Yesterday, I was discussing a book with an anthropologist. What could have been an interesting discussion, became, from my perspective, a futile one. We could not even agree on what constitutes an explanation and how such an explanation should be put to the test. This caused me to think: `What exactly is an explanation?’
To my opinion, the book we discussed is a very interesting and possibly inspiring one, but it does not yet offer an explanation ((NOTE: this is my first and preliminary reaction to a discussion I’ve had recently. It still fascinates me, so I’ll probably find myself writing about it more often in the near future. I will then give more details on the book I mentioned as well.)). Focused on the ‘narcissism of the minor differences‘, it states that conflicts arise especially when differences between groups are very small. I think this is an interesting thesis, but not yet an explanation. My main reason for this is that it does not explicate when a difference is small (as opposed to large) and what exactly is a conflict. According to my debating-partner, all can be interpreted as conflict and in every context it differs what is a ‘minor’ difference. Thereby, the supposed `explanation’ does not lead to new insights, for every ‘explained’ situation is described by even so much determinants. To me, that is not an explanation, but a label on a correlation.
Then the testing issue: the book illustrates the thesis of the minor differences nicely. This helps the reader to understand the arguments, and shows the potential value of it. But can we regard this as a test of the explanation? I think not. A proper test as I would like to see it compares the prediction / explanation under different circumstances, so not only the successes. If indeed minor differences between (the people in) groups lead to conflicts, than we should also be able to understand why in other situations no conflict arises when no small differences are present, or why when small differences are present not in all situations conflicts arise. All these types of situations should be compared with empirical reality.
So what it comes down to, is two things. I do not think that labeling a correlation is the same as offering an explanation. And I do not think that illustrating an explanation is the same as testing an explanation. Also, I fail to understand how empirical science could possibly make any progress when these arguments are not valid. Do you have any suggestions?