The True Crime Replication Crisis Part 5: Fraud

This week I have to say, we are getting to one of my favorite topics: straight up fraud. Prior to this we have covered a lot of things that can skew the thinking of otherwise good people despite their best efforts, which is the vast majority of issues we run in to, but today we’re going to cover those who intentionally deceived others. Even in the context of the replication crisis, straight up fraud cases make up a very small percentage of the concerns about research findings, but they are still worth focusing on as a potential trouble source.

Before we get started though, I want to mention a somewhat weird thing I’ve noticed over the past few years. I’ve noted that very often when it comes to research, people are often very quick to call human error and/or bias fraud, and then often too slow to call actual fraud, fraud. I have wondered why this is, and my suspicion is that it’s because well intentioned humans who make errors are often very ashamed and may not defend themselves as vigorously, whereas straight up fraudsters are extremely prepared to be challenged and are prepared to be aghast you would ever suspect them of anything. Thus the well intentioned error people seem a lot more “guilty looking” than the fight to death fraudsters.

So with that in mind, let’s talk about what fraud is and isn’t. Fraud is not making a mistake, even if it means you have to retract your study. Admitting you got it wrong and owning up to it is exactly what we want researchers to do. Fraud is also not publishing a faulty study you didn’t question rigorously enough because it matched your pre-existing beliefs, at this point most of us have accidentally share a link to a story that turned out to be false because it just “sounded true”. Fraud isn’t even necessarily only publishing certain outcomes in a study and failing to publish others. Many of these things can teeter towards fraud depending on the circumstances, but most people in their day to day lives will occasionally jump to conclusions or tell stories in ways that benefit them. It’s not a great human weakness, but it’s one we see often. So if those things aren’t fraud, what is? Well in the research world one of the main examples is data falsification. From making up numbers to pretending to have done experiments that never happened, this is an unfortunate reality of some research and it’s only through replication efforts that this can be uncovered.

The wildest example in the research world is actually fairly recent, the sordid tale of Francesca Gino. Gino was a Harvard Business School professor who, amazingly, specialized in “honesty and ethical behavior” research. Back in 2020, a graduate student raised concerns about one of her papers, and then tried to replicate it in 2021. She became suspicious that not only did the study fail to replicate, but the whole set of results seemed wildly implausible. She got some data bloggers involved, and things spiraled from there. To condense a very long story, Gino was eventually put on leave and ultimately her tenure was revoked and she was fired.

What’s interesting, given my second paragraph, is that this all came to the attention of most people because Gino sued both Harvard and the Data Colada bloggers for $25 million saying they were all defaming her. It was actually her own lawsuit that caused Harvard’s internal investigation of her to be released, which made her look incredibly bad. She has alternated between claiming she was the victim of sexism, that it’s all a big mistake and that she was framed. Her coauthors on the other hand, started a website to investigate all of the papers they’d worked with her on to make sure they knew which findings were reliable and which weren’t. While I will note that Gino has defenders still, it’s an interesting story of defensiveness in the face of accusations.

So how does this relate to true crime?

Well, I’d imagine much of the connection would be obvious, but I’d like to point out that in true crime we actually know pretty much from the get go that someone is actually straight up lying. In scientific research, fraud is always a possibility, but probably not more so than in regular human endeavors. It reminds me of the old stats 101 type problem, where you calculate things like “given that the child is a boy, what are the chances his name is John” vs “given that the child’s name is John, what are the chances that he is a boy” and they highlight those are wildly different answers. Here it’s the difference between “given that a scientist published a paper, what are the chances there is fabricated data?” and “given that a bunch of suspects have given different incompatible stories so someone is lying, what are the chances person X is lying”. Why do I point this out? Because as I mentioned at the beginning of this series, for some reason the average person I talk to is more open to hearing that a research study they heard about is wrong than they are to hearing the new true crime podcast they’re listening to is. This makes no sense because crime stories are almost by definition full of liars. One of the first types of lies little kids tell is lies to get themselves out of trouble. If you have even a passing familiarity with the Biblical story of the Garden of Eden, you’ll know that it’s alleged that the first crime humanity itself committed was to attempt to shift the blame for eating the apple. Lying about this stuff is as innate to human nature as it gets. So again, why are we so resistant to being skeptical about these stories when someone puts them on a podcast?

I think there’s a few things skewing our thinking with these. The first I think is that crimes tend to involve a lot of human error from the get go. Witnesses often don’t have the best memories of times/dates/sequences of events, so any attempt to call someone a liar has to be tempered with the frailty of human memory. Additionally, in many crimes, victims are purposely selected because they have pre-existing credibility issues, making things even harder to sort through. In the documentary about the fraudulent results from the Massachusetts state crime lab, a defense attorney notes that the number one risk factor for being falsely accused of a crime is already having a criminal record. Two fraudsters in two different labs got away with filing false drug test results for years in large part because the results mostly impacted known drug dealers.

Interestingly, this applies to any group who comes under fire. I don’t think it’s coincidental that the true crime genre exploded in popularity around the same time as George Floyd/Black Lives Matter gained steam, as “police framed/justice system railroaded innocent person” is perhaps the most popular true crime storyline. Just like having a criminal history does not make you automatically guilty of a crime, police having issues also does not negate the fact that nearly every defendant claims to be framed. There’s actually been some interesting discussion of this in defense attorney circles, with some attorneys arguing that all media that draws attention to the flaws of our justice system is useful, and some maintaining that this type of infotainment does more harm than good. Scott Greenfield, my personal favorite defense attorney/blogger, falls in the latter camp. For this post I went looking for his thoughts on True Crime and was interested that in the years since Serial debuted, he’s gotten even harsher than his initial skepticism. I’d recommend the whole thing, but I love his first three paragraphs that he wrote back in 2023 (bolding mine):

After the podcast Serial became a hit, the phone started ringing. The calls were from journalists, producers, wannabe podcasters, asking whether I had any cases involving a clearly innocent defendant who was abused by the system and ended up convicted and serving a lengthy sentence. Well, of course I did. We all do. But as it turned out, that really wasn’t the story they were interested in.

What they really wanted was a sympathetic defendant, the sort of innocent person people could love, and a simple, clear story of misconduct and abuse that ended with imprisonment. This was where I made the mistake. I had no stories like that, as few defendants were up for beatification before being charged with murder, and while there were arguments for the defense, and complex, messy problems along the way, it wasn’t as if the prosecution didn’t have a case to show they committed the murder.

The sort of post hoc contentions, like witnesses who recanted after they had nothing on the line or jailhouse snitches who say their cellies confessed to them, that true crime producers adored and thought critically valuable were the sort of things judges laughed off, as did I. People lie, all the time, for all sorts of reasons. Why is a post-trial recantation more credible than sworn trial testimony? Defendants bought witness silence or post-trial recantations on occasion. They often claimed innocence all along, even though they were guilty as sin. That’s the nature of criminal defense.

This is a man who makes his living in criminal defense pointing out the rather obvious fact that very few people get to trial without some pretty good evidence that they did it, and that people are constantly lying. If someone claims they lied under oath but now are telling the truth on a podcast, you may want to mark that person down in credibility. So what do we do here? Well, I think we have to approach these things with a huge eye towards fraud, both for the defendant and the podcaster. A few thoughts:

