Three ways research perpetuates injustices

By Barış Bayram

Barış Bayram (biography)

Why is it hard to recognise the full value of a new idea, research finding or other innovation? Why do people fail to properly appreciate other people or things most of the time? Can this help explain why injustices persist?

There is no “invisible hand” that allocates rewards according to capabilities or performance, including ensuring that academic research or social interactions are recognised in terms of scientific or ethical merits.

There are three main patterns causing what I call “unjust appreciation”:

  1. lack of intellectual development to determine values, merits and deserts (ie., just rewards)
  2. cognitive biases and social biases, especially related to status and groups
  3. tribalism, along with power and conflict considerations that rely on cost-benefit analysis.

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Capitalising on incommensurability

By Darryn Reid

Darryn Reid (biography)

How can we harness incommensurability as a pivotal enabler of cross-disciplinary collaboration?

Effective cross-disciplinary research across multiple traditional disparate fields of study hinges on logical incommensurability, which occurs because, in general, those ideas will have been constructed using incompatible frameworks to solve distinct problem formulations within dissimilar intellectual traditions.

In other words, the internal logical consistency of a discipline’s way of approaching problems is no guarantee of ability to be integrated with another discipline’s way of approaching problems. Incommensurability should come as no surprise to anyone involved in cross-disciplinary activities. What is pivotal here, however, is the view that incommensurability is not an obstacle to be avoided or feared but an enabler.

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Addressing societal challenges: From interdisciplinarity to research portfolios analysis

By Ismael Rafols

Ismael Rafols (biography)

How can knowledge integration for addressing societal challenges be mapped, ‘measured’ and assessed?

In this blog post I argue that measuring averages or aggregates of ‘interdisciplinarity’ is not sufficiently focused for evaluating research aimed at societal contributions. Instead, one should take a portfolio approach to analyze knowledge integration as a systemic process over research landscapes; in particular, focusing on the directions, diversity and synergies of research trajectories.

There are two main reasons:

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Can foresight and complexity play together?

By James E. Burke

James E. Burke (biography)

What is foresight and how does it differ from prediction? What role can complexity play in foresight? Does Cynefin® offer a possible framework to begin integrating foresight and complexity?

In this blog post, I describe how:

  • Foresight identifies clues for the future and integrates them into forecasts
  • Complexity theory offers ways to understand how the future emerges
  • Cynefin® gives us a framework of domains that allows us to better understand trends and forecasts.

What is foresight?

Foresight starts from a place of humility—we cannot predict the future—and an acceptance of ambiguity.

Read moreCan foresight and complexity play together?

Three types of knowledge

By Tobias Buser and Flurina Schneider

1. Tobias Buser (biography)
2. Flurina Schneider (biography)

When addressing societal challenges, how can researchers orient their thinking to produce not only knowledge on problems, but also knowledge that helps to overcome those problems?

The concept of ‘three types of knowledge’ is helpful for structuring project goals, formulating research questions and developing action plans. The concept first appeared in the 1990s and has developed into a core underpinning of transdisciplinary research.

The three types of knowledge, illustrated in the first figure below, are:

1. Systems knowledge, which is usually defined as knowledge about the current system or problem situation. It is mainly analytical and descriptive. For example, if you think of water scarcity, systems knowledge refers to producing a holistic understanding of the relevant socio-ecological system, including aspects like water availability, water uses, water management, justice questions, and their interrelations.

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Three complexity principles for convergence research

By Gemma Jiang

Gemma Jiang (biography)

How can principles adapted from complexity thinking be applied to convergence research? How can such principles help integrate knowledge, methods, and expertise from different disciplines to form novel frameworks that catalyze scientific discovery and innovation?

I present three principles from the complexity paradigm that are highly relevant to convergence research. I then describe three types of transformative containers that I have developed to create enabling conditions for applying complexity principles to convergence.

1. Ecosystem consciousness: An inversion of perspectives

Ecosystem consciousness is necessary because in complex systems the whole (ecosystem) is bigger than the sum of its parts; the wellbeing of the whole and the parts are interdependent and mutually reinforcing.

