For people trying to find unbiased answers, there are sometimes ways to get around the politically correct research mentality in academia. When the variable is a politically sensitive issue, the papers published studying the issue itself may be biased. They only have to data mine for the right control variables in order to prove their politically correct point. However, when an academic is trying to prove unrelated points they will often control for these variables in their studies. Looking at the average of many of these coefficients should give less biased information than a literature survey of the published studies that directly analyze the issue. I ran across this phenomenon when I was looking into age and productivity statistics. Of the studies looking at age and productivity, many had mixed results. This is partially because crystallized intelligence is not always worse than fluid intelligence and partially because age discrimination and the government provision of additional work training for older workers is a political issue. Looking at studies where firm productivity was analyzed in a different context provided more straightforward results: when the proportion of older workers was controlled for it had a significant negative sign. Topics where this approach could yield fruit:
- IQ and/or heritability of traits
- Protected classes such as women, minorities or the elderly
- The negative effects of tobacco, alcohol or pollution
- Inequality
- Any other politically contentious or politically correct issue