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May 26th, 2015 (Permalink)

Food is a Fallacy

Fads, I submit, are the very negation of reason. To be swept up in every new craze that comes along, to surrender oneself to idiocy just because everybody else is doing it―this to me, is the acme of mindlessness.
Source: Max Shulman, "Love is a Fallacy"

Slate had an article about a month ago, but which I just discovered, on the fallacious thinking behind food fads. Here's a taste:

Natural food is good. Evil foods harm you, but they are sinfully delicious, guilty pleasures. Good foods, on the other hand, are real and clean. … We’ve been primed to think this way. After all, the world’s most famous myth recounts a dietary fall from grace. Long ago, humans lived in an organic, all-natural, divinely designed garden, free from pesticides and GMOs and processed grains and sugar. But one day an evil advertiser came along and hissed, “Just eat this fruit.” Bam! Suddenly we were cursed with mortality, marital strife, labor pains, and agriculture. … Consider…“love of nature,” which is used to justify virtually every diet on the market, from gluten-free (modern Frankenwheat is unnatural!) to raw food (cooking is unnatural!). It turns out that the “appeal to nature” is a well-established fallacy, plagued by question begging…in addition to the inherent vagueness of the term natural. Nevertheless, people demand all-natural foods and dutifully avoid unnatural chemicals, oblivious to the irrational foundation of their preferences.
Source: Alan Levinovitz, "The Logical Failures of Food Fads", Slate, 4/21/2015

Try it, you might like it. The author is, of course, promoting a new book, and Harriet "The Skepdoc" Hall has a favorable review of it. Here's a tasty bite:

To many people science is suspect because of the steady stream of scientific reversals on butter, wine, or whatever food appears in the headlines. But [Levinovitz] points out that these are not reversals at all, because nothing was ever established in the first place. The headlines report single preliminary studies that are questionable, not scientific consensus based on an accumulated body of reliable data. True science is humble, cautious, and embraces complexity and uncertainty.
Source: Harriet Hall, "Food Faiths & Diet Religions", Eskeptic, 5/20/2015

Fallacies:

Update: Entirely by coincidence, as far as I know, Brian Dunning of Skeptoid has a podcast today on fads. Not all of the fads that he discusses concern food, but he does deal with juice fads, the dangerous practice of drinking unpasteurised milk, and the anti-gluten hysteria that provides Levinovitz' book its title. Here's a nibble to whet your appetite:

It's hard to say this often enough. Aches and pains usually eventually go away; that's the natural effect of our bodies healing themselves. When they do, our brains tend to credit whatever it was we were doing at the time. …. This is why scientists know that anecdotal experiences, even their own, are terrible ways to learn anything. Our personal experiences are subject to every sort of cognitive error. We have preconceived expectations. We make mistakes and misinterpret things. We have biases.
Source: Brian Dunning, "Listener Feedback: Fads", Skeptoid, 5/26/2015

Check it out.

Fallacies:


May 23rd, 2015 (Permalink)

In the Mail: The Philosophy of Argument and Audience Reception

The latest book by philosopher Christopher Tindale arrived today: The Philosophy of Argument and Audience Reception. Tindale has published a few previous books on argumentation, including one on fallacies and one on sophistry, each apparently from a point of view emphasizing rhetoric. These are all scholarly works and probably too advanced for the beginner, so if you're just starting out Tindale's textbook with Leo Groarke, Good Reasoning Matters, may be the place to start.

Source: Christopher W. Tindale, The Philosophy of Argument and Audience Reception, Cambridge University Press, 2015


May 20th, 2015 (Permalink)

So, what else is new?

Over the years, a number of readers have asked why there is no entry for the so-called "No-true-Scotsman Move" in The Fallacy Files. I've now at least partially remedied that oversight by adding it to the entry for Redefinition as a subfallacy of that fallacy. However, one important thing is missing from the entry, namely, a good real-life example. If anyone has such an example, please let me know.

Fallacy: The No-true-Scotsman Move


Fallacy Files Cafe
May 11th, 2015 (Permalink)

A Puzzle on the Menu

Check out today's menu at The Fallacy Files Cafe. The menu makes two emphatic statements: "Good food is not cheap!" and "Cheap food is not good!" Apparently, if you need to know the price of a dish before you order it, then you can't afford it.