  1. Compare the story being told to different sources/established facts: I’ve said it before but I’ll say it again, before you start any documentary or podcast, look for a summary of the facts so you can tell if something’s being left out. Remember that every single person involved, from the defendant to the witnesses to the podcaster, is highly motivated to make themselves look as good as possible. It’s also good to note that wanting your story to be public in and of itself is not a sign of honesty, see my prior comments about Francesca Gino being the one to get her own damning internal investigation released. Some people truly believe facts make them look better than they do.
  2. Beware of emotional investment, your own or others: Over a 10 podcast series, you can feel you get to know the host/the subject/whoever, which can lead you to overattribute credibility to them and become less skeptical as time goes by. By the time you finish it can feel mentally awkward to consider someone you’ve come to like a liar. This goes double for podcaster by the way, especially if they got exclusive access to some of the players in the case. I have a rule of thumb that when someone covers a controversial case and interviews someone extensively, then starts hemming and hawing about their opinion while saying “I guess we’ll never know”, they think the person’s guilty. With my local case, we had at least one documentary film maker admit that’s exactly what they did. The burden of highlighting someone’s case just to condemn them is too much for some people.
  3. Beware of applying big picture thinking to individual cases: We live in a world where people get raped. This does not mean every individual rape accusation is true. We live in a world where people falsely accuse others of rape. This does not mean every single claim something is a false accusation is true. Unfortunately, there’s an odd thing that happens with true crime I’ll call “true crime as though experiment” where people use a true crime case as a stand in for a bigger issue. This can work in the research world, where research that suggests something similar to prior findings actually can be considered more credible than novel research. But in a crime case? The facts of every single crime still matter on their own. Once a case gets big enough though, a surprising number of people will claim the exact details don’t matter because we need a “bigger conversation”, but good lord imagine if it was you stuck in the middle of things? If your loved one was murdered and someone else decided to fudge some details and portray the murderer sympathetically because they wanted to make a “bigger point”? You’d hate it, we all would. Always consider there are real humans at the center of things, and ask if they signed up to be your morality tale.
  4. Remember, people do in fact just make things up and people have been hurt by it: One weird thing I’ve noticed with some true crime assessments is that people will try to play “fair” and give everyone equal credit, like they all are lying a little bit. I think this comes from our natural instinct when we’re adjudicating arguments in our personal life. If you have two friends in a fight and you hear both sides, our instinct tends to be to split the difference and assume both have some points and both are being a little self serving. With many crime stories though, some stories are just incompatible. This happened in my local case, and I was surprised how many people wanted to try to split the difference between two extremely incompatible claims. I ended up having more respect for those who went all in on one side or the other than those who tried to “both sides” two stories that clearly could not coexist.
  5. Factual innocence is different from not guilty: As I have throughout this series, I will reiterate that I support the reasonable doubt standard and our justice system. However, I continue to ding some true crime folk for acting like “beyond a reasonable doubt” means the defendant should be given more deference vs every other person involved. As we saw at the height of the #metoo era, a claim of wrongdoing that never enters a courtroom can destroy lives very easily. Not as dramatically as actually being wrongfully convicted in a court of law, but well beyond a level that’s reasonable to accept. It surprises me therefore that so many podcasters take this responsibility so lightly. If you know that one person committed a murder and you spend hours talking about 6 suspects, you should be aware 5 of those people are innocent and you may have just helped ruin their lives. Even Sarah Koenig admitted she’s ashamed of this part of the Serial podcast, that it encouraged people to treat others as pieces in a puzzle to be solved rather than humans who had been through pain. I get the reason people focus on the person on trial, meticulously cataloguing every issue with the case against them, but it’s notable they tend to spend just a few minutes on the weaknesses of the case against alternative suspects, if they mention them at all. This mimics the tactic of defense lawyers who are explicitly there to do this, but I’m surprised it doesn’t weigh heavier on the conscience of those just doing it as a hobby. If the defense lawyer was wrong, he did his job. If you’re wrong, you actually just wrecked somebody’s life for entertainment.
  6. Watch how people address the victims: This is a somewhat weird one, but hear me out: the more dismissive a true crime podcast or a suspect is of the loved ones of the deceased, specifically those who could not themselves be suspects, the more I’d question the story. Victims by definition shift the attention away from neatly crafted stories, and thus seem to prompt outsized anger or complete dismissal from those seeking to push a narrative. A good recent example of this is Candace Owens attacking Charlie Kirk’s widow Erika. Owens has stated there was a conspiracy to murder Kirk, and it seems the further she went with the story, the more the grieving widow not asking similar questions annoyed her. Even if you believed Charlie Kirk was killed as part of a bigger conspiracy (I don’t) raging at a young widow would be a weird place to start in making your case. Watch how people treat the undisputed victims, and you’ll get a good insight in to where their focus is.

Ok, that’s all I have for today! Tune in next week when I go over some statistical issues.

To go straight to part 6, click here.

Pink Sparkle Unicorn Science

I unfortunately have a packed weekend and have not been feeling well, so no True Crime post today. Instead, I would like to mention something I was wrong about.

For years I have disliked the whole “science for girls” thing, believing that it was fairly condescending to slap pink on something sciencey and to declare it “for girls”. I believed this right up until I had to buy a present for a precocious 4 year old girl I know who is obsessed with all things pink, sparkly, and unicorn adorned. It had been requested I try to find something sciencey, so I decided to take a chance with, well, a pink sparkle unicorn science kit for girls.

She loved it. Last I heard she had told one of her parents to “go away, I’m doing scientist things”.

Worth every penny.

The True Crime Replication Crisis Part 4: Questionable Research Practices

Welcome back folks! This week we’re going to be diving in to questionable research practices, and their impact on the replication crisis.

There’s a few specific questionable research practices that we should cover here, but I want to start with the umbrella concept of “researcher degrees of freedom”. This is a concept that basically means that any time you want to do any experiment, there are a bunch of different ways to do things. Two people locked in separate room asked to create an experiment will almost certainly come up with two different ways of doing things, just because there is often not one right way to do anything. This is fine. What’s less fine is when people start making choices that we know have a high tendency to produce false positive results. Some of these include data dredging, selective reporting of outcomes, HARKing (hypothesizing after results are known), PARKing (pre-registering after results are known). So what are these things and how do they impact research? Let’s get in to it!

Ok, before we talk about the questionable research practices, I want to take a step back and remind everyone that at it’s core, science is largely about trying to deal with the problem of coincidences. We as humans have a tendency to see patterns that may or may not actually exist, and most scientific methods were developed with the idea that you need to separate out coincidences from true causal effect. For example, if a lady claims she can taste a difference in tea based on when the milk was added, you can design a randomized experiment to actually test her prowess. This helps us separate a few lucky guesses from a real effect. Now to reiterate, we almost exclusively have to use this to assess coincidences. If a woman says she could identify the strategy used to make and then promptly misidentified how her tea was made, we’d all move on. It’s mostly when something starts to look plausible that we have to really dig down in the scientific method to figure out what’s going on.

Enter data dredging. Often researchers get large data sets at one time, and may start to run something called exploratory data analyses, just to see if any interesting correlations emerge. This is fine! The problem is that it wasn’t always well communicated that this is what was being done. I’ve actually written about this before when covering some of Brian Wansink’s ongoing scandals and comparing it to my approach for my masters thesis. If you are looking at hundreds of data points, the chance of uncovering a coincidence goes way up, and there are actually statistical methods created just to solve for this problem. Data dredging often leads to spurious correlations, which are fine and relatively easy to deal with if you admit this might be a problem and that you’re going to have to investigate more to figure out if the correlation is real or not. The problem is that even very smart researchers can trick themselves in to thinking that a coincidental finding is more meaningful than it actually is. Andrew Gelman has done excellent work explaining this in his paper “The garden of forking paths: Why multiple comparisons can be a problem, even when there is no fishing expedition or p-hacking and the research hypothesis was posited ahead of time“. In it, he points out that no one has to do this on purpose:

In a recent article, we spoke of shing expeditions, with a willingness to look hard for patterns and report any comparisons that happen to be statistically significant (Gelman, 2013a). But we are starting to feel that the term fishing was unfortunate, in that it invokes an image of a researcher trying out comparison after comparison, throwing the line into the lake repeatedly until a fish is snagged. We have no reason to think that researchers regularly do that. We think the real story is that researchers can perform a reasonable analysis given their assumptions and their data, but had the data turned out differently, they could have done other analyses that were just as reasonable in those circumstances.

The papers go on to explain several examples, but the basics issue is that when you are looking hard for something, you will start unintentionally start expanding your definitions until you are very very likely to find something that is coincidental but you believe it fits in with your initial hypothesis. This can quickly lead to some of the other issues I mentioned earlier: failing to report all endpoints (because you only report the meaningful ones, leaving people in the dark that you actually tested other things), HARKing, basically stating after the fact that you “knew it all along”, and pre-registering after the fact (PARKing) where you take it a step further and state that this is what you were always looking for. Gelman has great examples, but XKCD perhaps put it best:

So how does this apply to true crime? Oh you sweet summer child, let me tell you the ways.

Remember a paragraph or two ago when I said “the basic issue is that when you are looking hard for something, you will start unintentionally start expanding your definitions until you are very very likely to find something that is coincidental but you believe it fits in with your initial hypothesis.“? This is so rampant in true crime you wouldn’t even believe it, and there’s literally no statistical test waiting in the wings to help sort things out.

For years, people have been aware that police can do this. Once they fixate on a suspect, everything that person does can look suspicious. Did the suspect get extremely upset when they heard their wife was dead? Suspicious, probably an act. Did they fail to get upset? Also suspicious! I would argue a large part of our justice system is set up specifically to guard against this issue, and it’s why we have a standard of “beyond a reasonable doubt”. People are fallible, our justice system is imperfect but acknowledges this exists. But as we’ve covered, the disparate and competitive true crime ecosystem takes very little time for self reflection and often breathlessly reports coincidences with no particular acknowledgement that sometimes a coincidence is just a coincidence.

This gets complicated by the fact that (as we covered earlier in this series), true crime type cases happen disproportionately in suburbs or smaller towns vs large cities. I actually have wondered if part of the reason is because it’s easier to have “coincidences” in places with smaller more stable populations. If a police officer gets called to a random murder in the projects, it’s very unlikely they will have a connection to whoever the victim/suspect is. A police officer in a town of 25,000 though? You’ve got a much higher chance of knowing someone who knows someone. Now if there are three officers who respond to a place where 4 people live? You have almost guaranteed someone has a connection. Suspicious!!!! You may think I’m exaggerating, but the case in my town involved DOZENS of things like this. It’s actually what first got me thinking about the connection with the replication crisis. I have had so many people say things like “you REALLY believe that it’s a coincidence that <one of the ten first responders> had a connection with <a relative of one of the four people there>.” Yes, actually I do. It would actually be pretty bizarre if there were literally no connections. I can’t run errands on a Saturday morning without running in to someone I know and you think a bunch of random people from the same town would have absolutely no connections to each other?

The problem here is that people way underestimate the probability of a coincidence. One of my favorite examples of this is “the birthday problem“, a classic stats problem that asks people what the chances are that two people in a randomly selected group of people have the same birthday. Most people are surprised to find out that you only need 23 people before the chances are 50/50 that you’ll get a match, and by 30 people you have a 70% chance of a match. The issue is that people forget you are not trying to find one particular birthday match, but any birthday match. This wildly increases the chance you’ll find something. For my problem above, let’s say you have 6 first responders. Each of them has some combination of parents, siblings, inlaws, children, neighbors and other “suspiciously close” people in their lives. Let’s give them 15-20 each. Now the 5 people at the scene who each have a similar number of people are compared to this. So in the end we have 100+ people compared to 60-80 people, all living in a similar area, and we are looking for ANY connection. What are the chances you think we find one? I’d say quite high! But in true crime land, stuff like this is stated like a stunning development.

