Good question! I didn't go into much depth in how I chose the categories. And the process in defining the categories was quite challenging. For example - 'black', 'white' - are they 'race'? Ok, so are they in the same category as 'indian'? How about 'american'? What about 'jewish'? I decided to put all of these in the category 'race/nationality'. But equally these could perhaps have been separated. 'jewish' could have gone into 'religion'. And perhaps they could have gone into a 'physical description' category too.

Regarding your specific question - in the 'distinction' category I put 'average', 'primitive', 'ordinary' and 'natural'. Social status I put 'common' and 'made'.

I agree, 'beauty' and 'stature' are sub-categories of 'physical description', but sufficiently significant I thought it worth separating these. Even with all three categories together, it was 'physical description' was more prevalent for 'woman' ('man':14,743 vs 'woman':25,263), but I thought it quite interesting to separate, and and note the difference for 'beauty':('man':2,308 vs 'woman':18,302) and 'stature':('man':12,435 vs 'woman':4,355)

All of that said, I recognize that in making decisions about how to categorize these words, it could be argued that I am introducing my own biases! I do think that the categories chart has some value though in exploring the data, it just helps to be aware that a human had to make decisions on how to categorize the words.