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.
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