Ok now, I’m going to take a step back and be fair for a second: if you’re trying to figure out who did a crime, coincidences may be something you have to look at. I’ve often been annoyed when people start yelling “correlation does not imply causation“, because of course it does. That’s the whole problem. Two items that are correlated may not be causal, but they are much more likely to be causal than two uncorrelated items. But just like with all coincidences, you have to test it against other things to figure out if it’s a coincidence or if you’re really on to something. Otherwise you’re just data dredging, desperately looking for anything that connects to jump off of.

And overinterpretation of data around crimes can cause a LOT of problems. One of the saddest parts of the book In Cold Blood (a classic by Truman Capote that kicked off the modern true crime genre) is when the killers were caught six weeks after murdering a family in a quiet town, Capote mentions many locals had trouble accepting the killers (who ended up confessing) because various coincidences had convinced them others were involved. Those types of issues can stick with you for YEARS, with people vaguely feeling you must have done something.

Ok, so you may be thinking I’m just calling out random individuals here, surely no big time groups report on coincidences like they are meaningful? Au contraire! Recently I saw a Charles Manson documentary that makes the charge that Manson was actually a CIA sleeper agent, based largely on the fact that a CIA member was operating near Manson for years. The guy pushing the theory goes in to great detail about this CIA agent, and how many places were linked to both Manson and this CIA operative. I was already feeling skeptical, when about three quarters of the way through the documentary, the main guy drops “it’s the perfect theory, I just can’t put them in the same room at the same time”. Wait what? Record scratch. So everything we’ve been talking about is just to explain that these two men lived in the same city for some period of time, but you can’t prove they ever met? That’s sort of a key piece of evidence! And this documentary was based on a whole book that was a NYTs best seller and is considered an “Editor’s pick” on Amazon. I don’t see how you consider any of this any more than data dredging, looking for some coincidence, any coincidence, you can use to prop up your theory.

And don’t even get me started on only reporting certain outcomes, this is endemic. One of the weirder examples I’ve come across is one of the most viewed Netflix true crime documentaries of all time The Keepers. This documentary looks in to the murder of a young nun in 1969, and correlates it with sex abuse allegations a woman (then a student) came forward with against a priest at the same school. The heroes are the now adult women who went to the school at the time, and it holds a 97% positive review on Rotten Tomatoes. Surely it can’t be a coincidence that a young nun turned up dead at a school where girls were being molested, can it? Well, it may not be that simple. The problem? The viewers are never told about the background of the primary accuser, which I got suspicious about when I heard she’d been offered a very low settlement. I went looking and discovered that the primary accuser admits that the memories of her abuse was all “recovered memories” that she had no idea about until decades later shortly after she started visiting a new therapist. She actually initially accused her uncle and dozens of strangers, then after a decade of accusations moved on to accusing dozens of school employees. All her initial accusations were actually documented pretty early on, as she filed a 1992 lawsuit that ended up enumerating all of them, including her own admission that many of her reported memories were verifiably false and (in her words) “bull crap”:

The documents go on to point out that even once she settled on the school, she first accused a different priest, then after finding out he was deceased, recanted and moved on to a new priest. And literally none of this is in the documentary. I don’t know what happened here and it sounds like the priest may have been creepy to some people, but it does feel relevant to know someone actually accused dozens of other people before they got to the person in question. There is another accuser, but interestingly the documentary does actually make clear she didn’t come forward until the first woman sent out a mass mailing to all her classmates. I’d really encourage you to read the whole article if you want a sense of how badly a smash hit true crime documentary can shape a narrative through omission.

So where does this leave us? Well, much like with correlated data points, I don’t think it’s wrong to point out coincidences, as long as they are properly contextualized. But a few things to keep in mind:

  1. Watch how big you’re making your data set. As mentioned, the more people you look at, the more likely you are to find odd coincidences. Expanding your timeline to everything dozens of people have ever done or to include all of their family members/friends/neighbors/acquaintances wildly expands your data pool. The bigger the data pool, the less meaningful every individual coincidence.
  2. Don’t discard data that doesn’t fit the narrative. It’s interesting to watch some coincidence finders totally discard certain coincidences with “well of course that person behaved strangely, they were in shock” while jumping all over other coincidences. I understand the temptation, but it’s always good to admit when your own side has holes.
  3. Be aware other people might have already discarded data before you got there. Most documentaries/podcast series have limited space and are going to discard some pieces of information and some of that information could have been important. My new suggestion for everyone is that if you must watch a true crime documentary, google the name + criticism before you watch it. Once someone gives you a slick narrative you are much less likely to care about information that could have shaped your conclusions had you known it beforehand. At least you’ll know when they’re breezing by something that could have been important.
  4. Compare coincidences to your own life/baseline probability. Some coincidences are more likely than others. For example, if you hear that someone bought a knife the day before someone got stabbed, but that someone else did laundry the day after, those are two weird coincidences right? Well yes! But also no. Just in my own life, I am several thousand times more likely to do laundry than I am to buy a knife, and I’d imagine most people are. We can certainly look at both people, but remember how frequently you yourself do the “suspicious” action. This also applies to relationships between people. I once had someone ask me how I felt about all the “close relationships” in our local case, and I pointed out the one they were talking about was somebody’s brother’s wife’s sister’s friend. Knowing a bit about their family, I asked them how close they felt to all their brothers wife’s sisters friends, and they admitted that actually did feel rather more distant when they mapped it out using their own brother/sister-in-law/sister of sister-in-laws friend. Again this is fine! But if film makers can make a benign scene feel ominous with scary music, so can true crimers make somewhat distant relationships feel close by saying them ominously.
  5. Understand the modern environment for information finding. One thing that is very new since the time of In Cold Blood or even JonBenet Ramsey is social media. Nowadays if a new crime occurs, it is trivially easy to go online and find who people might be connected to through Facebook. Suddenly, that guy who ran the trivia night you used to go to 20 years ago can be connected to you just as easily as your actual best friends from college or actual family members, making coincidences even easier to find. Additionally, there are even bigger groups of online sleuths desperate to track down leads, and they scour the internet finding even smaller and smaller discrepancies. I recently saw someone mention they believed JonBenet’s mother was complicit in her murder because of weird phrasing she used in an interview 10+ years after the fact. At that point your data set has become absolutely massive and you may need to take a break.
  6. Prioritize coincidences backed by other evidence. You’d think this would be obvious, but a coincidence that precisely fits the theory of the crime as backed by physical evidence is a lot more meaningful than “this person did something weird elsewhere”.

That’s all I can think of for now! So I’ll close with a quote from Frederick Mosteller “it is easy to lie with statistics, but easier without them.” If scientists attempting to adhere to good statistical methods can make these mistakes, those not even trying to watch their work are several times more likely to fall in to these errors.

To go straight to part 5, click here.

The True Crime Replication Crisis Part 3: More Problems with the Publication System

Hi friends! Last week we covered some problems with the publication system that helped cause the replication crisis in science, and this week we’re continuing in the same vein with three more topics. Ready? Good, let’s dive in.

Standards of Reporting

When people started getting interested in the replication crisis, one of the first things everyone wanted to do was figure out how bad it was. Before this could even be tested, an immediate problem was noticed: most papers don’t describe what they did well enough for anyone to even try to replicate it. And this was in cancer biology. Yikes. Now having actually written some papers in oncology and also having written work instructions for how people should do their job, I will state this is almost certainly for two reasons: it is not easy to write out what you did well enough for someone else to truly follow, and it’s very boring to try to do so. If you’ve ever tried to teach a kid how to do a multi step home chore, you’ve probably seen this. “Ok now put the soap in the dishwasher” quickly makes you realize you did not specify there is special dishwasher soap and a specific spot in the dishwasher for said soap. So basically this is not necessarily sketchy, but also could seriously impede replication efforts.

So how does this relate to true crime? Well, the biggest content delivery systems for true crime right now are podcasts and documentaries, which just so happen to be the hardest mediums to include any sourcing in. Depending on venue, court documents can be really inaccessible, police don’t tend to release a detailed timeline of their investigation until the trial, and even then they keep it pretty narrow to the specific case. So figuring out the big picture of how an investigation played out can actually be super hard and it’s extremely hard to find a source document to check if your podcaster/documentary film maker of choice is being honest or even just reading the facts the way you would have. I ran in to this recently when someone Tweeted out an “everything you think you know about Amanda Knox is wrong” type thread, and I decided I’d check a fact or two to see if this person was trustworthy. The problem? All the stuff necessary to do that is in Italian. I did eventually find a fan maintained document repository that has some translations, but it’s still wasn’t quite sure how to check a quick fact. I gave up.

This is not great because most of how we sort through which podcasts to listen to on history or politics or other topics come from a quick assessment of how honest people are, but with true crime it’s almost impossible to do this easily. Even when I talk to people about my local case it’s often very hard to send them sources for corrections, often the source is buried in the middle of 5 hours of testimony that has no transcripts, so you’d have to watch through hours of footage to link to the spot. So you’ve got a case where you are telling a story, but it is extremely hard for anyone to check the specifics of what you’re saying. That kind of set up has never once bred honesty. The only advice I can give here is to see if there are podcasts/documentaries from two different sides and try to consume both of them. At least then you’ll see what people leave in and what they leave out. And honestly? The crazier the story sounds for people’s behavior especially over long periods of time? Question it harder. Some interesting studies were pretty rightfully called in to question when people started pointing out they had very brief methods sections for very elaborate study set ups. “Dozens of people acted in insane ways for a period of several years” is a claim you should always be skeptical of. It’s not impossible, but always good to see if there is any nuance being left out. After all, if it happens in science where you’re required to write up everything and cite sources, it’s almost certainly happening even more often in podcasts that are required to do neither of those things.

