I haven't posted to the blog as much this term as I have in the past. Their just hasn't been a lot of interesting stuff out there. But two posts caught my eye. First, there's THIS ONE from the NY Times. The authors point out how much "Big Data" there is out there - a lot of it coming from the internet, where companies pay a lot to know where you "click." But there's a difference between Big Data and useful data. As they point out, "The things we can measure are never exactly what we care about. Just
trying to get a single, easy-to-measure number ...doesn’t actually help us make the right choice."
The authors are pointing out the limitations of a purely quantitative approach. I'm a "quant." I have been for a long time. But without context, quantitative information becomes "just more data." For context, you need to actually talk to people. You need not only to know WHAT behavior is (the quantitative), but WHY the behavior is (the qualitative). That's why quantitative and qualitative exist together in social science.
The authors point out that surveys are a good way to help bridge the WHY. That's because surveys can be intermediary between pure quantitative and pure qualitative. They can provide context in a way that can be displayed as numbers, or averages or other central tendencies.
The other article I ran across is HERE. It is a good review of why we do evaluation research. Unlike other scientific endeavors, evaluation research isn't about knowledge-for-its-own-sake. Instead, it serves a purpose. Like the first article I mention above, this one talks about gathering data in context. Context in evaluation research provides a direction to change things for the better - whether its in an organization or in a community. As the author points out, "“You can’t fatten a pig by weighing it.” In other words, you can’t get better at impact if all you do is measure."
