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Purpose: To provide an understanding of confirmation bias and ways to avoid it, in order to support good decision making on complex problems. Description: Confirmation bias manifests as follows: (1) We accept a story uncritically if it confirms what we would like to be true and reject it if it contradicts what we would like to be true. (2) We accept a fact as data, even if it is an outlier which is not backed up by large-scale data. (3) We accept data as evidence, even if it is consistent with rival theories, without looking for evidence that supports one theory and rules out all rival theories...
This video describes how a complexity science based toolbox, especially different types of modelling, is used in complex multiple use environments, such as the coastal zones of Australia, to examine different scenarios for sustainable fishing options. The video starts by describing elements of complexity such as operating at scales from minute organisms up to areas […]
These six videos provide perspectives from, respectively, the disciplines of clinical psychology, history, law, philosophy, physics and statistics on how each discipline deals with the unknown. Understanding and responding to unknowns does not fall neatly within a single discipline. Instead, different disciplines have different ways of thinking about and dealing with unknowns and there is […]
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A new discipline – Integration and Implementation Sciences (i2S) – could provide a systematic way to allow people to effectively mix-and-match concepts and methods from systems thinking, inter- and trans-disciplinarity, implementation science, team science, complexity science and other approaches to more effectively deal with complex real-world problems. i2S has three domains: 1) synthesis of disciplinary […]
Metaphors help people “understand the unfamiliar” and “make someone realise they’ve only been looking at one side of a thing.” Metaphors assist in closing “the gap in people’s ability to grasp something, or speed up what they’re already on track to see.” Designing metaphors involves generating multiple possible comparisons to find those that work well. […]
Demonstrates an effective method for quantifying consequences and likelihoods of risks, as well as for combining these assessments. Different kinds of risks are examined: death, injury and illness; economic; social; environmental; symbolic; external; and reputational. The authors show how these can be rated and combined, allowing for a rich appraisal of a wide range of […]
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Purpose: To provide an overview of problems with judging risk and how these can be overcome by groups using integrated elicitation processes. Description: A brief overview is provided about distortions in risk perception stemming from factors such as overconfidence, degree of personal experience and dreadfulness of the outcome. These lead to a range of ‘pathologies’ […]
This framework presents a structured way to review all the possibilities for understanding and acting on a complex problem. The questions are: “What do we know about the problem? What can different interest groups and academic disciplines contribute to addressing this problem? What areas are contentious? What are the big-picture issues? In other words, what […]
Purpose: To define who stakeholders are and what engagement with them is likely to contribute to a particular research project. Description: Discusses who stakeholders in research are, as well as reasons for engaging stakeholders. The benefits of stakeholder engagement are then further examined according to the type of engagement.  Defining ‘stakeholders’ The handbook (Durham et […]
Purpose: To ascertain everyone who has a perspective or knowledge that may be useful to the research. Description: Four different approaches to identifying stakeholders are extracted from Durham and colleagues (2014). It can be helpful to use one or more of them in any project. In identifying stakeholders, it is important to be inclusive, at […]

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