Concepts

Valuing diversity: The good, the original and the outsider

By Frédéric Darbellay

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Frédéric Darbellay (biography)

Stay in the norm, transform it or transgress it? If many researchers and teachers are comfortable in their disciplinary fold and providing good and loyal service to a well-defined epistemic community, more atypical profiles are also emerging, contributing to inter- and trans- disciplinary diversity.

I explore three complementary figures likely to cover the spectrum going from a good and respectable disciplinary worker (the Good) to the more disturbing figure of the Outsider, with the Original in between.

But first I want to share some reflections on how originality is (not) valued.

Originality in an uncertain world

Originality seems to be one of the supreme values of the knowledge economy, increasingly promoted in times of change and uncertainty. I, you, we all have to be original to find new solutions to old, new and future problems.

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Ten insights on the interplay between evidence and policy

By Kat Smith and Paul Cairney

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1. Kat Smith (biography)
2. Paul Cairney (biography)

How can we improve the way we think about the relationship between evidence and policy? What are the key insights that existing research provides?

1. Evidence does not tell us what to do

It helps reduce uncertainty, but does not tell us how we should interpret problems or what to do about them.

2. There is no such thing as ‘the evidence’

Instead, there is a large number of researchers with different backgrounds, making different assumptions, asking different questions, using different methods, and addressing different problems.

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Considering uncertainty, awareness and ambiguity as a three-dimensional space

By Fabio Boschetti

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Fabio Boschetti (biography)

The concept of unknown unknowns highlights the importance of introspection in assessing knowledge. It suggests that finding our way in the set of known-knowns, known-unknowns, unknown-knowns and unknown-unknowns, reduces to asking:

  1. how uncertain are we? and
  2. how aware are we of uncertainty?

When a problem involves a decision-making team, rather than a single individual, we also need to ask:

  1. how do context and perception affect what we know?

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Evolution of hot topics in team science / 团队科学中热点主题的演变

By Ying Huang, Ruinan Li, Yashan Li and Lin Zhang

A Chinese version of this post is available

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1. Ying Huang (biography)
2. Ruinan Li (biography)
3. Yashan Li (biography)
4. Lin Zhang (biography

What are the research hotspots in the Science of Team Science (SciTS) field? How have they evolved in the last decade?

We used conference programs from the annual International Science of Team Science (INSciTS) conferences held between 2010-2019 and the CorTexT Platform (https://www.cortext.net/) to select the top terms used with high frequency in the 852 titles and abstracts.

High-frequency terms and their evolution

The top 25 terms and their evolution are shown in Figure 1: evaluation / assessment (89 mentions), team science training (63), leadership (31), communication (30), curriculum (14),community (29), funding (13), mixed methods (13), model (13), Toolbox Project / Toolbox Dialogue Initiative (13), Clinical and Translational Science Award (CTSA) (11), graduate students (11), networks (26), education (20), tools (20), productivity (16), bibliometrics (19), framework (14), gender (11), readiness (8), distributed collaboration (7), multi-team systems (7), research network tools (8), team performance (7), multiple levels (5).

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Acknowledging and responding to criticisms of interdisciplinarity / Reconnaître et répondre aux critiques de l’interdisciplinarité

By Romain Sauzet

A French version of this post is available

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Romain Sauzet (biography)

What are the core arguments that critics of interdisciplinarity employ? Which of these criticisms can help to clarify what interdisciplinarity is and what it isn’t?

While some of the criticisms of interdisciplinarity stem from a general misunderstanding of its purpose or from a bad experience, others seem well-founded. Thus, while some must be rejected, others should be accepted.

I outline five different types of criticisms drawn from three main sources:
(1) academic writings (see reference list), (2) an empirical survey on interdisciplinarity (Sauzet 2017), (3) informal discussions. These criticisms extend the ideas presented in an earlier blog post, Why We Should Not Ignore Interdisciplinarity’s Critics by Rick Szostak. I reflect on how interdisciplinarity could be improved by attending to key criticisms.

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What lessons for improving interdisciplinary collaboration emerged from the 2019 Science of Team Science conference?

By Julie Thompson Klein and Ben Miller

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1. Julie Thompson Klein’s biography
2. Ben Miller (biography)

Six lessons emerged from the seven plenary panels at the May 2019 Science of Team Science conference hosted by Michigan State University in the US.

