Assessing assumptions about boundaries with critical systems heuristics

By Werner Ulrich

werner-ulrich
Werner Ulrich (biography)

How can those participating in research effectively reflect on their own assumptions about where they set boundaries around: problems, solutions, measures of success, knowledge claims and other aspects of research? These aspects are inevitably partial in the dual sense of representing a part rather than the whole of the total universe of conceivable considerations, and of serving some parties better than others.

How can examination of assumptions about boundaries be employed as an emancipatory practice to assess the assumptions of others and to point to better ways of serving the disenfranchised and marginalised?

I developed critical systems heuristics in the 1980s to support such boundary critique.

Read more

Four typical behaviours in interdisciplinary knowledge integration

By Annemarie Horn and Eduardo Urias

authors_annemarie-horn_eduardo-urias
1. Annemarie Horn (biography)
2. Eduardo Urias (biography)

Why do some collaborators in interdisciplinary teamwork clash? And why does collaboration between others seem smooth but not yield anything? What causes these differences in collaboration, and how can this inform interventions to support interdisciplinary collaboration and integration?

When we started teaching an interdisciplinary masters course, we expected it to become a battlefield, based on our reading of countless lists of the challenges of interdisciplinary collaboration. We thought that the students’ diverse study backgrounds – ranging from arts to medicine, and from social sciences to mathematics – would cause tensions; that they would disagree with each other about theories and methods that they were unfamiliar with and held opinions about.

Read more

Five lessons to improve how models serve society

By Andrea Saltelli

andrea-saltelli
Andrea Saltelli (biography)

Models are mathematical constructs better understood by their developers than by users. So should the public trust models? What insights can help society demand the quality it needs from modeling?

Mathematical modelling is a multiverse, where each scientific discipline adopts its own styles of modeling and quality control. Very little in the way of ‘user instructions’ is available to those affected by modeling practices.

This blog post presents five lessons to improve modelling that were developed as a manifesto by a cross-disciplinary group of natural and social scientists (Saltelli et al., 2020).

Lesson 1: Mind the assumptions

Read more

Understanding diversity primer: 2. Mental models

By Gabriele Bammer

primer_diversity_2

What are mental models and why are they important? How do they affect how problems are framed, understood and responded to? How do they affect how well those contributing to the research work together?

Mental models are a person’s understanding of the world and how it works, and are unique to each person. They exist in a person’s mind as a set of small-scale simplified models about different aspects of reality that are functional but necessarily incomplete.

Mental models apply to all aspects of reality ranging from concrete objects such as a ‘chair;’ to abstract concepts such as ‘trust;’ to geographical locations such as ‘Sydney;’ to connections, interconnections and causal relationships; and to simple and complex situations.

Read more

Three lessons for policy engagement

By Emily Hayter

emily-hayter
Emily Hayter (biography)

How can researchers be supported in communicating their research and in supporting policymakers to use research and evidence? Are there particular issues for researchers in the global south?

The three lessons presented here are based on the experience of INASP (International Network for Advancing Science and Policy), an international development organisation which has been working with a global network of partners in Africa, Latin America and Asia for nearly 30 years.

1. Policy engagement needs to build mutual understanding between researchers and policymakers as actors in a system (the ‘how’)

The research/policy space is not quite the chasm it is often presented as, needing a ‘bridge’ to cross between two distinct groups.

Read more

Intentional ecology: Building values, advocacy and action into transdisciplinary environmental research

By Alexandra Knight and Catherine Allan

authors_alexandra-knight_catherine-allan
1. Alexandra Knight (biography)
2. Catherine Allan (biography)

As a society, how do we encourage early and ethical action when building our knowledge and confronting serious challenges?

In this blog post we explore the conceptual framework of intentional ecology and apply it to a case study to illustrate how it deals with the question raised above.

Intentional ecology – foundations and actions

Intentional ecology, illustrated in the figure below, is a new conceptual framework that enables early, applied and relevant integrated action, as well as reflexive and dynamic approaches to implementation of conservation and sustainability measures. It’s a better way of doing science.

Read more

Four building blocks of systems thinking

By Derek Cabrera and Laura Cabrera

authors_derek-cabrera_laura-cabrera
1. Derek Cabrera (biography)
2. Laura Cabrera (biography)

Systems thinking itself is a complex adaptive system. Supported by empirical evidence, DSRP theory describes 4 simple rules that dynamically combine to explain the complexity of physical, natural, and social systems. Awareness of these patterns can help us to solve many societal and environmental problems.

