
The NHS in England has missed its four-hour A&E waiting time target with performance a...
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Thank you for downloading the More or Less podcast from the BBC. Statistically proven to be the very best numbers programme around. This is the extended edition of the programme first broadcast on BBC Radio 4. Hello and welcome to More or Less, the programme which resolves each year to cut down on unhealthy junk news and eat more tasty and nutritious statistics. This week, cancer. Huge BBC mistakes about inequality, NHS waiting times and statistical whoppers that are true but deeply misleading.
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Six hospitals declare major incidents amid the
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worst A and E waiting figure times for a decade.
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This week, NHS England published figures that revealed it had missed its four hour accident and emergency waiting time target. That's bad news in itself, but the numbers were particularly troublesome, with performance dropping to its lowest level for a decade. Well, the news prompted many loyal listeners to write to more or lessbc.co.uk to ask US questions, such as this one from Rachel.
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Have you considered looking at the reporting of the latest NHS winter crisis?
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There are lots of percentages being bandied
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about without any contextualising numbers, so it all feels pretty meaningless to me.
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Well, the government target used to be that 98% of people attending AE should be seen in less than four hours. It's been relaxed to 95%. But nevertheless, the NHS is still missing the target. In the Period October to December 2014, only 92.6% of people attending AE were seen within four hours. So why? What's going on? Various reasons have been mooted for the drop in performance and I put some of them to John Appleby, chief economist of the King's Fund, which is an independent health think tank. And my first question, suspicious fellow that I am, is exactly how is your weight at AE measured?
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When you go into an AE department, as soon as somebody sees you, a clinician, a nurse, the clock starts and they'll note down the time and that goes on your record. The clock will stop when you leave the AE department and you can exit the AE department in various ways. You can go back out the front doors, you can just go back home. You could go back home, but with a recommendation to see your GP, or you could be admitted into hospital. And about 20% or so of all people who go to A and E departments end up being admitted into a hospital bed in the hospital, and at that point the clock stops.
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The target's being missed quite widely now. Why is that?
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One explanation is that there's a lot of demand, there are a lot of people walking in the front doors or being carried in the front doors of AE departments and AE departments are having trouble coping with that number of people. And that will be part of the explanation. But interestingly enough, there are more attendances at AE departments in the summer than there are in the winter.
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But we don't have summer AE crises.
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We tend not to. No, we tend not to. The patients who are using AE in summer and winter there are slightly different proportions of patients, so that'd be another factor is what type of patient is using AE at different times of the year. In the summer, there is a tendency for them to be slightly less elderly people using them and proportionately more younger people. The problems tend to be less acute in winter you've got elderly people using AE more. It's not like Arthur Bobbins, 10 year old with a saucepan stuck on his head, sort of view of AE user. It could be an elderly woman with a broken hip with dementia and diabetes and various other problems. So more difficult cases.
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That's more representative of a winter case and that. And that's harder to deal with and
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more likely to be admitted into hospital. So whereas across all patients, it's about one in five will be admitted into hospital for further treatment as an emergency case, if you're over 65, it's 50%. It's an indication of more serious cases.
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And I understand how that would explain why you have winter A and E problems and you don't particularly have summer AE problems. What I don't understand is why the problems seem to be worse this winter than they were last winter or the winter before or the winter before that. What explains that difference?
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AE departments are not isolated, they're not sort of standalone units without any connection to other parts of the hospital. So in terms of people getting out of AE departments and into other parts of the hospital, that depends on what's going on elsewhere. Have we got more elective patients, that is non emergency patients using beds in hospital? Are beds being. I hate this phrase, but being blocked by patients. It's known as delayed transfers of care. We know delayed transfers of care have gone up. That's going to mean there are fewer beds in other parts of the hospital or there'll be pressure on those beds that can back up into the AE department for those patients who are waiting to get from AE into a bed in hospital.
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So there's this story that's told that funding has been cut for social care and that means that it's hard to discharge elderly people into the community because there's no one to look after them. Do you think that that story Is true?
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Yes, I do. Again, it's part of the sort of set of factors. The official figures on delayed transfers of care do try to break down the reasons for delays. It's partly pointing the finger of blame, if you like. About two thirds of them are actually to do with the NHS itself. There are problems there with handing over patients from one clinician to another or whatever, but there is a significant number where there has to be a care package put in place, put together by social services and social workers and so on.
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Do you think that any of this is just bad luck? You know, worse seasonal flu or worse weather or something like that, in terms
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of illness and the weather? Well, I don't know about you, but in my garden I've still got snapdragons which are still blooming from the summer. We haven't actually had a severe winter yet, and we may yet do. Historically, the real problems for the NHS in terms of AE and emergency don't come around Christmas. They're actually in towards the end of January and into February.
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So we've got a lot to look forward to.
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Well, we've got something to look forward to, yes.
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John Appleby of the Kings Fund this week on BBC2. Never before has money been so polarised. 85 people now own half the planet's wealth. Yes, that was a trail for the BBC2 programme, the Super Rich and Us. And as soon as the trail ran here on Radio 4, loyal listeners began emailing us at more or lessbc.co.uk.
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on the trailer on radio.
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Just heard a trailer on radio.
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85 individuals, 85 own half the world's wealth.
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Did I mishear?
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Really?
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And, well, they might email because it's not true, is it, Keith?
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No, it's not true.
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This is Keith Moore, one of the reporters here on the More or Less team.
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So we looked at a similar sounding statistic about a year ago. The claim that the world's richest 85 people have as much wealth as the poorest half of the world put together. That's three and a half billion people. The claim was circulated by Oxfam and their underlying data came from a report published by Credit Suisse.
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And this is one of those claims that is roughly true, although it doesn't necessarily help us understand the world. And you can read more details about our quibbles via our website, BBC.co.uk more or less. But we don't need to get into that now.
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No, we don't, because the BBC trail is making a different claim. Let's hear it again.
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Never before has money been so polarised. 85 people now own half the planet's wealth.
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So while the original claim was that the richest 85 people have more money than the poorest half of the world, this new claim is that the richest 85 people have as much money as as everyone else put together.
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And it's that small change of wording which takes the claim from roughly right to completely wrong. How wrong?
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Well, global wealth is about $263 trillion. Oxfam reckoned that the richest 85 people had 1.7 trillion between them. That still leaves about 261 trillion for the rest of us. So the BBC trail's mangled statistic is wrong by a factor of more than 100.
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That said, global wealth is still very unevenly distributed. It's probably true to say that about half the world's wealth is held by the richest 1%. But that's not 85 people, that's 70 million people. And to be one of them, you don't need to be a multi billionaire. You need net assets of about £500,000. Now, that includes housing. So if your house is worth more than half a million pounds and you've got a small mortgage or no mortgage, congratulations. You are one of the global 1%. Thank you, Keith.
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Most cases of cancer are the result of sheer bad luck.
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That was the Independent, and headlines and news bulletins around the world just couldn't get enough of a new study of cancer published at the start of the year. But more or less listeners, Philip, Rhiann, Simon, Alex and David each raised a quizzical eyebrow, spotting that there was some confusion in the reporting. They asked us to investigate and we discovered that to understand this research, it helps to go back to basics. What is cancer? We asked PZ Myers, a biologist and associate professor at the University of Minnesota Morris in the United States.
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Okay, so cancer is actually a pretty complicated disease. I mean, there's a lot of different kinds of cancer, but basically what you've got is a set of cells that are undergoing uncontrolled replication and are often doing things like being invasive and penetrating into other tissues they shouldn't. So it's basically a small population of cells that have gone nuts and have decided to take over.
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Right. So what about this new research that says cancer is largely a matter of bad luck? It was published in the journal Science, and the researchers, one of whom is a very eminent cancer expert, Bert Vogelstein, are from the Johns Hopkins School of medicine in the U.S. sadly, they were too busy to hop on the Phone to us. But PZ Myers explained what he thought they'd found.
