Apropos of our recent discussion on the estimation of historical population sizes, Sean Manning writes:
Some archaeologists have measured house sizes for Gini-coefficient-style studies aside from studying human remains to measure nutrition and rates of illness. I think that was what Michael E. Smith meant when he talked about hypothetical data: “archaeology can’t give social scientists population or GDP, but here are some things we can measure that might be useful for social science.”
I asked Manning where the quote came from, and he replied:
I think I got the idea from this response by Smith to a published paper:
This model of inequality in the Aztec Empire is not based on empirical data. While there is nothing wrong with hypothetical models per se, the paper is phrased as if it presents empirical findings. … There are simply not enough data available to do the kind of analysis presented in this paper. The tweaking of data and methods do not produce results that satisfy me as being reasonable estimates of the level of inequality in the Aztec Empire. Perhaps this is just an epistemological difference between our approaches to science and knowledge. Economists might look at this paper as a fine analysis, whereas archaeologists and historians will probably look at it as a study based on hypothetical data, and therefore divorced from the Aztec reality that we study.
Smith has a book that talks about the archaeology of inequality in Aztec Mexico: Timothy A. Kohler and Michael E. Smith, editors, Ten Thousand Years of Inequality: The Archaeology of Wealth Differences (University of Arizona Press, 2019).
Often in social science there is tension between what we can measure and what we would like to know.
You can apply models to the past, but you have to show it can predict the future first. This is done in astronomy all the time for historical eclipses, etc.
Wait – are you dismissing this work unless it can predict future income inequality in the Aztec Empire? If so, then my research is excellent: I predict zero inequality and zero income (with some epsilon below 100% confidence).
The model would need to predict the US, etc values to prove itself THEN you can plug in the guesstimated ancient values.
This seems like extremely basic stuff to me so I dunno how papers like this get through peer review.
Actually, this reminds me of the “billion tons” of copper missing from Michigan: https://en.wikipedia.org/wiki/Copper_mining_in_Michigan
The model of how much copper was mined is completely unvalidated, then the apparent deviation from the estimate is used to generate wild speculations.
Use a simple rule that if there is no demonstrated *predictive* skill (“explaining” historical data is easy and doesn’t count) we can ignore it.
The exchange between Smith (critique) and the authors is quite thorough and a good example of the kind of exchange I would like to see more often. I find the quote “archaeology can’t give social scientists population or GDP, but here are some things we can measure that might be useful for social science” quite strange, however. It sounds overly defensive, as if population or GDP are more worthy or useful measures than income inequality in the Aztec Empire. I see no need to be defensive about what archeologists study compared to economists or demographers. From what I see, Smith was making a point about this particular research: that while archeologists can provide useful measures, he didn’t find this particular work to be a good example. I have absolutely no background in this area, so I don’t have a comment about the merits either way. What I am commenting on is the predicate in the quote: why preface the comment with a caveat about what archeologists cannot provide, as if the GDP estimates are somehow superior measures in usefulness. But that implicit criterion, I guess Smith would agree with those economists who say that economics is the “queen of the social scientists.” I don’t agree with that – and if someone can point to the source of that sentiment, please do so (because I can’t remember).