Facilitating serendipity for interdisciplinary research

By Catherine Lyall

author-catherine-lyall
Catherine Lyall (biography)

How can institutions facilitate the serendipitous encounters that so often appear to characterise interdisciplinary careers? Is there an inherent hypocrisy in university leaders, research funders and policymakers claiming that they want to facilitate interdisciplinarity and then not creating the conditions that experienced interdisciplinarians say they need in order to foster this style of working?

Here I examine the importance of informal interactions, physical locations, the ‘small stuff’ and ‘slow research.’ I draw on interviews with British academics (at various career stages from postdoc to professor) whose doctoral studies had been funded by deliberately interdisciplinary studentship schemes. For more detail, including the sources of the quotations, see Lyall (2019).

Informality is crucial

Finding the time and space for informal discussions with colleagues is critical. What seems to be important is frequent, sustained dialogue (“bumping into people from different disciplines, while you’re having your coffee”) rather than one off events (“a workshop here, a sandpit there”). Senior academics of all complexions inevitably reflect back on the halcyon days of their time as postdocs, ruing the loss of that institutional culture that promoted “freedom,” “proximity to other people” and “the ability just to have a chit chat over coffee, come up with interesting ideas, perspectives that nobody had ever thought of before.”

A place to grow?

Communal spaces and informal meeting points (those “conversations in the corridor”) are important. Yet, when space is at a premium, it is these social spaces that are often turned into offices or teaching spaces. Less than a generation ago, universities would have an active university staff club where colleagues would eat together regardless of discipline, resulting in a lot of “accidental relationships” (Aldrich 2014: 55). None of the UK based universities that I visited seemed to maintain this staff club tradition, perhaps as a consequence of growth or, more likely, changing work cultures and increasing time pressures.

The disadvantages of universities being situated across multiple campuses, offices remote from the main campus or departments split across two buildings should not be underestimated:

[I]t’s about a ten minute walk but boy does that make a difference … it’s not the same thing as popping next door or meeting someone at coffee and being able to discuss your ideas.

Facilitating the small stuff

The ‘small stuff’ is about personal networks that:

  • are enduring (“You can look up experts in your department but it’s nowhere near the same as knowing that that was the person I sat next to when I did my PhD”)
  • arise through unexpected routes (eg., meetings with new colleagues on a picket line)
  • require creativity and personal responsibility
  • need mutually respectful spaces where “anything goes” and “it’s fine if you don’t understand something.”

This is related to the “strength of weak ties” (Granovetter 1973):

[I]t’s not exactly obscure stuff, you know about innovation and where it comes from and trying to create lots of weak ties across different networks, trying to maintain lots of different networks. There is actually theory behind this stuff and it flies in the face of what we’re told to do, which is target the topics everyone else is working on, target the big funding schemes that everyone else is targeting, target the top 10 journals that everyone else is targeting.

These weak ties are characterised as “indispensable to individuals’ opportunities and to their integration into communities” (Granovetter 1973: 1378) in contrast to strong ties, which encourage local cohesion but ultimately lead to fragmentation. In other words, strong ties are likely to foster cliques (as one might define a discipline), whereas weak ties are more likely to connect members to a breadth of different groups.

Interdisciplinary research as slow research

It is generally recognised that interdisciplinary research usually takes longer to produce results because, inter alia, of the extra time needed to access new literature, learn new concepts and perhaps build and foster dialogue within a new research team. Leahey et al. (2017) have shown numerically that this slowness contributes to a “productivity penalty” where interdisciplinary scholars gain greater prominence through citations but are less productive than their monodisciplinary peers with their publication output.

In their blog post on how transformative knowledge is co-produced, Stirling and colleagues urge us to resist the pressures of modern academia and describe interdisciplinary (or, in their case, transdisciplinary) encounters with research partners as a form of “slow knowledge” where these projects are not just “one-off” but reflect relationships sustained over time.

The Slow Science Manifesto (Slow Science Academy 2010) calls for time to ”misunderstand each other, especially when fostering lost dialogue between humanities and natural sciences” and points out that science needs “time to fail.” If contemporary academic life is indeed typified by “distractedness and fragmentation” (Berg and Seeber 2016: 90) what does this mean for interdisciplinary integration, which by Orr’s definition, is the very opposite of fast knowledge:

Fast knowledge is mostly linear; slow knowledge is complex and ecological (Orr 2002: 40).