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What it showed is a correlation between the number of cell divisions to produce a tissue and the likelihood that it would become cancerous. So what we're seeing in this paper is a quantitative description of what proportion of the errors that lead to cancer are caused by cell division rather than other factors like environmental causes or genetic causes. Some tissues are fairly stable. So, for instance, muscle and brain tissue does not divide once it's done developing. So those tissues have a very, very low likelihood of coming down with cancer, whereas things like the lining of your intestine is constantly being regenerated and sloughed off. And so those cells have a high proliferative output, and they're much more likely to become cancerous.
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So what the researchers were trying to do here wasn't to say what determines why some people get cancer and others don't. They were instead asking why some types of cancer are common and some are rare. Why do lots of people get lung cancer, but few people get cancer of the leg? And the answer to that question is this issue of cell renewal, or more precisely, the randomness of cell renewal or cel gone wrong. And the researchers call this randomness bad luck. Now, there are bacterial or viral infections that can put you at risk of cervical cancer or stomach cancer. You might say that catching one of them was bad luck. And you might inherit a gene that makes you prone to breast cancer or colon cancer. You might say that was bad luck. But that's not what the researchers mean when they say bad luck. They just mean this issue of cell division gone wrong. Got it, Ruth.
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Got it.
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This is Ruth Alexander, our producer.
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So there are genetic factors behind cancer, There are environmental factors, smoking, diet, pollution, and so on. And then there's just the luck of the draw, because one of these zillions of cell divisions in your body goes wrong.
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Yes, I think that's it.
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And the researchers say They've calculated that 2/3 of cancer variation is down to bad luck. Now, many media reports have simply concluded that this means that 2/3 of cancer cases are the result of bad luck, a random cel division gone wrong, and that these cases have no genetic component and can't be prevented by stopping smoking or improving your diet.
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And that's just wrong. But, you know, this is hard. We've been scratching our heads trying to figure out what this 2/3 number really means.
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We've read countless articles and blog posts by statistically savvy people and experts in this field. And the problem is they don't all agree.
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But then midweek, there was a glimmer of hope in the form of a clarification on the Johns Hopkins University website.
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So they're using the analogy of getting cancer is like getting in a car and going on a trip.
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They're saying it's like getting into a car accident. And so they're saying, using this analogy, we would estimate that two thirds of the risk of getting into an accident is attributable to the length of. Of the trip. The rest of the risk comes from bad roads, bad cars, etc. In terms of cancer, we calculate that 2/3 of the variation is attributable to the random mutations that occur in stem cell divisions throughout a person's lifetime, and the rest is environmental.
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So, yeah, but look, this paragraph, the next paragraph, they say we can't say that two thirds of accidents are caused solely by the length of the.
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That's just what they did. Say that's just what they did. That's. Isn't that what they said? Our best guess is that it's about correlations. The correlation between the parts of the body that have a lot of cell divisions going on and the parts of the body that are prone to cancer. If you imagine plotting a graph listing all these different types of cancer and you have the frequency of cell divisions on one axis and the frequency of cancer on the other axis. Now imagine the dots on the graph were scattered all over the place. There was no correlation. You'd say that there was no particular relationship between cell division, which is what these researchers call bad luck, and cancer.
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And if all the dots lined up perfectly, there'd be a 100% relationship between cell division and cancer. And the answer is somewhere in between. The dots on the graph line up pretty well. So the rate of cell division is about 2/3 correlated with the rate of cancer. So we think may what the researchers mean, maybe.
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Although if that's what they do mean, George Davy Smith, who's a professor of clinical epidemiology at Bristol University, is not impressed.
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Explaining the difference in risk between the leg and the lung is of no interest to anyone. Mendin says nothing about the contribution to cancers in the population. It's like getting two statistics, two estimates which bear no relationship to each other. And because you've got a number applying that number to some other domain.
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Now, there were lots of media reports with extremely simplistic views about the relationship between cancer and bad luck. So should we blame the media for getting this story wrong? George Davy Smith doesn't think so the
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subheading in Science is editorial, which was headed the bad luck of cancer. And the subheading was analysis suggests most cases can't be prevented. That subheading is just a not supported by the data by that analysis. So that is what's misleading. And in the press release the authors say that they've come up with a method which allows them to quantify the contribution of these stochastic or chance factors, which their method doesn't. So it's both in the journal and in the press release. And it's just not fair to attribute the misreporting of this to journalists. They've just copied what's in the journal and in the press release.
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And there's another problem here, and that's the idea that you can add up various contributions to risk the part that's preventable and the part that's pure luck and get a total of 100%. I mean, if I play Russian roulette and I shoot myself in the head, that was 100% preventable. But surely it was partly bad luck too, because after all, I might easily have survived. So here's George Davey Smith on the subject of luck and preventability.
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I think the issue is that there's just a fundamental misunderstanding about whether one can partition risk in the way that's done. There's a great difference between the risk of an individual getting cancer, you know, you getting cancer and your brother not getting cancer, for example, as against the actual preventability of cancer. And one doesn't say anything about the other.
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The headlines may have been misleading and the study itself may have some serious critics, but PZ Meyers thinks it's useful.
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What's important about the study is that it does say that if you have cancer. I think this is something that people who have cancer would like to hear. It's not something that you should blame yourself for.
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PZ Myers of the University of Minnesota. Morris.
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Ah, Tim, I've got news.
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What?
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I've just received a reply to my emails from one of the authors, Christian Tomasetti.
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Oh, fantastic. Clarity at last. What does he say?
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He says he's writing a technical paper to explain his previous paper.
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Brilliant.
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Maybe then we can do another more or less item to explain this one. In fact, I reckon we could spin this out into a multi part series. What do you reckon?
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I really don't think so. It'll never catch on.
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Whether it's from politicians or the press. The public are fed a diet of numbers and statistics on a daily basis and loyal listeners often get in touch to ask whether some of these statistics are true. And of course that is an important question. But it isn't the only question we should be asking. According to the Financial Times economics editor
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Chris Giles, what really matters much more than truth, I think, is fairness. So for some statistic to be a really good statistic to tell us something, it has to be both true or nearly true. But more importantly, it has to be fair. And I think we often care much more about literal truth than about whether something's fair or not. We often see politicians or even newspapers doing this. We see them finding things, sort of manipulating things so they are literally true, but give a misleading impression. And I think that's much worse. It's a much bigger whopper actually than saying something, getting something wrong, saying something is not true because you've been really rather devious if you do that. You've actually thought, how do I make something true give an impression of something that is actually not true?
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Now there's a fascinating example in front of me. A claim made late last year by the TUC, the Trades Union Congress, that since 2008 only one in 40 new jobs had been full time. And the fact checking website factcheck.org looked into this and they concluded that that was narrowly true. There was a way of constructing the figures so that that claim was true, but it was very misleading in a number of ways.
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It was a huge deal misleading because what happened was that the number of full time jobs from 2008, which was a peak in full time employment just before the recession, just before the recession, fell very rapidly and then from about 2011, 2012, I actually don't know what the true number date is, but I don't think it matters. From about that sort of time, full time employment began to rise really quite rapidly. So that in the most recent data, the number of full time employees is slightly higher than it was in 2008. The number of total employees is to going quite a lot higher. So you can say you have a little bit higher compared with a lot higher. You say 1 in 14 new jobs is only full time.
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So you're measuring from a peak. Then you go down this dramatic precipice and then there's this slow, slow climb up the other side of the valley and finally you've just slightly exceeded the previous peak. And at that point that's the point you choose to measure to get your statistic.
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Really, to be fair about this, you want to say, yes, the recession hit full time employment very hard and for the last three years it's actually been growing really rather fast and we don't know about the number, the proportion of new jobs which are full time because we don't have those statistics.
