Yea but you're ignoring biases in the data that are difficult or impossible to disentangle from the underlying effects. What happens when you see an area with 50% higher violent crime rate? Is that because there are a large number of crimes? Or is it because it's a neighborhood that is disproportionately targeted by police? How do you even attempt to control for that?
It's not that Bayesian stats can't help or can't offer insights, it's that it can easily reinforce underlying societal biases, and then it's harder to question because "it's science" and no one has to take any responsibility for its effects.
Our knowledge of crime rates doesn't come form arrest records, but rather victims surveys. Yes, we know that certain neighborhoods/populations have higher rates of crime and not just arrests.
I was arguing that it's not "premature" to analyze crime and policing data statistically. If we include and add in your insights--and I think it's foolish to think crime experts haven't thought of them before, but if they haven't:
I would still argue that it's not "premature" to look at crime and policing data; in fact, I'd say it's high time we did it.
tl;dr you are not addressing what I was arguing
(and to everybody else here, I was not advocation Bayes Theorem, I was relying on it as a baseline truth for synecdoche for statistical analysis. If you want to object to Bayes Theorem, that's on you, it wasn't my point...)
no one is objecting to Bayes' Theorem here at all. I am directly addressing your argument: there is _inherent_ bias in policing data, and doing a Bayesian analysis will make it very easy to fool ourselves into trusting the results while also allowing everyone in the room to absolve themselves of taking any responsibility for the consequences of doing so. Pretending we know how to debias policing data _broadly_ (i.e. we know how to do it in every locale and in every instance that the data will actually be _used by practicing law enforcement professionals_) is a perfect recipe for disaster.
what are you arguing for? no analysis? or do you wish to change the analysis? Or why do you claim that analysis is premature to remain on topic?
saying "inherent bias" is very vague and has more value as a political dog whistle than anything else... unless you'd like to suggest what the biases are and point out how you have this special knowledge and other crime experts don't.
for example, what is the bias in incoming 911 calls?
> what are you arguing for? no analysis? or do you wish to change the analysis? Or why do you claim that analysis is premature to remain on topic?
There's a difference between a team of academics/statisticians analyzing policing and crime data and then debating the resulting conclusions, and a widespread set of predictive policing tools that are designed to be used by feet on the ground. The former is great! and important. The latter is the problem.
> saying "inherent bias" is very vague and has more value as a political dog whistle than anything else... unless you'd like to suggest what the biases are and point out how you have this special knowledge and other crime experts don't.
The entire point I'm trying to make is that it's very _difficult_ to figure out what your data biases are because usually the data is _all you have_. My point isn't that I have "special knowledge" about where the biases are. I do not have any such special knowledge. Domain experts will have more "special knowledge" and by that I mean through their experience they will have hopefully learned difficult lessons about the limitations of certain types of data available to them, but even they will not have perfect knowledge about where all of the biases in their data are.
> for example, what is the bias in incoming 911 calls?
again, I do not know! Do you? Do you feel 100% sure to say that the propensity of someone to dial 911 would not be dependent on socioeconomic factors, or on the nature of the crime, or on the alleged perpetrator? Do white people feel more comfortable calling 911 on black or brown people than black or brown people calling 911 at all?
You can try to correct for certain biases if you have access to all of the relevant info (e.g. in the above example, we could in fact try to answer this question if (1) we had the actual background rate of crimes being committed, independent of 911 calls, (2) all of the relevant information (e.g. race/income of caller and perpetrator, the crime type, etc.), and even then we would be missing other biases that we may not be consciously trying to "correct" for). But even this is subject to lots of error (how do we get the actual baseline level of crimes? hint: you can't), and will miss other factors that we haven't thought of.
It's not that Bayesian stats can't help or can't offer insights, it's that it can easily reinforce underlying societal biases, and then it's harder to question because "it's science" and no one has to take any responsibility for its effects.