
ALEX HUGHES
UC Berkeley
JENNY LO
Grammarly
WILL MONGE
Good Research
Overview
Qual and quant are so divided these days—by academic discipline, language, communities of practice, job titles. Too often, quantitative research is conflated with data science (or vice versa), and data science with optimization algorithms or simply engineering. In many organizations, being “data-driven” tends to define “data” with a narrow conception of enumeration and (mis-) conceptions about the kind of evidence that is suitable to act on.
This tutorial critically examines this territory and move beyond it, empowering ethnographers to develop more interdisciplinary programs of inquiry. First the instructors review fundamentals of quantitative research and provide tools ethnographers can use to evaluate its quality and validity. Then they examine constraints and barriers to quant/qual collaboration, including time, funding, values, epistemological conflicts, organizational silos, and more. Finally, using core principles that underlie...