Science is one of those topics which is (interestingly) one of the most popular and interesting topics to the general public, this has been reflected by the introduction of “science”, “environment” “tech” and “health” sections in most national news outlets; from The Guardian to the BBC, and from the much maligned Fox News Network to the New York Times.
However as eloquently explained by Bora Zivkovic (community manager at SciAm blogs) in his christmas extravaganza blog post, even after the return of a conversational vibe with the internet, everything is to play for with respect to science journalism. We’re emerging from a dark age into a new enlightenment; one that will require a re-defining of the role of journalist.
What can be said about modern science journalism is that some do it very well, and others very, very badly (hence the bad reputation of Fox News on climate science, and the BBC’s false objectivity). Here are two articles, one from my local student newspaper’s science section and one from the BBC to illustrate the point:
I’m not going to say which is good and which is bad, but hopefully by the end of this article you will have some idea of what I think, the question is whether you agree*.
So what should the budding science journalist be avoiding like the plague? There are a great deal of things that you could and should be careful with, but sometimes flirting with them can produce a better article than if you don’t… so what are the cardinal sins?
Misrepresenting the Literature
This is cardinal sin number one; the scientific consensus represents humanity’s best guess at the answer to a set of problems and it is as close to the “truth” as we can get given the data available. The literature might well say lots of different things, but you can be almost certain that there will be one “general direction” in which the current of scientific thought is flowing. If the paper you are reporting disagrees then say so; but in science reporting context is King… without it you are no better than the man who stands around with the “The End is Nigh” sign… a dark age apothecary or dare I say it; The Daily Mail.
A classic example of this misrepresentation is the infamous case of MMR and Autism, where even today anti-vaccine groups are touting the findings of two pieces of research, both by one man, who was paid by biased legal interests to fix his results. For over 20 years the current of scienctific literature has flowed against his findings, saying there is no link between MMR and Autism, but repeatedly it gets reported as undisputed fact.
Another is the Climate Change denier’s claim that “in the 70’s science said we were entering an ice-age”. In fact, global warming has been on the table since the 50’s. It’s always been there, with a small number of papers in the 70’s indeed arguing for an ice-age with different data, but this blip disappeared with more data, and now science has crystalised around global warming and anthropogenic climate change.
It is quite rare that something comes along and causes a paradigm shift, causing science to literally be turned on its head. It is even rarer that this happens with one piece of research or a single piece of thought. Remember this, not everything will change the world tonight, most things will do it slowly, over time, and with help from the rest!
Thid is another BIG one, and it is fairly similar to misrepresenting the literature, don’t say the data shows something when it doesn’t, that is a bare-faced lie. Equally don’t say “temperatures cooled between 1995 and 1996 so global warming is false” if in the ten years preceding 1995 and post-dating 1996 show increases in average temperatures, that is worse than lying outright, because you are taking someone elses hard work and misrepresenting it. Where an outright lie is often easily checked and spotted, data mining gives someone a tangible focus and can give the lie a credibility it doesn’t deserve.
Similarly do not use a quote from someone that has been cut to agree with your agenda.
i.e.: if scientist A says:
“some say there’s probably no life in the universe, but we think they’re wrong and we think we know where to look”
DO NOT write :
“”No life in the universe” -said scientist A”
The scientific method calls for objectivity (or a lack of bias), as a scientist you have to try and avoid influencing the result of your experiments, when you publish a scientific paper you are forced by many publishers to declare any biases. After all if a paper about how good or bad smoking is for you is funded by a tobacco company, it may be less reliable than one that is funded by the public purse (taxation).
This can go too far though when it comes to journalism, where every view is given equal weight because the news outlet doesn’t want to offend anyone or get sued, this is often the case with BBC reporting in science. If you are afraid of getting sued because you present the scientific truth, perhaps you should consider reporting something other than science. Science doesn’t care about bias and false objectivity, it states the facts and presents the current consensus, however uncomfortable it may be for some people to hear.
Politics, Opinion and False Motive
Science doesn’t care how uncomfortable the facts are, but equally it remains unbiased when it tells them. If you are against homeopathy; science is on your side, but that doesn’t necessarily make practitioners of homeopathy liars or theives. Similarly if you are against climate change; science is against you, but that doesn’t make science a “left-wing-conspiracy” and doesn’t make the scientists liars and conspirators. Political opinion should remain squarely in the politics section, that’s why your news outlet has one, assigning false motives is something for the lawyers and reporting crimes, not science.
This emphatically does NOT mean you cannot have or express an opinion. You just have to be very, very careful about how you go about it, phrases like “I think” or “in the reporters opinion” exist for exactly that purpose, but beware the reader may disagree, possibly vehemently.
Statistics are hard, in my opinion they’re probably the hardest thing anyone has to get their head around when it comes to doing or reporting science. Benjamin Disraeli once said “there are lies, damn lies, and statistics.” He was right. If used correctly and chosen well a statistic can be the easiest way to convey something complex or nuanced. If chosen badly or misunderstood, muddying the waters and misrepresentation is inevitable.
Do you really know what “statistically significant” or what a “high p-value” is and what it means? If not then look it up, check what you’re going to say and if still in doubt, ask someone who knows how they work. Remember that there is never such a thing as a stupid question!
Hopefully this has all made sense to you, and as always I welcome any coments, criticisms and suggestions for rewording and things I need to add. I look forward to reading a lot of awesome quality science journalism in the future, not that I wouldn’t have done if I hadn’t published this!
Short-Link for this post: http://wp.me/pFUij-9d
*N.B: I think the dud article is the BBC one, further explanation at the blog “looking out to sea”.
Peterson, T.C., Connolley, W.M., and Fleck, J., 2008,“The myth of the 1970’s global cooling scientific consensus”, Bulletin of the American Meteorological Society, DOI:10.1175/2008BAMS2370.1
Zivkovic, B., 2010, “Observations: The line between science and journalism is getting blurry….again“, Scientific American, [ONLINE] Available: http://www.scientificamerican.com/blog/post.cfm?id=the-line-between-science-and-journa-2010-12-20