1. Understanding the nature of team science is crucial to monitoring team behavior, including managing conflict, diverse voices, and strong leadership.

The Science of Groups and Teams plenary panel affirmed one approach alone is not sufficient. It featured perspectives from psychology, management, and organizational behavior in two regional research institutions, the University of Michigan and Michigan State University.

2. Networking and collaboration increase access to pertinent expertise and skills, equipment, and other resources including funding, relevant techniques, education and training, visibility and recognition.

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Eight grand challenges in socio-environmental systems modeling

By Sondoss Elsawah and Anthony J. Jakeman

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1. Sondoss Elsawah (biography)
2. Anthony Jakeman (biography)

As we enter a new decade with numerous looming social and environmental issues, what are the challenges and opportunities facing the scientific community to unlock the potential of socio-environmental systems modeling?

What is socio-environmental systems modelling?

Socio-environmental systems modelling:

  1. involves developing and/or applying models to investigate complex problems arising from interactions among human (ie. social, economic) and natural (ie. biophysical, ecological, environmental) systems.
  2. can be used to support multiple goals, such as informing decision making and actionable science, promoting learning, education and communication.
  3. is based on a diverse set of computational modeling approaches, including system dynamics, Bayesian networks, agent-based models, dynamic stochastic equilibrium models, statistical microsimulation models and hybrid approaches.

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Fifteen characteristics of complex social systems

By Hamilton Carvalho

Author - Hamilton Carvalho
Hamilton Carvalho (biography)

What is it about complex social systems that keeps reproducing old problems, as well as adding new ones? How can public policy move away from what I call the Mencken Syndrome (in reference to a quotation from American journalist Henry Mencken) – that is, continually proposing clear and simple solutions to complex social problems – that are also wrong!

With this goal in mind, I have compiled a list of fifteen major characteristics of complex social systems based on the system dynamics and complexity sciences literatures, as well as my own research.

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Why do we protect ourselves from unknown unknowns?

By Bem Le Hunte

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Bem Le Hunte (biography)

Why do very few people enjoy sitting comfortably with their unknown unknowns? Why is there an uncomfortable liminality ‘betwixt and between’ the known and unknown worlds?

How can we explore unknowns in a more speculative, playful, creative capacity, through our imaginations? How can we use lack of knowledge to learn about ourselves and let it teach us how to be comfortable and curious in the midst of unknowing?

The power and allure of unknown unknowns have long been recognised by creative practitioners as a holy grail for inspiration. Borges wrote in The Library of Babel about a fictitious library where all books ever written existed together, but this library turns to a dystopia as the reader discovers that “the certainty that everything has already been written annuls us, or renders us phantasmal.”

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Decentering academia through critical unlearning in transdisciplinary knowledge production / Descentralizando la academia a través del des- aprendizaje crítico en la producción de conocimiento transdiciplinario

By Gabriela Alonso-Yanez, Lily House-Peters and Martin Garcia Cartagena

A Spanish version of this post is available

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1. Gabriela Alonso-Yanez (biography)
2. Lily House-Peters (biography)
3. Martin Garcia Cartagena (biography)

How can academic researchers working in transdisciplinary teams establish genuine collaborations with people who do not work in academia? How can they overcome the limitations of their discipline-based training, especially assigning value and hierarchy to specialized forms of knowledge production that privileges certain methodologies and epistemologies over others?

We argue that to truly engage in collaborative work, academics need to participate in deliberate processes of critical unlearning that enable the decentering of academia in the processes and politics of transdisciplinary knowledge production and knowledge translation. What we mean by this is that academics have to be willing to acknowledge, reflect upon, and intentionally discard conventional avenues of designing and conducting research activities in order to be authentically open to other ways of exploring questions about the world in collaboration with diverse groups of social actors.

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

Susan van ‘t Klooster and Marjolijn Haasnoot

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1. Susan van ‘t Klooster (biography)
2. Marjolijn Haasnoot (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?

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.

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

By Christiane Prange and Alicia Hennig

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1. Christiane Prange (biography)
2. Alicia Hennig (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.

In several Asian cultures, like China, dealing with high uncertainty and volatility is day-to-day business. The country overall scores comparatively low on the uncertainty avoidance index as illustrated by culture researcher Geert Hofstede (2001).

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