Procedural Bias

So in that last section we covered some issues that can arise with science even when everyone has the best intentions, and in this section we are going to cover another one. Procedural bias concerns arose from a thing called the Duhem-Quine hypothesis, that talks about how most scientific research actually rests on a bunch of different assumptions, including that your instruments are actually working correctly. In psychology research, there’s concerns that people could end up only testing their instruments/procedures if their tests show nothing, but could assume any positive result is proof their thesis is correct. This is a pretty human tendency right? If I ask you to show me how far you can hit a baseball and you don’t do well, you’ll probably ask for another try because your finger slipped/there was a loud noise/the wind blew the ball/etc/etc. But if the wind blows the ball in your favor, you would almost certainly accept the extra few feet. We tend to look for what went wrong when we don’t get a particular result we want.

In science? This is not a great tendency. But in the justice system? This is a feature not a bug! When someone is accused of a crime, they get a lawyer whose actual job is to sit and nitpick every single thing that was done to get to the point of indictment. This is good and how the system is supposed to work, a defense attorney who showed up and said “gosh your honor, it actually looks like the police did everything they could, guess we gotta take the L here” would be grossly negligent and probably lose their license. If the police searched a two block radius? Well why didn’t they search a 3 block radius? If the local police handled it? Why didn’t they call in the state police? If they called the state police? Why didn’t they call earlier. If they called early, what were they so worried about? Etc etc etc. Again, this is a good and proper design of the system and anyone who doesn’t get this type of representation should. But I think true crime has taken this tendency a little too far in a few different ways.

First, as trust in police declines, I’m seeing people put a surprising amount of trust in defense attorneys, as though they are not paid to question everything. If the police went right instead of left first, the defense isn’t saying “oh well everyone knows you go right first” because they necessarily believe that to be true, they are saying it because it is absolutely their job. You’d think this would be obvious, but especially with good defense attorneys I see a surprising number of people quote them as though they are authorities on the topic. This works in both directions, btw, with people claiming offense that a defense attorney claimed a rape victim actually consented (not a lotta defenses left if you don’t use that) or people saying the police were obviously wrong because the defense attorney said so.

None of this is to say that defense attorneys can’t cross ethical lines, and indeed, I’ve been discovering there are surprisingly few ways of reigning rogue defense attorneys in. However, the point is just because a defense attorney claims something does not mean it’s true or even what they would be claiming in a non-professional setting. One of the more interesting points I read while looking in to this is that while defense attorneys have done an excellent job branding themselves as defenders of our constitutional rights, it should be noted that defense attorneys at work are only defending their clients constitutional rights. They will absolutely argue that the police could have or should have violated other people’s constitutional rights if it will help their client. In the case I’m familiar with, the lawyers actually argued multiple times for warrantless searches for other people in a way many critics pointed out they’d be infuriated with if it was done to any of their clients.

So this is all fine for defense attorneys, who are doing their job. But I think this tendency has snuck in to true crime, particularly amongst people who fancy themselves civil rights defenders. If your answer to how one persons rights should have been preserved is to suggest violating someone else’s rights, then you’re not a civil rights advocate, you’re a fangirl. While courts attach certain rights to those on trial, it is absolutely insane to act like only those accused of crime have rights. A defense attorney doesn’t get the contents of my phone just because he wants it, he also has to offer evidence just like what had to be offered to get his or her clients phone. The constitution applies to all of us at all times, not just individual people at specific times.

All of this points to a slightly different problem I’ve noticed with a lot of true crime media and fans: they want it both ways using legal standards. Some time ago, I had a heated discussion with someone who felt differently than I did about our local case. She dismissed multiple things I said as “irrelevant to the court case” and declared she wanted to just follow the case like the jury would. Ok, fair enough! But less than 5 minutes later when she wanted to counter a different point, she promptly mentioned several things that had also not been allowed in to court. I’ve known this person for years and truly believe she was not trying to be manipulative, I think she actually didn’t notice what she was doing. I didn’t even notice what she was doing until I thought about it later, but since then I’ve proactively brought it up to people when I see it. We can either talk about everything from a strict legal perspective, or we can talk about it from a colloquial “do we think they’re guilty standard” but we can’t have two different standards depending on which part of the case we’re talking about. Make sure you’re machine’s working when you get results you like and when you get results you don’t like. Having two different standards is human nature, but it’s a recipe for disaster when it comes to truth.

Cultural Evolution

Ok, this is a fun one, based on a paper with a great name “The Natural Selection of Bad Science“. In it, the authors use some fun statistical methods to show that if scientists primarily get promoted based on publications, and there are no particular penalties for your study failing to replicate, the quality of science will, over time, optimize towards a high volume of low quality publications. They explain it this way:

An incentive structure that rewards publication quantity will, in the absence of countervailing forces, select for methods that produce the greatest number of publishable results. This, in turn, will lead to the natural selection of poor methods and increasingly high false discovery rates. Although we have focused on false discoveries, there are additional negative repercussions of this kind of incentive structure. Scrupulous research on difficult problems may require years of intense work before yielding coherent, publishable results. If shallower work generating more publications is favoured, then researchers interested in pursuing complex questions may find themselves without jobs, perhaps to the detriment of the scientific community more broadly.

Yuck.

So how does this apply to true crime? Well, as we covered in the publish or perish section, true crime is a highly competitive space and making sure you have a steady stream of content is more important than having an entirely accurate retelling of the story. Currently, there are almost no ramifications for those who are inaccurate, so one assumes the same dynamics will come in to play.

This is actually one spot where I think true crime may be in a slightly better spot than science, as there are some podcasters who literally make “we are going to do a ton of research and be moderate and careful” their brand. At least some of these have gotten a pretty dedicated following, so it is possible for consumers to demand more of this. With science, sadly, most of us never know people who toiled away in obscurity and then didn’t succeed in their field.

Ok, that’s it for this week! Next up we’ll start getting in to questionable research practices. Some of these are field specific so may not entirely apply, but we’ll see what we can draw out. Thanks for reading, and stay safe out there.

To go straight to part 4, click here.

The True Crime Replication Crisis Part 2: Problems With the Publication System

Welcome back! Last week we covered the proposed historical and sociological causes of the replication crisis and applied it to things we see in the true crime genre, and this week we’ll be doing a similar analysis with the group of causes under “problems with the publication system”. As a reminder, I’m loosely following the order in the replication crisis Wiki page, so if you want more you can go there. There’s about 6 reasons listed under the “problems with the publication system” section, so we’ll be taking those one at a time.

Publication Bias

Publication bias in science is a topic I’ve written a lot about over the years, but perhaps my most succinct post was when I covered it during my review of the Calling Bullshit course, where they did a whole class on it. I think the second paragraph I wrote during that post broke it down nicely:

This week we’re taking a look at publication bias, and all the problems that can cause. And what is publication bias? As one of the readings so succinctly puts it, publication bias  “arises when the probability that a scientific study is published is not independent of its results.” This is a problem because it not only skews our view of what the science actually says, but also is troubling because most of us have no way of gauging how extensive an issue it is.  How do you go about figuring out what you’re not seeing?

In science, some of the findings were skewed by people being more interested in doing novel research rather than trying to replicate others findings, the “file drawer effect” where papers that didn’t find an association between two factors were much less likely to be published, and (outside of science) the fact that the media will mostly focus on unusual findings rather than the full body of scientific literature. My guess is you already see where this is going, but lets think how this applies to true crime.

One of the first thing anyone who looks at true crime as a genre starts to realize is that the crimes covered by traditional true crime are almost never the most common type of crimes. While there’s no “average” homicide, there is certainly a “modal” one! If you were going to describe a typical homicide in the US, most people would pretty quickly come up with something close to this: a young adult man, shot with a handgun, by another young adult man he knows, during an argument or dispute, in a city setting.

Looking at the stats, we see why this would come to mind: about 80% of homicide victims are male, about 90% of perpetrators are male. Age-wise, crime is dominated by the young. The FBI data also tells us that firearms are used in about 73% of homicides, that you are much more likely to be killed by someone you know than someone you don’t know, and just based on population density alone we would assume most homicides happen in crowded cities. I didn’t include race in the “modal” case because it’s actually closer to 50/50 black vs white, but both homicide victims and perpetrators are disproportionately black. Now there’s a lot of holes in this data because we don’t always know who killed someone, but I think most people would agree based on the general news that these data match what we assume.

