Writing Ethnographic Fieldnotes, Chapter 6 - Processing Fieldnotes: Coding and Memoing

Text Exploration

In this chapter, the author describes how they code data that has emerged from fieldwork, using tutorials mixed with examples.

After working in the field and writing notes, a researcher eventually has to do something with the data in order to “speak to wider, outside audiences.” This is a shift from intense fieldwork to intense data “sifting”—looking for threads that can be connected to tell stories about what was observed, primarily for people who are not aware of that work.

The first step in this process is re-reading fieldnotes, and analytically coding them so that the content becomes “textual objects.” This is open coding, as the goal is to generate codes in a bottom-up manner. Next, researchers conduct focused coding, where topics that are particularly interesting are evaluated across interviews. Throughout both forms of coding, researchers are writing memos to capture emergent ideas; eventually these initial memos become integrative memos across research participants. Finally, themes emerge and are refined.

This is “at once inductive and deductive,” like “a carpenter alternatively changing the shape of a door and then the shape of the door frame to obtain a better fit.” (wtf)

Initial re-reading of field notes should be done across the entire set, and it’s recommended to read them as if they were written by someone else. This generates questions, and “the secret of coding lies in turning the answers to these questions into a distinctive kind of writing—a word or short phrase that captures and signals what is going on in a piece of data in a way that links it to some more general analytic issue.” Priority is given to processes rather than nouns.

Then, coding begins in the margin of the notes. Codes should identify analytic distinctions. They start to relate ideas to one-another. Open coding should not start with pre-set categories. A goal is to generate as many codes as possible. Along with coding, a researcher writes theoretical memos that are analytic, rather than commentary.

After initial coding, core themes emerge. Good themes allow the researcher to link them to other issues in the data. These themes are represented by the coded content, which are then collected in manageable sets; these sets are then used in focused coding. This forces comparisons between related incidents. Subcodes emerge, and along the way, the researcher writes integrative memos that start to elaborate ideas and link codes together. At this point, it is useful to “write with future audiences explicitly in mind.” This is where a theory emerges through the connections between content.