Before proceeding, let's make a couple of things clear: the first statement doesn't mean that just some good food isn't cheap, but that all good food isn't. Moreover, when it says that good food isn't cheap it means that it's expensive. Similarly, the second means that all cheap food isn't good, that is, it's bad.

The puzzle is whether these statements mean the same thing, or something different. Don't just guess! How would you show that your answer is correct? When you think you know, click "Solution" below.

Solution


May 7th, 2015 (Permalink)

What's new?

I've revised and extended the entry for the Quantifier-Shift Fallacy, replacing a cooked-up example with a real-life one. The new example is harder to understand than the previous one, but I think the fact that it comes from an actual argument made by a famous philosopher makes up for the additional difficulty. I've also added a technical appendix for those who know quantificational logic, or are interested in learning more about it.

Fallacy: Quantifier-Shift


May 2nd, 2015 (Permalink)

In the Email Bag

Lawrence Mayes writes:

Dr Henry Marsh, described as a brain or neurosurgeon, has made some frankly daft comments about cycle safety which have got into the press―probably only because they are daft.

Here's a quote from the good doctor that struck Lawrence as "daft"―see the Sources, below: "I see lots of people in bike accidents and these flimsy little helmets don’t help." Back to Lawrence:

There are two aspects to this story that should start alarm bells tinkling straight away. Firstly, we have someone giving an opinion outside his area of expertise and secondly it's all part of a book promotion.

He claimed that he has treated a number of patients involved in bike accidents whose helmets were "too flimsy" to provide any real protection. (I could also truthfully make that claim.) But what Dr Marsh misses is that regardless of the size of this sample it does not include those cyclists involved in accidents whose helmets protected them sufficiently so that they didn't require the intervention of a neurosurgeon nor would he have seen those cyclists who were not wearing helmets and were consequently dead.

This is an example of what's been called "the clinician's error"―see the Resource, below.

There is also the puzzling statistic coming from Bath University which appears twice in the Independent article; this is the reduction in berth that car drivers give cyclists wearing helmets, firstly as "around three inches" then a few paragraphs on as 8.5cm. The second time around it has had a bit of probabilistic decoration added: "In 2006 Dr Ian Walker…found that drivers were twice as like [sic] to get close to cyclists, an average of 8.5cm, when they were wearing a helmet" which, frankly I find incomprehensible (even if he meant "likely").

Whether the average distances are 2ft 9in and 3ft (or whatever the figures may be) seems, to me, to be largely irrelevant; the important figure is the relative accident figures for helmet wearers versus non-wearers.

Walker's study suggests that wearing a helmet may increase the risk of being hit by some unknown amount, but it can't justify changing one's behavior, since we don't know what the trade-off is between a greater risk of an accident and the protection of the head. Perhaps helmeted cyclists are somewhat more likely to be in an accident than unhelmeted ones, but less likely to be killed or seriously injured.

I draw two conclusions from this: firstly, brain surgeons are not as smart as popularly supposed and secondly you should wear a helmet, otherwise you could end up being treated by Dr Marsh.

In fairness, he's not a rocket scientist.

Sources:

Resource: The Clinician's Error, 3/3/2005

April 24th, 2015 (Permalink)

Wiki Watchee: The Persistence of Misinformation

One of the claims used in defense of the accuracy of Wikipedia is that misinformation inserted into the online "encyclopedia" is usually found and removed quickly, even in a matter of minutes. I've argued previously that this is an unjustified claim because the examples that can be pointed to are only those that have been found, which means that the sample we have is affected by survival bias―see the Wikipedia Watch for 12/21/2014, below.

Moreover, there is at least one known hoax that lasted nearly a decade before being discovered―see the watch for 3/16/2014, below. I suggested that what is needed to reliably evaluate Wikipedia for reliability is a systematic study of randomly selected articles by appropriate experts.

Now, a study of Wikipedia's accuracy has been conducted, though not the kind of general evaluation that I suggested. Nonetheless, it's a clever approach to studying the specific question of how rapidly misinformation gets corrected―see the Sources, below. What Gregory Kohs did was to insert pieces of misinformation into various Wikipedia articles and keep track of them. Unfortunately, the length of the experiment, which is measured only in months, cannot tell us how long such misinformation might last. However, it does show that the notion that most misinformation will be speedily fixed is incorrect, at least if one measures speed in terms of weeks. Many claims about the rapid repair of incorrect claims put it in terms of minutes, rather than weeks or even months, as shown by some of the quotes cited by Kohs. Yet, about two-thirds of Kohs' misleading edits lasted weeks, and half remained in place by the end of the experiment, more than two months later.