If you listen to true crime though? You won’t find that type of crime represented almost at all. I think nearly everyone who’s ever glanced at the news knows if you go missing, heaven help you if you’re anything other than a young attractive white woman, and true crime’s racism problem has been remarked upon for years. I asked ChatGPT which 20 true crime cases it thought got the most media attention in the US (post-1980), and it’s pretty clear these cases caught fire in part because they are so unlike the “typical” crime:

  1. OJ Simpson Trial (1994-95): famous defendant, white female victim, knife violence
  2. JonBenet Ramsey (1996): white female child victim, wealthy family, beauty pageants, strangled
  3. Menendez Brothers (1989): Wealthy family, kids murdering parents
  4. Jeffrey Dahmer (1991): Male victims, gay sex, cannibalism
  5. Casey Anthony (2008): Attractive female defendant, white female child victim, strangulation
  6. Scott Peterson (2002): White female pregnant victim, knife victim
  7. Central Park Five (1989): white female victim, not murdered
  8. Amanda Knox (2007): white female victim, white female defendant, stabbed
  9. Michael Jackson child abuse trials (1993, 2005): celebrity defendant
  10. OJ Simpson Robbery case (2007): famous defendant, already accused of a crime
  11. BTK Killer (2005): Serial killer
  12. Richard Ramirez “Night Stalker” (1980s): serial killer
  13. Waco Siege (1993): Mass death, cult
  14. Columbine high (1999): large school shooting
  15. Unabomber (1996): Mass death
  16. Tylenol murders (1982): multiple dead, unknown culprit
  17. Jodi Arias (2008): white female defendant
  18. Gabby Petito (2021): white female victim, social media star victim
  19. Michael Skakel/Martha Moxley: Kennedy connection for defendant
  20. Pamela Smart (1990): white female defendant

What’s interesting about this list is immediately a few things jump out: gun violence is very underrepresented with only a few cases (Menendez brothers, Pam Smart, Columbine, sort of Jodi Arias) involving a firearm. Outside of the mass deaths/serial killers, almost all of the cases involve someone who was at least middle class or higher. Very few cases involve a solo male victim, it’s mostly solo females or men dying in mixed groups. The exceptions are actually 2 cases where there were accusations of homosexuality (Dahmer, Jackson), and the remaining one is Pam Smart’s husband. There’s also a dearth of black or Hispanic victims by themselves, they only appear in groups. In other words, it’s pretty clear the true crime genre does not get hooked on your “average” crimes, they want the unusual ones. I asked Chat GPT what the modal true crime case was, and it summed it up this way: A White, female (often young) victim, killed in a domestic or intimate context, often by a male partner/family member, in an otherwise “safe” suburban setting. The perpetrator is either wealthy/celebrity or a seemingly ordinary middle-class person hiding darkness. The case includes salacious details, a highly publicized trial, and often an ambiguous or polarizing outcome.

Seems about right.

The problem here is if one pays attention to true crime, you are getting an inaccurate view of how crimes are committed and who the victims are. I think this not only skews people’s perception of their own risk of being a victim, but also people getting weirdly judgmental of police departments. Once I started poking around at older true crime cases, I found that an incredibly common criticism is when police treat a big unusual case as though it was going to be a normal case. Well, yeah. Even large police departments may not be prepared for a celebrity perpetrator, simply because we don’t have too many celebrities running around killing people. The day the call comes in for a surprisingly big case, no one flags for the police “actually better send your best guys down there and double the amount of resources available, this case is going to be on Dateline next year”. They are operating under the assumption they will be responding to the modal crime story, true crimers believe they should have been prepping for the modal true crime story.

I also think it’s very relevant how many of these cases happen in quiet suburbs or small towns. In the case I’ve become familiar with, we’ve had 4 murders here in 40 years, and our county has a murder rate of 1/100,000 a year. That’s on par with the safest countries in the world. The idea that taxpayers were going to pay through the nose to keep our police department in a constant state of readiness for unusual events disregards how most taxpayers actually function. Indeed, there was an audit done on our local police department during all this, and one of their conclusions was “if you want your police trained for unusual events, you’re going to have to increase their training budget so they can go do that” and people FLIPPED OUT. And these were the people who were most viciously critiquing the police! Even after years of unrest they were still unwilling to increase the training budget, believe that (as one person actually publicly put it) “you can just watch CSI to know what you should do”. Sure, and you can skip medical school if you watch old ER reruns.

And finally, I think a lot of people justify the focus on white wealthy attractive people with a sort of “trickle down justice system” type philosophy. If we can only monitor how the police handle the most vaunted in our society, this will somehow trickle down to help the poor and the marginalized. The problem is, I’ve never seen particular evidence that’s true. How did the myriad of resources poured in to JonBenet Ramsey’s case help anyone? I grew up near Pam Smart, and I don’t recall that case making much difference after things settled down. Indeed, I think these cases often give us a false impression of what accused killers and victims “worthy” of sympathy look like. Indeed, attractive people are much more likely to get preferential treatment in every part of the justice system. They are arrested less often, convicted less often, and get shorter sentences when they do. It’s hard to get numbers on what percent have a college degree, but even the most generous estimates suggest it’s around 6% of inmates compared to 37% of the general population. The pre-jail income average for prisoners is about $19k a year. Wealthy educated attractive people have very little trouble getting their stories boosted, the people who need help are those not in those groups.

All of this to say, listening constantly to a non-random assortment of cases is not going to give you a good sense of how our justice system works on a day to day basis, any more than only publishing (or pushing) flashy science results gave us a sense of scientific fields. As a pro-tip, when you hear about a case that’s gaining traction, it’s not a bad idea to try to find a couple similar non-famous cases with victims/perpetrators who aren’t wealthy or attractive to see how those cases were handled. Your concerns may remain, but at least it will give you a baseline to work from that typical true crime reporting lacks.

Mathematical Errors

One interesting issue that has played in to a few replication attempts seems almost too silly to mention, but typos and other errors can and do end up influencing papers and their published conclusions. Within the past few days I’ve actually seen this happen at work when we found out that an abstract had the wrong units for a medication dose we wanted to add to a regimen. The typo was mg vs g, so it would have been a very easy typo to make and a pretty disastrous issue for patients. So at least a few replications might fail due to simple human errors in pulling together the information. For example, an oft quoted study saying that men frequently leave their wives when they are diagnosed with cancer was quickly retracted when it was found the whole result was a coding error. The error was regrettable, but what’s even worse is I still see the original finding quoted any time the topic comes up. It’s not true. It was never true, the finding would definitely not replicate. Even the authors admit this, but the rumor doesn’t die.

So how does this relate to true crime? In almost every major case I’ve peaked at, rumors get going about things that did/didn’t happen, and it is very hard to kill them once they’ve started. One good example is actually the Michael Brown/Ferguson case, where it was initially reported he said something like “Hands Up, Don’t Shoot”, a phrase so popular it now has it’s own Wikipedia page. The problem? It doesn’t exist. When the DOJ looked in to the whole thing, the witness who initially said it happened no longer said it did, none of the evidence matched this account, and it’s considered so debunked even the Washington Post ran an article titled “Hands up Don’t Shoot Did not happen in Ferguson“. For the public though? This is considered gospel. I’ve told a few people in the past few years that this didn’t happen, and they look at me like I kicked a puppy. When I’ve pulled up the WaPo headline, Wiki page or DOJ report, they’re still convinced something is wrong. How is it possible something so repeated just…didn’t happen?

I’m not sure but this is way way way more common in true crime reporting than anyone wants to believe, especially on the internet. Shortly after my local case was resolved I saw a Reddit thread about it on a non-true crime subreddit, and people were naming the evidence that most convinced them of their opinion, 7 out of the first ten things listed didn’t occur. And I’m not talking “are disputed” didn’t occur, I’m talking “both the defense and prosecution would look at you like a crazy person if you made these claims in court” stuff. People were publicly proclaiming they’d based a guilt or innocence opinion on stuff they’d never checked out. Since then I play a game in my head every time I talk to someone about the case, I count how many pieces of evidence they mention before they get to one that’s entirely made up. 90% of people don’t get past their third piece of evidence before they quote something made up. That is…not great.

Interestingly when I’ve corrected people, they generally look at me like I’ve missed the point and I’m dwelling on trivialities. To that I have two responses:

  1. If it’s worth your time to lie about it, it’s worth my time to correct you.
  2. If I were being accused of a heinous crime I didn’t do, whether in court or just in public opinion, I would want people to correctly quote the evidence against me. So would you. So would everyone. These are real people’s lives, this is not a TV show plot you’re only half remembering.

It’s totally fine in my mind not to be super familiar with any famous public case btw, but if you’re going to speak on it and declare you have a strong opinion, you may want to make sure all of your foundational facts are true. With the internet providing so much of our information now, it is really easy to mistakenly quote something you saw someone tweet about rather than something you actually saw testified to.

Publish or Perish Culture

When you take up a career in science, publication is key to career advancement. One of the issues this leads us to is that papers with large or novel findings are far more likely to be published than those that don’t have those qualities. And what’s less interesting than spending tons of time and resources on a study that someone already did just to say “yeah, seems about right, slightly smaller effect size though”. If there’s no particular reward for trying to replicate studies, people aren’t going to do it. And if people aren’t going to do it, you are not going to spend too much time worrying about if your own study can be replicated or not. One can easily see how this would lead to an issue where studies replicated less often than they would in a system that rewarded replication efforts.

So with true crime, the pressure is all on people to make interesting and bold claims about a story to catch eyes. The remedy for this has basically always been defamation claims, and if you think replications are slow and time consuming, boy have I got news for you about defamation claims. Netflix got incredibly sloppy with it’s documentaries and has a stack of lawsuits waiting to get sorted out in court, but progress is glacial.

This problem has been heightened by the influx of small creators who don’t actually have a lot to lose in court. If you work for the NYTs and report something wrong, your employer takes the hit. If you have a tiktok account you started in your parents basement, you can pretty much say whatever you want knowing no one’s going to spend the cash to go after you. This is starting to change as people realize they need to send messages to these content creators who make reckless accusations, but change is slow. Even true crime podcast redditors have wondered how some of the hosts get away with saying all the stuff they do and why more people don’t sue. Oh, and now the mainstream media can just report on the social media backlash rather than report on things directly. Covington Catholic helped set some better guidelines for this, but the problem remains that none of this has improved the accuracy of reporting.

