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A rough version of a talk I’m doing at uni. Thought I’d try out recording it. Thoughts?
The journey continues. After reading “What is this thing called science” by A. F. Chalmers, I got a rush of blood to the head and decided to take the plunge. It is fascinating stuff, and what is particularly interesting to me is that, as a geologist, I was born just after probably the most significant revolution in geology of all time – the plate tectonics revolution. It is an amazing story of the progress of science, one that should be told and analysed more (and if I have the time, I will!)
So now, the history and philosophy of science is firmly on my agenda. Here’s the recent additions:
Karl Popper, The logic of Scientific Discovery
Thomas Kuhn, The Structure of Scientific Revolutions
Paul Feyerabend, Against Method
The astute reader will note the lack of Lakatos here. My mistake, let me get through these three first…
Also, this may take me a while – lacking a formal education in philosophy, some of these folks can be quite obtruse… but you get there in the end…
In the coming month I will be producing a short film profile of Gary Cass, a scientific researcher in the soil science/agriculture section of the Faculty of Natural and Agricultural Sciences at the University of Western Australia where I am studying a Masters in Science Communication.
Red Wine Dress, Micro'be. Photo Ray Scott, courtesy of Bioalloy.org
He is famous for the Red Wine Dress. He used to work in a vineyard and he noticed a thin film of slime that developed on red wine when Acetobacter infected it and turned it to vinegar (a wine-maker’s worst nightmare). Being an artistic person, he wondered whether it would be useful as a fabric. The film was in fact threads of nanofibre-scale cellulose that is the ‘poo’ of the bacteria. So he got together with an artist and developed the world’s first “Red Wine Dress”. As creative as that was, what he’s realised is that the same cellulose fabric is potentially useful in other applications. He’s now involved in further research into these materials.
The great thing is that all you need is wine, sugar and the bacteria to produce it. It can even be used to produce biofuels. In other words, we could have a multi-use biofuel technology – wine, fabric and fuel all from the one crop. It’s far more land efficient than sugar cane for instance. The spooky part is what a colleague of his is doing in the States – he’s taken gene’s from the Acetobacter and put them in cyanobacteria, so now these little bugs photosynthesise to produce the same cellulose. All they need is water, sunshine and carbon dioxide!
I spoke to him yesterday and he is passionate about creativity in science. One of the things he does is teaching at a school here, Shenton College. It’s a program he developed where he gets the kids (year 11s) to learn earth history, biology and genetics using artistic methods. So for instance, one kid coded a musical score from his basic DNA sequence. Another group of girls put the process of abiogenesis to dance! The reaction has been very positive and he’s now getting international attention for his approach. He thinks that creativity is an essential part of scientific progress (really shouldn’t come as a shock to anyone, that, but it does challenge traditional ideas) and that for too long science education has stifled that. Art is a natural medium to reintroduce it, and the strong boundary between art and science has been unnecessarily created. He struggles somewhat with the question of whether he’s an artist or a scientist! He did agree however, that really it’s depends on the work he’s doing – when testing hypotheses, he’s a scientist, when developing creative ideas, he’s more of an artist.
My film will be a profile of him with a focus on the Shenton college program, with some background about the red wine dress.
A few links about him:
http://www.news.uwa.edu.au/business-briefing/grow-your-own-dress-uwa
and here’s a little film about an exhibition with him: http://www.youtube.com/watch?v=f-F2RD1KZT4
his website: http://bioalloy.org/o/ and particularly the dresses: http://bioalloy.org/o/projects/micro-be.html and the evolution pages: http://bioalloy.org/o/projects/bioalloyevolution.html
I am interested in the information that is lost as scientists proceed from experiment to publication. The real factors that slip through the cracks of expediency. What is more important in the communication of research, the method, or the factoid results that come from it? Are we too trusting in the scientific method? Has peer-review become a substitute for a wider interrogation of method?
These are just a few questions going through my mind as I read “Simplification in Scientific Work: An Example from Neuroscience Research” – a 1983 article by the late Susan Leigh Star. I was particularly struck by an early observation in the article that “published scientific conclusions tend to present results as faits acomplis, without mention of production of decision-making processes.” I am not sure that this is so true today, but I am intrigued by the possibility that it is exactly that loss of information (as research is presented with a higher degree of ‘granualrity’) that opens a door for skepticism in the wider community. When a large body of research by multiple scientific schools tends to agree on a matter, there is sometimes an impression given that they are all doing exactly the same experiments. Whilst the broad methods are the same, of course expedient decisions are made and this causes subtle differences. These are not always thoroughly explained, even if they are justified. I can’t help but think that something in this is relevant to the skeptical program in climate change. Is this what lets in the calls of “conspiracy”?
More to read, more to do. I have a few other things on my plate, but this is an intriguing line of research.
When you think of a scientist, you probably imagine a person dressed in a white lab coat, wearing thick glasses and adorned with white, straggly hair. Perhaps you think of Albert Einstein. The reality is quite different; scientists, overall, do not conform to this stereotype. They do not have a particular uniform, and they do not wear a badge. What makes someone a scientist?
