Syndromes and permutations

By Jennifer Skillen, Gordon Rugg and Sue Gerrard

Some diagnoses are clear and simple, and give you a crisp either/or categorisation; either the case in question has a positive diagnosis, or it doesn’t. Diagnosis involves identification of the cause of a problem; this may occur in medicine, or in mechanical fault finding, or in other fields. This article focuses on medicine, but the concepts involved are relevant to diagnosis in other fields.

The diagram below shows crisp either/or diagnosis visually; cases either go in box A or box B, with no other options.

Not all diagnoses are this simple. Medical syndromes are an example. A syndrome in the medical sense involves a pattern of features that tend to co-occur, but where the cause is unknown. They typically involve multiple signs and symptoms, each of which may or may not be present in a particular case. (Signs are features that can be observed by someone other than the patient; symptoms can only be observed by the patient.) Making sense of syndromes, and of how to diagnose syndromes, is difficult, and often encounters problems with misunderstandings and miscommunications.

This article discusses ways of defining syndromes and related issues. Its main focus is on medical diagnosis, but the same principles apply to problems in other fields that have the same underlying deep structure.

Games people play, and their implications

By Gordon Rugg

There are regularities in how people behave. There are numerous ways of categorising these regularities, each with assorted advantages and disadvantages.

The approach to categorisation of these regularities that I’ll discuss in this article is Transactional Analysis (TA), developed by Eric Berne and his colleagues. TA is designed to be easily understood by ordinary people, and it prefers to use everyday terms for the regularities it describes.

I find TA fascinating and tantalising. On the plus side, it contains a lot of powerful insights into human behaviour; it contains a lot of clear, rigorous analysis; it has very practical implications. On the negative side, it doesn’t make use of a lot of well-established methods and concepts from other fields that would give it a lot more power. It’s never really taken off, although it has a strong popular following.

An illustrative example of why it’s fallen short of its potential is the name of Berne’s classic book on the topic, Games People Play. When you read the book, the explanation of the name makes perfect sense, and the deadly seriousness of games becomes very apparent. However, if you don’t read the book, and you only look at the title, then it’s easy to assume that the book and the approach it describes are about trivial passtimes, rather than core features of human behaviour.

In this article, I’ll look at some core concepts of Transactional Analysis, and how they give powerful insights into profoundly serious issues in entertainment, in politics, and in science.

The image below shows games at their most deadly serious; Roman gladiatorial combat, where losing could mean death.

By Unknown author – Livius.org, Public Domain, https://commons.wikimedia.org/w/index.php?curid=3479030

Content analysis, part 2

By Gordon Rugg

Other types of content analysis

In a previous post, I gave a brief overview of a widely used, vanilla flavour type of content analysis. It’s far from the only type.

There are methodological debates about most things relating to content analysis, which have been running for the best part of a century, and which don’t look likely to end any time soon. There are, in consequence, numerous different types of content analysis, and many approaches to content analysis. The following sections give a very brief description of some of those other types. I’m planning to write in more detail about them at some point, when there’s nothing more exciting to do…

The apparent attraction of average faces

By Gordon Rugg

In a previous article, we looked at what happens when you take two concepts that are normally viewed as opposites, and instead treat them as two separate concepts. We used the example of what happens when you treat liking and disliking as two separate concepts, and ask people to rate items in relation to both liking and disliking.

The result is that people are willing and able to do so. The image below shows types of response that we’ve seen in real data.

Item A has been rated low both for liking and for disliking; it’s just boring, with little to be said for or against it.

Item B has been rated high both for liking and for disliking; it produces strong but ambivalent feelings. An example that we saw involved university departmental websites, where some were strongly liked because they signalled high quality, but simultaneously strongly disliked because that same signal of high quality was viewed as implying unforgivingly high expectations.

Item C has been rated high like/low dislike by some participants, and low like/high dislike by others. This is informally known in the UK as the Marmite effect, where people either love something or hate it, with few people in between.

This approach of uncoupling apparent opposites is well established in some fields, but isn’t yet widely known outside them. We’ve been using it for a while in software evaluation, where it’s invaluable for improving software mockups before committing to the final design. We’ve also blogged about ways of using it to represent expressive and instrumental behaviour; handedness; and gender roles, going back to the literature where we first encountered it, in Bem’s work on androgyny (Bem, 1974).

The advantages of using this approach are clear when you see examples. In the next section, we’ll look at the background theory on which it works. We’ll then apply it to an apparently paradoxical finding about facial attractiveness, to show how the underlying issues can be swiftly and easily teased apart via this representation.

Mental models and metalanguage: Putting it all together

By Gordon Rugg

The previous articles in this series looked at mental models and ways of making sense of problems. A recurrent theme in those articles was that using the wrong model can lead to disastrous outcomes.

This raises the question of how to choose the right model to make sense of a problem. In this article, I’ll look at the issues involved in answering this question, and then look at some practical solutions.

The Rugg and Taylor “Cryptologia” article on the Voynich Manuscript

By Gordon Rugg and Gavin Taylor

Standard disclaimer: This article represents our own opinions, and does not reflect the views of Keele University or of Gavin’s employer, Heath Lane Academy, Leicester.

We’ve recently had an article published in Cryptologia about our work on the Voynich Manuscript, which was discussed in New Scientist. The Cryptologia article is behind a paywall, so in this article we’ve summarised the key points, for anyone who wants some more detail.

