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It is fine to incarcerate people solely for what they put into their own bodies. It is very common for governments to do this.
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Guilt by Association
AKA Bad Company Fallacy, Company that You Keep Fallacy

Category: Fallacies of Relevance (Red Herrings) → Ad hominems (Genetic Fallacies)

Guilt by Association is a fallacy in which a person rejects a claim simply because it is pointed out that people she dislikes accept the claim. This sort of "reasoning" has the following form:

  1. It is pointed out that person A accepts claim P.
  2. Therefore P is false
It is clear that sort of "reasoning" is fallacious. For example the following is obviously a case of poor "reasoning": "You think that 1+1=2. But, Adolf Hitler, Charles Manson, Joseph Stalin, and Ted Bundy all believed that 1+1=2. So, you shouldn't believe it."

The fallacy draws its power from the fact that people do not like to be associated with people they dislike. Hence, if it is shown that a person shares a belief with people he dislikes he might be influenced into rejecting that belief. In such cases the person will be rejecting the claim based on how he thinks or feels about the people who hold it and because he does not want to be associated with such people.

Of course, the fact that someone does not want to be associated with people she dislikes does not justify the rejection of any claim. For example, most wicked and terrible people accept that the earth revolves around the sun and that lead is heavier than helium. No sane person would reject these claims simply because this would put them in the company of people they dislike (or even hate).

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5
Circumstantial Ad Hominem
Category: Fallacies of Relevance (Red Herrings) → Ad hominems (Genetic Fallacies)

A Circumstantial ad Hominem is a fallacy in which one attempts to attack a claim by asserting that the person making the claim is making it simply out of self interest. In some cases, this fallacy involves substituting an attack on a person's circumstances (such as the person's religion, political affiliation, ethnic background, etc.). The fallacy has the following forms:

  1. Person A makes claim X.
  2. Person B asserts that A makes claim X because it is in A's interest to claim X.
  3. Therefore claim X is false.
  1. Person A makes claim X.
  2. Person B makes an attack on A's circumstances.
  3. Therefore X is false.
A Circumstantial ad Hominem is a fallacy because a person's interests and circumstances have no bearing on the truth or falsity of the claim being made. While a person's interests will provide them with motives to support certain claims, the claims stand or fall on their own. It is also the case that a person's circumstances (religion, political affiliation, etc.) do not affect the truth or falsity of the claim. This is made quite clear by the following example: "Bill claims that 1+1 =2. But he is a Republican, so his claim is false."

There are times when it is prudent to suspicious of a person's claims, such as when it is evident that the claims are being biased by the person's interests. For example, if a tobacco company representative claims that tobacco does not cause cancer, it would be prudent to not simply accept the claim. This is because the person has a motivation to make the claim, whether it is true or not. However, the mere fact that the person has a motivation to make the claim does not make it false. For example, suppose a parent tells her son that sticking a fork in a light socket would be dangerous. Simply because she has a motivation to say this obviously does not make her claim false.

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2
Poisoning the Well
Category: Fallacies of Relevance (Red Herrings) → Ad hominems (Genetic Fallacies)

This sort of "reasoning" involves trying to discredit what a person might later claim by presenting unfavorable information (be it true or false) about the person. This "argument" has the following form:

  1. Unfavorable information (be it true or false) about person A is presented.
  2. Therefore any claims person A makes will be false.
This sort of "reasoning" is obviously fallacious. The person making such an attack is hoping that the unfavorable information will bias listeners against the person in question and hence that they will reject any claims he might make. However, merely presenting unfavorable information about a person (even if it is true) hardly counts as evidence against the claims he/she might make. This is especially clear when Poisoning the Well is looked at as a form of ad Hominem in which the attack is made prior to the person even making the claim or claims. The following example clearly shows that this sort of "reasoning" is quite poor.

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4
Appeal to Common Practice
Category: Fallacies of Relevance (Red Herrings)

The Appeal to Common Practice is a fallacy with the following structure:

  1. X is a common action.
  2. Therefore X is correct/moral/justified/reasonable, etc.
The basic idea behind the fallacy is that the fact that most people do X is used as "evidence" to support the action or practice. It is a fallacy because the mere fact that most people do something does not make it correct, moral, justified, or reasonable.

An appeal to fair play, which might seem to be an appeal to common practice, need not be a fallacy. For example, a woman working in an office might say "the men who do the same job as me get paid more than I do, so it would be right for me to get paid the same as them." This would not be a fallacy as long as there was no relevant difference between her and the men (in terms of ability, experience, hours worked, etc.). More formally:

  1. It is common practice to treat people of type Y in manner X and to treat people of type Z in a different manner.
  2. There is no relevant difference between people of type Y and type Z.
  3. Therefore people of type Z should be treated in manner X, too.
This argument rests heavily on the principle of relevant difference. On this principle two people, A and B, can only be treated differently if and only if there is a relevant difference between them. For example, it would be fine for me to give a better grade to A than B if A did better work than B. However, it would be wrong of me to give A a better grade than B simply because A has red hair and B has blonde hair.

