Human Biology Open Access Pre-Prints

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Since Frank Livingstone proposed the idea that there are no races, only clines, in 1962, little has changed in the way that anthropologists study and, ultimately, estimate ancestry. The way in which we talk about the study of human variation may have changed--shifting away from “racial” labels and towards those of supposed ancestral origins--but the methods with which we label and analyze groups, however termed, has remained the same. In this paper, I suggest a new theoretical approach to ancestry estimation that does not rely on group labels using Howells Craniometric dataset as an example. In the suggested workflow, the data structure themselves into natural clusters, which I am referring to as Morphogroups, without the reliance of a group label. Each Morphogroup is explored for sub-groups and the process is repeated until no further distinctions can be made. At each level an individual is compared to the Morphogroup in a descriptive manner focusing on similarities and differences. Lastly, a multi-iteration classification procedure, using random forest modeling, is implemented to classify by Morphogroup. In this test, hierarchical clustering was used to identify the optimal number of natural clusters within the data and principal components analysis was used to explore Morphogroups. Using my suggested workflow, three main Morphogroups were identified with each having different numbers of subclusters ranging from 0-8. Morphogroup correct classifications are typically in the mid 90 percent and the accompanying sex estimations between 93-100% correct. Additionally, for anyone who has access to R, I have provided a markdown file that shows all of the code used for this paper step-by-step at I want to make it clear this is not the way I think this should be done, rather one of myriad ways it could be done. Human variation and identity are not static and we need to stop thinking of them as such. It is on us to help one another get better at rethinking and redefining what is possible for our field.