The background

Our involvement with the Voynich Manuscript started when Gordon needed a test of concept for the Verifier method that he had developed with Jo Hyde, for detecting errors in previous research into hard, unsolved problems.

The Voynich Manuscript is a book in a unique script, with odd illustrations, which had previously been believed to be an undeciphered text, either in a unidentified language or in an uncracked code. There were serious problems with both those explanations for the manuscript. If it was an unidentified language, then it was an extremely strange one. If it was an uncracked code, then it was either astonishingly sophisticated, or was based on a very unusual set of principles. The third main possibility, namely that the manuscript contained only meaningless gibberish, had been generally discounted, because there are numerous odd statistical regularities in the text of the manuscript, which everyone believed were much too complex to have been hoaxed.

Gordon’s work showed that this belief was mistaken, and that the most distinctive qualitative features of the Voynich Manuscript could be replicated using low-tech hoaxing methods. This resulted in an article in Cryptologia in 2004.

Gordon’s initial work, however, did not address the quantitative statistical regularities of the text in the manuscript.

Our recent article in Cryptologia addresses this issue, and shows how the most distinctive quantitative features of the VMS can be replicated using the same low-tech hoaxing methods as Gordon’s previous work. These features arise as unintended consequences of the technology being used, which produces statistical regularities as unplanned but inevitable side-effects.

Taken together, these two articles show that the key unusual features of the Voynich Manuscript can be explained as the products of a low-tech mechanism for producing meaningless gibberish.

New Hyde and Rugg website

By Gordon Rugg

The new version of the Hyde & Rugg website is now live, here:

http://www.hydeandrugg.com/

Among other things, it contains a resource section which pulls together our articles on a range of topics, including academic craft skills for students, elicitation methods, requirements, design, and education theory.

There’s also a section about our research, plus a section on the codes we’ve worked on. Again, these pull together our previous blog articles into a structured framework.

Over the next few months, we’ll be adding more material, particularly in the sections on academic craft skills and on our research.

We hope that you’ll find the site a useful complement to this blog.

 

Doomsday predictions as expressive behaviour

By Gordon Rugg

There was a classic article on Pharyngula recently about a group who donned bright yellow t-shirts to announce the imminent end of the world. It’s far from the first time that this announcement has been made; it’s probably not going to be the last.

So why do people keep making this announcement? Do they really believe that this time is going to be different, or is there something deeper going on?

As you might have guessed, usually there’s something deeper going on. The same underlying principle crops up in a wide range of forms, and is particularly prominent in politics, where it can cause a lot of problems.

The explanation begins with a topic that we discussed recently on this blog, namely expressive behaviour. It then moves on to systems theory, luxury, sex and power. The end of the world is a fine, rich topic…

http://freethoughtblogs.com/pharyngula/2015/10/07/they-had-t-shirts-made/

Originally posted on: http://www.rifuture.org/world-ends-today-see-you-tomorrow.html

(Image used under fair use terms, as part of an academic article about background theory.)

Beyond the 80:20 Principle

By Gordon Rugg, Jennifer Skillen & Colin Rigby

There’s a widely used concept called the 80:20 Principle, or the Pareto Principle, named after the decision theorist who invented it. It’s extremely useful.

In brief, across a wide range of fields, about 80% of one thing will usually come from 20% of another.

In business, for example, 80% of your revenue will come from 20% of your customers. In any sector, getting the first 80% of the job done will usually take about 20% of the resources involved; getting the last 20% of the job done will usually be much harder, and will take up 80% of the resources. The figure won’t always be exactly 80%, but it’s usually in that area. Good managers are very well aware of this issue, and keep a wary eye out for it when planning.

Here’s a diagram showing the principle. It’s pretty simple, but very powerful. However, that doesn’t mean that it’s perfect. It can actually be developed into something richer and more powerful, which is what we’ll describe in this article.

200 posts and counting

By Gordon Rugg

Our earliest posts included a lot of tutorial articles about specific concepts and methods, such as graph theory and card sorts.

Our more recent posts have increasingly often featured broader overviews, and demonstrations of how concepts and methods can be combined. This has included a fair amount of material on academic craft skills, where we’ve looked systematically at how to turn abstract academic concepts such as “good writing” into specific detail.

We’re planning to continue this move towards the bigger picture in our posts over the coming year. We’ll look at how formalisms from knowledge modelling can make sense of a range of features of society, including belief systems and organisational systems.

On a more prosaic level, we’ll continue our tradition of offbeat humorous articles.

In that tradition, the closing part of today’s article is this inimitable quote; we hope it brightens your day.

“I don’t play a lot of tuba anymore. It’s not the most common or useful instrument. There’s a reason there’s not a lot of tuba in a heavy rock and roll band. I’m just glad I was able to use it to help people,” he says.

“At the end of the day, I was just at the right place at the right time with a sousaphone.”

http://www.thedailybeast.com/articles/2015/07/22/meet-the-man-who-beat-the-kkk-with-a-tuba.html

Notes and links

There’s more about the theory behind this blog in my latest book:

Blind Spot, by Gordon Rugg with Joseph D’Agnese

http://www.amazon.co.uk/Blind-Spot-Gordon-Rugg/dp/0062097903

Overviews of the articles on this blog:

https://hydeandrugg.wordpress.com/2015/01/12/the-knowledge-modelling-book/

https://hydeandrugg.wordpress.com/2014/09/19/150-posts-and-counting/

https://hydeandrugg.wordpress.com/2014/04/28/one-hundred-hyde-rugg-articles-and-the-verifier-framework/