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Leadership in participatory modelling

By Raimo P. Hämäläinen, Iwona Miliszewska and Alexey Voinov

1. Raimo P. Hämäläinen (biography)
2. Iwona Miliszewska (biography)
3. Alexey Voinov (biography)

What can leadership discourse in the business literature tell us for leadership in participatory modelling?

Here we explore:

  • the difference between leadership and management in participatory modelling
  • different leadership styles and participatory modelling
  • three key leadership issues in participatory modelling: responsibility for best practices and ethics, competences, and who in the participatory modelling team should lead.

How does leadership differ from management in participatory modelling?

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Why we need strengths-based approaches to achieve social justice

By Katie Thurber

Katie Thurber (biography)

Achieving social justice by overcoming social inequality is a burning complex problem. In research which aims to contribute to achieving social justice, what does it mean to move from a deficit discourse to a strengths-based approach? How does such a change impact on the understanding of social inequality, as well as on actions taken to overcome it?

I am part of a group researching Australian Aboriginal and Torres Strait Islander health and we have been grappling with these questions. The issues are also more broadly relevant.

What is a deficit discourse?

A deficit discourse focuses on problems. A common example is the comparison of the group of interest to another social group that has better outcomes. The focus may be on the size of the gap between the groups.

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Can examining cross-disciplinary interactions illuminate unknown unknowns?

By Rick Szostak

Rick Szostak (biography)

Unknown unknowns are challenges that we will face in future that we do not foresee today.

Here I argue that an important subgroup of unknown unknowns occurs when some phenomenon that we know a lot about has an unexpected effect on another phenomenon that we know a lot about, especially when there are few links between the two silos of knowledge. An example is unanticipated “interactions” between medications prescribed by medical practitioners from different specialities. Here I explore such disciplinary interactions more generally.

Disciplinary scholars focus on interactions among the phenomena that their discipline studies, but usually ignore interactions with phenomena studied in other disciplines.

Read moreCan examining cross-disciplinary interactions illuminate unknown unknowns?

What is 3-dimensional team leadership?

By Bradley L. Kirkman

Bradley L. Kirkman (biography)

It is useful to think about teams as having three dimensions:

  1. the team as a whole
  2. the individuals in the team
  3. the subteams within the overall team, or the smaller subsets of team members who cluster together to work on specific tasks. With teams taking on more and more complex tasks, it is not uncommon for members with similar skills to tackle various assignments over a period of time and then integrate their outputs into the larger, overall team.

How does a leader know when to focus on which dimension?

The secret lies in knowing how a particular team best carries out its tasks, specifically a concept known as interdependence.

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The “ABC’s” of interdisciplinarity

By Stephen M. Fiore

Stephen M. Fiore (biography)

What are the attitudinal, behavioral, and cognitive issues that influence interdisciplinary collaborations?

The illustrations I provide here are based upon 20 years of experience working in research environments with scholars ranging from philosophers, anthropologists, and sociologists, to historians, economists, and ecologists, to psychologists, computer scientists, and neuroscientists. This experience has helped to illuminate what creates challenges during interdisciplinary interactions and what also can contribute to effective collaborations and help scholars learn from each other.

Attitudinal issues

Often times interaction is stifled when collaborators maintain some form of disciplinary disdain. The characteristics of disciplinary disdain include lack of respect or a form of contempt for another disciplinary approach, or condescension toward another discipline. An example is the view basic researchers sometimes show for applied research.

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Interdisciplinarity and synergy in collaborations

By Loet Leydesdorff

Loet Leydesdorff (biography)

What is the difference between “interdisciplinarity” and “synergy?” Why does it matter? How can indicators of interdisciplinarity and synergy be conceptualized and defined mathematically? Can one measure interdisciplinarity and synergy?

Problem-solving often requires crossing boundaries, such as those between disciplines. However, interdisciplinarity is not an objective in itself, but a means for creating synergy. When policy-makers call for interdisciplinarity, they may mean synergy. Synergy means that the whole offers more possibilities than the sum of its parts. The measurement of synergy, however, requires a methodology very different from interdisciplinarity. In this blog post, I consider each of these measures in turn, the logic underpinning each of them, and I specify the definitions in mathematical terms.

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