Kevin McConway is Emeritus Professor of Applied Statistics at the Open University in the UK, where he taught statistics, mainly to adult students in a wide range of disciplines. He has researched collaboratively across natural and social science. Kevin has developed a strong interest and involvement in statistics in the media. In particular he was as adviser for eleven years and an occasional contributor to the BBC radio program More or Less, which aims to support the public understanding of numbers in the news. He has worked with and helped train journalists in understanding and communicating statistics, often through the UK’s Science Media Centre where he is a member of the advisory committee. He tweets on @kjm2.
Episode Description
Talking about statistics with my journalism colleagues is the basis of what brings this show together. But speaking about, and communicating statistical work with journalists, and understanding our interdisciplinary relationship in the era of fake news and misinformation is more important than ever. That's the focus of this week’s episode of Stats and Short Stories with guest Kevin McConway.
+Full Transcript
Bailer
Talking about statistics with my journalism colleagues as the basis of what brings this show together, but speaking about and communicating statistical work with journalists, and understanding our interdisciplinary relationship in this era of fake news and misinformation is more important than ever. That's why we're delighted to have Kevin McConway as a guest on this episode of Stats and Short Stories. McConway is emeritus professor of Applied Statistics at the Open University in the UK, where he taught statistics mainly to adult learners in a wide range of disciplines. He developed a strong interest and involvement in statistics in the media, and was an advisor for 11 years and an occasional contributor to the BBC radio program, more or less. He's worked with and helped train journalists in understanding and communicating statistics, often through the UK science Media Center, where he's a member of the Advisory Committee. I'm John Bailer, and I'm joined by Rosemary Pennington and Richard Campbell, my journalism colleagues here at Miami University for this Stats and Short Stories conversation with Kevin McConway. Kevin, you've been involved with some fascinating work over your career. And you know, so now I got to know how did you get involved in this kind of structure, a science Media Center, and what led you to connect with the media and journalism?
Kevin McConway
Well, you know, there's a way in which I've kind of always been interested in statistics in the media. And early on in my career, I did write a couple of brief things for sort of journalistic articles. But it really, and I've often used journalism examples in my teaching to statisticians, but I guess it really got going. I think it was 2005. This was before the science Media Center. What happened is that the Open University where it where I worked, has a long term relationship with a BBC, because the BBC used to carry broadcasts around teaching in the early days of the university, you know, so there's been relationship going on for years, it's changed now, they don't carry our teaching now. But we do still make programs, we do still co produce some programs with them on the radio and on the television. And a lot of these things are kind of quite big budget nature programs, or programs for engineering. And what happened was, it was decided by a process that we should be doing more in radio to do with mathematics and statistics, maybe on TV as well, but it went into radio. And actually, me being the first one to suggest it, I said, Well, this is a great program, more or less about numbers just started off on radio four. And, you know, maybe we should do something like that. And the decision was not that we should do something like that. But we should co produce that program, we should provide some money and input into that program. And that meant that there had to be an involvement with the organ University. And that to be walked in the jargon was called an academic advisor. And I had to do that, because while I was asked to do that, nd, you know, I thought this is a great job, actually. So it started working with them. It was quite complicated at the beginning, because the university liked to monitor the scripts and check the scripts, but it's not it's not really scripted like that because there wasn't time for the Current Affairs program. But anyway, I kind of worked through that. And I worked with them in helping to check out ideas they had for programs, telling them where they might be able to find numbers, making suggestions for programs myself. And then if it was something I knew a lot about, or in some cases, it was something that nobody seemed to know anything about. I will be the person discussing it on air with the presenters. So I kind of did that. And in the end, I ended up doing that for 11 years, and I still work with him occasionally. Now, I only stopped because I retired from my full time post. So other people do it now. But because of that my interests have kind of grown, I started talking more to people who've been doing this kind of work in other ways. One that was David Spiegelhalter, who I've known for, you know, we overlapped in terms of doing our PhDs together a very long time ago. So I knew he was working on this, he'd moved to be the professor of the public understanding of risk. So I went and worked with him for a bit. I worked in Berlin and worked with