Wednesday, August 6, 2014

Counting Cancer

Bleak accounting.

Best line:  "To understand the Bailar-Smith analysis, we need to begin by understanding what it was not."  The reason that I like that one so much has nothing to do with the Bailar-Smith analysis, of course.  I like it because it illustrates an important truth about critical reading; most of the time, we spend all of our time talking about what a text says, but what about what it doesn't say?  Where does it leave matters unclear?  By examining those questions, we can begin to understand the arguments of text at their deepest level.

Here is what this section makes me think:  One CAN argue with data.  What the data tells us can sometimes depend on what the provider of the data wants us to think. And sometimes, we can tell what they want us to think by what they don't say as much as what they do say.

3 comments:

  1. One of the biggest issues with arguing with data, aside from the bias each person is going to apply to it (whoever is presenting the data might view some things as more important than others) as you pointed out, is that it only helps if people listen to it. What I have experienced in all my 16 years of being alive is that people don't listen to data when it doesn't agree with them.
    People form opinions about everything, even without data. They decide that this is true, or that is true, based on what they hear on the news or online. That wouldn't really be a problem, except that they then cling to this uninformed decisions with a passion. They are loath to admit that they were wrong, and so they are far more likely to listen to someone who agrees with them, yet has little evidence to back up their argument, then to change their mind and listen to someone who has mountains of evidence. Now, when you confront a disease like cancer, you run into the issue of radical mastectomy. Though the evidence pointed to a lack of results from radical surgery, what people heard in the news and from friends told them it worked, and once the public gets an idea into their head, it takes a long time to convince them they're wrong.
    Another problem I've just thought of, which goes along with bias, is that data rarely ever points in one single direction. More often than not, many conclusions, all perfectly valid, can be drawn from the same information. To tie this all in, it means that, due to the bias people apply to information and the preemptive opinions that are formed, data is actually one of the least important argumentative assets, outside of science.

    I don't actually know if ANY of that made sense. It did in my head!

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    Replies
    1. Sorry. I just realized that I probably misunderstood what you were saying. I think I'm actually agreeing with you...sorry...

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    2. You are agreeing with me :) But, you don't have to be sorry. I am grateful for the way that you expanded upon my idea. I should add that I like the way that the data is used to help Bailar and Smith come to a conclusion about prevention and then the way that Mukherjee has used this to transition to Part Four.

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