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Chris, there's an election coming. I'm sure you've noticed. Have you noticed any true but unfair claims being made by the parties in the run up?
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Well, I think this is a really good time to look at sort of other ways that you can make true but unfair claims. Labour at the moment are saying that the Conservatives are going to cut public spending so hard it's going to take it back to the levels of the 1930s, a time before there was a
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National Health Service and when young people left school at 14.
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Now this statistic originally came from the Office for Budget Responsibility, so it has a very fine heritage.
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But actually, and it must be true
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in some sense true, roughly as far as we know, the stats aren't brilliant here, that total public expenditure as a share of national income is projected to be cut to about the level of 1938. But 1938 is not representative of the 1930s at all.
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There's a lot going on in 1938.
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I would have thought we were rearming, we were building quite a lot of spitfires and the like in 1938. In fact, the 35% number is very different from the 30s as a time before rearmament. In fact, public spending in the 1930s was roughly about 25% of national income, so a full 10 percentage points lower. So it really isn't in any way fair to say public spending is being cut to the level of the 1930s. It might be 1938 or 1939, yes, but not the 30s.
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And that leaving aside the question of the fact that the economy is as a whole is far, far bigger and therefore public spending as a whole is far bigger.
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And there's a different number of pensions and everything. So the whole thing is a really rather silly comparison in many, many ways, but just in that narrow point. It isn't the 1930s, but it's not just Labour. Let's be very clear. There's another way you can say things which are true but unfair. One way is often to have a lot of implied causality in a statement, when actually we don't know of any causality at all. So the Conservatives like to say things
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like today, against a difficult global backdrop, I can report higher growth, lower unemployment, falling inflation and a deficit that is falling to today a deficit that is half what we inherited. Mr. Speaker, our long term economic plan is working.
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We stuck to our long term economic plan and the economy recovered. The causality is very clear in that statement. Because we stuck to the plan the economy recovered. We have no idea why the economy really recovered in 2013. Lots of people have lots of different reasons and some people even say it's because they didn't stick to the plan that the economy recovered. So actually, economists are really rather sort of in the dark about why the economy suddenly did recover. But it's certainly wrong, I'd say, and unfair to say it was because the conservatives stuck to the plan. That might end up with history to be true, but we don't know that yet.
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Chris Giles of the Financial Times and we'll continue to keep a close eye on the statistical claims being lobbed back and forth as we approach this year's general election revealed the best and worst
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countries in the world to grow old
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India Tops New Global Slavery Index Shanghai
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Teens Top International Education Ranking if you read the news online or log onto social media, you must have seen headlines like those. You may even have been tempted to click on one country. Rankings on all manner of subjects seem to be everywhere. But are they reliable? Helen Joyce, the international editor of the Economist, had her suspicions, which led to an article all about these rankings.
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We cited in the article this pair of academics, Kelly and Simmons, who had done an extraordinary Internet search of rankings. And they had found that from say, pre1974, when there was basically nothing like this, to now, it's multiplied by many, many, many times the number of country rankings.
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Helen explained what was behind that increase.
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Mixture of reasons. One is just the Internet, the data is available, and then the second reason is also to do with the Internet. They're catnip for the sorts of things that get shared on social media. People love rankings and then this feeds back into people who create indices. That's why they do it. If you have a policy that you want to get taken seriously, one great thing you can do is create an index. It'll get picked up, it'll get reported, it'll get shared.
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Well, rankings then are flourishing because we in the media pay attention to them. So should we. An example of good practice, says Helen Joyce, is the Pisa rankings, which compare the attainment of 15 year olds in maths, reading and science across 65 different countries.
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It's meticulous. They go to an enormous amount of trouble and they don't produce a ranking from the results, although they do score countries. They try to explain to journalists and everyone else who uses it that, you know, there's a margin of error around each country that it's not fair to make a lot of one or two points of difference. Of course people do produce a ranking
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from it, so that's how to do cross country comparisons. Well, what about how to do them badly?