We briefly present DSRP theory which describes four universal patterns and their underlying elements—identity (i) and other (o) for Distinctions (D), part (p) and whole (w) for Systems (S), action (a) and reaction (r) for Relationships (R), and point (ρ) and view (v) for Perspectives (P).

We describe these four building blocks and show how they can be mixed and matched. We conclude with some additional key aspects of the theory.

Read more

Place-based methodologies in transdisciplinary research

By Alexandra Crosby and Ilaria Vanni

authors_alexandra-crosby_ilaria-vanni_1
1. Alexandra Crosby (biography)
2. Ilaria Vanni (biography)

How can place-based methodologies be integrated into transdisciplinary research?

Locating research in a real physical place is vital in building culture and making important insights more visible to diverse audiences. But for many researchers and community members, place is more than location. People have important attachments to place that change and influence the outcomes of transdisciplinary research, which is one reason to integrate some place-based methodologies into your projects. Our research studio ‘Mapping Edges’, for example, employs place-based methodologies to identify, analyse and amplify civic ecologies and to propose more sustainable ways to design and live in cities.

Place-based research engages with multiple methodological debates, reflecting humanities and social sciences’ increasing interest in space and place.

Read more

Integrating context, formats and effects in transdisciplinary research

By tdAcademy 2021 GAIA paper authors

authors_td-academy-2021_gaia-paper
Author biographies

What are the key aspects of transdisciplinary research and how can they be integrated effectively?

Four key aspects of transdisciplinary research are:

  • context dependencies
  • innovative formats
  • societal effects
  • scientific effects.

These are illustrated in the figure below, along with a summary of an ‘ideal’ transdisciplinary research process.

1. Context dependencies

Context dependencies are the factors that influence both the research design and the interpretation of results and include:

Read more

A collaborative vision and pathways for transforming academia

By The Care Operative and “Transforming Academia” workshop participants at 2021 International Transdisciplinarity Conference

authors_care-group_workshop-participants_transforming-academia
Author biographies

What do we want academia to be like in 2050? Is academia on the right track? What will it take to agree on and realize a joint vision that can steer life in science towards a more sustainable and agreeable place to work, to learn, to share and to appreciate knowledge?

The issues raised here are based on a workshop with more than 40 participants at the International Transdisciplinarity Conference 2021. The discussion was initiated and hosted by the Careoperative, a leadership collective motivated to explore, embody and pollinate transformational sustainability and transdisciplinary research.

Read more

Basic steps for dealing with problematic value pluralism

By Bethany Laursen, Stephen Crowley and Chad Gonnerman

authors_bethany-laursen_stephen-crowley_chad-gonnerman
1. Bethany Laursen (biography)
2. Stephen Crowley (biography)
3. Chad Gonnerman (biography)

Have you ever been part of a team confronting a moral dilemma? Or trying to manage deep disagreements? For that matter, on a more down-to-earth level, how many times has your team tried to settle an agreed file naming convention? Many team troubles arise from value pluralism—members having different values or holding the same values in different ways. Below, we describe problematic value pluralism and suggest steps for dealing with it.

What are values, and how do they cause problems?

Here, we’re talking about a “value” as a desire (conscious or unconscious) that directs a person’s actions. It could be a guiding ideal or a whimsical preference, for example. Most of us have multiple values and over time we have organized them so that they provide us with guidance in most of the situations we encounter.

Read more

Judgment and decision making with unknown states and outcomes

By Michael Smithson

Michael Smithson
Michael Smithson (biography)

What issues arise for effective judgments, predictions, and decisions when decision makers do not know all the potential starting positions, available alternatives and possible outcomes?

A shorthand term for this collection of possible starting points (also known as prior states), alternatives, and outcomes is “sample space.” Here I elucidate why sample space is important and how judgments and decisions can be influenced when it is incomplete.

Why is sample space important?

When it comes to dealing with unknowns, economists and others traditionally distinguish between “risk” (where probabilities can be assigned to every possible outcome) and “uncertainty” (where the probabilities are vague or unknown). Both of those versions of unknowns assume that decision makers know everything about the sample space.

Read more