Concluding questions

As an interdisciplinary community, can we create opportunities to step back and think through issues and processes related to the generation of high-quality interdisciplinary research? If interdisciplinarity is characterised by “slowness,” what implications could that have for career choice given different institutional environments (interdisciplinary research centre versus traditional university department, for example)? How do researchers who are striving for ways to establish more meaningful interdisciplinary research engagements, (often through less structured, serendipitous encounters) avoid becoming anathema in the modern academy?

To find out more:
Lyall, C. (2019). Being an Interdisciplinary Academic: How Institutions Shape University Careers. Palgrave Pivot: Cham Switzerland. (Book information): https://www.palgrave.com/gb/book/9783030186586

References:
Aldrich, J. (2014). Interdisciplinarity. Oxford University Press: Oxford, United Kingdom.

Granovetter, M. S. (1973). The Strength of Weak Ties. American Journal of Sociology, 78, 6: 1360-1380.

Leahey, E., Beckman, C. M. and Stanko, T. L. (2017). Prominent but Less Productive: The Impact of Interdisciplinarity on Scientists’ Research. Administrative Science Quarterly, 62, 1: 105-139.

Orr, D. W. (2002). Nature of Design: Ecology, Culture, and Human Intention. Oxford University Press: Oxford, United Kingdom.

Slow Science Academy. (2010). The Slow Science Manifesto. (Online): http://slow-science.org/.

Biography: Catherine Lyall PhD is Professor of Science and Public Policy at the University of Edinburgh, UK. Her career at the University of Edinburgh has progressed from part-time Research Officer to Personal Chair via numerous research contracts within grant-funded research centres and a period as Associate Dean for Research Careers. She has brought this experience to bear in the book described in this blog post. She is a science policy researcher and evaluator of knowledge exchange and interdisciplinary research activities who has acted as a consultant to a number of public bodies including the UK Economic and Social Research Council (ESRC), Scottish Funding Council, and the European Commission.

Detecting non-linear change ‘inside-the-system’ and ‘out-of-the-blue’

Susan van ‘t Klooster and Marjolijn Haasnoot

Author - Susan van ‘t Klooster
Susan van ‘t Klooster (biography)

Change can be expected, envisioned and known, and even created, accelerated or stopped. But change does not always follow a linear and predictable path, nor is it always controllable. Novelty and surprise are inescapable features of life. Non-linear change can involve threats or opportunities.

Although it defines the world we live in, who we are, the outlooks we have and what we do, we often do not relate to non-linear change in a meaningful way. What is holding us back from engaging with it? How do we deal with non-linear change? And what are promising ways forward?

Author - marjolijn-haasnoot
Marjolijn Haasnoot (biography)

Why is thinking about and anticipating non-linear change difficult?

Generally speaking, non-linearity is difficult to define and conceptualize, because there are multiple interacting forces at the intersection of many domains, manifesting on different spatial and temporal scales and many different actors and (often conflicting) perspectives are involved. As a result, both the nature of change, its underlying causalities, potential chain reactions, and its potential effects are uncertain and at best partially knowable.

Non-linearity is also difficult to grasp because it is about processes and events that may or may not happen. Such processes and events are complex and uncertain and can lead to different perspectives and disagreement between stakeholders. When non-linearity occurs, it may come as a surprise or shock and may have a disruptive effect. It is no understatement to say that we are inexperienced with respect to non-linearity.

Instead, we are much more experienced in reasoning from some evolutionary development. As a result of this general tendency to focus on logical consequences of causal patterns in the past and the present, being confronted with non-linear change may generate insecurity, confusion and a general feeling of discomfort. These feelings can result in ignorance and paralysis of decision making. Thus, refraining from thinking about it makes us vulnerable.

