I can’t remember who said this, but there are basically only two types of thinkers (hence writers) – lumpers and splitters. Lumpers are those casual, freethinking types who put things together as the big picture, not being too bothered by the small details. They’re often wrong but at least they convey the broad outlines more or less helpfully. Splitters are the obsessive perfectionists who burrow into the tiny facts and often can’t see the wood for the trees. They’re usually right about things but hell to argue with.
Recently I was involved in a workshop on science research writing and it raised some old fears and new perceptions. Am I a lumper or a splitter? Do I leap buildings at one bound or train my microscope on minutiae?
I have to wonder. Are we fatefully divided into synthesisers and analysers, one versus the other, and never the twain shall meet. Is that necessarily true? My guess is that we all have a bit of both in our make-up. When it comes to writing complex researched material we all tend to get stuck at basically the same points – on the synthesis of the big picture, and on the analysis of details. That’s why a writing method to solve both sets of problems needs to be learnt and applied by anyone who aims to produce meaningful, evidence-based but clear and concise research papers and reports.
The frustrating condition known as writer’s block – where you stare and stare at a page of nothing – is a symptom of difficulties with both lumping and splitting. You can’t write because you can’t force the ideas and the data into a meaningful pattern. So you grind to a halt.
As a professional writer I can’t afford to stand still. Writer’s block has its advantages: it allows you to think through what you are doing. But if it happens because you are indulging in avoidance behaviour, or because you are stuck on detail, or because the big picture is too big after all and you are afraid of sketching it, it’s time to seek a practical solution.
For years, in my own work as a non-fiction author in the field of popular science writing, I’ve been developing my own home-made system of lump-and-split as a computerised writing method. I use mind-mapping to lump things together and a database of notes & sources to split things into detailed bits. Together, these techniques overcome what I regard as the main problem in research writing: how to form a unified whole from a mosaic of ideas and evidence. How, in other words, to build a bridge between the mind and the manuscript.
Our minds have an amazing ability to conceptualise things as a whole. Present your mind with any collection of seemingly random facts and somehow, subconsciously as well as consciously, it finds ways to make a pattern of them and explain them. In my writing workshops I use a funny little exercise called “random writing” to demonstrate how the mind works as a super-synthesiser. Take five ordinary words that have no apparent thread of meaning or connection with each other, and write a paragraph using them. You can do it – and do it quickly – without any real effort. One of these exercises is demonstrated in the powerpoint presentation here.
At the same time, our minds do seem to lack the colossal data-crunching power of computers. We don’t reduce things to tiny bits. If we do, we often get lost in the finer points (that’s where so much of the obsessive energy of habitual splitters is wasted).
Most journalists, like me, are lumpers because that’s the nature of the game. You have to quickly assemble the main facts from a variety of sources and convey “the story” to your audience in as few words as possible. Most scientists are trained to be splitters because the empirical data contain the findings that will either confirm or contradict their hypotheses. You can’t tell the story unless you can prove it.
I’ve interviewed a lot of scientists and reported their work, and it’s always the case that we have to establish a common mode of communication before the real conversation can begin. Basically I say: Please explain this as you would to your grandmother. That works. The scientist splitter becomes a lumper, and I try to go halfway by grasping the intricacies of the splitting process.
Yet journalists and scientists have this in common: they are detectives, sorting through facts and findings to discover the truth and impart it to readers. So at what point do the big picture and the little details converge? The world of information is becoming far more complex for all of us, and we need techniques to aid the mind to do its work.
It is true to say that as the global village gets smaller, the universe of meaning is expanding. It is expanding uncontrollably fast and into dimensions that were unimaginable to previous generations. They did not have access to the instant communication technologies that now fill our mental spaces. We are bombarded with new discoveries and new theories on a minute-by-minute basis through our cellphones and iPads. We would feel lost if we didn’t receive this constant updating – yet it leaves us more puzzled than before, unable to consolidate our knowledge.
