Recoding can occur with a more attuned perspective using First Cycle methods again, while Second Cycle methods describe those processes that might be employed during the second and third and possibly fourth … review of data. As you code and recode, expect — or rather, strive for — your codes and cat- egories to become more refined. Some of your First Cycle codes may be later subsumed by other codes, relabeled, or dropped all together.
As you progress toward Second Cycle coding, there may be some rearrangement and reclassi- fication of coded data into different and even new categories.
This was preparatory fieldwork before an action research project that attempted to empower children with strategies, learned through improvised dramatic simu- lations and role-playing, for dealing with bullying in the school environment. I initially categorized their responses into Physical and Verbal forms of oppression. From codes and categories to theory Some categories may contain clusters of coded data that merit further refinement into subcategories.
As a very basic process, codifying usually follows an ideal and streamlined scheme as illustrated in Figure 1. Keep in mind that the actual act of reaching theory is much more com- plex and messy than illustrated. So, what major themes or concepts can be developed from these categories? An obvious theme we noticed was that, in later childhood, peer oppression is gen- dered.
We could not, in confidence, formulate a formal theory from this study due to the limited amount of fieldwork time in the classrooms. It diagnostically shows which children are leaders, followers, resisters, and targets; who is influential and who is ignored; which children may continue to assert dominance in later grade levels; and which children may succumb to those with more authority in later grade levels.
This assertion also progresses from the particular to the general by predicting patterns of what may be observed and what may happen in similar present and future contexts. A datum is initially and, when needed, secondarily coded to discern and label its content and meaning according to the needs of the inquiry. Qualitative researchers are not algorithmic automatons. Make a note of it in an analytic memo see Chapter Two when it happens, for it can sometimes guide your continued coding processes.
A set of themes is a good thing to emerge from analysis, but at the beginning cycles there are other rich discoveries to be made with spe- cific coding methods that explore such phenomena as participant process, emotions, and values. What Gets Coded? But what exactly gets coded in the data? The authors first outline major units of social organization into: 1. Lofland et al. Amounts of data to code One related issue with which qualitative research methodologists disagree is the amount of the data corpus — the total body of data — that should be coded.
Some e. Wolcott, feel that every recorded fieldwork detail is worthy of consideration, for it is from the pat- terned minutiae of daily life that we might generate significant social insight.
Others e. The danger is that the portions deleted might contain the as yet unknown units of data that could pull everything together, or include the nega- tive case that motivates a rethinking of a code, category, theme, concept, theory, or assertion. Postmodern perspectives on ethnographic texts consider all docu- mentation and reports partial and incomplete anyway, so the argument for main- taining and coding a full or reduced data corpus seems moot.
Amount notwithstanding, insure that you have not just sufficient qualitative but sufficient quality data with which to work that have been appropriately transcribed and formatted see Poland, The beginning of my fieldwork career, however, was a major learning curve for me, and I coded anything and everything that was collected.
I advise the same for novices to qualitative research. Of course, there will always be brief passages of minor or trivial consequence scattered throughout interviews and field notes. So, what gets coded? Slices of social life recorded in the data — participant activities, perceptions, and the tangible documents and artifacts produced by them. The process does not have to be approached as if it were some elusive mystery or detective story with deeply hidden clues and misleading red herrings scattered throughout.
The Mechanics of Coding As you prepare text-based qualitative data for manual i. Creswell , pp. Selected programs have areas dedicated to storing intriguing quotations for later access. The codes or quotes may even be so provocative that they become part of the title, organizational framework, or through-line of the report.
For example, in my study of theatre of the oppressed i. Preliminary jottings Start coding as you collect and format your data, not after all fieldwork has been completed. Be wary of relying on your memory for future writing.
Get your thoughts, however fleeting, documented in some way. Also make certain that these code jottings are distinct in some way from the body of data — bracketed, capitalized, italicized, bolded, etc. The first and widest column contains the data them- selves — interview transcripts, field notes, etc.
The second column contains space for preliminary code notes and jottings, while the third column lists the final codes. I keep playing the lottery, though, in hopes of dreams of early winning those millions. No retirement luck yet. Write your code words or phrases completely rather than abbreviating them to mnemonics or assigning them reference numbers. What are they trying to accomplish? What did I learn from these notes? The answer depends on the nature of your data, which particular coding method you select for analysis, and how detailed you want or need to be — in other words, more filters to consider.
