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Discussion in 'GMD Social Forum' started by Zephyrus, Jan 20, 2015.
trying to work out if this was supposed to indicate money or jizz
It's a tiny violin stop projecting you degenerate.
Yeah. As reprehensible as genuine racism is, a lot of what passes for "anti-racism" nowadays is just a war on noticing.
Noticing racial differences?
Ah, just making sure I understand.
Can noticing be a neutral/indifferent behavior?
I feel that a large part of the argument between FD and HBB had to do with HBB's assumption that "noticing" a larger percentage of blacks than whites commit crimes. "Noticing" this fact led HBB to describe blackness as a predictor for crime, which isn't actually a factual statement--it's an interpretive statement, and interpretations are never neutral.
I'd suggest that noticing certain details of everyday life are almost always inextricable from the interpretations we derive from them, meaning that noticing itself is always a prejudiced behavior that deserves some discussion (maybe not the media excess that we find on the internet nowadays, but in some measured capacity).
And yes, I realize that what I just said is an interpretive statement.
I believe he eventually qualified it as non-immigrant blacks in America is a predictor for criminality, which of course would still be problematic to many people anyway.
Non-immigrant blacks are responsible for a disproportionate amount of crime, violent and otherwise. Calling these descriptive statistics "interpretative" requires some degree of mental gymnastics. Now, the word "predictive", to be used more empirically, requires other statistical analyses. You could call these analyses "interpretive", but so what? How dare we attempt to make sense of the data?
Larry David was taken to task for noticing the level of representation of Jews among the accused Hollywood harassers. Ironically, their representation is probably proportional or even below the proportional to the number of Jews in the entertainment industry, but we can't be sure because those sorts of statistics aren't readily available. The ADL and similar organizations would rather no one even have descriptive statistics of anything, since those are needed to begin informed interpretations.
Edit: Of course, somehow no one bats an eye when the opioid crisis is considered a "white problem".
I didn't call the statistics themselves interpretive, although someone with more acumen than I probably could decipher how they are, to some degree. I called the predictor comment interpretive, and suggested (interpretively) that interpretations of data are probably inextricable from our noticing them, making it difficult to see how noticing is a purely passive/neutral/indifferent act. Even statistical analysis has to be perspectivally oriented (i.e. we have to choose what phenomena we wish to observe).
Also, what makes you think I'm saying we shouldn't interpret data? My entire career is founded on the notion of interpretation. All I'm saying is that interpretation can't be foreclosed to criticism, even if some of the criticism is ideologically motivated and/or rhetorically vacuous. I think the resistance you find to certain comments has to do with the idea that interpretations based on statistical evidence are somehow immune to criticism.
Shit really hits the fan when opportunism meets interpretive data.
Agenda A makes it about race, agenda B makes it about poverty, agenda C makes it about values, agenda D makes it about culture, agenda E makes it about police practices and they're all looking at the same data.
There's a degree to which we don't choose what to observe, at least not directly. If you live in a high crime environment, you will have different observations than someone who lives in a gated community. If you happen to buy the NYT, you will have different observations than someone who reads TMZ. Now those are more superficial examples compared to statistics collecting, but if we want to talk about crime, to what degree can one claim bias in routine governmental crime stats collecting? The US collects more thorough statistics than all countries afaik, as it relates to crime. While you can massage data, there's little evidence that is occurring in crime statistic collection and reporting.
I'm resistant to moralizing over the data.
I don't think it's moralizing to suggest that blackness as a predictor for crime disregards alternative contributing factors, whether they be class, education, socioeconomic opportunities, lifestyle representation, etc. Or additionally, to suggest that statistics are filtered through definitions and degrees of criminality that can be easily manipulated.
It's not that the numbers themselves are inaccurate, but that they don't reflect a stable motivation, cause, or category for the crimes they document.
Can you provide an example of this filteration?
That the definition for violent crime includes unarmed burglary in some states, but not in others; drug trafficking in some states, and not in others. Or that a nonviolent crime becomes violent if a police officer sprains his ankle during an arrest. Or that violent crime is sometimes defined by the occurrence of bodily injury, which downplays threats of violence or intention to commit violence, etc.
My point is that there are statistics for violent crime that tag unarmed offences as violent, and that tips the scales. If someone is simply in possession of an illegal firearm while transporting drugs, that doesn't make the crime an unequivocally violent offense; but it does rationalize calling it a violent offense when an officer can say "he has a gun."
Well if the data is cherry picked state by state that may be an issue, but the FBI's UCR attempts to bypass these potential issues with uniform reporting:
Part I offenses could generally be described as "violent crimes", while Part II offenses are not. But "violent crime" isn't explicitly a UCR term, although on page 55 it does refer to "Part I violent crimes", which may be in reference to the distinction between crimes against persons vs crimes against property eg, Part I Offenses against Persons being violent crime. If we wanted to be uniform, we might simply use Part I/Part II designators.
No, it's factual. Correlative and not necessarily the essence of the link, but still factual. One can measure the percentage of X, Y, and Z people in various populations, measure incidence of Q event in the same populations, and mathematically determine whether or not the presence of any of said people in said population predicts the incidence of Q event. The interpretation comes after; "The presence of X people but not Y and Z people predicts Q event BECAUSE <insert opinion here>."
That's a good thing for collecting general stats, you're right; although it doesn't do anything about the ways that certain areas define various kinds of crime.
Unfortunately, crime stats by race don't communicate the alternative social causes that likely contribute to crime. So, again, choosing to collect stats on "frequency of crime by race" (or some such) is already making an interpretive move. For what it's worth, I think they're important statistics to have. But the observation is already interpretive, since it's choosing a particular set of parameters.
Describing them as "X people" is an interpretive move. You could alternatively choose to describe them as "black people" or "poor people," or "non-white people" or "uneducated people." Each label carries its own interpretive connotations.
This is a major topic in philosophy of science, and it has to do with whether observations are theory-loaded or not, to use language from Ian Hacking and Paul Feyeraband. Observations of unknown quanta (e.g. detecting radio waves before their classification) could be argued as theory-free observations. The problem is you can only really identify a theory-free observation ex post facto. It's incredibly difficult to distinguish theory (or interpretive connotations) from pure observation in the act of doing so.
Does it disregard it or does the very idea of blackness as a predictor include class, education, socioeconomic opportunities, lifestyle representation etc? I'd assume all these alternative contributing factors are why blackness is a predictor because they're all overwhelmingly part of what it means to be a non-immigrant black person in America.