In all of this the computer is boon to thinking. We have to hope that computers don’t soon take over our thinking and make us their slaves. Frankly, I think that is a nightmare promoted by science fiction writers, and like all nightmares it evaporates in the light of day. There is no tool that can beat the human mind at summarising, understanding and strategising, and no quantum computer is likely to match us in imagination. But we can use the power of computers to enhance our mental operations. Amazing tools are now available on the web and in electronic resource libraries to help us lump and split, investigate and speculate, inquire and compile.
I mentioned my home-made writing system. Freemind, a free mind-mapping tool, is an absolute wonder. It replaces the old paper doodling habit with a programme that lets you doodle and then converts your branches and keywords to a comprehensive list. This is fantastic both for planning a project (or a section of writing) and for analysing the work of others. On the database side, my old Lotus Approach database – certainly one of the most user-friendly programmes ever devised to allow amateurs to process records – has been superseded.
I am now making the somewhat arduous and painful transition to a new programme, Filemaker (originally designed for the Apple platform but now available on pc). I first tried the Brilliant database hoping that it would at least match Approach in user-friendliness but it doesn’t seem to be well supported by the suppliers. Filemaker has a truly brilliant Research Notes start-up package that does all the things I tried to do with Approach, and better.
It captures documents, data tables, sources, Internet cut-and-paste, images and media files. It has fields for précis (essential when boiling down the detailed notes) and you can export everything as text in any order, with any selection. Using the relational power of the database you can compile your first draft of a written paper according to any list of keywords which will then extract only what you want.
And hey presto – there you are – you have jumped the gap between lumping and splitting. Freemind mind-mapping and Filemaker Research Notes produce, for me, the perfect solution to the age-old writer’s problem of how to consolidate the big picture with all the small details contained within it. This is not to say that the system is foolproof or does your writing for you. There is plenty left to do after you have your first crude database-generated draft of the text. But at least you have the words on paper (or onscreen) and can begin to cut and paste, rewrite and edit for the eventual final text.
Just knowing I have a database behind me gives me the confidence, at least most of the time, to avoid writer’s block. The mind-map to database method is not a magic wand but it certainly helps to overcome blind lumping (guessing at facts and randomly using the evidence) as well as fanatical splitting (ignoring the context to pursue irritating blips without end).
Mind-mapping can be done on paper where you simply tear up and throw away what doesn’t work out. It’s easier on the computer screen. You can move branches around, revise keywords, save and come back later, and generally let your mind play around with the pattern until it satisfies. This is why the mind-map should never be shown to others and certainly never decorated to look good – it isn’t a finished work of art but a work in progress.
Learning to handle a database for research writing is a project in itself. Though most of what you must do to capture and organise your research into entry forms comes naturally and intuitively, you still need to know how to apply the functions that will extract the best of your findings and ideas without losing anything. In my workshops I spend a good deal of time explaining, demonstrating and getting participants to practice database writing techniques.
There are dozens of other good computer utilities to help writers. I love using fog indexes (readability scoring) to show research writers how long words and wandering sentences, abstract expression and unsignposted text, succeed in fogging up the reader’s mind. We must use plain English, not some unknown language, even where scientific terminology and complex ideas have to be communicated – indeed, especially in these circumstances!
We have come a long way from the wax tablet of the Romans and the messenger with the forked stick. We have infinitely pliable electronic text and instant messaging. Still, there is no substitute for coherent thought and the careful organisation of your materials.
The question many may ask is “When does a database become necessary?” Not if you’re just writing a letter to a friend or a short presentation for your circle of colleagues. That should all come out of your head, from the best computer in existence, the brain. But if your research fails to pass the dining-room table test, it’s time to use a database.
The dining-room table test? Simple: if your books, notes, papers, slides, CDs and other research materials reach the point where they are falling on the floor, you need a database. If not before! – Graeme Addison