She has just completed several poignant vignettes about some of her most difficult students. I thought I was so ready for this population because I had taught other groups of kids.
But this is such a unique situation, the inner city school. There are more and more schools that are turning into inner city schools. I had to learn about the culture, I had to learn the language, I had to learn the gang signals, I had to learn what music was allowed, what t-shirts they could wear on certain days and not on other days.
There was just a lot to learn that I had never even thought about. Now this word excerpt is represented with seven codes rather than one. I state the numbers not to suggest that more is better or that less is more, but to highlight that lumping is an expedient coding method with future detailed subcoding still possible , while splitting generates a more nuanced analysis from the start.
Each approach has its advantages and disadvantages aside from the obvious factors of time and mental energy required. Lumping gets to the essence of categorizing a phenomenon while splitting encourages careful scrutiny of social action represented in the data.
But lumping may lead to a superficial analysis if the coder does not employ conceptual words and phrases, while fine-grained splitting of data may overwhelm the analyst when it comes time to categorize the codes. During Second Cycle coding, you might collapse the original number of First Cycle codes into a smaller number as you reana- lyze the data and find that larger segments of text are better suited to just one key code rather than several smaller ones. The quantities of qualities Lichtman projects that most qualitative research studies in education will generate 80— codes that will be organized into 15—20 categories which even- tually synthesize into five to seven major concepts pp.
The final number of major themes or concepts should be held to a minimum to keep the analysis coherent, but there is no stan- dardized or magic number to achieve. Wolcott , p. The codebook or code list Since the number of codes can accumulate quite quickly and change as analy- sis progresses, keep a record of your emergent codes in a separate file as a code- book — a compilation of the codes, their content descriptions, and a brief data example for reference.
CAQDAS programs, by default, will maintain a list of codes you have created for the project and provide space to define them. This can be reviewed periodically — both on the monitor screen and on hard copy — as coding progresses to assess its current contents and possible evolution. Maintaining this list provides an analytic opportunity to organize and reorga- nize the codes into major categories and subcategories.
This management tech- nique also provides a comparative list if you are working with multiple participants and sites. MacQueen et al. Also note that a codebook differs from an index, the latter being a coded composite of the data corpus, organized alphabetically, hierarchically, chronologically, categorically, etc. Once a statistical test has been adminis- tered this way, they can then use computers with software specifically designed to calculate numeric data. Coding and qualitative data analysis have their equivalent trial.
The reason is that each class assignment of data gathering is relatively small-scale and thus a manageable project to analyze in this manner. Coding manually Trying to learn the basics of coding and qualitative data analysis simultane- ously with the sometimes complex instructions and multiple functions of CAQDAS programs can be overwhelming for some, if not most. Your mental energies may be more focused on the software than the data. I recommend that for first-time or small-scale studies, code on hard-copy printouts first, not via a computer monitor cf.
Bazeley, , p. There is something about manipulating qualitative data on paper and writing codes in pencil that give you more control over and ownership of the work.
After you feel the codes are fairly well set from your initial hard-copy work, then transfer your codes onto the electronic file. Even proponents of CAQDAS recommend that hard-copy printouts of code lists and coded data be generated occasionally to permit you to work with tra- ditional writing materials such as red pens and highlighters to explore data in fresh ways.
Coding electronically After you have gained some experience with hard-copy coding and have developed a basic understanding of the fundamentals of qualitative data analy- sis, apply that experiential knowledge base by working with CAQDAS.
Keep in mind that CAQDAS itself does not actually code the data for you; that task is still the responsibility of the researcher. The software efficiently stores, orga- nizes, manages, and reconfigures your data to enable human analytic reflection.
As with all word-processed work on a computer, backup your original files as a precautionary measure. This becomes vital for its coding and retrieval functions to work consistently and reliably.
Figure 1. Patents pending. Passages have to be formatted in prescribed ways and contain the exact same word or phrase, however, for this function to work accurately.
Searches or queries of coded passages can even find where particular codes co-occur, over- lap, appear in a sequence, or lie in proximity to each other. The varying sizes of the squares within the matrix indicate the relative frequency of such matches. CAQDAS also permits the researcher to shift quickly back and forth between multiple analytic tasks, such as coding, analytic memo writing, and exploring pat- terns in progress.
