Argumentation in science talks a lot about the evidence side of things and how to provide a argument through science. With science you can use receive testimony and statistics. These are both things that we have talked about earlier in the year and are important aspects of this chapter. Statistics in science is important because "arguments are frequently based on statistical probability and are always open for further questioning" (Pg.218). When a person can make an argument and provide statistical evidence to that argument it makes their argument stronger. For example if I said "money grows on trees" most people would shoot down my argument claim. But if I said " 2/3 scientists state that money grows on trees" and then provide a credible source, more people are reluctant to believe what I am saying. Therefore it's important for scientist to require statistics from their data or labs etc to help support an argument. Whereas testimony, "stands alone as grounds for an argument from authority" (Pg. 219). It can stand alone because it allows a person to express their opinion or talk about facts that they are aware of in relation to the argument. I personally believe that statistics help an audience to believe or side with an argument more than testimony would but if the two are combined, they're most powerful. For example if someone gives a testimony on what they maybe know about global warming but then provide statistical evidence, they instantly come off as more applicable to talk about the topic at hand. Statistics and Testimony are extremely important in science because science gives us statistics and science gives people a reason for testimony.
There were a couple of terms I found in this chapter that I wish were explained a little more. First, the concept of uncritical responses to refutation is only covered briefly. I think that this is one of the most fundamental barriers to effective public argumentation in the United States right now. I find this issue most concerning for the liberal party. Recalling the last election and the concept of 'incremental' argumentation, I feel that people demonstrated a massive failure of critical thinking by voting for third parties or not voting. People who were disappointed with Hillary Clinton's candidacy in place of Bernie Sanders decided to either continue voting for Bernie or not vote altogether. Neither of these strategies amounted to effective support of their cause, and they constitute the uncritical "knee-jerk" reaction described in this chapter. In this case, uncritical response to opposition worked directly against the interests of the decision-makers. A...
Hello, Brooke! I enjoyed reading your blog post about argumentation in science. I have to agree with you that statistics do provide a more logical appeal to accepting an argument. I think that if statistics were not provided for an argument such as the one you made about money growing on trees then I would not believe it. But also I find it important that testimony is another factor that supports statistics. For example, if someone who is losing weight uses weight watchers it can be scientifically proven with facts that it works, but until someone shares their experience with it the decision maker may not feel confident in buying into it. So I think it depends on what is being argued as well, for sure I believe that both of these things can be used congruently.
ReplyDeleteHi Brooke. I believe your post encapsulates Chapter 13 effectively and you provided strong analysis of various components of argumentation in science to help all of us better comprehend how to approach scientific argumentation. I especially enjoyed when you spoke about statistics, and I think we should definitely be paying close attention to them. We should be thorough in our analyses of statistics to make sure not only that they come from credible sources but also that the statistics aren't misleading or are manipulated to serve a particularly biased agenda. I feel like we see this especially in the realm of social media. I often stumble across misleading statistics and unreliable sources used in articles or in arguments used on social media platforms on a daily basis. I believe we all can be more responsible in making sure we provide critical analysis of statistics we come across in any setting, especially on social media platforms.
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