Friday, March 7, 2014

Google Scholars and Statisticians or "Why I've Stopped Giving a Shit"

Over the past 2 years, I've spent a great deal of time on the internet; not because I don't have a life (although that much is true), but because I was internally learning and documenting something.

At the time of my arrival for a long-term stay on the internet, I had no idea what I was going to find. There are vast communities of people who hold views that I saw (and for the most part, still see) as being absolutely ridiculous. They went against everything I had ever been taught, and it challenged me to look deeper into the subjects I had already been introduced to.

For many of these topics, knowledge of statistics is imperative, because no matter what field you go into, you can be sure that you'll need to allude to some type of statistic to make your case; without it, you haven't much of a basis for new claims. However, as the old saying goes, there are lies, damn lies, and then there are statistics. Many people use statistics falsely or manipulatively -- it's difficult to understand because a lot of times, statistics can just be molded to fit your preconceptions; in these cases, you'll find that more often than not, there are counter-statistics that show the opposite of what the last data set suggested. There are also times where you find statistics supporting your claims, but fail to understand the nature of those statistics. There are also those situations where people blindly regurgitate studies and "statistics" to prove their case, but those sources are flawed for one reason or another.

At the same time, there are "Google Scholars" who base their information off of what they find on the internet, and not from what they've been introduced to through formal education. These people, as I've found, are almost always mistaken, because in simply looking things up in an attempt to prove something (or even simply learn), you'll often skip a few steps in the process, as there is no formal organization to what you're investigating most of the time. For example, in my post on "Lewontin's Fallacy" and Race (note how I'm not using links, because it adds to my point), somebody tried telling me that there is less variation between dogs, wolves and coyotes than there is between human races. They based this off of citing a book, which I have now read and reviewed, on the evolution of dogs, which alluded to mt-DNA. If the person knew what mt-DNA was before citing it as evidence, and understood how those species have evolved, they wouldn't have cited the book as evidence.

So what is the relevance of all of this?

I had two posts planned in the upcoming weeks: one on explaining falling fertility rates in developed countries, and one explaining racial disparities in violent crime. Both were inspired by the "race realist" crowd and the latter was specifically inspired by Jared Taylor and American Renaissance. What were the cases being made in my posts?

In my post on falling fertility rates, I planned on providing explanations which had substantial evidence, and dismissing claims that had been otherwise disproved (such as feminism, contraception and homosexuality all being explanations for falling TFR. Of course, the former doesn't explain falling TFR in Japan, the second has been shown to have minimal effect, and the latter shows no significant trend). In my post on race and crime, I planned on providing explanations for why there is a high correlate (and yes, there is a correlate). These explanations include poverty, socioeconomic status, population density, and so on. Other claims would assert that black people are just more likely to commit crime for the simple fact that they're black. This, of course, ignores decades of research in criminology, and ignores dozens of other hypotheses which have been shown to have a direct correlation, unlike race.

For the first post, it's very easy to find information. For the second, things can become tricky or misleading. Last night, I sat beside a friend of mine explaining the nature of the correlates, and we noticed that there really is a higher rate of crime committed by blacks than whites. I spent some time trying to figure out how the nature of the statistics may be skewing the results, such as the example of how minority groups are naturally skewed towards committing a higher rate of interracial crime by the simple fact that they're a statistical minority. It took me a while, but then the answer hit me like a brick in the face, and I felt so ashamed of myself for forgetting everything I had ever been taught in criminology.

Poverty, no shit Sherlock (regression analysis shows that poverty can explain at least half of the racial variance in crime).

I immediately deleted both of my posts and came to write this one.

In hearing all of these new hypotheses on the internet, I had turned away from the research that had already been done on the topics. For many of the subjects, it doesn't take much to disprove the claims I had heard: really, Wikipedia has done a good job of that on its own.

Yet I've spent so much time stressing over people who take idiotic stances such as denying anthropogenic climate change, criticizing Canadian health care, accusing feminists/homosexuals as being responsible for falling fertility rates, or claiming that blacks are inherently prone to criminal behavior (or are naturally less intelligent than whites). Many of these claims can be dismissed with about as much effort as it takes to find evidence for them, and many of these topics have largely been addressed and are now ignored by relevant experts.

The point of studying and analyzing these topics, for me, was to show people answers to questions that may not be intuitively obvious; however, for a majority of the subjects I've addressed, if someone wants the answer, they can easily find it.

Most internet debates, then, are for people who have already come to their own conclusions and don't care to challenge them; they have an agenda now.

Thus ends my case study of internet debating/conflict -- in such nonconstructive arguments, my time is wasted, and I am not coming to any new or revolutionary conclusions. Most of the time, I'm just reaffirming what has already been known for years and is now taught extensively in relevant institutions and fields of study. This being said, from now on, I'm going to seriously reconsider what I discuss on my blog, and when I come up with an idea, I'm going to ask myself: "has this already been said a thousand times before?"

Because if a thousand voices all confirming the same thing still haven't convinced the (m)asses, then my voice probably won't change it either.

Thank you for reading.

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