Since most readers of this book are more than likely newcomers to qualitative data analysis, I assume that manual coding will be the first method you employ. Thus, I pre- sent the coding profiles with that assumption in mind. Provocative questions are posed for consideration that could possibly generate new and richer codes Olesen et al.
Ultimately, team members must coordinate and insure that their sometimes indi- vidual coding efforts harmonize, particularly if a central data base and CAQDAS system are employed. For these types of collaborative ventures, intercoder agreement or interpretive con- vergence — the percentage at which different coders agree and remain consistent with their assignment of particular codes to particular data — is an important part of the process see Bernard, , pp.
Discussion provides not only an opportunity to articulate your internal thinking processes, but also presents windows of opportunity for clarifying your emergent ideas and possibly mak- ing new insights about the data.
Ezzy , pp. Though applicable for team researchers as well, the lone researcher can benefit most from these recommen- dations to assess the trustworthiness of her account: 1 check your interpreta- tions developed thus far with the participants themselves; 2 initially code as you transcribe interview data; and 3 maintain a reflective journal on the research project with copious analytic memos.
Necessary Personal Attributes for Coding Aside from such cognitive skills as induction, deduction, abduction, synthesis, evaluation, and logical and critical thinking, there are seven personal attributes all qualitative researchers should possess, particularly for coding processes.
First, you need to be organized. Organization is a set of disciplined skills that can be learned and cul- tivated as habits. The multiple codes you generate will need an organized framework for qualitative analysis.
And despite the electronic filing systems of hard drives and CAQDAS, you will still encounter and manipulate many pages of paper in qualitative work. Date and label all incoming data and keep multiple digital and hard copies as backup. Virtually every writer of qualitative research methods literature remarks that coding data is challenging and time- consuming.
Some writers also declare how tedious and frustrating it can be. Take breaks from your work when you need to, of course — this will keep you refreshed and alert.
But cultivate a personal work ethic and create an environ- ment and schedule that enable you to sustain extended periods of time with analytic tasks requiring your full concentration. Third, you need to be able to deal with ambiguity. The acts of coding and cod- ifying are not precise sciences with specific algorithms or procedures to follow.
Yes, occasionally answers may suddenly and serendipitously crystallize out of nowhere. But at other times, a piece of the analytic puzzle may be missing for days or weeks or even months. Rich ideas need time to formulate, so have trust and faith in yourself that these may emerge in due time.
But remember that you can accelerate the process through analytic memo writing. Fourth, you will need to exercise flexibility. Coding is a cyclical process that requires you to recode not just once but twice and sometimes even more. Virtually no one gets it right the first time. If you notice that your initial meth- ods choices may not be working for you or not delivering emergent answers you need, be flexible with your approach and try a modified or different method all together.
Virtually all researcher-developed coding schemes are never fixed from the beginning — they evolve as analysis progresses. Fifth, you need to be creative. Noted ethnographer Michael H. We generally advocate that qualitative researchers remain close to and deeply rooted in their data, but every code and category you construct or select are choices from a wide range of possible options.
Creativity also means the ability to think visu- ally, to think in metaphors, and to think of as many ways possible to approach a problem. Creativity is essential for your data collection, data analysis, and even for your final written report. Sixth, you need to be rigorously ethical. Honesty is perhaps another way to describe this, but I deliberately choose the phrase because it implies that you will always be: rigorously ethical with your participants and treat them with respect; rigorously ethical with your data and not ignore or delete those seem- ingly problematic passages of text; and rigorously ethical with your analysis by maintaining a sense of scholarly integrity and working hard toward the final outcomes.
The seventh and arguably most important skill you need for coding is an extensive vocabulary. In qualitative research, our precision rests with our word choices.
A thesaurus review of a key word chosen as a code or category may introduce you to an even better — and more precise — word for your analysis. The majority of readers would most likely find the discussion tedious or irrelevant compared to the more important features, such as the major categories and findings.
Plus, scholarly journals place length restric- tions on article manuscripts, so some components of the research story must be left out and, more often than not, codes and coding fall by the wayside.
Stewart, Just acknowledge that the long time and rigor- ous effort you put into, and joyous personal analytic growth you experience through, coding and analytic memo writing are private affairs between you and your data cf.
Constas, That suggests that the methods profiled here are like tested recipes guaranteed to produce successful dishes every time. Each qualitative study is context-specific and your data are unique, as are you and your creative abilities to code them. My own qualita- tive research projects, in fact, have ranged from the realist to the literary and from the confessional to the critical van Maanen, But as a theatre prac- titioner, my discipline acknowledges that we must attend to both the art and craft of what we do to make our stage production work successful.