The most amusing, and at the same time sad, aspect of this experiment is what happened when it ended and Kohs tried to correct the remaining misinformation himself:

The second craziest thing of all may be that when I sought to roll back the damage I had caused Wikipedia, after fixing eight of the thirty articles, my User account was blocked by a site administrator. The most bizarre thing is what happened next: another editor set himself to work restoring the falsehoods, following the theory that a blocked editor’s edits must be reverted on sight.

Sources:

Previous Wikipedia Watches: 12/21/2014, 3/16/2014


April 23rd, 2015 (Permalink)

Headline

Do doctors understand test results?

An old rule of journalism goes: headlines that end with a question mark can safely be answered "no". So, it probably won't come as a surprise to you that the article with the above headline gives evidence that doctors often do not understand test results―see the Source, below.

Of course, I would hope that if doctors were readers of this website they would understand the results of medical tests better, since we've examined all of the mistakes discussed in the article:

Check it out.

Source: William Kremer, "Do doctors understand test results?", BBC News, 7/7/2014

Acknowledgment: Thanks to Lawrence Mayes for calling this article to my attention.


April 19th, 2015 (Permalink)

Rolling Stone's Worst-Case Scenario

If you had no idea things were that bad, they probably aren't.―Joel Best

Columbia University's Graduate School of Journalism recently released its report on the now retracted Rolling Stone (RS) magazine story about an alleged campus gang rape―see Source 3, below. It's an important and interesting case study of how journalism can go wrong. The report itself is long, but well worth reading. There are also a number of shorter but excellent commentaries―see Sources 4 through 6, below.

The report claims that confirmation bias played a role in what went wrong:

The problem of confirmation bias―the tendency of people to be trapped by pre-existing assumptions and to select facts that support their own views while overlooking contradictory ones―is a well-established finding of social science. It seems to have been a factor here.

I like Megan McArdle's description of "classic" confirmation bias―see Source 5, below:

Classic confirmation bias means that you ask questions that would confirm your theory, rather than ones that would disconfirm it. Say I give you a set of numbers in a set: 2, 4, 6, 8. Now, I say, tell me what the rules for inclusion in this set are. You can ask me a number, and I'll tell you whether it's in the set. Almost invariably, the next numbers people suggest are "10" and "12," and when you agree they're in the set, they proudly announce that the set is "even numbers." False: The set is "all positive integers." Why did they fail? Because they only suggested numbers that would confirm their theory, which also happen to be in the set. What they didn't do is suggest an odd number to see if it might also qualify.

While it's a good thing that people are becoming aware of confirmation bias, I'm not so sure that it played much of a role in this case. Instead, the reporter, editor, and fact-checker seem not to have insisted even on finding evidence in support of the accusation, let alone against it. They simply seem to have accepted the accuser's account, and in lieu of seeking out evidence to support or refute it, the reporter wrote and her editor edited the story in such a way as to conceal that it was based entirely upon one woman's accusations. As Jean Kaufman writes―see Source 4, below:

[RS] appear[s] to have jettisoned those time-honored procedures [of journalism] for reasons that were most likely both ideological and self-serving: the story was a perfect fit for their pre-existing biases about campus rape and its perpetrators, and the tale was so sensational that it could practically guarantee them a record number of readers. In other words, it was far too good to fact check. …Rolling Stone set out to find a particular type of narrative and [it] got a sensational one. They then were willing to suspend the journalistic standards they profess to hold dear in order to protect it from too many questions. That’s not journalism, it’s activism. For reporters, the greater their initial bias in one direction or other, more care must be taken to overcome it with more due diligence, not less….

McArdle appears to agree:

What I see when I read through the…report is the story of journalists who had an incredible story, one that would get them readers and professional acclaim, and, perhaps most important, give them the opportunity to right a great wrong. Their excitement about the story, their determination to tell it, blinded them to the problems, so that the old joke about a story being "too good to check" actually came true, with terrible consequences. And that should be a lesson to every journalist out there: The better your story, the harder you need to work to disconfirm it. Because the odds are, your brain is sending you all the wrong signals. Of course, it's not exactly news that our emotions can mislead us. That's why we have professional rules, such as "always contact the other side for comment," in the first place. Rolling Stone got taken by a fabulist. But it was not the victim of fraud; it was a co-conspirator in self-deception.

