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January 9th, 2018 (Permalink)

Quote Watch: Don't Be Fooled

I've just started reading a book entitled Don't Be Fooled: A Citizen's Guide to News and Information in the Digital Age, which certainly sounds useful. In its preface the author, John H. McManus, offers a short autobiography, which begins:

In this book I argue that information-providers should be transparent so you'll know when to power up your skepticism shields. Nelson Mandela once said "where you stand depends on where you sit."1

So, let's raise our skepticism shields. Did Nelson Mandela actually once say that? First of all, what does it even mean? I sit in my chair, but I don't stand in it. Clearly, it's supposed to have something to do with bias, since the preface in which it occurs is titled "A Confession of Bias". "Where you stand" can refer to the "positions" you take on issues, but what does "where you sit" mean? Here's how McManus interprets it:

Without being aware of it, we absorb biases from where we are situated in society. Our race, gender, religion, generation, geography, class and nationality each have a great deal to do with how we perceive the world.1

Okay, but why should all of that be called "where you sit", as opposed to "where you're from" or "who you are" or "where you lie down"? Anyway, the fact that the quote doesn't make much sense coming from Mandela should help raise those skepticism shields.

If you search for this quote on the internet, you'll find many sites that attribute it to Mandela, including some quotation sites. However, none of those occurrences that I have found include a citation to a source for the quote. Also, we have seen previously that many quote sites are not to be trusted2, as they often include fake quotes and misattributions. Finally, the earliest attribution of the quote to Mandela that I've found is from 2010, which certainly doesn't rule out that he said it, but it is further reason to doubt it. Moreover, prior to 2010, the quote has been called "Miles' Law" after Rufus Miles.

Who was Rufus Miles3? If you're like me, you've never heard of him before. One common phenomenon of quotesmanship is that things said by little-known people―such as Rufus Miles―are put into the mouths of famous people―such as Nelson Mandela. Ralph Keyes calls this the axiom that "famous quotes need famous mouths"4. Even better, of course, if the famous mouth belongs to a highly-admired person, such as Mandela. In that way, the quote is given an air of authority that it would otherwise lack. Most people would be skeptical of a quote attributed to someone they've never heard of, but not so if the same quote is put in the mouth of a famous wise man.

In an article from 1978, Miles himself claimed authorship of the quote5, and here is how he explains the "law":

…[T]he basic lesson of Miles' Law was that there was no such thing as pure objectivity in the arena of budgeting or public policy making in general. Every person has a function to perform and that assigned responsibility markedly influences one's judgment.6

Miles was a bureaucrat writing for the Public Administration Review, and his law is one of seven "maxims" of management7. It's clear from Miles' discussion and examples that what he meant by "where you stand depends on where you sit" is that the "positions" that a bureaucrat takes on issues depend upon where in the bureaucracy he is positioned. So, where he "stands" depends upon where he "sits", that is, where his office and his chair is, what building he works in, what department or agency he works for.

Of course, the fact that Miles claimed authorship of the "law" doesn't necessarily mean that he did author it. Did Nelson Mandela at some time in his long life say it? Possibly; I certainly can't prove that he didn't8. However, even if he did say it, it's likely that he was repeating something he had heard. It is far more likely that Miles came up with the saying than Mandela did, and the clincher for me is the fact that the quote makes more sense in its bureaucratic setting than as a general maxim about bias.

I've just begun to read McManus' book, and it may well be a highly useful and accurate one despite its inauspicious beginning. McManus either did not raise his "skepticism shields" when confronted with the alleged Mandela quote, or he's not much of a researcher―I hope the former. It's so easy to discover that the attribution of the quote to Mandela is at least doubtful that I suspect that McManus just didn't bother to check it. Instead of the purported Mandela quote, McManus should have kept in mind the old journalistic saying: "If your mother says she loves you, check it out."9


  1. John H. McManus, Don't Be Fooled: A Citizen's Guide to News and Information in the Digital Age (2012), "A Confession of Bias"
  2. See, for instance: Who is Adolph Hitler and why does he keep saying these terrible things?, 9/11/2017
  3. You can read his short obituary here: "Rufus Miles Jr., 85, Aide to 3 Presidents", The New York Times, 4/15/1996
  4. Ralph Keyes, "Nice Guys Finish Last Seventh": False Phrases, Spurious Sayings, and Familiar Misquotations (1993), p. 20
  5. Rufus E. Miles, Jr., "The Origin and Meaning of Miles' Law", Public Administration Review, Vol. 38, No. 5 (Sep.-Oct., 1978), pp. 399-403
  6. Miles, p. 400
  7. Miles, p. 403
  8. Moreover, the burden of proof is not on me to disprove it. The burden is on McManus or anyone else who claims that Mandela said it to offer some evidence that he did. So far, there is no evidence he did.
  9. Chip Scanlan, "If Your Mother Says She Loves You: A Reporter's Cautionary Tale", Poynter, 4/17/2003

January 5th, 2018 (Permalink)

Poll Watch: Big Nothin'