getgiggle. Renza psychologists worked on this stuff quite heavily, and really got interesting ideas. And David was already working with the science Media Center. And he said, Well, you could work with the science Media Center as well. They always want people to write comments on pieces of research involving statistics that are coming out. Why don't you do that? So I started doing that. I think it was 2011. And what the science Media Center is, it's kind of strange. It was set up in 2002. If I remember rightly, in the UK, partly because there was a lot of what was seen as bad reporting of science going on at the time, things to do with MMR and autism was just one of the examples that was happening Roundup. of time. And the decision was to set up something which was eventually turned into what's a sort of independent Press Agency for science as a whole. And it tries to collaborate with the media, it to get scientific ideas to get scientists, including statisticians, David Lee, quite a few of us to talk to the media in ways that will help the media, it helps trained scientists in in collaborate with the media does some media training itself, and things like that. And I think it's had quite a lot of influence in improving the reporting of science in the, in the main media in the UK, I'm talking here about the main daily newspapers, the main broadcasters, not so much impact in other areas, but that's what it's done. And over the years, I've kind of got more and more involved with that I'm on their Advisory Committee, and, and so on. So I do a lot of work with them, it's how it used to work in the past. It was really quite nice, because what would happen would be somebody do a bit of research, somebody would decide to press release this research, it'd be under embargo. And therefore you might have to two or three days to read the paper, figure out what they were going on write something saying this is a complete rubbish or this is really good, whatever it was, and, you know, put in some nice personal quotes, everything, send it off, and, you know, that would have an effect. Of course, since there are more and more preprints these days, this gap where there's an embargo doesn't happen. So you find that you have to churn the stuff out at an enormous rate. I mean, some of these comments are right, they're not just like, two or three sentences, you know, they can be 2000 words or more. And, you know, usually then maybe 1000 words, and you have to churn out 1000 words in an hour, and ish. Otherwise, the journalists have written their story, because of the fast turn of news. And it's quite hair raising stuff at times, and you do get things wrong, but hopefully not very often.
Pennington
I wonder, how do you think social media has impacted the space of communicating stats and science? Because I think you, you are sort of talking about journalistic deadlines, and how, with the Science Media Center, that can sort of put you in a tough bind. And I wonder, if social media and the ability for things to sort of circulate very quickly, has also sort of complicated this work of communicating statistics to journalists, clearly, but also to a broader audience more clearly?
Kevin McConway
I think it has I mean, I really don't know how many regular people out there read all the tweets of God about about statistical topics, but I know, it's not just one or two, you know, they really are quite heavily read and, you know, similar things on Facebook and things in close Facebook groups where you don't even know what's going on, you know, this, this, this whole goes on. And I think that means, I mean, what I've observed for journalists is that they need to take this into account they need, you know, if they're writing about something, they need to say, look, you might have seen this on Twitter. There's another point of view on this, from such and such a person. And all they can tell you about where that where it is, is to point to a tweet that this person made. And just putting all this together is just really complicated. I mean, I mean, that's one reason why I think, long form journalism that manages to write decent long stories and put all this stuff together is great, but you know, that doesn't always have a huge audience. And you know, most people are seeing the three minute report on the TV news, or reading a tweet completely out of context and getting it wrong. And I mean, I can't wish this hasn't hadn't happened. I mean, it has happened, that's the world we're in. And it's great that this stuff gets communicated so quickly, but it makes life harder than it was.
Bailer
So I have a sort of last question to wrap this up. So you know, I work with these journalist types you know, and you know, we've we've come to some we've come to some cultural agreements here we've we've found common ground that actually what you're talking about, actually a journalist? Yeah. No, she could have said that you don't know what you're talking about. John, that may be his. But this has been a great I, you know, I've learned a tremendous amount from my colleagues. And I think a lot about what kind of what they value and how they frame stories. And it's really helped me think about this, I guess I'd like to close our short story here with you, you kind of giving us your own perspective on some of the difference sort of the Compare and contrast paper that you would write about status systems and journalists, what do we what are some of the things that you see is very strong connections and similarities? And what are some of the differences?