There might be some cases in which the fact that most people accept X as moral entails that X is moral. For example, one view of morality is that morality is relative to the practices of a culture, time, person, etc. If what is moral is determined by what is commonly practiced, then this argument:

  1. Most people do X.
  2. Therefore X is morally correct.
would not be a fallacy. This would however entail some odd results. For example, imagine that there are only 100 people on earth. 60 of them do not steal or cheat and 40 do. At this time, stealing and cheating would be wrong. The next day, a natural disaster kills 30 of the 60 people who do not cheat or steal. Now it is morally correct to cheat and steal. Thus, it would be possible to change the moral order of the world to one’s view simply by eliminating those who disagree.

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380
Ad Hominem Tu Quoque
AKA "You Too Fallacy"

Category: Fallacies of Relevance (Red Herrings) → Ad hominems (Genetic Fallacies)

This fallacy is committed when it is concluded that a person's claim is false because 1) it is inconsistent with something else a person has said or 2) what a person says is inconsistent with her actions. This type of "argument" has the following form:

  1. Person A makes claim X.
  2. Person B asserts that A's actions or past claims are inconsistent with the truth of claim X.
  3. Therefore X is false.
The fact that a person makes inconsistent claims does not make any particular claim he makes false (although of any pair of inconsistent claims only one can be true-but both can be false). Also, the fact that a person's claims are not consistent with his actions might indicate that the person is a hypocrite but this does not prove his claims are false.

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3
Biased Generalization
AKA Biased Statistics, Loaded Sample, Prejudiced Statistics, Prejudiced Sample, Loaded Statistics, Biased Induction

Category: Fallacies of Presumption

This fallacy is committed when a person draws a conclusion about a population based on a sample that is biased or prejudiced in some manner. It has the following form:

  1. Sample S, which is biased, is taken from population P.
  2. Conclusion C is drawn about Population P based on S.
The person committing the fallacy is misusing the following type of reasoning, which is known variously as Inductive Generalization, Generalization, and Statistical Generalization:
  1. X% of all observed A's are B's.
  2. Therefore X% of all A's are B's.
The fallacy is committed when the sample of A's is likely to be biased in some manner. A sample is biased or loaded when the method used to take the sample is likely to result in a sample that does not adequately represent the population from which it is drawn.

Biased samples are generally not very reliable. As a blatant case, imagine that a person is taking a sample from a truckload of small colored balls, some of which are metal and some of which are plastic. If he used a magnet to select his sample, then his sample would include a disproportionate number of metal balls (after all, the sample will probably be made up entirely of the metal balls). In this case, any conclusions he might draw about the whole population of balls would be unreliable since he would have few or no plastic balls in the sample.

The general idea is that biased samples are less likely to contain numbers proportional to the whole population. For example, if a person wants to find out what most Americans thought about gun control, a poll taken at an NRA meeting would be a biased sample.

Since the Biased Sample fallacy is committed when the sample (the observed instances) is biased or loaded, it is important to have samples that are not biased making a generalization. The best way to do this is to take samples in ways that avoid bias. There are, in general, three types of samples that are aimed at avoiding bias. The general idea is that these methods (when used properly) will result in a sample that matches the whole population fairly closely. The three types of samples are as follows...

Random Sample: This is a sample that is taken in such a way that nothing but chance determines which members of the population are selected for the sample. Ideally, any individual member of the population has the same chance as being selected as any other. This type of sample avoids being biased because a biased sample is one that is taken in such a way that some members of the population have a significantly greater chance of being selected for the sample than other members. Unfortunately, creating an ideal random sample is often very difficult.

Stratified Sample: This is a sample that is taken by using the following steps: 1) The relevant strata (population subgroups) are identified, 2) The number of members in each stratum is determined and 3) A random sample is taken from each stratum in exact proportion to its size. This method is obviously most useful when dealing with stratified populations. For example, a person's income often influences how she votes, so when conducting a presidential poll it would be a good idea to take a stratified sample using economic classes as the basis for determining the strata. This method avoids loaded samples by (ideally) ensuring that each stratum of the population is adequately represented.

Time Lapse Sample: This type of sample is taken by taking a stratified or random sample and then taking at least one more sample with a significant lapse of time between them. After the two samples are taken, they can be compared for changes. This method of sample taking is very important when making predictions. A prediction based on only one sample is likely to be a Hasty Generalization (because the sample is likely to be too small to cover past, present and future populations) or a Biased Sample (because the sample will only include instances from one time period).

People often commit Biased Sample because of bias or prejudice. For example, a person might intentionally or unintentionally seek out people or events that support his bias. As an example, a person who is pushing a particular scientific theory might tend to gather samples that are biased in favor of that theory.

People also commonly commit this fallacy because of laziness or sloppiness. It is very easy to simply take a sample from what happens to be easily available rather than taking the time and effort to generate an adequate sample and draw a justified conclusion.

It is important to keep in mind that bias is relative to the purpose of the sample. For example, if Bill wanted to know what NRA members thought about a gun control law, then taking a sample at a NRA meeting would not be biased. However, if Bill wanted to determine what Americans in general thought about the law, then a sample taken at an NRA meeting would be biased.

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