Hence, I must have an attunement to various methods of classroom practice because my professional responsibilities require that I do. Some methods are organizational, managerial, time-efficient, and related to carefully planned curriculum design.
Yet I empha- size to my students that such processes as the creative impulse, trusting your instincts, taking a risk, and just being empathetically human in the classroom are also legitimate methods of teaching practice. Education is complex; so is social life in general and so is qualitative inquiry in particular.
A metacognition of method, even in an emergent, inductive-oriented, and socially conscious enterprise such as qualitative inquiry, is vitally important. This introduction focused on codes and coding.
There is an accompany- ing heuristic with this process — writing analytic memos, the subject of the next chapter.
Insights emerge also from the subconscious and from bodily memories, never penned on paper. There are serendipitous connections to be made, if the writer is open to them.
Writing and analysis comprise a movement between the tangible and intangible, between the cerebral and sensual, between the visible and invisible. Interpretation moves from evidence to ideas and theory, then back again. There can be no set formulae, only broad guidelines, sensitive to specific cases. Your private and personal written musings before, during, and about the entire enterprise is a question-raising, puzzle-piecing, connection-making, strategy-building, problem-solving, answer-generating, rising-above-the-data heuristic.
Robert E. What is an Analytic Memo? Think of a code not just as a significant word or phrase you applied to a datum, but as a prompt or trigger for written reflec- tion on the deeper and complex meanings it evokes.
Let me clarify that I use analytic memo as my term of choice because, to me, all memos are analytic regardless of content. Some methodologists recommend that you label, classify, and keep separate different types of memos according to their primary purpose: a coding memo, theoretical memo, research question memo, task memo, etc.
But I have found it difficult in my own work to write freely and analytically within the bounded parameters of an artificial memo category as a framing device. Dating each memo helps keep track of the evolution of your study. Giving each memo a descriptive title and evocative subtitle enables you to classify it and later retrieve it through a CAQ- DAS search. Depending on the depth and breadth of your writing, memos can even be woven as substantive portions into the final written report.
Also important to note here is the difference between analytic memos and field notes. Field notes may contain valuable comments and insights that address the recommended categories for analytic memo reflection described below. Thus, personal field notes are potential sites in which rich analysis may occur.
I recommend extracting these memo-like passages from the corpus and keeping them in a separate file devoted exclusively to analytic reflection. Future direc- tions, unanswered questions, frustrations with the analysis, insightful connections, and anything about the researched and the researcher are acceptable content for memos. So keep a small paper notepad and something to write with, or a hand- held digital audio recorder, nearby at all times for brief jottings or reminders in lieu of computer access.
Below is one of the coding examples from Chapter One. Extensive memo writing, as illustrated below, over just one small passage of coded data, such as that above, is most unlikely. The example is kept deliber- ately brief to show how the same piece of data can be approached from mul- tiple angles for analytic memo writing. In what ways are you similar to them? They just, sigh, put me down all the time, too. School became a place where I dreaded going.
Barry probably dreaded it, too. Focusing on your a priori [determined beforehand] articulated research questions, purposes, and goals as analysis progresses will keep you on track with the project. Start by writing the actual question itself then elaborate on answers in progress. This middle school dead period seemed to have influenced and affected his moody entry into high school, but he overcame it.
So now, the task is learning what hap- pened to Barry beginning in ninth grade that changed him for the better. Reflect on and write about your code choices and their operational definitions. Define your codes and rationalize your specific choices for the data. To be rejected is one of the most devastating acts for a tween and a child and a teenager and an adult. I know I was. Reflect on and write about the emergent patterns, categories, themes, and con- cepts.
Remember that individual codes eventually become part of a broader scheme of classification. As I continue analysis, that code may be more conceptual than I think at this point in the study. Reflect on and write about the possible networks links, connections, overlaps, flows among the codes, patterns, categories, themes, and concepts.
One of the most criti- cal outcomes of qualitative data analysis is to interpret how the individual compo- nents of the study weave together. First-draft diagrams of network relationships between and among concepts are also possible as analytic memo content see Appendix C for an extended example. Networking makes you think of possible hierarchies, chronological flows, and influences and affects i.