There is one factor that I think played a role in this debacle that's not mentioned in the Columbia report. Moreover, it does not involve a failure to live up to journalistic standards, but instead a standard practice in journalism, namely, that of searching for a dramatic anecdote to build a story around. Jay Rosen is the only commenter on the case that I've noticed mention this problem―see Source 6, below:

The most consequential decision Rolling Stone made was made at the beginning: to settle on a narrative and go in search of the story that would work just right for that narrative. The key term is emblematic. The report has too little to say about that fateful decision, probably because it’s not a breach of procedure but standard procedure in magazine-style journalism. (Should it be?) This is my primary criticism of the Columbia report: it has too little to say about the “emblem of…” problem. [Ellipsis in the original.]

Initially, RS's article was supposed to be about the general problem of rape on university campuses and how administrations tend to deal with it. The reporter then set out to find the most dramatic case she could to illustrate this general problem, and presumably settled on the gang rape story because it was the most extreme and horrifying one she found. However, there are problems with this approach to reporting:

Sources:

  1. "Carl Sagan on Alien Abduction", NOVA, 2/27/1996
  2. Joel Best, Stat-Spotting: A Field Guide to Identifying Dubious Data (2008), pp. 11, 111-113
  3. Sheila Coronel, Steve Coll & Derek Kravitz, "Rolling Stone and UVA: The Columbia University Graduate School of Journalism Report", Rolling Stone, 4/5/2015
  4. Jean Kaufman, "Too Good to Fact Check", PJ Media, 4/7/2015
  5. Megan McArdle, "Rolling Stone Can't Even Apologize Right", Bloomberg View, 4/6/2015
  6. Jay Rosen, "Rolling Stone’s ‘A Rape on Campus.’ Notes and comment on Columbia J-school’s investigation.", Press Think, 4/6/2015

Fallacy: The Anecdotal Fallacy


April 17th, 2015 (Permalink)

New Version: Statistics Done Wrong

Alex Reinhart's Statistics Done Wrong, which was formerly only a website, is now a book in various formats, including paper! The new book is claimed to be three times the size of the web version. Unlike such books on statistics aimed at a general audience as Darrell Huff's and Joel Best's, it's not about the kind of statistical errors made by journalists reporting on scientific studies, or by advertisers or advocates misreporting them. Rather, it describes the mistakes that scientists themselves make, and that lead to so many false and conflicting results. Reinhart discusses the following statistical mistakes that we've met here previously: the base rate fallacy, the multiple comparisons fallacy, and the regression fallacy. I haven't read the new book, but the web version is very clearly written, and has a minimum of actual math if that sort of thing scares you. So, this is not an introduction to statistics, but it does what such introductions don't do, which is explain the logic and illogic of statistics in a way that even non-mathematicians can understand.

Source: Alex Reinhart, Statistics Done Wrong


April 15th, 2015 (Permalink)

Puzzle it Out

If you haven't racked your brain enough doing taxes, there's a clever puzzle making the rounds that you might be interested in. It's being called a "math" puzzle, perhaps because it was a problem in a math olympiad for high school students in Singapore. However, it's really just a logic puzzle, since no mathematics is required to solve it. The original version of the puzzle was controversial enough that The New York Times published an article about it―see the Source, below. The controversy seems to have been at least partly due to the original wording of the puzzle, which was ungrammatical and unclear because it was presumably written or translated by someone who was not a native speaker of English. Revised and unambiguous wording of the puzzle is given in the Times article, and the solution is also clearly explained. Check it out.

Source: Kenneth Chang, "A Math Problem From Singapore Goes Viral: When Is Cheryl’s Birthday?", The New York Times, 4/14/2015


April 6th, 2015 (Permalink)

The Logical Problem of Evil

And God saw every thing that he had made, and, behold, it was very good.
And the evening and the morning were the sixth day.―Genesis 1:31, KJV

Chris Cox sends the following story that I expect many readers can sympathize with:

When I was in the 6th grade in Catholic school we learned about Lucifer and how he was God's most brilliant angel. And then, through pride, he fell from God's grace and became Satan and was cast into Hell. Thence he has tempted man to sin so he can gather their souls into Hell and deny them heaven.

