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Slippery Slope

Slippery slope is a fallacy in which a person asserts that one event follows another and so on, thus forming a chain reaction of these events. It is said to be fallacious, since even though there is no proper argument available for the next event to occur, it is believed it will definitely occur.

There have been many real examples as far as slippery slope is considered, and we ourselves forms one part of it. For instance, if we consider a case of legalising the practice of euthanasia, one may readily follow a conclusion that it will result in non-voluntary or even involuntary euthanasia. Thus, it is believed first step itself should be curbed in order to stop the series of steps.

We are well aware that when a minor heart attack occurs, we believe it will definitely result in major heart attack, though there is no direct link between two. Similar is the case with obesity, it is believed obesity will result in new diseases, though fat person can also be medically fit.

In recent years, the world has observed new diseases like SARS, MERS and Ebola, which are resulting in slippery slope, and people believe every new disease is going to cause the number of deaths than the previous known diseases.

Currently, some people believe allowing same sex marriage may result in new kinds of sexual diseases and far stronger than HIV and syphilis, while others believe it may have consequence that people may even demand marrying their animals. This is a complete fallacy.

Another example is, if we ban smoking, then people will start taking soft drugs and then move on to hard drugs, and the crime rate will go up and up. We should therefore prevent crime by allowing smoking. Live in relationship in itself provides basic sexual needs, so it will result in less number of marriages is another slippery slope. What we have observed so far is that first step in itself should be so strong so as to provide greater slope that may result in more number of resultant events.

At last, it all depends on us whether we go with logical consistency and use some statistics to find the result or we simply hit in dark to reach the consequence, which will eventually provide slippery slope and will result in false result that may not be the actual result of the first step.

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