A lot of public opinion poll reporting is fake news in the sense that there's no news in it1. More precisely, it might be called "manufactured news" since the "news" is the poll itself. If the numbers have changed since the previous poll, that's news! If they haven't, that's news too! A current example has the following headline:

Trump weekly job approval up to 39 percent, highest in months

The article under this headline2 is quite short, though not as short as it should be. If you're an experienced poll watcher, I suggest reading the whole article, which takes less than a minute. Then, you can compare your observations to my comments, below:

Excerpt Comment
The approval rating for the week was an improvement from Trump's low of 35 percent, seen just weeks before.
Four percentage points? Is that significant? What is the margin of error for this poll? That's not reported!
The last time Trump's weekly approval was at 39 percent was in July, according to Gallup. The president…had an overall approval average of 39 percent for 2017.
So, another headline for this report could have been: Trump Job Approval Rating Holds Steady
The president's latest weekly approval rating in December came after he scored his first legislative victory with congressional Republicans on tax reform.
So that probably caused the increase….
However, the Republican-backed tax plan does not appear to be widely popular with the American people. An NBC News–Wall Street Journal poll last month found that only 24 percent of Americans believed the tax plan was a good idea.
…um, never mind.

According to Gallup3, the margin of error (MoE) for this poll is ±3 percentage points. However, the previous week's approval rating was 37%, which is within the MoE. Furthermore, as recently as the middle of November, the rating was at 38%. So, in about six weeks the rating improved one whole percentage point.4

You can't blame the reporters who write this stuff: they've got a job to do, and they can't let the fact that there's no news stop them.


  1. For a "Poll Watch" example from last year, see: No Margin for Error, 5/4/2017
  2. Julia Manchester, "Poll: Trump weekly job approval up to 39 percent, highest in months", The Hill, 1/3/2018
  3. "Trump Job Approval (Weekly)", Gallup, accessed: 1/5/2018.
  4. See: Margin of Error Errors, How to Read a Poll.

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December 25th, 2017 (Permalink)

A Puzzling Christmas Greeting

Here is my Christmas greeting to you:


Can you figure out what it means?



December 23rd, 2017 (Permalink)

Quote, Misquote

Who said it?

The strongest reason for the people to retain the right to keep and bear arms is, as a last resort, to protect themselves against tyranny in government.

Some, including economist Walter Williams1, have attributed this statement to Thomas Jefferson. However, there is no reason to think that Jefferson said or wrote this2. Its earliest appearance in print seems to be in 1989, so it was probably concocted about that time. However, who actually created the quote we don't know, except that it probably wasn't Jefferson.

Just as some gun rights advocates misquote Hitler as a proponent of gun registration3, others also misquote the Founding Fathers in support of unrestricted access to firearms. The Hitler misquote smears by association4 those who support restrictions on guns, whereas bogus quotes of the Founding Fathers do the reverse: instead of damning gun registration by associating it with the Nazis5, they appeal to the authority6 of Founders such as Jefferson to support the right to keep and carry guns. Given the second amendment to the constitution, I would think it ought to be easy enough to find genuine quotes from the Founders to support that right without having to make them up, but maybe it's just easier to invent them than do boring research.


  1. Walter E. Williams, "To Keep And Bear Arms", George Mason University, 3/24/2000
  2. See the following sources:
  3. See, for one example: Who is Adolph Hitler and why does he keep saying these terrible things?, 9/11/2017
  4. See: Guilt by Association
  5. See: The Hitler Card
  6. See: Appeal to Misleading Authority

December 17th, 2017 (Permalink)


Senators push for funding bill to include money for sexual harassment training*

So far, they've had to learn by doing.

* Jordain Carney, "Senators push for funding bill to include money for sexual harassment training", The Hill, 12/14/2017. Via: Glenn Reynolds, "I Don't See Why, They Seem Pretty Damn Good at it Already", InstaPundit, 12/15/2017.

Is this the Worst Pie Chart Ever?
December 15th, 2017 (Permalink)

Charts & Graphs:
A Half-Baked Pie Chart

Before you read any further, take a look at the pie chart to the right. What do you make of it?

I came across this chart in a column by mathematician Keith Devlin1, who focuses on the fact that the chart seems to show a pie cut into two pieces, one representing the richest 1% and the other the remaining 99%. However, the "1%" piece looks to be about 23% or 24% of the pie, leaving the "99%" piece representing the remaining 76% or 77%.

First, here's a brief explanation of what the chart is actually trying to convey―if you need more, see Devlin's discussion. A careful reading of the title of the chart reveals that the pieces of the pie actually represent the share of taxes paid by each income group, not the income groups themselves. In other words, the richest 1% pay about 24% of taxes, whereas the remaining 99% of us pay only the remaining 76%.

This combination of two sets of percentages in one pie chart―percent of the population in terms of wealth, and percent of federal tax paid―is confusing, but I doubt that anyone would be seriously fooled by it. Since the percentages and the sizes of the slices are so at odds, one is led to read the title of the chart to resolve the confusion. I want to focus, instead, on a couple of other problems that Devlin does not comment on, one of which I think is more seriously deceptive.

