in theory about prioritising time to reflect and learn?

Discomfort sometimes provides the necessary nudge in the ribs that reminds us to keep reflecting and learning. The discomfort of listening to the presentation of a colleague you like and respect, but having very little idea what they’re talking about.

Accountability and adapting to surprises

July 10, 2026August 27, 2019

By Patricia Hirl Longstaff

Image of Patricia Hirl Longstaff — Patricia Hirl Longstaff (biography)

We have all been there: something bad happens and somebody (maybe an innocent somebody) has their career ruined in order to prove that the problem has been fixed. When is blame appropriate? When is the blame game not only the wrong response, but damaging for long-term decision making?

In a complex and adapting world, errors and failure are not avoidable. The challenges decision-makers and organizations face are sometimes predictable but sometimes brand new. Adapting to surprises requires more flexibility, fewer unbreakable rules, more improvisation and deductive tinkering, and a lot more information about what’s going right and going wrong. But getting there is not easy because this challenges some very closely held assumptions about how the world works and our desire to control things.

Let’s not kid ourselves. Sometimes people do really dumb things that they should be blamed for. What we need is to be more discriminating about when finding blame and accountability is appropriate.

Why model?

August 11, 2023August 20, 2019

By Steven Lade

What do you think about mathematical modelling of ‘wicked’ or complex problems? Formal modelling, such as mathematical modelling or computational modelling, is sometimes seen as reductionist, prescriptive and misleading. Whether it actually is depends on why and how modelling is used.

Here I explore four main reasons for modelling, drawing on the work of Brugnach et al. (2008):

Prediction
Understanding
Exploration
Communication.

I start with mental models – the informal representations of the world that we all use as we go about both our personal and professional lives – and then move on to formal models.

Linking collective impact to the characteristics of open living systems

August 11, 2023May 21, 2019

By Lewis Atkinson

How can communities most effectively achieve collective impact, moving from fragmented action and results to collective action and deep, durable systems change? In particular, what can those seeking to understand the characteristics required for collective impact learn from the characteristics of open living systems?

In this blog post I link five characteristics for collective impact, based on Cabaj and Weaver (2016) with 12 characteristics of open living systems drawn from Haines (2018, building on the work of Ludwig von Bertalanffy).

The five characteristics for collective impact are each necessary, but on their own insufficient to achieve impact because they are all parts of the same method of systems change:

What every interdisciplinarian should know about p values

April 15, 2022April 30, 2019

By Alice Richardson

In interdisciplinary research it’s common for at least some data to be analysed using statistical techniques. Have you been taught to look for ‘p < 0.05’ meaning that there is a less than 5% probability that the finding occurred by chance? Do you look askance at your statistician colleagues when they tell you it’s not so simple? Here’s why you need to believe them.

The whole focus on p < 0.05 to the exclusion of all else is a historical hiccup, based on a throwaway line in a manual for research workers. That manual was produced by none other than R.A. Fisher, giant of statistical inference and inventor of statistical methods ranging from the randomised block design to the analysis of variance. But all he said was that “[p = 0.05] is convenient to take … as a limit in judging whether a deviation is to be considered significant or not.” Convenient, nothing more!

Incommensurability, plain difference and communication in interdisciplinary research

March 11, 2022April 9, 2019

By Vincenzo Politi

Where does the term incommensurability come from? What is its relevance to interdisciplinarity? Is it more than plain difference? Does incommensurability need to be reconceptualized for interdisciplinarity?

Incommensurability: its origins and relevance to interdisciplinarity

‘Incommensurability’ is a term that philosophers of science have borrowed from mathematics. Two mathematical magnitudes are said to be incommensurable if their ratio cannot be expressed by a number which is an integer. For example, the radius and the circumference of a circle are incommensurable because their ratio is expressed by the irrational number π.

Knowledge asymmetry in interdisciplinary collaborations and how to reduce it

January 21, 2026February 26, 2019

By Max Kemman

How can tasks and goals among partners in a collaboration be effectively negotiated, especially when one party is dependent on the deliverables of another party? How does knowledge asymmetry affect such negotiations? What is knowledge asymmetry anyway and how can it be dealt with?

What is knowledge asymmetry?

My PhD research involves historians who are dependent on computational experts to develop an algorithm or user interface for historical research. They therefore needed to be aware of what the computational experts were doing.

Metacognition as a prerequisite for interdisciplinary integration

September 11, 2024February 5, 2019

By Machiel Keestra

What’s needed to enable the integration of concepts, theories, methods, and results across disciplines? Why is communication among experts important, but not sufficient? Interdisciplinary experts must also meta-cognize: both individually and as a team they must monitor, evaluate and regulate their cognitive processes and mental representations. Without this, expertise will function suboptimally both for individuals and teams. Metacognition is not an easy task, though, and deserves more attention in both training and collaboration processes than it usually gets. Why is metacognition so challenging and how can it be facilitated?

Developing a ‘capabilities approach’ for measuring social impact

September 11, 2024November 27, 2018

By Daniel J. Hicks

daniel-hicks — Daniel J. Hicks (biography)

Why do familiar metrics of impact often seem “thin” or to miss the point of research designed to address real-world problems? Is there a better way to measure the social impact of research?

In a recent paper (Hicks et al., 2018), my coauthors and I identified a key limitation with current metrics and started to look at how concepts from philosophy — specifically, ethics — can help us explain the goals of our research, and potentially lead to better metrics.

What’s the problem?

To understand the limitations of current metrics for measuring the social impact of research, it is useful to understand two distinctions, between resources and goals and between inward-facing and outward-facing goals for research.