Even if the content creators confine themselves to facts, they often aren’t their facts. Like all social media, pumping out weekly content is king, and most people simply do not have time to thoroughly research cases themselves. A surprising number of true crime podcasts have been hit with plagiarism accusations, including one where they were just reading other people’s articles on air without attribution. Given that podcasts often end up licensing their content, this drives a lot of possibly sticky legal issues. So what are the consequences for this? As of right now almost nothing. The podcast named in the article above just removed the episode, and as of this writing is the 6th most listened to podcast in the world. Publish or perish, good research be damned.

All right we have a few more publication issues to cover, but I think I’ve gone on long enough and will save that for next week. Stay safe everyone!

To go straight to part 3, click here.

The True Crime Replication Crisis: Part 1

Welcome back folks! Last week I started to introduce a new series on the relationship between the issues in true crime and the issues in scientific publishing that led to the replication crisis. I am going to start working through some of the proposed causes for the replication crisis in science, and connecting them to similar issues in true crime. I’m going through these in the order the Wikipedia page on the replication crisis, and today we start off with some big picture stuff: historic and sociologic causes. So what did we see in science?

Scientific Senility, Overflow Theory, and the Enemies of Quality Control

The first thing that caught my eye is that the replication crisis in science was predicted all the way back in 1963 by a man named Derek de Solla Price, who might have been one of the first scientists to study, well, science itself. Solla Price became alarmed at the exponential growth of scientific publication and the inability of science itself to police a body of knowledge that was doubling every 10-15 years. Indeed, we see that the amount of money sunk in to scientific research has jumped over the years:

He was afraid the science would reach the point of “senility” after it saturated, where further findings were simply nonsensical. He also grew concerned that increased participation in science would not inherently mean more of the best and brightest would enter science, but rather that the best scientists would get bogged down working in a competitive field and the quality of your average scientist would decrease.

These predictions seem prescient, as decades later scientists are indeed bemoaning scientific “overflow“, or the phenomena when the “quantity of new data exceeds the field’s ability to process it appropriately”. Additionally, it’s been noted repeatedly that the huge influx of money in to science meant that doing research that got funding was as important as doing good research.

Finally, they wrap up by noting that science was subject to three forces that can compromise the ability to prioritize quality control on any topic: mediatization, commodification and politicization. All of those factors have only increased the competing forces in science, and made it all the harder for people to focus on the original purpose.

So How Does This Apply to True Crime?

The exponential growth of science has been almost nothing in comparison to the exponential growth of true crime content. Google ngram has an interesting visual of the number of times the phrase “true crime” has been mentioned in books over the years:

Yup, looks like exponential growth to me! Additionally we know that the number of true crime podcast listeners has tripled in the last five years (6.7M (2019) to 19.1M (2024), and that true crime content is fueling the documentary boom on streaming services (6 of the top 20 in 2020, 15 of the top 20 in 2024). Now if science, whose stated goal is to aim for truth with a pre-existing system of peer review to screen work, can’t handle keeping up with the enormous influx of new information, how is true crime supposed to keep track of it’s quality while pumping out new content? After all, with science you still have multiple barriers to entry (education, institutional affiliation, etc) and a set format for your work. With true crime, literally anyone can hook up a microphone and start a Tiktok or podcast, and the stated goal is often story telling, with truth as a secondary aim.

This also suggests that de Solla Price’s concern about a massive influx of scientists degrading the average quality also has some applicability to the true crime space. While there are many well credentialed and thoughtful true crime content producers, they will always be competing with others who may be trying less ethical ways of getting attention. Indeed, as my town got flooded with true crime content producers, I was somewhat fascinated to look in to the backgrounds of some of these people. A surprising number of the smaller creators were people who literally could not hold regular jobs due to their own prior run ins with the law. Over the course of watching some of the feuds that started between them, I learned at least one podcast host had confessed in writing to others she’d ended up realizing a lot of the story being peddled was unsupported by evidence, but unfortunately she had a lot of debt and her podcast was now the most successful it had ever been so she couldn’t stop. She ended up pairing up with one of the biggest true crime podcasts going and gets 10s of thousands of views on Youtube, in case you’re curious. Trafficking in other people’s pain is big business.

While I point some of this out just because it annoys me, I am not sure many people are aware of how big this ecosystem has gotten. For every major Netflix documentary, there are thousands of TikTokers and Youtubers doing secondary reporting/commentary, and millions of people viewing their content. Learning all the facts of a lengthy and complicated case is probably just as hard as many scientific fields, and getting everything right takes an extraordinary amount of effort most people don’t have time for in the YouTube/Tiktok era. So we’re left with the three challenges mentioned above:

  • Mediatization: “If it bleeds it leads” has been a truism in media since William Randolph Hearst popularized the phrase in the 1890s. When trying to capture eyeballs, you are going to have to make whatever you are saying entertaining. If scientists can be sucked in to overstating their own findings based on the siren call here, do you really think a documentary film makers are going to overcome this temptation? After all, science has it’s own hierarchy and prestige/awards, true crime is nothing without the media. It is media. Additionally, the media environment for true crime has changed recently from “those experienced enough to get a newspaper job or book deal” to “those who can host a podcast or Youtube channel”, which opened up the floodgates to anyone who wanted to jump in.
  • Monetization: Most scientists have a base salary they are working with and then competing for grants, almost every true crime content creator is reliant on the popularity of their content for money. I made a personal rule not to listen to any content creator who doesn’t maintain a day job, otherwise bending to your audience is not just a temptation, but a financial necessity. Additionally, some of the top content creators have ended up making millions, so there’s a real upside here if you can get your content to hit well enough. Most scientists can only make that kind of money if they hit a blockbuster drug or something like that.
  • Politicization: Just like science got sucked in to a lot of political fights, so has true crime. The most classic case of this might be OJ Simpson, where the case got massive play in part as a way of people expressing their racial anxiety. The impact of politics on this case can be seen clearly by the profound increase in people who believe OJ was guilty by year. As the political conditions changed, so did people’s assessment of the evidence:

While the OJ case is perhaps the clearest example of this, we also know that sensational crime tends to follow the anxieties of the age. Serial killers dropped as mass shootings increased. We may now be entering an era of political assassinations. Some of the true crime “truther” type movements seem to reflect a general distrust of “official” stories, as we see even suspects who plead guilty get rabid fanbases that maintain their innocence.

I think it’s safe to conclude that in both science and true crime, a large influx of participants, money and eyeballs combined with political anxieties have had an impact on the quality of content. Interestingly, I actually encounter more people currently who are willing to be skeptical of science than those who are willing to be skeptical of crime reporting. I think there’s a feeling that the average lay person can suss out a guilty person vs a not guilty person, but I’m not sure that’s true if you’re not hearing all the facts. Our assessment of stories and their truthfulness can often hinge on small details, so it’s important to note that all the same forces that acted on science are present in even larger amounts in true crime.

That’s all I have for now, in the next installment we’ll be looking at problems with the publishing system for both science and true crime.

To go straight to part 2, click here.

The True Crime Replication Crisis: Intro

I started stats and data blogging back in 2012. Those were heady days back then, as the scientific replication crisis (which called in to question the validity of many published scientific findings) was just being uncovered and would indeed would first be called a crisis in November of that year. It was a fun time to be a blogger who knew a thing or two about research, and while I was always a little niche blog with a small but excellent set of readers, I did get the occasional nod from bigger accounts for some of my work. Topics to comment on were plentiful, a good number of people were interested, and it was overall a good way to improve my scientific communication skills.

Over the next decade+, life got busier, my health got more difficult, and my blogging trailed off. A lot of people even in non-stats and research fields knew to question numbers, and blogging was replaced by shorter form social media. I was pretty content just hanging out on the sidelines. I didn’t much expect to revisit that, until a rather unexpected event got me thinking about data blogging and the replication crisis again: I found myself near the epicenter of a true crime shit storm.

If you’ve followed this blog long enough to have some familiarity with me personally and have any familiarity with true crime, you might be able to guess which case. I don’t plan on publicly naming it due to the extreme toxicity around it, but if you’re a regular feel free to shoot me a message and we can chat privately. For everyone else I will only reassure you that neither I nor anyone close to me was directly involved, but I was physically extremely close to the location of the crime and most of the major players, enough that it was extremely hard to ignore even if we’d wanted to. It’s a weird feeling to watch national media descend on mundane places you’ve been to hundreds of times, and to suddenly have people commenting on your town as though it’s their new favorite TV show. We couldn’t check in for appointments without people catching their breath when they saw the town name, and everyone wanted to know your opinion. It was WEIRD. I also got a first hand look at a genre of media I hadn’t spent much time with: true crime. It was rather eye opening, but I couldn’t shake the feeling that I had seen a lot of these issues before. I started looking around at other true crime cases to see how they were handled in the media, and I slowly put it together. This was the replication crisis all over again. Many of the same errors, many of the same issues, sucking a whole different group of people in with various logical fallacies, questionable motivations, and creative data twisting.

I couldn’t find anyone else drawing this comparison, so I decided I needed to blog about it. I want to write the guide I wish I’d had before I had to assess a true crime case from the ground up.

Ready? Ok, let’s go!

So how are we going to do this?

I’ve been trying to figure out how to lay out all the reasons for the replication crisis, and really the most comprehensive thing I’ve found is the Wikipedia page. I’ll be using this archive page from September 10th, just so no one rearranges the article on me halfway through this series. I’m mostly going to focus on the causes and how I think statistical issues actually apply more broadly to the way we evaluate all evidence even outside of traditional scientific study.

