Coding for Qualitative Researchers
Saldana, J. (2009). The coding manual for qualitative researchers. Los Angeles, CA: SAGE.
Summary: In this chapter, Saldana defines various terms related to codes and coding. He also gives a rationale for why individuals code.
Chapter 1: An Introduction to Codes and Coding
· Purposes of the Manual
· What is a Code?
o “A code in qualitative inquiry is most often a word or short phrase that symbolically assigns a summative, salient, essence-capturing, and/or evocative attribute for a portion of language-based or visual data (p. 3).”
o “Just as a title represents and captures a book or film or poem’s primary content and essence, so does a code represent and capture a datum’s primary content and essence (p. 3).”
o Coding Examples
§ Decoding means reflecting on the data to figure out its essence.
§ Encoding entails identifying and labeling the datum with a code.
o Coding for Patterns
§ Pattern characteristics include :
· “similarity (things happen the same way)
· difference (they happen in predictably different ways)
· frequency (they happen often or seldom)
· sequence (they happen in a certain order)
· correspondence (they happen in relation to other activities or events)
· causation (one appears to cause another) (Hatch, 2002, p. 155 as cited in this Saldana text).”
o Coding Filters
§ Coding filters differ by the researcher and are determined by the researcher’s lens.
o Coding as Heuristic
§ Coding is cyclical.
§ “Coding is not just labeling, it is linking (p. 8).”
§ “I advocate that qualitative codes are essence-capturing and essential elements of the research story that, when clustered together according to similarity and regularity – a pattern – they actively facilitate the development of categories and thus analysis of their connections (p. 8).”
· Codifying and Categorizing
o “To codify is to arrange things in a systematic order, to make something part of a system or classification, to categorize (p. 8).”
o From Codes to Categories
§ Categories can be broken down into sub categories, which are supported by codes. Ex.
· Category Name
o Subcategory 1 Name
o Subcategory 2 Name
o Recoding and Recategorizing
§ Coding is done more than once.
§ “Qualitative inquiry demands meticulous attention to language and deep reflection on the emergent patters and meanings of human experience (p. 10).”
o From Codes and Categories to Theories
§ Theories are similar to key assertions.
§ They move from the particular to the general using inference, asserting that what happened in this particular context could occur in other similar contexts, or by predicting patterns that could occur in other contexts.
o The Differences Between Codes and Themes
§ They are different.
§ “A theme is an outcome of coding, categorization, and analytic reflection, not something that is, in itself, coded (p. 13).”
· What Gets Coded?
o Some advocate everything and anything as a data source.
o Some advocate only the essential.
o Units of Social Organization
o Amounts of Data to Code
§ Only experienced researchers should code the essential because they are then able to feel which data are important and relevant for coding purposes.
· The Mechanics of Coding
o The way we format our coding and our documents is a choice and therefore influences the data analysis. As the researcher, we are selecting where an essential break occurs, which might be different for someone else. Therefore, it is our interpretation and we must recognize that.
§ Precoding is highlighting, bolding, underlining, etc. key words or phrases in the text that stand out upon an initial read.
o Preliminary Jottings
§ Recommends a three column approach: (1) Raw Data, (2) Preliminary Codes, (3) Final Code
§ Keep analytic memos.
o Questions to Consider as You Code
§ “What strikes you? (p. 18).”
§ Refers to Emerson, Fretz, & Shaw (1995)’s set of questions on p. 146:
· “What are people doing? What are they trying to accomplish?
· How, exactly, do they do this? What specific means and/or strategies do they use?
· How do memebers talk about, characterize, and understand what is going on?
· What assumptions are they making?
· What do I see going on here? What did I learn from these notes?
· Why did I include them? (p. 146 as cited in Saldana p. 6).”
o Coding Contrasting Data
· The Number of Codes
o “Lumping” and “Splitting” the Data
§ “Lumping gets to the essence of categorizing a phenomenon while splitting encourages careful scrutiny of social action represented in the data (p. 20).”
§ Even though lumping takes less time, it can sometimes leave out essential data.
§ Splitting is more time consuming and tedious, but it is more detail-oriented.
o The Quantities of Qualities
§ The number of suggested codes and themes varies among researchers.
o The Codebook or Code List
§ Keep one especially if you are working with multiple colleagues on the same project.
§ It is good to include in the dissertation appendix.
· Manual and CAQDAS Coding
o Coding Manually
§ Recommended for novice researchers and simple research projects.
o Coding Electronically
§ Recommended once experienced at coding and for complex research projects involving multiple participants.
o Data Formatting for CAQDAS
o Coding Capabilities with CAQDAS
o Searches and Queries with CAQDAS
· Solo and Team Coding
o Coding Collaboratively
§ Can often bring new perspectives and insights to the data.
o Coding Solo
§ Recommends engaging in shop talk with other colleagues so that they can push your thinking.
· Necessary Personal Attributes for Coding
o Comfort with ambiguity
o “Rigorously Ethical” (i.e. honest)
o Extensive Vocabulary
· On Method
o Neat analogy for the exclusion of the coding details and procedures in the report: “When you invite important guests to your home for dinner, you don’t ask them to appear two or three hours before the scheduled serving time to watch you cook in the kitchen. They arrive just before the meal to feast on and enjoy what you’ve worked so hard to prepare (p. 30).”
o Coding as Craft