Saldana Ch. 5 and 6

Saldana's The Coding Manual for Qualitative Researchers

Ch. 5: Second Cycle Coding Methods

The Goals of Second Cycle Methods
The second cycle of coding is the point at which the myriad codes created in the first cycle get refined into larger codes or categorical labels. The idea is to begin finding trends or themes within the data which can eventually be assembled into a theory or model. We have to be careful that our categories are not too disparate; if they are, we are probably misrepresenting some things because data will not tend to hold such variety without overlap.

Second Cycle Coding Methods
Pattern coding: a meta-code that pulls the existing codes into a smaller number of codes or categories
Focused coding: looks for frequent or high intensity codes to identify salient features of the text
Axial coding: reassembles split data; looks for dominant and subordinate codes to create a categorical system that specifies the properties and dimensions of categories
Theoretical coding: Identifies a core category and formulates codes that relate the data to that category; can be theory-driven or emergent
Elaborative coding: Uses categories/themes from a previous study to interpret the data; strengthens the theory by seeing how well the prior coding set explains the new data
Longitudinal coding: Used for life-long studies; notes increase/decrease in study variables, accumulations, epiphanies, idiosyncracies, constancy, and missing data

Ch. 6: After Second Cycle Coding
It can be difficult to transition from fully-coded data to making theoretical claims. There are many different formats that research can take, so Saldana focuses on solidifying ideas.

Focusing Strategies
The "top 10" list: Use the 10 most interesting or varied pieces of data to illustrate the salience or breadth of your research
The study's "trinity": Identify the three most important concepts in your research and figure out the relationship between the three
Codeweaving: Using the major codes in your research, tell a story that structures the relationships between the codes
The "touch test": Look at your codes and find those that are things-- what can be touched? These codes need to be abstracted a level (mother to motherhood)

From Coding to Theorizing
Elements of a theory: Identify the if/then components or relationships within your coding
Categories of categories: Place your existing categories into larger categories

Formatting Matters
Rich text emphasis: Bold major concepts and italicize important assertions
Headings and subheadings: Use headings and subheadings to structure an argument

Writing About Coding
It is helpful to include as much information about the methods you used as possible. This includes everything from the data acquisition and sampling to the computer programs you used to code and manage the data. Make sure to emphasize major outcomes of the analysis.

Ordering and Reordering
Analytic storytelling: Tell the story of your analysis in a chronological way
One thing at a time: Write about concepts or categories one at a time, keeping them separate initially
Begin with the conclusion: If having trouble writing, begin with the conclusion

Assistance from Others
Peer and online support: Have peers (in person or online) look at your work and provide suggestions
Searching for "buried treasure": Have readers of your work look for important ideas or assertions that are not explained

Saldana Ch. 3

The Coding Manual for Qualitative Researchers, Ch. 3

First Cycle Coding Methods

The first cycle of coding is the initial coding of data. Saldana identifies seven types of first cycle coding: grammatical, elemental, affective, literary, and language. Each of these types has several particular coding methods associated with it. The second cycle of coding is characterized as more analytic, and it includes classifying, prioritizing, integrating, synthesizing, abstracting, conceptualizing, and theory building.

Choosing the right type of coding is dependent on several factors, and the choice should be guided by your research question, your paradigmatic and methodological choices, and exploratory work with your data set. Saldana suggests a generic coding method for figuring out the right type of coding for your data, begging with attribute coding and followed by structural/holistic coding, descriptive coding, and in vivo, initial, or value coding.

Grammatical Methods

Attribute coding: Used for nearly all studies, attribute coding goes before the text and lists all relevant attributes to the data set, including qualitative and quantitative properties.

Magnitude coding: This adds an alphanumeric measure of intensity to another coding scheme

Subcoding: Creates a secondary code to accompany a primary coding system. The subcode is hierarchically below the status of the primary code.

Simultaneous coding: Utilizes a second code of equal standing or importance to the primary code, at the same time on the same texts

Elemental Methods

Structural coding: Codes related to questions asked during interviews/recurrent topics from participants; especially useful with large numbers of participant responses following a similar structure

Descriptive coding: Creates codes related to the topic of qualitative data. This is different from codes referring to the content.

In vivo coding: Uses the language of the data to code instead of labels chosen by the researcher

Process coding: Codes through use of gerunds—what the language is doing conceptually or what an observed participant is physically doing

Initial coding: Open-ended approach that breaks data down into parts and compares them; iterative

Affective Methods

Emotion coding: Labels emotions experienced or recalled by participants

Values coding: Codes values, attitudes, and beliefs expressed in participant responses

Versus coding: Codes for binaries, dialectics, and rivalries

Evaluation coding: Used to evaluate programs, evaluation coding makes value judgments (non-quantitative) and attempts to describe, compare, and predict success from a program

Literary and Language Methods

Dramaturgical coding: The application of dramatic elements to qualitative data (not just Burke’s pentad), drawing from Goffman and impression management

Motif coding: Uses index codes for classifying folk tales, myths, and legends; the motif is the smallest unique unit in the story

Narrative coding: Open form of coding whatever the researcher considers a narrative; done from a literary perspective

Verbal exchange coding: Aims at finding a generic form of conversation. Codes precise transcripts of conversations as phatic communication, ordinary conversation, skilled conversation, personal narratives, and dialogue.

Exploratory Methods

Holistic coding: Looks for themes and issues by taking in qualitative data as a whole rather than analyze line-by-line.

Provisional coding: The creation of a set of codes before analyzing the data based on existing knowledge of the texts

Hypothesis coding: Coding done with a predetermined set of codes aimed at testing a particular hypothesis

Procedural Methods

Protocol coding: Protocol coding occurs when all coding is done by a rigid, preset system rather than an open or iterative process

Outline of Cultural Materials (OCM) coding: Coding that follows the OCM, a topical index for anthropologists and archaeologists

Domain and taxonomic coding: An ethnographic type of coding, domain and taxonomic coding looks for cultural knowledge; it separates processes into steps, looks for cultural categories, and identifies semantic relationships (strict inclusion, spatial, cause-effect, rationale, location for action, function, means-end, sequence, and attribution).

Causation coding: Looks for causal beliefs in qualitative data; notes dimensions of causality, including internal/external, stable/unstable, global/specific, personal/universal, and controllable/uncontrollable

Themeing the Data

A theme is a phrase or sentence that identifies what a unit of data is about or means. Creating themes means finding groupings of implicit ideas among the coded data.