Comments for Thandi: Week 2


Should psychology be written for the layman or should science be exclusively for scientists?

There have been times over the past two years when I’ve read a psychology article or piece of research and have barely been able to understand a word of it. Indeed scientific work in general often seems to be written in a code only decipherable to experts in that field; (the work described here is barely even English:  something that I think could limit science in the long run and may also be partly responsible for all those media misunderstandings we heard about in the semester 1 blogs. That is not to say, however, that current styles of scientific writing should be removed, as they serve an important function in the scientific community.

One of the chief functions and ethical responsibilities of scientific research is to conduct research that will benefit society and add to the sum of human knowledge. Surely then, scientific knowledge should be made available to everyone. But all too often the theories are presented as being far too complicated for the layman to understand, which limits scientific knowledge to the privileged few. To be fair it would be unreasonable to expect someone with no scientific background at all to understand string theory if we just simplify the explanation. But on the other hand excessive use of incomprehensible language promotes academic snobbery and may be off-putting for laymen, thus limiting future public interest in the subject. Also, keeping science exclusively for scientists is likely to foster mistrust in science as a whole (for some reason I’m imagining a strange Orwellian dystopia, where all science has become a cult, and knowledge is only given to initiates deemed worthy/intelligent enough by a higher power….. oh wait, things are already like that). Anyway, with the spreading use of jargon in scientific papers is it any wonder that the public and media often have wild misconceptions about science? (

Every subject develops its own specific language over time; composed of jargon, abbreviations and references to well-known theories or discoveries from within that field; and this development is inevitable. While it may seem incomprehensible to an outsider (I doubt I would be able to make much sense of a paper on seismology, even with Google and Wikipedia on hand) most of these abbreviations and suchlike have usually been created to make published work easier to read and understand for other scientists in the same field. Imagine, for example, if all neuropsychological papers had to include the full names of brain regions. Having to write out ‘posterior region of the superior temporal sulcus’ in full every time you wanted to refer to that area would not only make papers a pain to write, but also make them extremely heavy reading for other researchers. Scientific writing is designed to communicate complex scientific ideas to other scientists in an effective and understandable way; and in that respect I believe it has definite value.

In my opinion, writing papers that are aimed at an audience of experts is absolutely fine and often completely necessary in order to communicate theories effectively and enable scientific progress. HOWEVER, I also think that this information should also be readily available (and understandable) for the layman). Magazines like New Scientist publish research in a way that is accessible for non-experts; and there are many internet sites (e.g.,, that discuss theories and research in layman’s terms, without sacrificing the more complex concepts on the altar of simplicity. Also, thanks to sites like this one: even creative writing students can sound like experts in psychology!

Things I write when I can’t think of a specific topic

In a 2010 TED talk, Michael Shermer spoke about self-deception and belief; specifically how the human race seems hardwired to see patterns in the world around us (  Our brains can interpret random patterns into coherent shapes, for example the Rorschach inkblot test or hidden object illusions such as: Shermer theorises that we may be evolutionarily predisposed to see patterns in the world around us, as such a skill would help us survive in a possibly hostile world. For example; learning to be cautious when we hear a rustle in the bushes as it might be a predator is far less costly than assuming that it’s just the wind and only finding out its a predator when we’re just about to be eaten. Or: if there is food on this tree now, there may be food on similar trees; or on the same tree next year etc. Thus our pattern seeking tendencies can be of great benefit to us; they can help us learn, make connections and (as Fay taught us last semester) allow us to make schemas so we can navigate the social world smoothly.

However this tendency to see patterns can lead us astray. As Shermer examines in his talk, pattern-seeking can lead to superstitious beliefs, paranoia or simply drawing false conclusions. This last one is particularly important to us as science students as there is always that temptation to infer a cause-and –effect relationship. Of course we get taught that we must very cautious about this, but then we also get taught that if p<0.05 then we can reject the null. YAY! The problem is that scientific investigation is almost like a high-tech extension of our innate pattern-seeking behaviour and is, in some ways, just as fallible to false conclusions as we are in our daily lives. There is a trend in science to rely on statistical significance a little too much when all it really says is how likely it is for something to have occurred by chance. But we, as the great pattern-seekers of the world, have a tendency to forget that a p value of 0.05 could mean that whatever happened is just an extremely improbable fluke.  Critics of the overuse of statistics in modern science have found many instances where a significant result has been accepted wrongly and too readily by the researchers and sometimes the scientific community in general (

While I support the use of statistics in science, I do think that our desire for patterns and connections in the world can lead us astray; and we should be very careful not to let a significant p-value become the statistical equivalent of superstitiously touching wood to guarantee good luck.


(Watch the TED talk guys, its a lot better than this blog, I promise!)