I will not, generally speaking, be commenting on court procedures or rules of evidence etc. There are many other people much better placed to do that than I. What I will be covering is how I’ve covered data here in the past: how should you as a media consumer evaluate a claim you hear? If you watch a true crime documentary or listen to a podcast, what should you look for? How should you think about the different claims? One of the reasons I’m not naming the specific case I got familiar with is because I think most of this should apply to every case you hear about.

But wait I’m not totally sure what the Replication Crisis is!

Oh, yeah. Sorry about that, I should have clarified earlier. The replication crisis, broadly speaking, was the slow realization that in many scientific fields published research couldn’t always be replicated. This a cornerstone of scientific research, and having a study not replicate is a bad sign your initial findings may not have been all that correct. For example, if I tell you that on average men are taller than women, it shouldn’t matter if you get a sample from Montana, Maine or Minnesota. If your sample size is large enough and random, you should find the same thing. The problem that started to occur is people would get very large and compelling findings that would disappear during subsequent studies. There were a lot of reasons for this, which we will go in to going forward but also feel free to search “replication crisis” on this blog for a lot of my prior writing on the topic. Here’s a sample.

Great thanks, but what do you mean by “true crime”?

True crime is not crime in general, but rather that genre of media that covers crime. This includes books, movies, podcasts, documentaries and other media that goes more in depth in to crimes, perpetrators or trials. The genre is actually pretty broad, while we typically think about murders or other sensational cases, it can also include fraud cases like John Carreyrou’s Bad Blood reporting on the Elizabeth Holmes/Theranos scandal. It can involve missing person cases or open cases, or it can revisit cases where we already have a conviction. The vast majority (about 75%) of fans are women, and it’s the third biggest genre of podcast on iTunes. It has extremely high market penetration, with about 85% of people saying they’ve consumed at least some true crime content. True crime is the number one podcast content choice for women and your average true crime podcast listener consumes more content than your average podcast listener in general. There’s also a heavy social aspect, true crime podcast listeners are far more likely to recommend their favorite podcasts to others. Overall it’s a several billion dollar market with individual podcasts making millions per year. My Favorite Murder literally calls their fans “the Fan Cult” and “Murderinos”.

I’ll start in next week with more historical and sociological causes, but I want to point out we’re already seeing some similarities. It was at exactly the moment scientific research started becoming more lucrative and in demand, and scientists started becoming superstars that we started seeing cracks form. That’s not a coincidence, but I will follow up in a future post.

To go straight to part 1, click here.

Index:

The True Crime Replication Crisis: Part 1

The True Crime Replication Crisis Part 2: Problems With the Publication System

The True Crime Replication Crisis Part 3: More Problems with the Publication System

The True Crime Replication Crisis Part 4: Questionable Research Practices

The True Crime Replication Crisis Part 5: Fraud

The True Crime Replication Crisis: Part 6 Statistical Errors

The True Crime Replication Crisis Part 7: Random Other Issues

The True Crime Replication Crisis Part 8: Consequences

State and Country Level Can Be Excellent Plausibility Checks for Your Pet Hypothesis

I was on Twitter/X recently and ended up following two rather interesting conversations started by Tweets with strong claims. Of course I can’t find them again, but one asserted that teachers unions were the cause of our educational problems in this country, and the other asserted that the only way to fix the falling birth rate was to raise the status of men in this country. Both of these were interesting enough for me to start following the thread, and people quickly countered them both.

For the teacher’s union claim, it was pointed out that there are 5 states where teachers can unionize, but they are not allowed to do any collective bargaining: Texas, Georgia, North Carolina, Virginia, and South Carolina. One would assume without this power, these unions are pretty weak and indeed that’s what we see. So are these the areas with the best educational outcomes? No. According to this ranking they are 40th, 30th, 34th, 9th and 38th respectively. Those rankings are all over the place, but it’s hard to see a compelling case in that data that defanging a union is a simple solution to our educational woes.

Similarly with the claim that raising the status of men will raise the birth rates, we can actually look at the countries that are worst on the gender equality index. Yemen is currently considered the worst country in the world for this, and here’s how their birthrate has gone in the last few decades:

Here’s Afghanistan, Syria and Iran:

Now while these birthrates are higher than the US, it’s hard to miss that they are also falling. Even if one could overthrow the US and install Afghanistan style gender relations, it’s not clear that line would stop falling at all.

Now none of this is to say these hypotheses had no value, changes to unions or to male status might actually help the intended issues, but it’s important to be aware of their limitations from the jump. In both of these tweets these solutions were presented as clear and obvious with no caveats, but a quick look at real world data suggests they are not going to be silver bullets. For example, you say that Afghanistan is confounded by the unrest there, but how do you suggest you boost male status more effectively than the Taliban with less unrest? What damage are you suggesting unions are doing outside of their collective bargaining? Whatever your hypothesis is, let’s find a place that’s already doing it and see if it worked. If a strong effect doesn’t jump out at you, you have to temper your expectations.

We see this all over the place too, to the point where it’s a good first test for any hypothesis you have. Do you think people aren’t having babies because we don’t have a generous social safety net, free daycare or ample maternity leave? Let’s find some countries that have those things already:

Uh oh, that’s lower than the US. Again, maybe those things will help, but they clearly can’t be the full problem.

The Assistant Village Idiot recent put up a post about the belief by RFK Jr and others that psychiatric meds. The countries with the top anti-depressant consumption are Belgium, Greece, Spain, Iceland and Canada. These countries don’t come anywhere near the US for public mass shootings. We have 8-9 times Canada’s population and 27 times the number of public mass shootings. So we now have to explain why these medications would have a large impact in one country but not another. It’s possible! But it does involve invoking a bunch of other factors not part of the original statement.

Got time for one more example? I’ve spent the past 2+ years hearing that my state (Massachusetts) had a super corrupt police force and an aggressive justice system based on one high profile case that happened in my town. It might surprise you to hear then that Massachusetts actually has the lowest incarceration rate in the country. We incarcerate 241 people per 100,000 residents. I’ve had to talk about this with people from Virginia (679 per 100k), Alaska (744 per 100k) and Illinois (433 per 100k). None of them were aware how high their incarceration rates were, comparatively speaking. Can we come up with a story where Massachusetts has an incredibly corrupt police force and aggressive justice system that only incarcerates people at a fraction of the rate of other states? Maybe, but it’s challenging. Add in the fact that we are bottom 5 for police involved killings, and your job gets even harder.

Like I said, state and country level data may not entirely disprove a hypothesis, but it does give a good first glance in to how compelling your case is. When I’ve pointed this out to people in various situations in real life, the first response I often get is “oh well of course there are other factors”. But normally we started this whole conversation because they made a statement that there was just one compelling factor. We can certainly back off to “it’s a bunch of things”, but that’s not typically where the conversation started. I understand in the social media age declarative statements are king, but state and country comparisons are pretty good at moderating conversations rather rapidly. Highly recommended.

On Hoarding

I am now at the age where I, along with most of my friends, have retired parents. This has led to a natural increase in the discussions of the problems of aging, some of which I expected and some of which I did not. One thing I’ve been surprised by is the number of people I’ve had mention to me recently that their parent(s) have a problem with hoarding. This piqued my interest because I have no direct experience with this (my parents have made a big point of continuously going through their stuff), but when I started to mention that I was hearing this a lot more, I started to get more stories of people’s parents or friends parents who were struggling with this. And these stories were bad. This wasn’t “moms house is a little more cluttered than I’m comfortable with”, these were stories of rooms being rendered fully unusable, important things going missing, and fears of having to be the one to clean it up after they pass away. So what’s going on here? Is this a case of increased awareness, expanded definitions or a real uptick? Turns out it might be all three! Let’s dig in.

What is Hoarding Disorder?

Hoarding disorder is actually a fairly new diagnosis, first introduced in to the DSM in 2013. Prior to that it was considered a subset of obsessive compulsive disorder. The full criteria is here, but it’s basically the psychological inability to get rid of stuff in a way that ends up negatively impacting your life or health. People keep accumulating stuff whether through compulsive overbuying or just refusal to discard anything in such a way that their homes fill up. The estimates are that about 19 million Americans reach the criteria. It’s estimated about a quarter of all preventable fire deaths happen due to hoarding.

One of the more interesting things I found while looking in to this is that a group called Hoarding UK actually publishes something called the “Clutter Index Rating“, a visual guide to what level of clutter might require help or intervention. They recommend that a 4 or above might require help. Here’s an example of their visual for the kitchen:

I was relieved to discover my house does not fall in the problem zone.

Why are we hearing more about this now?

Well, a few reasons. Between the reality show “Hoarders” debuting in 2009 and the new diagnosis being added in 2013, the public did start having a new level of awareness of this disorder. This led to more people talking about it, which tends to lead to more people identifying that their dads inability to throw out any newspaper he’d ever gotten had a real name.

Next, there’s the obvious issue that stuff is easier to accumulate now than ever before. Could you fill up a house with random stuff back in 1900? Sure but it would have taken a lot longer. Interestingly this post was inspired by someone encountering a (likely) hoarder who tried to pick up some stuff they’d left our for free by the side of the road, and despite her whole car being full of random stuff, she started asking if they had anything else laying around she could look at.

But finally, hoarding is not evenly distributed across the lifespan: it is far more common in those over 65. People who just had a clutter problem in their younger years may turn in to full blown hoarders later in life, so as the baby boomers cross age 65 we can expect to see an increase in those impacted. Interestingly despite the initial link to OCD, it actually seems it’s more closely linked to depression. People who have divorced, lost a spouse or are otherwise isolated may be even more vulnerable. Unsurprisingly, this also means that the pandemic boosted the problem, though it’s not clear if that persisted. Sadly, some major cases of hoarding aren’t discovered until the affected person passes away.