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We did pick out one index called the Global Slavery Index and it's produced by an NGO called Walk Free. You know, it's tackling a very important subject which is modern day slavery, including things like child marriage, forced trafficking of people, forced labour. These are not things that people have good figures on. So they made some, shall we say heroic assumptions based on very tiny surveys and so on. And then the most shocking thing that they did is there are some countries for which there are literally no estimates whatsoever, not one single figure you can use. So they go beyond the using small figures, out of date figures, incomparable figures. And they actually used figures for some countries, for other countries on the grounds that they were vaguely similar. There is an estimate of the amount of slavery that's happening today in the United Kingdom. So they used that estimate for Ireland and Iceland on the grounds that they were also island nations and then they didn't have figures for some parts of Europe. So they used figures from the United States, I mean, I guess on the grounds they were, you know, modern western nations with similar GDPs, new land borders and so on. If you were trying to get some ballpark figure for the total number of slaves in the world today, this is just about something that you could imagine doing to come to a headline figure. I think already it's a bit shoddy, but anyway. But if you're then going to rank countries and then the worst thing they did was they actually named and shamed the bottom countries. And when you think how poor the data were, that's really totally unfair.
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The Global Slavery Index that Helen Joyce was referring to was from 2013 and walk free informed us that it has since improved its methodology, releasing a new survey in November 2014. But I'm sorry to say there are still countries included in the rankings for which there is no available data. So there is a danger that performance indices can be misleading in an ideal world. Then would Helen do away with them altogether?
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I do think there's a place for rankings and for categorising countries in say four or five categories because I think it's really clear and it's hard for politicians to wriggle out of a clear cut judgement. It's just that if you're going to do that, you have to be doing it with the most incredible integrity. And you also have to be completely transparent about what you're doing.
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Helen Joyce, the international editor of the Economist, on how she'd like people to behave when compiling international rankings. Well, that's all we have time for, but we'll be back next week, so please keep your questions and comments coming in to more or lessbc.co.uk. our website, where you can subscribe to a free download of the programme, is BBC.co.uk until next week. Goodbye. This is the extended edition of More or Less, first broadcast on BBC Radio 4 and produced in association with the Open University.
More or Less (BBC Radio 4): "A&E Waiting Times" — Episode Summary
Date: January 9, 2015
Host: Tim Harford
This episode of "More or Less," hosted by Tim Harford, delves into the numbers behind headline-grabbing statistics in the news, including NHS Accident & Emergency (A&E) waiting times, the accuracy of claims about global wealth inequality, the reporting of cancer research, and the use (and misuse) of statistics in political debate and global rankings. The aim is to separate statistical fact from fiction and encourage fair, accurate interpretation.
[00:43–06:15]
A&E departments depend on bed availability in the rest of the hospital. Delays in patient transfer (“delayed transfers of care”) impact flow.
Cuts to social care funding mean some elderly patients can’t be discharged safely — social services must find care packages, causing hospital bed bottlenecks.
“About two thirds… are actually to do with the NHS itself… but there is a significant number where there has to be a care package put in place, put together by social services…” — John Appleby [05:15]
Not so far: Mild winter so far. Historically, crises peak end of January and into February.
“We haven’t actually had a severe winter yet… the real problems for the NHS in terms of A&E don’t come around Christmas. They’re actually towards the end of January and into February.” — John Appleby [05:50]
[06:15–08:43]
Oxfam’s claim: 85 richest people have as much wealth as the poorest half of the world; BBC publicity distorted this further.
Keith Moore: “So while the original claim was that the richest 85 people have more money than the poorest half of the world, this new claim [from the BBC trail] is that the richest 85 people have as much money as everyone else put together…. and it’s that small change of wording which takes the claim from roughly right to completely wrong.” [07:38]
Oxfam: 85 people = $1.7 trillion; Global wealth = $263 trillion. So, 85 people do NOT have half the world’s wealth.
Reality: About half of all global wealth is held by the richest 1% (about 70 million people, including many UK homeowners).
