Statistics is often used to engineer equality by pouring resources into a priority group at the expense of the so-called "stronger" group, but social engineering promotes nothing but unequal opportunity--mainstreaming for one, and disenfranchisement for the other. True "equality for all" means exactly that (if one values equality, that is), so you can't both organize to benefit or prioritize one group (ie. women/children/men/wealthy/poor...etc.) at the expense of another group, and still remain an egalitarian. But there's no question that the facts of a situation are indeed the facts--that men earn more than women for instance--but the general facts shouldn't blind us and keep us from respecting and observing that people do exist outside the "average." This we tend to forget as we cater to the mediocrity of the middle. Our minds fall prey to heuristics and stereotypes, ignorance rules the day, and statistics makes it possible.
Furthermore, if it's wrong to claim about individuals, then it's wrong to claim about groups of those same individuals. Insensitivity is more than just being disrespectful to individuals, it should also include showing disrespect to groups of people. This isn't to say that we should censor ourselves, just that we should not tolerate disrespectful speech, even if the thrust of that disrespect is supported by evidence (statistics). We might agree that saying "Bobby is stupid," is insensitive, but how much less insensitive is saying, "the group that Bobby belongs to ("boys," for example) is a whole batch of stupidity"? We think we're good people when we dodge the bullet of hurting someone's personal feelings as we use statistics to justify our personal prejudices against the group that person belongs to, but it doesn't make it right, or valid, to do such. We ignore individuals and insult groups of humans en mass, and we think these numerical truths we are using to accomplish this categorization are doing society a service. They are most likely not.
I also believe in focusing on severity over statistics. Numbers are used as a form of distancing oneself from tragedy. To headline on "only 20 people killed" kind of makes whatever happened in the story seem insignificant. That's a lot different than simply saying, "20 people killed." Likewise, if only one kid got raped in a juvenile detention center in the last hundred years, who am I to disqualify the significance of that for the victim by referring back to numbers--by saying, essentially, "well, it wasn't so bad, you were the only one in the last hundred years!" The point being, if it was severe enough, and it hurt the victim, then no other quantity should get in the way of that "fact". Severity over statistics. Bruises over averages. Humans over outliers. Cases over representative samples. People before numbers.
I think this constant need to frame tragedy in a numerical context is a defense mechanism built into us to maintain our personal perspective rather than have it subject to the full weight of the tragedy itself. This is normally supposed to be of great benefit to the human, but in these times of constant information, we find ourselves turning away from tragedy at a rate unseen in human history. When you read something appalling, you automatically search for reasons to discredit what you're reading so as to not have to feel upset over it, even if it's a minuscule piece of information missing, or any tiny part that may not relate to your personal circumstances (so you don't have to believe that it happened).
This is especially true if the victim is not your typical victim (a "man" getting raped, for instance). People only seem to get fired up about things when they fit into a preconceived schema (ie. "women are always victims"), and otherwise ignore and underestimate all else to distract themselves from the validity of the tragedy before them. In all truth, I don't know what is worse, a mind like mine (which tends to take all sources of information at their word), or the multitude of minds that need constant verification for every detail before they feel any human emotion, period.
If you can find a reason not to feel bad about something you see, do you not feel better as a result? You could say then that the reason we study things at all is so we can "feel" in control of a situation we feel powerless about. Instead of feeling that gut reaction of disgust regarding rape, for instance, we study it and put a whole bunch of numbers in our heads to persuade ourselves into thinking of it in terms of percents and averages rather than faces and names. And when we do that, we underestimate the names and faces, particularly those we have cast to the side as "outliers." We create a society, an organization, that caters to the statistical average, and not only ignores the "outlier" but even flat out mocks him, and takes pleasure in his dejected circumstance. The male victim of rape is one such outlier that is routinely mocked and underestimated.
People underestimate the human element in the rightfully quantitative social sciences. I don't. I concern myself with that which people underestimate.
I also believe in focusing on severity over statistics. Numbers are used as a form of distancing oneself from tragedy. To headline on "only 20 people killed" kind of makes whatever happened in the story seem insignificant. That's a lot different than simply saying, "20 people killed." Likewise, if only one kid got raped in a juvenile detention center in the last hundred years, who am I to disqualify the significance of that for the victim by referring back to numbers--by saying, essentially, "well, it wasn't so bad, you were the only one in the last hundred years!" The point being, if it was severe enough, and it hurt the victim, then no other quantity should get in the way of that "fact". Severity over statistics. Bruises over averages. Humans over outliers. Cases over representative samples. People before numbers.
I think this constant need to frame tragedy in a numerical context is a defense mechanism built into us to maintain our personal perspective rather than have it subject to the full weight of the tragedy itself. This is normally supposed to be of great benefit to the human, but in these times of constant information, we find ourselves turning away from tragedy at a rate unseen in human history. When you read something appalling, you automatically search for reasons to discredit what you're reading so as to not have to feel upset over it, even if it's a minuscule piece of information missing, or any tiny part that may not relate to your personal circumstances (so you don't have to believe that it happened).
This is especially true if the victim is not your typical victim (a "man" getting raped, for instance). People only seem to get fired up about things when they fit into a preconceived schema (ie. "women are always victims"), and otherwise ignore and underestimate all else to distract themselves from the validity of the tragedy before them. In all truth, I don't know what is worse, a mind like mine (which tends to take all sources of information at their word), or the multitude of minds that need constant verification for every detail before they feel any human emotion, period.
If you can find a reason not to feel bad about something you see, do you not feel better as a result? You could say then that the reason we study things at all is so we can "feel" in control of a situation we feel powerless about. Instead of feeling that gut reaction of disgust regarding rape, for instance, we study it and put a whole bunch of numbers in our heads to persuade ourselves into thinking of it in terms of percents and averages rather than faces and names. And when we do that, we underestimate the names and faces, particularly those we have cast to the side as "outliers." We create a society, an organization, that caters to the statistical average, and not only ignores the "outlier" but even flat out mocks him, and takes pleasure in his dejected circumstance. The male victim of rape is one such outlier that is routinely mocked and underestimated.
People underestimate the human element in the rightfully quantitative social sciences. I don't. I concern myself with that which people underestimate.
No comments:
Post a Comment