Fallacies Logical Fallacies Slippery Slope Is a Term Paper

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Fallacies

Logical Fallacies

Slippery slope is a logical fallacy where one event is said to lead to another event, which in turn leads to another event, which in turn has significant consequences. For example, a person might argue that if one person is given a pay rise, everyone else will expect a pay rise, and that everyone will expect continual pay rises, and that the organization will go bankrupt. The fallacy occurs because there is no definite link between the initial event and the ones that are said to follow it. The problem in relation to critical thinking is that there is no validity to the reasons. This is especially problematic because the reasons are based on what might happen, with the possibilities of what might happen almost endless. This means that for every event there will be the possibility of coming up with a series of chain reactions that lead to some terrible consequence. However, just because the consequence is a possibility does not mean that it will happen. The other problem in regards to critical thinking is that a slippery slope argument can be effective because many people will react to the possibility of the final consequence. This means that even though the argument is not valid, it can still be effective because it draws on people's fears. An individual can then agree with the argument based on an emotional response linked to their fear.

An example of the slippery slope argument can be seen in the Entrepreneur magazine article titled "Risky business: Before a defective product becomes your downfall, learn how to protect yourself." In this article, Henricks argues that defective products can lead to an organization's downfall, calling defective products "seeds of destruction." Henricks uses this argument to convince organizations and entrepreneurs to take action to avoid litigation from defective products. The slippery slope argument made is that a defective product will lead to the injury of a consumer or vendor, that litigation will result, and that this litigation will cause the organization to go bankrupt and fail. This is a logical fallacy because it is not definite that the series of events will occur. A defective product will not necessary cause an injury. If an injury is caused, it will not necessarily lead to litigation. And if litigation does occur, it will not necessarily lead to bankruptcy. This shows that there is no definite link established between the initial problem and the final consequence. Instead, the series of events described are based on assumptions about what will happen because of the initial problem. This makes the claim an example of the slippery slope fallacy. As noted, Henricks uses this argument to convince organizations and entrepreneurs to take action to avoid litigation. The argument works based on creating fear in readers because of the prospect of failure and bankruptcy. This shows how even though the argument is based on a fallacy, it can also be convincing to readers who may be motivated by the fear of the possible consequences.

Hasty generalization is another logical fallacy. Hasty generalization occurs when a conclusion is made based on a sample that does not represent the norm. This can include a sample that is too small to make a general conclusion, or a sample that does not represent the conclusion that is being made. An example might involve stating that 50% of consumers do not like a product based on a sample of only four people, where two said they like a product and two said they did not. In this case, the sample size is not large enough to establish that 50% of all consumers dislike a product. Another example might involve saying that most employees prefer having a male boss, with this conclusion based on interviewing the employees of one male boss and the employees of one female boss. This conclusion is a hasty generalization because the sample does not represent the whole population and because the sample may not be a measure of whether male or female is preferred. Instead, the preferences of the sample may be based on the nature of the individual and not on whether they are male or female. Another example might involve concluding that employee stress levels have decreased in recent years, based on a sample that only includes part-time workers. This is a hasty generalization because the sample does not match the conclusion being made, but represents only a portion of the population. The problem with the hasty generalization fallacy is that the reasons for the conclusion are not a valid support for the conclusion. This is especially problematic because in some cases the reasons for the conclusion will not be stated. For example, an author might say that 1 in 10 people are unhappy with their working conditions, but not provide the details of what sample this is based on. This can result in people accepting the statistic without questioning whether or not it is valid. Even if the sample information is provided, many people will notice the statistic more than the sample and not notice that the sample makes the statistic invalid.

An example of the hasty generalization fallacy is seen in the Entrepreneur magazine article titled "Risky business: Before a defective product becomes your downfall, learn how to protect yourself." In this article, Henricks says that defective products are widespread. The support given for this conclusion is a consumer report finding that 1 in 3 toys violated safety standards. This is a hasty generalization because the article does not refer specifically to toy manufacturers, but to manufacturers in general. This means that the 1 in 3 finding of defects in toys does not mean that all products have a similar defect rate. For this reason, this evidence does not mean that defective products are widespread. The evidence only shows that defective toys are widespread. However, the author uses this evidence to make a generalized claim about all products. This example of the fallacy also shows how many readers may not take in the detail that the statistic is related only to toys. Instead, the 1 in 3 finding may stand out more and be the detail that is noted. Because of this, readers might accept the author's claim that defective products are widespread even though there is no valid evidence given. Another example is seen in "Do women manage differently?," which describes the CEO of Warnaco, Inc., Linda Wachner. In this article, it is argued that women have a different management style than men. This is done by describing Linda Wachner's management style. For example, Wachner is described as being encouraging to her staff. This is followed by the statement that "women are comfortable persuading, encouraging, and motivating, while men often want to issue orders and have them followed" (Daft 1997, p. 27). This is an example of a hasty generalization because Linda Wachner is not a true representation of how all women manage. This is a case where the sample size of just one person is not enough to make a generalization about all women.

Post hoc is a fallacy where a connection is assumed between two events simply because one happened before the other. For example, an organization might achieve record sales in a certain month. It might be assumed that this is because a new manager was hired the month before. While this is possible, if there is no definite link to show that the new manager caused the increased sales, than this is a post hoc fallacy. As another example, an employee might make an error one morning and be told that they are being retrenched in the afternoon. They might assume that they are being retrenched because of the error just because it happened previous to being retrenched. In reality, they may be…

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