Jessica Otis Receives Major NSF Grant
RRCHNM Professor and Director of Public Projects Jessica Otis has been awarded $443,425 from the NSF to support her digital work on the history of the plague in early modern London. The project, called “Assessing the Arithmetic of Early Modern London’s Bills of Mortality,” involves the creation, publication and computational analysis of a dataset of weekly and annual mortality statistics produced for the city of London between 1603 and 1752.
Plague was one of the most dreaded diseases in early modern England. The city of London alone lost an estimated 225,000 people to plague in the century between 1563 and 1665. As an extension of government attempts to track plague deaths during outbreaks, London officials started publicly distributing a weekly series of mortality statistics called the Bills of Mortality at the turn of the seventeenth century. Jessica’s project uses the Bills of Mortality to investigate how lived experiences of plague outbreaks intersected with an emerging quantitative mentality among the people of early modern England. It examines how ordinary people aggregated, transformed, and interpreted death counts in order to draw conclusions about changes in the early modern use of and trust in numbers over time. In doing so, the project investigates contemporary perceptions of numbers and historicizes a quantitative method of knowledge generation that has become central to twenty-first-century understandings of the world.
The foundation of this project is the Bills of Mortality dataset, created through the digitization of primary sources and their subsequent transcription in DataScribe: specialized software designed at RRCHNM to create validated structured datasets from historical sources. The project deploys custom Python code on this dataset to assess the arithmetical accuracy of bills’ internal calculations and their summary statistics. It combines this assessment with close reading of historical sources in order draw conclusions about early modern use of and trust in numbers. Underlying these analyses are two questions: (1) Did people put their trust in the authority of the bills’ internal sums and extracted summary statistics because of the mathematical accuracy of their compilation, reflecting a belief in the importance of correctly quantifying mortality for assessing risk? (2) Did people put their trust in the bills’ numbers because they were numbers, seeing the bills and their mortality statistics as an inherently trustworthy form of knowledge because of its numerical basis?
The project also supports a variety of secondary and student-driven analyses on the dataset. By including student researchers, the project models interdisciplinary paths for students interested in both historical and STEM research and demonstrates the myriad career and research options available at the intersection of history and STEM.