We describe two different, but potentially synergetic, approaches in which detecting and monitoring seeds of change are key: ‘inside-the-system’ and ‘out-of-the-blue’, illustrated in the figure below. Both approaches share the idea that systems can become unstable beyond a critical value. Induced by fluctuations within a system and by external disturbances, a system can instantaneously change. In his book Earth in the Balance (2000), former US Vice President Al Gore uses the analogy of a pile of sand. Dropping one grain after another on a pile of grain does not budge the ‘grain system’. Instead, it slowly builds a stable cone. However, at some point, a critical value is reached, which causes the cone to collapse. Each approach discussed below has a different search light for finding system thresholds and changes.

vantklooster_detecting-non-linear-change_ inside-the-system-out-of-the-blue
Different search lights: ‘Inside-the-system’ and ‘Out-of-the-blue’ (Copyright: Susan van ‘t Klooster)

Finding seeds of non-linear change – ‘inside-the-system’

This approach searches primarily for system indicators that may be an early warning prelude to change and adaptation tipping points. Coherent and longitudinal monitoring of these indicators can help to:

  • create a deeper insight into the system’s dynamics;
  • signal changes that jeopardize (or provide opportunities) for achieving defined objectives in a timely manner;
  • change plans and strategies to continue to achieve the objectives under changed conditions;
  • implement actions not too early nor too late; and to avoid investing too much or too little (Haasnoot et al., 2018).

By focusing on those seeds of change we know relatively well because they are part of the current system – so-called ‘known unknowns’, – we become more conscious about potential new conditions and situations.

An example is adaptive planning in the context of Dutch delta management, where important change indicators include observed and projected sea-level rise along the coast, global mean sea-level rise, storm surge frequency and frequency of alarms to close storm surge barriers.

Finding seeds of non-linear change – ‘out-of-the-blue’

This approach searches for so-called ‘wild cards’: low-probability/high-impact events that may be a prelude to a major, sudden and disruptive break with the status-quo.

Signals of change are found beyond the dominant frames and outside the system. The focus here is on cross-cutting trends and events that may surprise us by coming ‘out-of-the-blue’. We do not know if they may happen, the rapidity with which they may unfold nor their potential effects.

It is, therefore, explicitly not the objective to predict and control such disruptive threats (or opportunities). Instead, this approach is aimed towards:

  • scaling down our blind spots towards our future;
  • becoming more literate in understanding the nature of potential disruptors;
  • being more prepared once our current systems are challenged;
  • avoiding a panic reaction and creating an information and strategic advantage.

These changes are considered ‘unknown unknowns’, but it is possible to imagine what some of these changes could be, such as energy becoming available in a limitless supply, the collapse of a major currency, average global life expectancy increasing to 120 years or a new pest that wipes out grain crops.

Strengths and weaknesses

Both approaches have their own strengths and weaknesses. A risk of the ‘inside-the-system’ approach is that signals that are outside ‘the system’ and that do not fit into a dominant mental frame, remain unnoticed. To avoid tunnel vision, it is important to actively search for signals that could change current paradigms (potential game changers) beyond the system.

A weakness related to the ‘out-of-the-blue’ approach is the difficulty of making a solid link with decision-making.

At the same time, both approaches can reinforce one another: The strength of the first lies in its solid systems knowledge and link with decision-making. The second approach has a strong imaginative potential, that can be used to avoid perceptive and interpretive biases.

Four questions we should ask ourselves to detect change

How can we better integrate both perspectives and create synergies between them? Synergy starts by asking the following four questions:

  • Descriptive: What emergent trends (‘inside-the-system’) and potentially disruptive events (‘out-of-the-blue’) do we see or can we imagine? This involves using both systems knowledge and imaginative power.
  • Estimative: How (un)certain are we? This involves embracing, explicating and using multivocality, instead of assuming consensus.
  • Generative: What is the relative impact? This involves focusing on both direct and indirect effects.
  • Responsive: What can we do in response? This involves linking analysis to action, eg., adapting a plan or strategy, preparatory action, installing/altering a monitoring system, communication about outcomes for awareness raising, and further research.

Monitoring both in and outside the system helps to detect and anticipate change and to prepare in a timely fashion if needed.

Final remarks

Do you have suggestions for other ways to deal with non-linearity? Do you have useful examples where ‘inside-the-system’ and ‘out-of the-blue’ approaches have been successfully used to deal with non-linearities?

References:
Gore, A. (2000). Earth in the balance. Ecology and the human spirit. Earthscan: New York, United States of America.

