Day Fourteen: Expertise
SDS 237: Data Ethnography
Lindsay Poirier
Statistical & Data Sciences, Smith College
Fall 2023
Draw a “map of data science” - sort of like you would draw a map of the world. What’s at the center of your map? What features are at the periphery? Where are the mountains? Rivers? Centers? Forbidden areas?
Turn to a neighbor and discuss:
- How does your map reflect certain assumptions of what counts as data science vs. non-data-science?
What were some of the key takeaways about interviewing from our last lecture?
What makes something a science? Discuss with your table.
Boundary Work
- Examines the work that society does to set the boundaries of science vs. non-science
- Acknowledges that differently situated people have different ways of justifying what makes something scientific vs. non-scientific
- Helps establish science’s epistemic authority through credibility contests and cartographic contrast
Examining the Boundaries of Data Science Expertise
- What separates an expert from a non-expert?
- Training? Credentials? Publications? The way they dress? The way they talk?
- Can you draw a distinguishing line around a data science expert?
- How does this create barriers to participation?