One day a Monsignor came around to ask us questions about what we had learned and to allow us to ask him questions. I had been thinking about how God was all-powerful and how he was all-good, as taught in the first two pages of our catechism. So I asked the Monsignor why God didn't just snap his fingers and make the Devil disappear. As I remember he paused for a moment then said, "Well, there are some things God does without our understanding them. These things will be revealed to us when we join him in heaven." Or words to that effect.

Over the the last thirty years or so I had been thinking of that classroom and why God would create Satan, Hell and all the other suffering, all because of Adam and Eve disobeying him (not to mention the fact he knew they were going to disobey him, and all the mental entanglements that gets you into). I also had been reading several books and articles in various publications. After some time I came to the conclusion that there was no god.

The argument I use comes from the first two or three pages of that first St. Joseph's catechism. In those pages we were taught that God was all-powerful, all-good, and all-knowing. Which brings me, finally, to my argument from evil that a perfectly good god can't create a universe with evil in it. Or as Paul Kurtz asked in his publication, Free Inquiry, "Why doesn't God abolish evil?

  1. He can't, and is therefore not Omnipotent, or
  2. He won't, and is therefore not Omnibeneficent."

My question concerns any fallacies in all of this: Is it sound?

You're raising a difficult problem that philosophers have written whole books about, but I'm not going to. In order not to write a whole book about it, I'll pass quickly over some complexities and carefully avoid distracting side issues. For lengthier but not book-length treatments, see the Sources, below. Also, as a logician and not a theologian or philosopher of religion, I will concentrate on a few logical points raised by your account:

Sources:

Resource: Anthony Gottlieb, "Candide and Leibniz’s garden", Voltaire Foundation, 2/3/2015. A brief discussion of the relationship between Candide and Leibniz. Contains some untranslated French.

Update (4/10/2015): A reader wrote to offer a version of the "free will" solution to the problem of evil, which I mentioned in the note to Source 1, above. This was one of the side issues that I was trying to avoid, but perhaps it's not obvious that it is a version of the "best of all possible worlds" defense.

The basic idea of the free will argument is that God created a world in which we have free will and that means we are free to do evil. With respect to free will and evil, there are four types of possible world that God could choose from:

  1. There is free will and there is evil. This seems to be the type of world we live in.
  2. There is free will but there is no evil. Some will claim that this type of world is not really possible, since if people have free will then it's possible that they will commit evil. However, free will does not necessitate that we commit evil, for if it did then in what sense would we be free? Therefore, it's possible that God could have created a world in which we have free will but have freely chosen not to commit evil. However, many philosophers have believed―wrongly in my opinion―that it is impossible for God to create people with free will who commit no evil, so let's put this possibility to one side.
  3. There is no free will but there is evil. This might also seem, at first glance, not to be possible but there is what's called "natural" evil, which is the evil resulting from earthquakes, volcanic eruptions, hurricanes, diseases, and so on. Thus, it's possible to have a world in which there is no "moral" evil―that is, the evil done by people with free will―but still have natural evil. However, it's arguable that a world in which we lacked free will would be one in which natural evil did not matter to us, since we would then be like "robots". For this reason, let's also put this possibility aside.
  4. There is no free will and no evil.

So, ignoring possibilities 2 and 3, the choice that God faced was between worlds of type 1 or 4, that is, between a world in which there was free will and evil (1) or one in which there is no free will and no evil (4).

Now, why would God choose 1 over 4? Presumably, because free will is of such great value that a world with both free will and evil is better than one with no free will but no evil. If that were not the case, then God would have chosen to create a worse world than He could have. Why would He do this? Only because he either could not help it, did not know any better, or did not wish to create the best world he could; in other words, only if he is not omnipotent, not omniscient, or not omnibenevolent.

Therefore, if God exists and is all three "omni"s, then Leibniz was right that this is the best of all possible worlds.

Source: Tim Holt, "The Free Will Defence", Philosophy of Religion, 2008

Previous Entry

The gambler's fallacy extends to the financial and investment markets. There is simply nothing like a fail proof investment or "get rich scheme" in the new trend of binary options. Although there are now serious binary option providers in Germany, such as BDSwiss which is EU regulated, prospective investors are cautioned to have realistic expectations to avoid the investor's fallacy.

The Gambler's fallacy spans international borders and technology, as Aussie players are now enjoying pokies on their mobiles according to this atn.com.au gaming page, which paints a surprising portrait of the Australian gaming market.

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