So what do we do about this?

Well, much like any difficult psychological problem, there’s not one clear answer. My local council on aging has resources and my state also supplies support, particularly to landlords who may need to evict a hoarder. There are 12 step programs and traditional therapy options, there are services that will clean your house out. However, it is noted that cleaning the house out has a 100% recidivism rate if no other support is given. My state provided this interesting little decision tree, which I appreciated:

But overall this will depend a lot on local resources and exact circumstances. Not an easy spot to be in if you’re a loved one.

Is Life Expectancy the Right Way to Measure Health Care Success?

On my last post, I gave a few scattered thoughts about the UKs healthcare system vs the US system. In the comments, a very astute commenter mentioned that life expectancy was not a great way of measuring how well your health care system was working. This is an excellent point that I think deserves some discussion.

If you start looking in to the US healthcare system, you will very quickly run across a graph like this one that shows health care spending vs life expectancy:

There’s a variety of these charts but they all show the same thing: the US spends the most on health care per capita by a good margin, but does not have the highest life expectancy in the world. We’re about 5 years behind a country like Japan (84.7 years vs US 79.3 years), despite us spending 3 times what they do ($4k vs $12k per capita). I think it’s worth diving in to why this is, and why it may or may not be an accurate measure of how our healthcare system is doing.

Life Expectancy Calculations

There’s a actually a few different ways to calculate life expectancies, and the exact details of what you’re trying to do matter quite a bit. But one thing most ways of calculating it have in common is that they are all impacted quite a bit by people who die young. This is an issue a lot of us are familiar with when looking at historic life expectancies, which tend to be weighed down by the high number of children who died before their 5th birthday. This is a big enough issue that the UN actually looks at both life expectancy from birth and life expectancy at age 15, just to account for both child mortality and mortality at older ages.

So the point is, if you’re in a developed country and you want to understand why your life expectancy looks like it does, the first thing to take a look at is what kills your young people. So what kills young people in the US? Guns, drugs and cars.

Guns, Drugs and Cars

Ok, so before we go any further, I want to acknowledge that the topics of guns, drugs and cars tend to get people a little worked up. Given this, I want to clarify why I’m going in to this. I am NOT attempting to recommend any particular policy solution to the things I’m talking about below. I’ve done some of that in other posts over the years, but in this post I am specifically focusing on 1. If guns, drugs and cars kill people in the US at rates higher than in other countries and 2. If those deaths can be stopped by healthcare spending. This is important because again, that graph above gets used All. The. Time.

If life expectancy has some factors going in to it that cannot be fixed with healthcare spending, then that is a reason to take that graph a little less seriously next time you see it. Alright, with that out of the way, let’s look at some data!

Since 1981, the single largest killer of those under age 44 in the US has been “unintentional injuries”. This is a large category that includes drowning, poisoning, falls, motor vehicle accidents and “other” accidents. 90% of them are motor vehicle accidents or poisoning, and “poisoning” is the broad category that includes (and indeed is dominated by) recreational drug overdoses. Here’s a quick comparison of the top causes of death for those age 1-44 in 1981 vs 2023. Note: these are raw numbers, not population adjusted. ChatGPT suggests the under 44 population probably went up by 22 million people during the 42 years covered here.

19812023
Unintentional injuries58,50083,300
Malignant neoplasms22,00017,400
Homicide17,90016,900
Heart Disease16,40016,100
Suicide15,90023,400 (now #2 cause)

You can quickly note that the two categories here that the healthcare system has the most control over malignant neoplasms (cancer) and heart disease both went down during the timeframe we’re looking at here. Homicides also went down, but suicide and injury deaths went up. Given that in the US suicides are about 50% firearm deaths and homicides are about 80%, we can pretty accurately sum up the top killers of young people as “guns, drugs and cars” So how does this compare to other countries? Well the Global Health Data Exchange visualization tool can help us there. I picked a few countries that show up as having higher life expectancies than the US for less money to compare us to on the top causes of death, and here’s what I got. Note: I had to pick one age category for the visualization, and they didn’t have exactly the age 1-44 used above, so I used 15-49. We’re just getting a sense of the differences here. Anyway, here’s what I got:

Road injuries: the US sees twice as many deaths per capita as the next closest country, and substantially more than the lowest comparison countries I picked.

Drug abuse deaths (aka overdoses): again, we lead substantially here.

Suicide: we are one of the top here, but are much closer to other countries

Homicide (aka “interpersonal violence”): again, we are top

Cancer (aka “neoplasms”): we are middle of the pack

Heart disease: back at the top

So again, guns, drugs and cars appear to have a rather substantial impact on our mortality in younger people, and it’s not clear what our healthcare system could do differently to stop this. For motor vehicle accidents and murders, the health care system is mostly involved after the fact. There’s some argument that we could maybe improve our care of severely wounded people, but I don’t think anyone is really making the argument that our trauma care in the US isn’t as effective as that in Japan. It seems more likely that there’s just a lot more car accidents and violent incidents here. Healthcare spending can’t stop that.

For suicides and drug overdoses, one can argue perhaps that a better funded mental health/rehab system could help things, but as anyone who has dealt with a suicidal or addicted family member knows that it’s not quite as simple as that.

I will note that I often hear obesity thrown out there as another issue the US faces, and I think this is true based on the cardiovascular disease numbers. The only reason I don’t include it in “the big three” is because it is mostly taking out people in later years, and while we are above most other countries, our problem isn’t twice as bad like it is with road deaths, homicides or overdoses. We could definitely add it in though, and we’d still get back to healthcare spending not changing much. New medications like Ozempic might change that math, but up until recently that was pretty true.

I also leave it out because honestly I’ve heard waaaaaaaaaaaaay too much “if we stopped spending money on medication and let everyone go to the farmers market, we’d be great!” type stuff. That’s a nifty idea but it’s still not gonna change car crash deaths, overdoses or homicides, and so the bulk of our problem remains.

Impact on Life Expectancy

Ok, so what does this do to life expectancy, and how do we know this is the major driver? Well the Financial Times did an interesting analysis here. It’s paywalled, but the author did a Twitter thread here. Some graphs were included, like this one that shows that US citizens over 75 basically have the same life expectancy as our peer countries, whereas those under 40 have a much greater chance of dying:

This graph shows a similar thing, the probability of dying at a particular age is much higher for young people in the US vs peer countries, and similar for older ages:

If you look at the actuarial tables from the Social Security Administration, you can see this as well. Those tables look at a hypothetical cohort of 100,000 people born in the same year and show how many will still be living at each age. The UK releases similar data:

US – maleUK – maleUS – femaleUK – female
Age at which 1 in 100 of the cohort are deceased16242134
1 in 2035504957
1 in 1050605966
1 in 562696974

People in the US are just more likely to know someone who died young.

Other Causes

I actually couldn’t find a comprehensive source for top issues with our life expectancy in the US, but I did finally think to use ChatGPT to ask, a resource I’m still not used to. I was pleased that despite not using it until this point in the post, the top causes it listed that are making the biggest impact are drugs, cars and guns. I asked it a few different ways how much we could add to our national life expectancy if those were closer to peer nations, and it suggested we’d add 2-5 years, which if you’ll recall would put us up much closer to the top.

After it listed those causes, we got in to a few (cardiovascular and metabolic disorders) which can be tied to obesity. It also added in smoking, maternal health, and general mental health. Racial differences, socioeconomic status and access to healthcare were listed last, with an estimate we could get back about a year of life expectancy if we fixed all of that.

To reiterate the point that things that impact young people count a lot more than things that impact older people, ChatGPT estimated that “solving” the opioid crisis would give us back about a year of life expectancy for our entire population. “Solving” obesity? About half a year. Stunning when you consider how many more obese people there are than opioid addicts, but again, one death of a 22 year old takes off 56 life years, as much as 11 people dying at 74 rather than 79.

Immigration?

One weird data point I encountered while doing this work is the differences in how countries count non-citizens. I couldn’t verify how each country counted immigrants/illegal immigrants/refugees, but it seems likely that how they do that counting could impact their overall numbers. I don’t know for sure but I would guess that those raised in third world without adequate access to nutrition or health care may always have higher medical needs (including translation services) and lower life expectancies than those who have always lived in a first world country. Differences in counting is going to matter quite a bit here.

Impact on Healthcare Spending

So finally we loop back to the ultimate topic: are we really spending more money for worse outcomes? Well yes, sort of! But it’s not really the healthcare systems fault. If you have two countries with the same exact health care system but one country has people who get in lots of car accidents and the other doesn’t, life expectancy will be lower and costs will be higher. External injury deaths are a huge driver of mortality in the young, and if they are not equal across populations their outcomes will be unequal. The healthcare system mostly cannot prevent these deaths, they are just dealing with what comes across their door.

It’s worth noting that in addition to the deaths counted above, there are also going to be a bunch of people impacted by car crashes, drugs and guns who won’t die but will end up with health problems that will both cost money and shorten their lifespan. Many people I know who were in bad car accidents when they were younger end up with early arthritis in the impacted joints or other issues. Former drug users also may carry long term issues like Hepatitis C or HIV infections. Basically the pool of people who died under 50 is just the center of a much larger group of those injured early on who may have issues. These will also run up healthcare costs.

Again, none of this is to say what, if anything, we should do about these risks. But it is important to know when you see the spending/life expectancy graph exactly what we’re dealing with, and what can or can’t be fixed simply by throwing healthcare dollars at it.