Entomologies of qualitative coding - image from Lisa Williams https://www.flickr.com/photos/pixellou/5960183942/in/photostream/

I was recently privileged to chair a session at ICQI 2017 entitled “The Archaeology of Coding”. It had a fantastic panel of speakers, including Charles Vanover, Paul Mihas, Kathy Charmaz and Johnny Saldaña all giving their own take on this topic. I’m going to write about my own interpretation of qualitative coding archaeologies in the next blog post, but for now I wanted to cover an important common issue that all the presenters raised in their presentations: coding is never finished.

In my summary I described this as being like the river in the novel Siddhartha by Herman Hesse: ‘coding is never still’. It should constantly change and evolve, and recoil from attempts to label it as ‘done’ or ‘finished’. Heraclitus said the same thing, “You cannot step twice into the same rivers” for they constantly change and shift (as do we). When we come back to revisit our coding, and even during the process of coding, change is part of the process.

I keep coming back to the image of butterflies in a museum display case: dead, pinned to the board with a neatly assigned label of the genus. It’s tempting to approach qualitative coding with this entomologist’s approach: creating seemingly definitive and static codes that describe one characteristic of the data.

Yet this taxonomy can create a tension, lulling you into feeling that some codes (and frameworks) are still, complete, and don’t need revision and amendment. This might be true, but it usually isn’t! If you are using some type of open-ended coding or grounded theory approach, creating a static code can be beguiling, and interpreted as showing progress. But instead, try and see every code as a place-holder for a better category or description – try not to loose the ability for the data to surprise you, and the temptation to force quotes into narrow categories. Assume that you are never finished with coding.

Unless you are using a very strict interpretation of framework analysis, your first attempt at coding will probably change, evolve as you go through different sources, and take you to a place where you want to try another approach. And your attempts at creating a qualitative classification and coding system might just end up being wrong.

Even in biology, classification attempts are complicated. While the public are still familiar with the different ‘animal kingdom’ groupings, attempts to create a taxonomy in the ‘tree of life’ common descent model are now succeeded by the modern ‘cladistic’ approach, based around common history and derived characteristics of a species. And these approaches also have limitations, since they are so complex and subjective (just like qualitative analysis!).


For example, if you use the NCBI Taxonomy browser you will see dozens of entries in square brackets. These are the misclassified organisms which have been currently recognised, species placed in the wrong genus. These problems don’t even include the cases when one species is found to be many unique but significantly separate species on closer study. This has even been found to be the case for the common ‘medicinal’ leech!


Trying to turn the endless forms most beautiful of the animal ‘kingdoms’ into neat categories is complex, even when just looking at appearance. And these taxonomic groupings tell us little of the diverse range of behaviour and life behind the dead pinned insects.

In a similar way, when we code and analyse qualitative data, we are attempting to listen to the voices of our respondents, and change the rich multitude of lives and experiences into a few key categories that rise up to us. We often need to recognise the reductive nature of this practice, and keep coming back to the detailed rich data behind it. In a way, this is like the difference between knowing the Latin name for a species of butterfly, and knowing how it flies, it’s favourite flowers, and all the details that actually make them unique, not just a name or number.



In Siddhartha, the central character finds nirvana listening to the chaotic, blended sound of a river, representing the lives and goals of all the people in his life and the world.

“The river, which consisted of him and his loved ones and of all people, he had ever seen, all of these waves and waters were hurrying, suffering, towards goals, many goals, the waterfall, the lake, the rapids, the sea, and all goals were reached, and every goal was followed by a new one, and the water turned into vapour and rose to the sky, turned into rain and poured down from the sky, turned into a source, a stream, a river, headed forward once again”

Like the river, qualitative analysis can be a circle, with each iteration and reading different from the last, building on the previous work, but always listening to the data, not being quick to judge or categorise. Until we have reached this analytical nirvana, it is difficult to let go of our data, and feel that it is complete. This complex, turbulent flow of information defies our attempts to neatly categorise and label it, and the researcher’s quest for neatness and uncovering the truth under our subjectivity demands a single answer and categorisation scheme. But, just like taxonomy, there may never be a state when categorisation is complete, in a single or multiple interpretation. New discoveries, or new context can change it all.

We, the researcher, are a dynamic and fallible part of that process – we interpret, we miscategorise, we impose bias, we get tired and loose concentration. When we are lazy and quick, we take the comfort of labels and boxes, lulled into conformity by the seductive ease of software and coloured markers. But when we become good qualitative researchers: when we are self-critical and self-reflexive, finally learning to fully listen, then we achieve research nirvana:

“Siddhartha listened. He was now nothing but a listener, completely concentrated on listening, completely empty, he felt, that he had now finished learning to listen. Often before, he had heard all this, these many voices in the river, today it sounded new. Already, he could no longer tell the many voices apart, not the happy ones from the weeping ones, not the ones of children from those of men, they all belonged together”


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Tags : qualitativecoding ,   classification