Kevin McConway
Right? Well, I mean, probably the main similarity is that there are very different ways. Actually. What we want to do is to get at the truth or rather, that's what most of us want to do. And you No, there are times when, if I talk to colleagues, statisticians, they just go on about all journalists addressing a whole bunch of liars. They just want to get their own point of view across whenever they don't want evidence of it getting a bite in the leg. And that is that I mean that in my experience, certainly for Health and Science journalists, at least you know, the ones I've worked with most, that's simply not true. They get embarrassed if they find out about getting something wrong, they really do want to get things right. But there are important differences as well. I mean, one difference, I think this is less marked than it was. And that's great. Obviously, statisticians are where numerous journalists are, on the whole not so numerous. And I think there are some problems in general journalism training about journalists, not just not learning enough about how the most basic numbers get put together. I mean, some of the things that even quite eminent journalists have, sort of demonstrate their own resume by numbers are quite, quite hair raising, you know, they don't understand percentages. But let's not let's not go into that. They can be told they want to learn. But journalists are better at telling stories, I mean, statisticians ought to be good at telling stories, because that's what we do when we're collaborating, you know, with scientists in other areas, you know, this is a story I see coming out of the data, and this fits into what you're trying to see. But actually, what most of us aren't that good at it, and journalists are journalists who can get stuff into a small space. And we ought to take account of that. I mean, there's also the question of deadlines. You know, I mean, we have deadlines in statistics, you know, for heaven's sake, I got to finish this data analysis by two months from now, or I have to do this peer review. And, look, they've only given me a month, or, or, or these days shorter and shorter, maybe only a fortnight, you know, they get done. But journalists, it's no, if I don't get this thing out in an hour, or by tomorrow morning, or something, it's not going to appear. And we have to learn to cope with that, because there's nothing we can do about it. It's just the kind of work given of the work. But I mean, I think the main thing is we just have to listen to each other, we have to, we have to understand more about the conditions under which we, we both work, because they are different. But as I say, I think we have the same aim of wanting to get evidence based information across to other people. That's why I do it.
Campbell
That's brilliant. I would also add, John, I would add to that one thing that I've learned from working with John over the years, there aren't very many professions that I would call the generalist professions, you have to know a lot about a lot of different things. And I think that's one thing that I've found is similar between statisticians who work on a lot of different projects that are very, very different. And journalists who are often asked to do stories about things they know nothing about, and they have to research and do them. I think in an era where we're so dominated by specialists, it's important to have these professions that talk to each other and, and are interested in kind of working across boundaries.
Kevin McConway
I absolutely could not agree more. I mean, I mean, does this fit in with this famous thing that John Tukey said it was allegedly said, the great thing about being a statistician, you get to play in everybody's backyard. And you know, that is why I'm a statistician. I can remember once, because of the Open University, if you're on the faculty, you can study courses for free, and I want to take a philosophy course. And the philosophy tutor started by saying, Oh, it's great. The great thing about being a philosopher is you can be in any part of the library, and you're working. And I thought, Well, yeah, and if you're a statistician, you can be in any part of me, there's a few years ago, when people still have libraries, you can be in any part that I be, you can be in anybody's lab, you can be in anybody's field site, you know, wherever you be in space for heaven's sake, and you could still be working and you never get bored. I mean, thanks. That's great if I didn't have to, I've talked to journalists, and they say, the good thing about journalism is, yeah, you get to specialize in something, perhaps. But actually, it's changing all the time, you don't get bored. And that's one thing that we applied stoicism to journalists very much do have in common. And I think that's why once we get to know each other, we get on it.
Bailer
Well, that's a beautiful place to bring us to a close. Well, you know, that's all the time we have for this episode of stats and short stories. Kevin, thank you so much for being here. Stats and Stories is a partnership between Miami University’s Departments of Statistics, and Media, Journalism and Film, and the American Statistical Association. You can follow us on Twitter, Apple podcasts, or other places you can find podcasts. If you’d like to share your thoughts on the program send your email to statsandstories@miamioh.edu or check us out at statsandstories.net, and be sure to listen for future editions of Stats and Stories, where we discuss the statistics behind the stories and the stories behind the statistics.