"One woman stated that it even made guys look "manly". So manly equals violent?" (529)
In Gayle Smith's "The Wife-Beater", many fallacies are used. This quote can been seen as a hasty or sweeping generalization because she is using only one woman's reaction to jump to the conclusion that every woman thinks that the shirts make men look more manly. She is also jumping to the conclusion by saying someone looks manly means that they are also violent just because of the common name the shirt has developed. She uses her own emotions to connect the woman's reaction to her point she is trying to make, when there is no evidence to prove the other women agrees that manly equals violent, or that the shirt portrays that thought.
A fallacy is in the quote "Everybody wears them" (528). Here Smith again is using hasty or sweeping generalization. She is trying to hook the reader in to her article by finding some common ground they can agree on. This might have worked better if she used the word "majority" instead of "everybody". This overwhelming generalization that everyone wears a wife-beater stated in the very first sentence of her article is a fallacy, therefor possibly affecting the reader to feel that the rest of what she is saying may not be accurate and view her argument as invalid.
"More than 4 million women are victims of severe assaults by boyfriends and husbands each year" (529). Smith tries to play on to the reader's emotional side by giving this sad statistic. She also tries to use this to strengthen her argument. But the problem with that is that it has no relevance to the previous statement or to the argument as a whole she is trying to make. Although the statistic may be true, there is no effective reason to put it into her argument because it is irrelevant. This type of fallacy is known as Non Sequitur (It Does Not Follow)
In your first statement about the quote, "Manly equals violent?" I think you are right when the authors uses the fallacy, hasty or sweeping generalization. The author makes reference to one woman stating that men look manly when they wear the wife-beater t-shirt. I agree that she only uses one woman's opinion, and makes it seem as though it's how all women feel. Her argument is weak and doesn't convince me that all men who wear these shirts are violent.
ReplyDeleteYour second point makes a lot of sense. It is a very sweeping and broad statement, but is also very untrue. It is a good introduction to her argument and is very attention grabbing, it makes you want to continue reading to find out what she is talking about.
When you talk about the Non Sequitur fallacy, I see your point that she goes off topic of the t-shirt argument. I also think that this quote also goes well with the fallacy misleading statistics, because she uses what could have been a random number that she just made up. She doesn't reference her statistics to any kind of research study. She uses the statistic to grab the reader attention, but also to appeal to the readers emotions and empathy for abuse victims. Your blog on this argument really caught my attention, it got me thinking deeper about the term "wife-beater", its negative message, and how people use it freely and without thinking about what the phrase "wife-beater" really means for victims of abuse.
Hey Shaena,
ReplyDeleteI agree with your first fallacy. The way the author stated the quote was a harsh way to put it. She is essentially saying that all manly men are violent, which is very invalid. I also think that this fallacy could be classified as Personal Attack, or Argument Ad Hominem. This fallacy affects the validity of the argument by attacking the motives or character. By doing this, it causes the readers attention to divert from the facts of an argument. Rather then focusing on the negative significance of the "Wife-Beater", the author slides the readers attention to her opinion. You also did a very good job on your third fallacy. You backed your assumption on it very well. I didn't see it this way but the author did insert a irrelevant statement into the argument. I also think that this fallacy could be acknowledged as Misleading Statistics. The author wants us to believe that the statistic is true without being proved. You showed other ways to look at the quotes and had evidence to think the way you did, great job Shaena! (: