Jon Brauer and Jake Day recently wrote a response to my build stuff post, Should more criminologists build stuff on their Reluctant Criminologists blog. Go ahead and follow Jon’s and Jake’s thoughtful work. They asked for comment before posting – I mainly wanted to post my response to be more specific about “how much” I think criminologists should build stuff. (Their initial draft said I should “abandon” theoretical research, which is not what I meant (and they took out before publishing), but could see how one could be confused by my statement “emphasis should he flipped” after saying near 0% of work now is building stuff.)
So here is my response to their post:
To start I did not say abandon theoretical research, I said “the emphasis be on doing”. So that is a relative argument, not an absolute. It is fine to do theoretical work, and it is fine to do ex-ante policy evaluations (which should be integrated into the process of building things, seeing if something works well enough to justify its expense I would say is a risky test). I do not have a bright line that I think building stuff is optimal for the field, but it should be much more common than it is now (which is close to 0%). To be specific on my personal opinion, I do think “build stuff” should be 50%+ of research criminologists’ time (relative to writing papers).
I am actually more concerned with the larping idea I gave. You have a large number of papers in criminology that justify their motivation not really as theoretical, but as practical to operations. And they are just not even close. So let’s go with the example of precise empirical distributions of burglaries at the neighborhood level. (It is an area I am familiar with, and there are many “I have a new model for crime in space” papers.) Pretend I did have a forecast, and I said there are going to be 10 burglaries in your neighborhood next month. What exactly are you supposed to do with that information? Forecasting the distribution does not intrinsically make it obvious how to prevent crime (nature does not owe us things we can manipulate). Most academic criminologists would say it is useful for police allocation, which is so vague as to be worthless.
You also do not need a fully specified causal chain to prevent crime. Most of the advancement in crime prevention looks more like CPTED applications than understanding “root causes” (which that phrase I think is a good example of an imprecise theory). I would much rather academics try to build specific CPTED applications than write another regression paper on crime and space (even if it is precise).
For the dark side part, in the counterfactual world in which academics don’t focus on direct applications, it does not mean those applications do not get built. They just get built by people who are not criminologists. It was actually the main reason I wrote the post – folks are building things now that should have more thoughtful input from academic criminologists.
For a specific example, different tech companies are demo’ing products with the ultimate goal of improving police officers mental health. These include flagging if officers go to certain types of calls too often, or using a chatbot as a therapist. Real things I would like criminologists like yourselves being involved in product development, so you can say “How do we know this is actually improving the mental health of officers?”. I vehemently disagree that more academic criminologists being involved will make development of these applications worse.
The final part I want to say is that apps need not intrinsically be focused on anything. I gave examples in policing that I am aware of, because that is my stronger area of expertise, but it can be anything. So let’s go with personal risk assessments. Pre-trial, parole/probation risk assessments look very similar to what Burgess built 100 years ago at this point. So risk stratification is built on the idea that you need to triage resources (some people need more oversight, some less), especially for the parole scenario. Now it is certainly feasible someone comes up with a better technological solution that risk stratification is not needed at all (say better sensors or security systems that obviate the need for the more intensive human oversight). Or a more effective regimen that applies to everyone, say better dynamic risk assessments, so people are funneled faster to more appropriate treatment regimes than just having a parole officer pop in from time to time.
I give this last example because I think it is a an area where focusing on real applications I suspect will be more fruitful long term for theory development. So we have 100 years and thousands of papers on risk assessment, but really only very incremental progress in that area. I believe a stronger focus on actual application – thinking about dynamic measures to accomplish specific goals (like the treatment monitoring and assignment), is likely to be more fruitful than trying to pontificate about some new theory of man that maybe later can be helpful.
We don’t have an atom to reduce observations down to (nor do we have an isolated root node in a causal diagram). We are not going to look hard enough and eventually find Laplace’s Demon. Focusing on a real life application, how people are going to use the information in practice, I think is a better way for everyone to frame their scientific pursuits. It is more likely a particular application changes how we think about the problem all together, and then we mold the way we measure to help accomplish that specific task. Einstein just started with the question “how do we measure how fast things travel when everything is moving”, a very specific question. He did not start out by saying “I want a theory of the universe”.
I am more bullish on real theoretical breakthroughs coming from more mundane and practical questions like “how do we tell if a treatment is working” or “how do we know if an officer is having a mental health crisis” than I am about someone coming up with a grander theory of whatever just from reading peer reviewed papers in their tower.
And here is Jon’s response to that:
Like you, we try to be optimistic, encouraging, and constructive in tone, though at times it requires serious effort to keep cynicism at bay. In general, if we had more Andrew Wheeler’s thoughtfully building things and then evaluating them, then I agree this would be a good thing. Yet, if I don’t trust someone enough to meaningfully observe, record, and analyze the gauges, then I’m certainly not going to trust them to pilot – or to understand well enough to successfully build and improve upon the car/airplane/spaceship. Meanwhile, the normative analysis is that everything is significant/everything works – unless it’s stuff we collectively don’t like. In that context, the cynic in me things we are better off of we simply focus on teaching many (most?) social scientists to observe and analyze better – and may even do less harm despite wasted resources by letting them larp.
Jon and Jake do not have a an estimate in their post on what they think the mix should be building vs theorizing (they say pluralist in the post). I think the near 0 we do now is not good.
Much of this back and forth tends to mirror the current critique of advocacy in science. The Charles Tittle piece they cite, The arrogance of public sociology, could have been written yesterday.
Both the RC group and Tittle’s have what I would consider a perfect enemy of the good argument going on. People can do bad work, people can do good work. I want folks to go out and do good, meaningful work. I have met plenty of criminologists (and the flipside the level of competence of many software engineers) to not have RC’s level of cynicism.
As an individual, I don’t think it makes much sense to worry about the perception of the field as a whole. I cannot control my fellow criminologists, I can only control what I personally do. Tittle in his critique thought public sociology would erode any legitimacy of the field. He maybe was right, but I posit producing mostly irrelevant work will put criminology on the same path.
Andrew Wheeler 