This morning I presented a paper at the AAA meeting in Minneapolis as part of a panel I co-organized with Joe Feldman, titled “Challenging Anthropology in the 21st Century.” My paper focused specifically on the social network of US academic anthropology and how hiring networks can contribute to – or at the very least reflect – embedded hierarchies within the discipline. You can download a copy of the paper here. The abstract is below:
“Anthropologists often strive to point out social inequality while using their research to promote meaningful social change. However, academic anthropology can sometimes reproduce the very problems of social inequality that its scholars tend to rail against. Past research on U.S. academic hiring networks has shown evidence of systematic inequality and hierarchy, attributed at least in part to the influence of academic prestige, which is not necessarily a reflection of merit or academic productivity. Using anthropology departments’ websites, we gathered information on all tenured and tenure-track faculty in PhD-granting anthropology programs in the U.S., totaling 1,918 individuals in all. For each faculty member, we noted their current institution and PhD-granting institution, which we treated as a “tie” between those academic programs. With these data, we applied methods from social network analysis (SNA) to examine U.S. academic anthropology’s social network, and we identified multiple factors that help to explain its structure. In this paper, we report on our preliminary findings and we discuss how they can be used to help rethink social reproduction in academic anthropology.”
Nicholas C. Kawa 
Thanks for this! Really interesting. Is a higher-resolution version of the map available?
HI Matan, thanks for your interest in the paper. I’ll send you a few of the network map images in higher res via email. Cheers!
This is, indeed, a very interesting paper. Have you gone on to do further analyses or publications on this? I’d love to see higher res. versions of your network maps, too, if possible.
thanks for bringing this important perspective to our field!
HI Jeanne, thanks so much for your interest in the paper. I’m currently getting back to work on it this semester. I’ll be doing quite a bit more with the statistical and network analysis before I submit it for publication. This was the first shot at it. I can send you some of our network maps via email. cheers!
thanks so much! I’ll look forward to your next installment
Great paper, Nick I love it. And it also proves you as a flexible anthropologist, comfortable with more than the typical methods. I was wondering if you could add more info: how do you know students from the top ten Universities don’t publish more? they have a career counselor in the department? aren’t better funded and therefore attend more conferences and therefore network more? Or that there isn’t a culture of departmental support in the job search? Would be nice to round up your conclusion aligning it with the intro. As soon as you demonstrate these two aren’t the case.. then you don’t even need to say it again, it becomes evident that…the system is fucked up!
Hi Luisa, thanks for reading it! This was a first draft and I’m currently developing a longer version that includes some statistical analyses using data from the National Research Council that was used to evaluate anthropology doctoral programs. Here’s a brief excerpt from our new paper: “To predict the number of faculty placements an anthropology program makes in other PhD-granting programs, we tested eight independent variables: university endowment, US News and World Report ranking, publications per faculty, average citations per faculty, percentage of faculty with grants, awards per faculty member, average GRE score of graduate students, and average number of PhDs graduated per year. We limited this analysis to the time frame of 2000 to 2016 to assess only the most recent data and to control for changes in departmental prominence over time. After running several exploratory analyses, we dropped three variables from the model that offered little explanatory power or that overlapped significantly with other variables, and thus presented problems of multicollinearity. These excluded variables were, notably, the US News and World Rank, publications per faculty, percentage of faculty with grants. With the five remaining variables – university endowment, citations per faculty, awards per faculty, average GRE scores of grad students, average number of PhDs graduated per year – our model produced an r-square value of .785, thus explaining 78.5% of the variation in placements across programs.”
There are still lots of questions that this analysis raises and we’re continuing to work through our interpretations. When I have a complete draft of the new paper, I’m happy to pass it along. Hope you are well!