Specifically with anti-gender-identity based hate crime, we can see that anti-transgender hate crime has one of the highest incident numbers for any individual cohort, despite knowing that only 0.6% of the population identifies as trans according to data presented earlier in this thread.
You are generalizing from the specific, here. The data that you appear to be referencing is only looking at murder rates.
You’ve then set up a straw-man argument. The straw is in the data that you’ve not incorporated into your mental model: the rates of crimes other than murder.
At question is 1) the validity of using murder rate to predict to frequencies of other victim-having crimes and 2) the validity of ignoring between-group variation when drawing conclusions about the relative frequency of crime between different groups.
Also, your methodological techniques are faulty - ease of comparison is not a means in which to determine the validity of a comparison.
https://www.pewresearch.org/fact-tank/2020/11/20/facts-about...
> Also, your methodological techniques are faulty - ease of comparison is not a means in which to determine the validity of a comparison.
This is a straw-man, nowhere do I argue that "ease of comparison is a means in which to determine the validity of a comparison." I do, however, argue that the comparison of murder rates in gen pop to the murder rates of trans pop is a valid comparison. Perhaps you'd like to elucidate why you don't think it is.
Additionally, pointing out errors of generalization and particularization is not a straw-man tactic of argument. It is a direct conflict with your argument on the grounds of scientific validity - are you actually measuring what you think you are measuring?
Setting aside that we haven’t yet established that murder rates are reliable predictors of other victim-having crimes, there is a deeper problem, that another commenter was trying to point out to you in terms of Bayesian probability.
To draw the conclusion that I drew, which I continue to defend (for clarities sake: that the LGBTQIA+ community is disproportionately affected by victim-having crime), you would need to look at data that partitions the general public into its various sub-groups and compares the frequency of victim-having crime between all of the individual sub-group, in all combinations.
Such a statistical technique is frequently used in empirical studies of populations, across disciplines.
Statistical analysis of these between-group variations is where you are able to draw out conclusions such as “blacks are disproportionally convicted of certain crimes” or “LGBTQIA+ are disproportionately victims of murder, physical abuse, emotional abuse, and widespread discrimination”.
> Perhaps you’d like to elucidate why you don’t think it is [a valid comparison]
There may very well be some valid conclusions to draw from data about murder rates for the whole population compared to a given sub-group, but that methodological technique suffers from the so-called “law of averages”.
See the Expectation values example in https://en.m.wikipedia.org/wiki/Law_of_averages, for example.
In the scientific community, it is common knowledge that research methodologies based on statistical analyses of between-group variations is a technique that is sensitive to patterns that would not appear in a comparison with the average.
I'm not sure if you're being purposefully obtuse here, but there's an obvious correlation between the drop in "violent crime" (homicide, murder, assault, manslaughter, etc.) and "violent victimization" (physical abuse, sexual abuse, verbal abuse, etc.). Do I have to calculate the correlation coefficient for you?
> In the scientific community, it is common knowledge that research methodologies based on statistical analyses of between-group variations is a technique that is sensitive to patterns that would not appear in a comparison with the average.
I don't believe the comparison here suffers from the law of averages. And even if it did, the difference between the two data sets' deviation isn't high enough to be of any significance.
I don't have a narrative. I look at the data and draw conclusions. You start with conclusions and try to morph the data to fit them. I'll even grant you that sexual crimes go underreported (heck, have 43% to bring up that number up), but even so, it wouldn't account for a "disproportionate" number of crime against trans people. It would barely equal the rate of the general population. You're seriously trying to argue that trans crimes are underreported by multiple factors? That's quite the claim.
> I think we'll have to agree to disagree, and please stop downvoting me.
FYI, you can't downvote direct children on HN.