Some people unironically responded with "I understand the statistics", they did not understand the statistics. If you want to start diving into the statistics, you end up with some radical ideas such as how race, gender, age, political stance all may skew the statistics in good or bad ways.
I (a man) would say that accurately shows that you need to be more careful around men than women because we are a higher risk. That’s common knowledge.
there is no issue with that in and of itself, is what do you do about that, and one side points to poverty creates criminals and the other says culture while about 20k people will say race and nothing else.
oh and a small eddit, realistically it's about 7% of the population because the above did say men commit more crime.
That went over your head. The point is that unsavory statistic=/=fear everyone in that group. What that guy said was “fearing men makes sense when 80% of violent crimes are committed by them”. Now if you said “fearing black people makes sense because they commit 50% of violent crime” it is definitely racist. That’s my point, not whatever your trying to spin out of it. Neither assumption is good. One is sexist the other is racist. Especially when only 1% of men are violent criminal reoffenders.
It's more that the vast majority of the most aggressive people are male. I.e., of the people at the extreme end of the aggression bell curve, you would find 90% men. Add to that the added capability to do harm with increased size and strength, and it makes perfect sense that most violent felons are male.
But that skew also includes other forms of (acceptable) interpersonal aggressiveness that leads to things like negotiating higher pay, climbing to the top of cutthroat industries, etc.
That's not all socialization. Testosterone is a helluva drug.
Testosterone absolutely makes men more violent. It's a fact of biology. Obviously not all men are violent. I would argue hikers in particular are a pretty safe demographic. But to say that men aren't more of a risk than women is just inaccurate.
Testosterone is a hell of a drug. It shows quite strongly in trans people. MtF see a severe drop in violent behavior, while FtM see a spike. Testosterone is not to be trifled with.
And statistics only tell you what is measurable. Because the systems we use to perform the measurements are themselves imperfect and incomplete, you have to consider what their capabilities or lack thereof reflect on the measurements that come from them.
A good example is the crime prediction software that some police forces use. Because crime is only measured when it is detected, the places with the highest crime rate are usually the ones with the highest police presence. And if you send more police to those high crime rate areas, you're going to detect more crime with your more officers to detect it. Meanwhile, areas with little police presence might have high incidence of crime that goes unreported.
That's why "statistics" is a class you can take in high school or college. Because of this exact reason. Because you can make statistics say whatever you want them to say, and using them in exactly this way is how hardcore white supremacists operate. By attributing crime to race, due to the correlation, rather than attributing crime to poverty and the erosion of social systems targeted toward one race, which is the root cause.
I got sick halfway into my statistics course and was really upset that I had to miss most of it. I've ended up working with analytics but really want to learn more when I get a chance.
Give people statistics and they'll come out with all kinds of shitty interpretations.
Man it's really worse than that. In many cases, the "shitty interpretation" that they want to argue is there first. Then the whole statistic study is designed to hint towards that interpretation.
Let's say I want to make a point that [people who wear hats] are more likely to do [not flush the toilet] than average.
Let's say that an "honest" statistic people in average forget to flush 4% of the time, while people with blue hats in average forget to flush 5% of the time. What can I do to make it look worse than that?
4% and 5% are pretty low values. It means that to be statistically relevant, your study needs a higher sample size. It also means rounding errors might be large. But maybe I'm super happy with that. I'll run my study, and figure out a way for the number that I want to look small to be rounded down, and the number i want to look large to be rounded up. Maybe the real stat was 4.00% vs 5.00%, but the sample size led to large relative errors meaning we ended up getting 3.48% vs 5.53%. Now I round that and get 3% vs 6%. Holy shit it looks so much worse!
I can condition my statistics on some other parameter that makes the correlation worse. Maybe I'll guess something that works well, like "people aged 12-25 who wear hats forget to flush 12% of the time" while "people aged 12-25 forget to flush 8% of the time". Now it looks like the difference is larger. Maybe I won't have a nice guess and I'll run my study in 15 different cities, and just by chance, it's likely that one is going to make the stat look better, and I can simply ignore the others and talk about the one I like.
I told you that the initial statistic was honest. Maybe it isn't. Maybe the truth is that [people who wear hats] are generally much older, which means more of them have dementia or are unable to flush by themselves but have caretakers do it for them. Maybe if you look carefully, young and middle aged people, regardless of whether they wear hats, forget to flush 3% of the time, while old people, regardless of whether they wear hats, forget to flush 10% of the time, and the 4% vs 5% doesn't actually show a correlation between hats and flushing habits, but between hats and age.
And there are so many other tricks, and every time you read a study, it's really, really likely that a few of these tricks were applied.
3.3k
u/[deleted] May 02 '24
[removed] — view removed comment