October 2016

Month

1. Much has happened since Why Most Published Research Findings Are False, the much-discussed PLOS essay by John P. A. Ioannidis offering evidence that “false findings may be the majority or even the vast majority of published research claims….” Why are so many findings never replicated? Ioannidis listed study power and bias, the number of...
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evidence-based social innovation
Recent developments in evidence-based decision making in the nonprofit/social sector. Practical ways to discover and exchange evidence-based insights. References, resources, and links to organizations with innovative programs. Data-Driven is No Longer Optional Whether you’re the funder or the funded, data-driven management is now mandatory. Evaluations and decisions must incorporate rigorous methods, and evidence review is...
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When presenting findings, it’s essential to show their reliability and relevance. Today’s post discusses how to show your evidence is reproducible; next week in Part 2, we’ll cover how to show it’s relevant. Show that your insights are reproducible. With complexity on the rise, there’s no shortage of quality problems with traditional research: People are...
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man tying necktie
1. Present controversial evidence with just one slide. Throw out your slide deck and try the Extreme Presentation method, developed by Andrew Abela and Paul Radich during years of presentations at Procter & Gamble, McKinsey, and other leading companies. The technique involves first showing the audience the big-picture concept so they’ll immediately have a sense...
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What works reading list
1. When nudging fails, what else can be done? Bravo to @CassSunstein, co-author of the popular book Nudge, for a journal abstract that is understandable and clearly identifies recommended actions. This from his upcoming article Nudges that Fail: “Why are some nudges ineffective, or at least less effective than choice architects hope and expect? Focusing primarily...
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Museum musings.

Pondering the places where people interact with artificial intelligence: Collaboration on evidence-based decision-making, automation of data-driven processes, machine learning, things like that.

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