Quantifying the Science-Humanities Gap

Project Summary

Spenser Easterbrook, a Philosophy and Math double major, joined Biology majors Aharon Walker and Nicholas Branson in a ten-week exploration of the connections between journal publications from the humanities and the sciences. They were guided by Rick Gawne and Jameson Clarke, graduate students from Philosophy and Biology.

Themes and Categories
Paul Bendich

Project Results

The team painstakingly created citation networks for several major philosophy journals and then analyzed the network structure using Gephi. Among other analyses, they found that a small fraction of the philosophy papers in this network were responsible for most of the citations to science journals. They presented their findings to the Moral Attitudes and Decision-Making Lab, and the dataset they created will be used next fall in an undergraduate philosophy class, funded under iiD's Data Expeditions program.

Aharon presenting at the Moral Atittudes and Decision-Making Lab

Download the executive summary (PPTX).

Disciplines Involved

  • Philosophy
  • Network Analysis

Project Team

Undergraduates: Nicholas Branson, Aharon Walker, and Spenser Easterbrook

Project Mentors:


Related People

Related Projects

Understanding how to generate, analyze, and work with datasets in the humanities is often a difficult task without learning how to code or program. In humanities centered courses, we often privilege close reading or qualitative analysis over other methods of knowing, but by learning some new quantitative techniques we better prepare the students to tackle new forms of reading. This class will work with the data from the HathiTrust to develop ideas for thinking about how large groups and different discourse communities thought of queens of antiquity like Cleopatra and Dido.

Social and environmental contexts are increasingly recognized as factors that impact health outcomes of patients. This team will have the opportunity to collaborate directly with clinicians and medical data in a real-world setting. They will examine the association between social determinants with risk prediction for hospital admissions, and to assess whether social determinants bias that risk in a systematic way. Applied methods will include machine learning, risk prediction, and assessment of bias. This Data+ project is sponsored by the Forge, Duke's center for actionable data science.

Project Leads: Shelly Rusincovitch, Ricardo Henao, Azalea Kim

Project Manager: Austin Talbot

Producing oil and gas in the North Sea, off the coast of the United Kingdom, requires a lease to extract resources from beneath the ocean floor and companies bid for those rights. This team will consult with professionals at ExxonMobil to understand why these leases are acquired and who benefits. This requires historical data on bid history to investigate what leads to an increase in the number of (a) leases acquired and (b) companies participating in auctions. The goal of this team is to create a well-structured dataset based on company bid history from the U.K. Oil and Gas Authority; data which will come from many different file structures and formats (tabular, pdf, etc.). The team will curate these data to create a single, tabular database of U.K. bid history and work programs.

Project Lead: Kyle Bradbury

Project Manager: Artem Streltsov