Transcend the local and particular of your study, and reflect on how your observations may apply to other populations, to the bigger picture, to the generalizable, even to the universal. Explore possible metaphors and symbols at work in your data that suggest transferability.
Speculate on how your theory predicts human action and explains why those actions occur. Once lost, we go inward; once lost, we hide. Positioning theory from the s and s might be relevant here. Reflexive and interactive positioning are the dynamics at work within Barry and among him and his peers. Reflect on and write about any problems with the study. The act is also a way to raise provocative questions for continued reflection, or to vent any personal frustrations you may be feeling about the study.
Reflect on and write about any personal or ethical dilemmas with the study. Ethical issues of varying magnitude arise in virtually every study with human participants.
Most of these dilemmas are usually unforeseen, based on what par- ticipants unexpectedly bring to interviews or what the researcher observes in the field that counters her value, attitude, and belief systems. Reflection keeps you attuned to these matters and may help you brainstorm possible solutions. Maybe asking his mother to talk about those years rather than Barry will get the info to help me plot his life course? Reflect on and write about future directions for the study.
Each qualitative research project is unique and cumulative in nature. The more you interview participants and observe them in natural social settings, the more ideas you generate for possible future research action. As data collection and analysis progress, you may discover missing elements or a need for additional data.
You may even reconceptualize your entire initial approach and find inspiration from a new insight about the phenomenon or process under investigation.
But the tween years are elusive to me. Find a site and get back in touch with what happens from sixth through eighth grades. Reflect on and write about the analytic memos generated thus far.
Though this may happen on its own accord, the researcher will also have to consciously achieve it. Perhaps my attempt to systematically cat- egorize these data is proving useful for what could become an evocative narra- tive analysis instead?
That can be a good thing, though — a place for inward reflection, deep introspection — before that break- through moment — I hope. Reflect on and write about the final report for the study. Fresh, innovative and clear this book traces the history and development of grounded theory method, and examines how the method is evolving for new contexts today. It sets. I suspect that this book will never be far from my side over.
It is a must-have tool book for moving from data analysis to writing for publication! The Coding Manual for Qualitative Researchers. Fundamentals of Qualitative Research by Johnny Saldana. Thinking Qualitatively by Johnny Saldana. Qualitative Data Analysis by Matthew B. In modern Western society having a spirit animal or animal identity can sometimes be framed as social deviance rather than religious or totemic diversity.
Jessica Ruth Austin investigates how Furries use the online space to create a 'Furry identity'. She argues that for highly identified Furries, posthumanism is an appropriate framework to use. For less identified Furries, who are more akin to fans, fan studies literature is used to conceptualise their identity construction. This book argues that the Furries are not a homogenous group and with varying levels of identification within the fandom, so shows that negative media representations of the Furry Fandom have wrongly pathologized the Furries as deviants as opposed to fans.
Popular Books. The software efficiently stores, organizes, manages, and reconfigures our data to enable human analytic reflection.
Some programs even enable coding of digital audio and video documents stored in their files. In most qualitative studies, coding is a solitary act as the lone ethnographer intimately at work with his or her data Galman, but larger fieldwork projects may involve a team coding.
In a research team, multiple minds bring multiple ways of analyzing and interpreting the data, build copes and coding also builds a team through the creation of shared interpretation and understanding of the phenomenon being studied. Team members can both code their own and others' data gathered in the field to cast a wider analytic net and provide a "reality check" for each other. In collaborative ventures, intercoder agreement or interpretive convergence is an important part of the process.
In coding solo, although we are working as a lone ethnographer, we need to discuss with a colleague or mentor about our dilemmas in coding and analysis to find better connections between categories in progress. Necessary Personal Attributes for Coding. For coding processes, all qualitative researchers should possess seven personal attributes. First, we need to be organized. Second, we need to exercise perseverance. Third, we need to be able to deal with ambiguity.
Fourth, we will need to exercise flexibility. Fifth, we need to be creative. Sixth, we need to be rigorously ethical. Finally, the seventh need for coding is an extensive vocabulary. The researcher's code development descriptions and coding processes are the methods towards a final report.
Qualitative research projects should be ranged from the realist to the literary and from the confessional to the critical.
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Jump to Page. Search inside document. Purposes of the Manual 2. What Is a Code? Coding examples Coding for patterns Coding filters Coding as a heuristic 3. Codifying and Categorizing From codes to categories Recoding and recategorizing From codes and categories to theory The differences between codes and themes 4. What Gets Coded?
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