Warning: Reductionism can result in distorted vision, poor judgment and difficulty in operating a humanitarian project.
There’s a popular trend today among many humanitarians, aka the aid and development sector, to try to show the benefit of their projects – be it digging a well, feeding kids or improving access to basic health care – with scientific data.
That’s good in principle, if you have a well-designed study that produces meaningful data. But that can be a big if when what you are trying to test is a reduction in poverty, social and economic improvements, healthy behavior change or many of the other aims of aid and development.
It’s much easier for scientists to test a more isolated intervention, like say taking a pill, than it is to even figure out how best to track and attribute the potential impact of many humanitatian efforts. And it’s worth noting that the scientific community is finally acknowledging that even their most refined efforts in reductionist deduction, peer review and attribution often fail.
NY Times Scientific Pride and Prejudice
Economist Trouble at the Lab
Forbes NIH Promises to Make Science Less Wrong
The mainstream scientific community likes to call this a ‘reproducibility’ problem, saying the overall reliability and self-correcting nature of the scientific method(s) remain intact. But when it is noted, as in the NYTimes op-ed, that a team of scientists could only confirm the findings in six of more than 50 ‘landmark’ cancer studies, there is cause for concern.
Meanwhile, the humanitarian sector has a different problem. It tends to suffer from a lack of data or consensus on how best to measure the impact of various initiatives aimed at fighting poverty, diseases of poverty or other kinds of human inequity. The field did not arise, like science, from a desire to know so much as from a desire to help.
So will it help if humanitarians become more like scientists? Maybe. Maybe not. Continue reading