The answer is in the way they think. They employ “the scientific method”. But what is the scientific method? The concept really boils down to a way of formulating ideas and testing them; a way of explaining the world through systematic observation and hypothesis testing. In short, a way of telling reality from fantasy. Read the rest of this entry »
One of the great frustrations in science is getting good data. Collecting it yourself can be a boring, longwinded and seemingly pointless exercise, especially if you are collecting data on multiple variables when you know you’ll only use a few (a common thing in geology). Getting legacy data from others can be even harder. Incomplete data sets, different files, wrong formats, wrong headings etc etc… These are all issues we face. However, having complete data is golden – you don’t want your work usurped by another on the basis that they had more complete data and so could see the real picture.
So it seems in the climate change debate, we now see a real problem emerge. One that actually does cause a few problems for the climatologists who have provided the evidence for “AGW”. New Scientist recently published a piece correctly (in my opinion) highlighting this as a significant concern, but one with some seemingly intractable barriers to resolution. Large chunks of important data are sitting with commercial rights within the vaults of institutes around the world. Governments would pay penalties for their general release. This is not good for the science and only fuels speculations from the deniers. It is indeed a pity that the deniers can’t get their hands on it because then they could do the same tests and come to conclusions that add to the debate. However, all this should not be mistaken as a conspiracy – it is normal in many scientific fields to have data sets locked up under commercial arrangements (or government legislation). Science has worked around this for years and continues to do so. Climate science itself has worked successfully under this regime too. Perhaps this is just another storm in a teacup.
We’ve had government bailouts for banks, perhaps its time for governments to put some money and legislation behind freeing up these data sets completely. Pay-off the commercial interests, legislate for data freedom. It would be a nice shot in the arm for a needlessly troubled science. I suspect only the deniers have anything to fear.
There seems to be a common thread amongst sceptics out there that science is done via something that looks a little like the Council of Nicaea. That is to say, that a committee of scientists decides what is “doctrine” before instructing publishers what to print. There is confusion between the ways the legal system (or political system) works and how science works.
Lets have a look at some typical tasks in a scientist’s professional life:
1. Data collection. This can be the longest and hardest (and most boring) phase. This is where hours are spent over test-tubes, or, in my case, hours in the hot sun staring closely at rocks. Whilst you may be thinking about the end-game in this phase, the task is usually so routine that bias hardly exists (if it does, it is because the method itself is biased, or you’re just sloppy). Actually, there will be mistakes, but these tend to revert to the mean, so will be cancelled out in the final analysis.
2. Hypothesis generation. I put this after data collection to bait some people, but actually, it has to be said that hypotheses are generated throughout the scientific process. The important thing is that you are only testing the original hypothesis whilst conducting an experiment designed to test that hypothesis. Other ones must wait for other experiments. There is no harm in “hypothesis-driven research” – this is what science is. However, this is different to biased research driven towards a pre-determined conclusion. Note the difference – a hypothesis is actually tested, a pre-determined conclusion is circular.
3. Data analysis. Here comes the statistics. So you have the data, and you see patterns. Are they significant? This is a technical, statistical question that determines whether you can use your data (gathered in 1. above) to test the hypothesis (2. above). If there is no significant result, then there is no support for the hypothesis from your results. THIS DOES NOT MEAN IT IS DISPROVEN. It is more like an absence of evidence, which, as the saying goes, is not evidence of absence. If the results show a statistically significant result, then you can compare it with your hypothesis. Now a hypothesis can be disproved – proposing that the sky looks blue and finding it to look green would be an example. Unfortunately the opposite does not apply. If your result concurs with your hypothesis, it lends support to it, but does not prove it. It can never prove it due to a quirk of inductive logic that demonstrates that no matter how many positive examples you show in support of a proposition, since the set of possible examples is infinite, you cannot rule out a counter-example emerging next. Which is quite different from the deductive logic of mathematics, where 2 + 2 = 4 as a result of the system itself.
To make a long story short, the last juicy step is publication.
Now you run into trouble. You’ve done your experiment, and supported your brilliant earth-shattering hypothesis. Will anyone believe you?
To find out, you detail your method (and the back story – why you felt it worthy of research) and your results and a bit of discussion on what it all means. Then you send it for peer review. This is a blind (well semi-blind – sometimes people work out who the reviewers are) process where your reviewer doesn’t know who wrote the paper and is asked to appraise the science, comment, and put their opinion on whether it is fit to publish. Most papers fail this test on the first pass, and the majority never make it to publication. What tends to define success is that the paper details a properly conducted line of research taking into account previous work in a similar field. Failure in peer-review doesn’t mean that there is a conspiracy against you – it usually means your paper is either not relevant to the journal in question, or that you need to write up your science better. Without peer review, this statement cannot be made with any certainty about a paper.
Also, consider that how the media treats science is not the same as the science itself. Science is only balanced in its reporting in so far as it “objectively” reports the outcomes of research and the opinions of researchers. So 90% of scientists might agree with a broad-based position, but it only takes one from the 10% to balance a journalists report – giving a 50/50 impression. Note also the diversity of opinion that will lie within the 90% who agree – these people do not speak to a common mantra, they merely assent to certain generalisations.
So next time you see controversy about methods and “conspiracies” to promote one “side” of an argument over another, consider the above and consider that most scientists are too busy with the steps involved to also hold some sort of cabinet meeting on how to bend the entire scientific community. After all, that would be like herding cats.
