My research investigates how networks of collaboration evolve and influence the work of professionals and experts, particularly in the scientific and medical fields. I use a variety of methods including open-ended unstructured interviews, ethnography, network and text analysis.

Collaboration and Decision-Making In Medical Specialties

Growing specialization within professions leads to social differentiation and the development of specialty specific evaluation and knowledge. Using ethnographic and interview methods, my dissertation investigates how different medical specialties manage the care of terminally ill patients.

Despite the growing number of different specialties in medicine with different ideas of what constitutes success and a good case, care for the terminally ill depends upon a tight coupling between clinicians from disparate areas. Focusing on the case of Hospice and Palliative Medicine, I find new specialties springing up that work to transform the work styles of other specialties to allow for the production of a working consensus and success in the face of impending death.

Status and Subfield: The Distribution of Sociological Specializations across Departments

The fundamental insights of the Sociology of Science and of Knowledge is that our epistemic endeavors are not solely governed by the ideals of the scientific method. Recognition, personal achievement and career advancement in science is influenced by the individual characteristics of the scholars that produce knowledge. Using the discipline of sociology as a case study, we examine how different subfields are distributed across PhD granting departments in the United States and how the demographic composition of these different subfields influences their relative status.

In collaboration with Austin Kozlowski, now available as a preprint on SocArXiv.

Introduction to Plain Text Software for Research and Writing

A variety of recent scandals and revelations have demonstrated the need for a more open scientific process where researchers and writers are able to document the methods they adopted to get from their empirical observations of the world to their insights and findings. This need has been felt most acutely in the social sciences where a number of notable and influential findings have failed to replicate, and a number of scandals have undermined trust. A suite of powerful open source and plain text software has developed that allows researchers and writers to adopt transparent research and writing methods, but the steep up front cost of adopting these tools and the ease of use of What You See Is What You Get programs like Microsoft Word and Google Docs prevents many researchers and students from adopting them.

In Introduction to Plain Text Software for Research and Writing provides a practical introduction to plain text software that assumes nearly no foreknowledge of how computers work, and outlines the appropriate cognitive attitude for working with plain text software, an attitude that helps to promote efficiency and clarity with important scientific implications for how we conduct research. I outline the use and utility of dynamic documents with $\LaTeX$, RMarkdown, creating cogent and potent tables and figures, and the fundamentals of interacting with plaintext software using the terminal.

Sample chapters are available in the plaintext section of this site and a full draft is available upon request.