I am Professor of Sociology at Duke University. (→ Read a short biosketch.)
Recent Writing
9 May 2020
To save everyone some time, here’s a generator for the next five years of conceptual advances in social theory. Choose once at random from each column to secure your contribution.
| Column 1 |
Column 2 |
| Sequenced |
Stratification |
| Algorithmic |
Differences |
| Automated |
Capital |
| Robust |
Contagion |
| COVID |
Masking |
| Epidemiologic |
Others |
| Viral |
Politics |
| Rhizomatic |
Inequality |
| Infectious |
Sexualities |
| Compartmentalized |
Classification |
| Pandemic |
Causality |
| Epizootic |
Discrimination |
| Transmissible |
Polarization |
| Leucocyte |
Paradox |
| Intersectional |
Bodies |
| Corona |
Disparities |
| Liquid |
Isomorphism |
| Genomic |
Populism |
| Nucleotide |
Interdependence |
| Masked |
Colorism |
28 April 2020
My post about Apple’s mobility data from a few days ago has been doing the rounds. (People have been very kind.) Unsurprisingly, one of the most thoughtful responses came from Dr. Drang, who wrote up a great discussion about the importance of choosing the right baseline if you’re going to be indexing change with respect to some time. His discussion of Small Multiples and Normalization is really worth your while.
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23 April 2020
Update
I’ve added a GitHub repository containing the code needed to reproduce the graphs in this post, as what’s shown here isn’t self-contained.
Apple recently released a batch of mobility data in connection with the COVID-19 pandemic. The data is aggregated from requests for directions in Apple Maps and is provided at the level of whole countries and also for a selection of large cities around the world. I folded the dataset into the covdata package for R that I’ve been updating, as I plan to use it this Fall in a course I’ll be teaching.
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16 April 2020
The other day Nature reported some preliminary results from a study of COVID-19 symptoms that’s being carried out via a phone app. The report noted that loss of sense of smell (or “Anosmia”) seemed to be a common symptom. The report was accompanied by this graphic, showing the co-occurrence of symptoms in about 1,700 self-reports via the app.
A species of Venn Diagram showing the co-occurrence of reported COVID-19 symptoms.
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10 April 2020
The covdata logo
Partly because it grew out of a few code-throughs I was doing, but mostly as a classroom exercise, I pulled together a small data package for R called covdata, available at https://kjhealy.github.io/covdata/. It contains COVID-19 data from three sources:
National level data from the European Centers for Disease Control. State-level data for the United States from the COVID Tracking Project. State-level and county-level data for the United States from the New York Times.
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