One problem with this chart that Devlin does not discuss is that a graph of any kind is unnecessary to convey this information. With only two income groups being compared, it is easier and clearer to do so in words. As it is, the chart just confuses matters. One of the earliest questions you should ask yourself before making a graph is: Can this data be more easily understood in a graph than in words? If not, don't do it. Charts shouldn't just be pretty pictures to adorn your words, and they especially shouldn't be misleading pictures unless your goal is to mislead people.

The pie chart was put out by a group called "Tax March"2, which organized a number of marches earlier this year to protest President Trump's refusal to make public all of his tax returns. In other words, it's an anti-Trump political pressure group. Now, this doesn't necessarily mean that the pie chart was intended to mislead people, even if it had that effect, but it does mean that it deserves no benefit of the doubt. This is a group with an agenda, and anything they put out should be treated with skepticism. As Ronald Reagan should have said: "Don't trust; verify!" Is this the Worst Pie Chart Ever?

The original graph was an animated GIF that if clicked on would produce the following additional chart3. Here, you can see the point of the chart: the piece of the pie representing the tax share of the wealthiest 1% shrinks from about 24% to approximately 20%, with the remaining piece increasing a proportional amount. If you don't get the point, the second chart provides the helpful pointers: "The rich pay less" and "We pay more".

But do we non-rich folks really pay more? Now, this is not a fact check, it's a logic check, so I'm just going to assume that the percentages shown by both charts are correct.

What worries me is the words: "We pay more": "more" what? This a dangling comparative, that is, a comparison lacking one of the items compared. "We pay more" could mean that we, the 99%, pay more taxes than we used to. In fact, that is what I expect most people who see the chart will believe. However, what the chart shows is that we, the 99%, will pay a larger share of the total tax burden, which is not the same thing as paying more taxes.

If this point isn't sufficiently clear, think about it this way: Suppose that the entire amount of federal tax paid is a billion dollars, and that the top 1% in income pay 240 million of that, which is 24% of the total. That means that the remaining 99% of taxpayers would pay 760 million, or 76%.

Suppose, further, that an across-the-board tax cut reduced the total amount of tax paid to 900 million, of which 180 million―20% of the total―is paid by the richest 1%, and 720 million comes from the rest of us―80%. In this scenario, everyone is paying less tax, but the share paid by 99% has increased. For all that we can tell from the chart, this is what will happen under the proposed tax plan.

How many people who look at this chart will come away thinking that the rich are getting a tax cut, but the rest of us will actually end up with a tax raise? I expect that it's probably less than 99%, but much greater than 1%.


  1. Keith Devlin, "Clash of representations", Devlin's Angle, 12/14/2017.
  2. See: Matt Stevens, "The Tax March Explained: Protesters Hope to Pressure Trump Into Releasing Returns", The New York Times, 4/15/2017. I'm pleased that they didn't decide to call themselves "the Million Person Plus One Giant Inflatable Chicken March", or the like; see: The Million "Million X March" March, 6/18/2014.
  3. I was unable to find the original of this chart, so I'm copying only the unclickable version supplied in Devlin's column.

December 2nd, 2017 (Permalink)

New Book: Dollars and Sense

Thankfully, I have no complaints about the title of Dan Ariely's new book with Jeff Kreisler. But, what's up with this subtitle: "How We Misthink Money and How to Spend Smarter"? How can we "misthink" money if we can't think it? I think I understand what the subtitle is getting at: this is a book about the mistakes we tend to make in thinking about money, and how to avoid them.

Ariely is a psychologist and author of the previous book Predictably Irrational, which I've read and referred to in passing here. It's been almost ten years since I read that book, so unfortunately I don't remember much about it. In the intervening years, Ariely has written some other books that I haven't read, including The Upside of Irrationality―whose title I was put off by, as I don't think irrationality has an "upside". I am interested in reading the new book because I could benefit from learning how to avoid financial mistakes. Couldn't we all?

December 1st, 2017 (Permalink)

What's New?

This weblog has been rather quiet for the last month or two because I've been engaged in the long-delayed project of revising all of the fallacy entries. As part of that project, I've added a new fallacy: The Fallacy of the Heap! More accurately, it's sort-of new, because this is the same fallacy of vagueness that used to be listed under the name "Slippery Slope", along with the causal fallacy of the same name. In other words, it's a new entry for an old fallacy under a new name.

I'm in the process of splitting the old Slippery Slope entry into two distinct entries, one for the fallacy of vagueness, and the other for the causal fallacy. The first part of that task is now done. As mentioned in the new entry, the Fallacy of the Heap is sometimes referred to as "the slippery slope fallacy". However, "slippery slope" is most commonly used to refer to the causal mistake. Though, as explained in the new entry, the vagueness and causal fallacies are sometimes related, they are distinct fallacies and for that reason should have distinct entries and distinct names. There's reason to believe that some readers were confused by two different fallacies being discussed in the same entry under the same name, so this change should clear that up. For the time being, the entry for Slippery Slope is still the same old entry, but will soon be revised to cover only the causal fallacy.

New Fallacy: The Fallacy of the Heap

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