Haasnoot, M. van ’t Klooster, S. and van Alphen, J. (2018). Designing a monitoring system to detect signals to adapt to uncertain climate change. Global Environmental Change, 52: 273-285. (Online) (DOI): https://doi.org/10.1016/j.gloenvcha.2018.08.003

Biography: Susan van ‘t Klooster PhD researches and advises strategic policy and decision-making processes as a freelance consultant in the Netherlands. She specializes in foresight methodology, practice and processes. Her research interests include evaluative foresight, evaluative risk assessment and anticipatory monitoring. Her research covers a wide range of areas, including adaptive water management, spatial planning, environmental policy, population health, education, (aviation) security, social security and employment and migration management.

Biography: Marjolijn Haasnoot PhD is a senior researcher/advisor at Deltares (an independent institute for applied research in the field of water and subsurface) and Associate Professor at Utrecht University in the Netherlands. She specializes in water management, climate adaptation, integrated assessment modeling and decision-making under deep uncertainty. Over the past 20 years she worked on international and national research and consultancy projects assessing impacts of climate change, sea level rise, socio-economic developments and alternative management options to develop robust and adaptive plans. She developed the Dynamic Adaptive Policy Pathways (DAPP) method to support decision making under uncertain change. She was one of the founders of the Society for Decision Making under Deep Uncertainty.

This blog post is part of a series on unknown unknowns as part of a collaboration between the Australian National University and Defence Science and Technology.

For the eight other blog posts already published in this series, see: https://i2insights.org/tag/partner-defence-science-and-technology/

Scheduled blog posts in the series:
January 28, 2020: How can resilience benefit from planning? by Pedro Ferreira
February 11, 2020: Why do we protect ourselves from unknown unknowns? by Bem Le Hunte
February 25, 2020: Theory U: a promising journey to embracing unknown unknowns by Vanesa Weyrauch

 

Stakeholder engagement in research: The research-modified IAP2 spectrum

By Gabriele Bammer

author - gabriele bammer
Gabriele Bammer (biography)

What options are available to researchers for engaging stakeholders in a research project? What responsibilities do researchers have to stakeholders over the course of that project?

Despite increasing inclusion of stakeholders in research, there seems to be little guidance on how to do this effectively. Here I have adapted a framework developed by the International Association for Public Participation (IAP2 2018) for examining how the public are engaged in government decision making. The research-modified IAP2 spectrum, written from a researcher perspective, is shown in the figure below. Continue reading

Research integration and implementation: Building resources and community

By Gabriele Bammer

author - gabriele bammer
Gabriele Bammer (biography)

This is the fourth annual “state of the blog” review.

For the past four years the blog has worked well, achieving significant growth. In 2020 we’re planning improvements, mainly to make specific resources easier to find and access. In 2019 there were a number of firsts, including surpassing 250 blog posts and 300 authors. Check out the nine blog posts published in 2019 that achieved more than 750 views. And if you are looking for something thought-provoking to read over, what for many, will be a holiday break, see below for a selection of gems. Continue reading

Good practice in community-based participatory processes in Aboriginal and Torres Strait Islander research

By Jan Chapman, Alyson Wright, Nadine Hunt and Bobby Maher

author - jan chapman
Jan Chapman (biography)

How can participatory process in Aboriginal and Torres Strait Islander communities be made adaptable and flexible? How can theoretical frameworks take into account the cultural and geographical complexities of communities and their contexts?

Here we provide five key principles that we have found useful in engaging communities in the Mayi Kuwayu Study (https://mkstudy.com.au/). These include: community decision-making; involvement in study governance; community capacity development; effective communications; and, long-term and multi-engagement processes. Continue reading

Yin-yang thinking – A solution to dealing with unknown unknowns?

By Christiane Prange and Alicia Hennig

author - christiane prange
Christiane Prange (biography)

Sometimes, we wonder why decisions in Asia are being made at gargantuan speed. How do Asians deal with uncertainty arising from unknown unknowns? Can yin-yang thinking that is typical for several Asian cultures provide a useful answer?

Let’s look at differences between Asian and Western thinking first. Western people tend to prefer strategic planning with linear extrapolation of things past. The underlying mantra is risk management to buffer the organization and to protect it from harmful consequences for the business. But juxtaposing risk and uncertainty is critical. Under conditions of uncertainty, linearity is at stake and risk management limited. Continue reading