“If your house is worth more than half a million pounds and you’ve got a small mortgage or no mortgage, congratulations. You are one of the global 1%.” — Tim Harford [08:12]
[08:43–17:50]
It doesn’t address why individuals get cancer; nor does it say that two-thirds of cancer cases are unpreventable or unrelated to lifestyle or genetics.
The “2/3” statistic refers to variability between cancer types and not to causation of cases in the population.
“[Media reports] simply concluded that this means that two thirds of cancer cases are the result of bad luck… and that these cases… can’t be prevented… That’s just wrong.” — Tim Harford [12:32]
“The subheading … was: ‘analysis suggests most cases can’t be prevented.’ That subheading is just… not supported by the data.” — Prof. George Davey Smith [15:27]
[17:50–23:20]
“We often see politicians or even newspapers… finding things… so they are literally true, but give a misleading impression. And I think that’s much worse.” — Chris Giles [18:09]
TUC claim: Since 2008, only “one in forty” new jobs are full-time — narrowly true if you cherry-pick start/end points, but misleading ("measuring from a peak" effect).
Labour claim: Spending cuts will take public spending back to “1930s levels”—not a fair comparison, as the 1930s were influenced by pre-war economy and 1938 itself was atypical.
Conservatives: Link economic recovery directly to their “long-term plan” — implied causality not supported by data.
“Economists… are really rather sort of in the dark about why the economy suddenly did recover… It’s certainly wrong, I’d say, and unfair to say it was because the conservatives stuck to the plan.” — Chris Giles [22:44]
[23:31–27:28]
“People love rankings and then this feeds back into people who create indices… That’s why they do it.” — Helen Joyce [24:20]
Good Example: PISA rankings (student attainment) are transparent about uncertainty and discourage simplistic league tables.
Bad Example: The Global Slavery Index used estimates from one country for others with superficially similar characteristics, due to lack of data.
“They used that estimate [of slavery in the UK] for Ireland and Iceland on the grounds that they were also island nations…” — Helen Joyce [25:24]
Rankings can be useful when created with transparency and integrity, but using poor data and ranking individual countries can be “totally unfair.”
“If you’re then going to rank countries and then the worst thing they did was they actually named and shamed the bottom countries. And when you think how poor the data were, that’s really totally unfair.” — Helen Joyce [26:41]
"If you’re going to do that, you have to be doing it with the most incredible integrity. And you also have to be completely transparent about what you’re doing.” — Helen Joyce [27:09]
“If you’re over 65, it’s 50%. It’s an indication of more serious cases.”
— John Appleby, on winter A&E admissions [03:52]
“So while the original claim was that the richest 85 people have more money than the poorest half of the world, this new claim is that the richest 85 people have as much money as everyone else put together…. and it’s that small change of wording which takes the claim from roughly right to completely wrong.”
— Keith Moore [07:38]
“If your house is worth more than half a million pounds... congratulations. You are one of the global 1%.”
— Tim Harford [08:12]
“What it showed is a correlation between the number of cell divisions to produce a tissue and the likelihood that it would become cancerous.”
— PZ Myers [10:07]
“The subheading [in Science] … was: ‘analysis suggests most cases can’t be prevented.’ That subheading is… not supported by the data.”
— Prof. George Davey Smith [15:27]
“We often see politicians or even newspapers… finding things… so they are literally true, but give a misleading impression. And I think that’s much worse.”
— Chris Giles [18:09]
“If you’re then going to rank countries and then the worst thing they did was they actually named and shamed the bottom countries. And when you think how poor the data were, that’s really totally unfair.”
— Helen Joyce [26:41]
This episode masterfully picks apart widely reported statistics, revealing how “headline numbers” can mislead without context and fairness. Whether it’s NHS waiting times, breathless claims about global wealth, interpretations of cancer research, politicised employment figures, or provocative international rankings, "More or Less" reminds listeners to question not just the truth, but also the fairness and context of every number in the news.