Advocate or Honest Broker?

By Gabriele Bammer

Gabriele Bammer (biography)

To mark the first anniversary of the Integration and Implementation Insights blog, we launch an occasional series of “synthesis blog posts” drawing insights across blog posts on related topics.

What is our social obligation as researchers to see our findings implemented? And how should we do it? When is it appropriate to advocate loudly to drive change? When should we focus on informing decision makers, stepping back ourselves from direct action? How can we know that our research is ‘good enough’ to act on and not compromised by our own values, interests, cognitive biases and blind spots?

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Model complexity – What is the right amount?

By Pete Loucks

p-loucks
Pete Loucks (biography)

How does a modeler know the ’optimal’ level of complexity needed in a model when those desiring to gain insights from the use of such a model aren’t sure what information they will eventually need? In other words, what level of model complexity is needed to do a job when the information needs of that job are uncertain and changing?

Simplification is why we model. We wish to abstract the essence of a system we are studying, and estimate its likely performance, without having to deal with all its detail. We know that our simplified models will be wrong. But, we develop them because they can be useful. The simpler and hence the more understandable models are the more likely they will be useful, and used, ‘as long as they do the job.’

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Four things everyone should know about ignorance

By Michael Smithson

michael-smithson
Michael Smithson (biography)

“Ignorance” is a topic that sprawls across a grand variety of disciplines, professions and problem domains. Many of these domains have their own perspective on the unknown, but these are generally fragmentary and often unconnected from one another. The topic lacks a home. Until fairly recently, it was a neglected topic in the humanities and human sciences.

I first started writing about it in the 1980’s (e.g., my book-length treatment, Ignorance and Uncertainty: Emerging Paradigms), but it wasn’t until 2015 that the properly compiled interdisciplinary Routledge International Handbook on Ignorance Studies (Gross and McGoey 2015) finally appeared.

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Should I trust that model?

By Val Snow

val snow
Val Snow (biography)

How do those building and using models decide whether a model should be trusted? While my thinking has evolved through modelling to predict the impacts of land use on losses of nutrients to the environment – such models are central to land use policy development – this under-discussed question applies to any model.

In principle, model development is a straightforward series of steps:

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Five principles for achieving impact

By Mark Reed

Mark Reed (biography)

What key actions can help research have impact? Interviews with 32 researchers and stakeholders across 13 environmental management research projects lead to the five principles and key issues described below (Reed et al., 2014).

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Ten communication tips for translational scientists

By Sunshine Menezes

sunshine-menezes
Sunshine Menezes (biography)

As someone who works with scientists, journalists, advocates, regulators, and other types of communication practitioners, I see the need for translational scientists who can navigate productive, start-to-finish collaborations between such groups on a daily basis.

This translation involves the use of new, more integrated approaches toward scientific work to confront wicked environmental problems society faces.

In spite of this need, cross-boundary communication poses a major stumbling block for many researchers. Science communication requires engagement with potential beneficiaries, not just a one-way transfer of information.

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Should water scientists be advocates?

By Patricia Gober

gober
Patricia Gober (biography)

Efforts to improve the use of models to support policy and practice on water resources issues have increased awareness of the role of advocacy and public engagement in the modeling process. Hydrologists have much to learn from the recent experience of climate scientists who have discovered that scientific knowledge is not independent of the political context in which it is used but rather is co-produced by scientists and society.

Despite a strong consensus among climate scientists in the Intergovernmental Panel on Climate Change’s (IPCC) 2013 report that “warming of the climate system is unequivocal,” approximately one-third of the USA’s population still does not believe that global temperatures have risen over the past 100 years and does not trust the things that scientists say about the environment.

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