“So What?” – Your BI-Weekly Guide to Advocacy With Impact
Lovingly selected and lightly snarked by Team APEP: David Devlin-Foltz, Susanna Dilliplane, and Alex Gabriel
When 230 indicators are not enough
You’ll recall that back in March 2016 the UN Statistical Commission’s Interagency and Expert Group on SDG Indicators (IAEG-SDGs) agreed on 230 indicators with which to monitor progress. Aside from having an acronym that’s nearly as cumbersome as its full name, this group only took us partway toward understanding progress on development goals. As IIED points out in this brief: “Indicator data cannot explain how or why change occurred, nor the significance of the change.” Enter evaluation – specifically, evaluation that is sensitive to contextual and sub-national variation when explaining the what, why, where, and for whom of development results.
Visualizing research for policymakers
We like pointing out pretty pictures – almost as much as we like poking fun at really unfortunate ones. But we don’t often get a chance to step back and think critically about data viz’s contribution to evidence-based decision making. Check out SciDev.Net’s recent report examining whether and how data viz can encourage the use of research to inform policy. As the authors note, policymaking is a complex process. You may get policymakers to look at and engage with your research, but getting them to use it in their decision making is a “notoriously difficult goal to achieve” – and to empirically test.
The measure broken down on the side of the road
It’s hot in the city – time for us all to pile into our cars and head for the beach. And despite the euphoric coming-out party for Tesla’s Model 3, we seem to be particularly inclined to pile into an SUV or truck. But before we start debating who’s the greenest of them all, we might ask: against what measure? As this Wired article points out, the EPA’s method for evaluating compliance with Corporate Average Fuel Economy (CAFE) standards is “bonkers” – based on outdated and flawed assumptions of driving conditions. It hits on one of our favorite gadfly themes: skepticism regarding measures that have become standard in a field.