Pitfalls of Relying on "Lived Experience" to Resolve Debates over Public Policy

This oft-used trope overlooks the difficulty of generalizing from individual cases and of making accurate assessments of their policy implications.

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Activists, politicians, commentators, and others often say that we should judge policy issues based on the "lived experience" of members of various groups, particularly those that have been victimized by various types of injustices. Thus, if we want to understand and combat racism, we should rely on the lived experience of minority groups who are its victims. If the problem is sexism, we should credit the lived experience of women. Both left and right trot out victims of school shootings to use their lived experience to bolster their respective positions on how to combat gun violence.

In a recent article, philosopher Tim Hsiao highlights some of the shortcomings of this popular mantra:

[A]re lived experiences really that special? No. Quite simply, appeals to "lived experiences" are exercises in bad statistical reasoning….

To see why, let's suppose that I made the argument that smoking causes cancer, and that I backed this up with a mountain of scientific data and peer-reviewed studies. Now suppose that someone responded to all of this with the following: "But my grandpa Bob smoked cigarettes all of his life and never developed cancer! So smoking doesn't cause cancer after all!"

Would you be convinced by this reply? I hope not. Smoking is a contributory cause of cancer: those who smoke have a much higher likelihood of developing certain cancers than those who don't because the act of smoking contributes something toward that outcome, even though that outcome doesn't always happen….

The point behind the example is that personal anecdotes do not invalidate statistical generalizations, which are by nature probabilistic….

Lived experiences are often vividly used by progressive activists as evidence of widespread injustice, accompanied with a call for action and social change. Yet basing one's entire case for widespread injustice and sweeping social change on lived experiences is, quite simply, bad statistical reasoning. Why should one's personal experience of (say) racism carry any special weight? Should the experience of the smoker who never developed cancer also carry special weight?  What about the experience of the unvaccinated person who never got a preventable illness? Or the experience of the chronic gambler who managed to keep his life intact?

The point is not that experiences of racism are like these other experiences or to cast real experiences of racism in a negative light. The point is that one cannot prove or disprove generalizations simply based on personal experiences. This is a pretty basic rule of statistical reasoning that seems to have been lost on many people who should know better. Just because one experiences racism (as I have) does not show that racism is widespread or deeply ingrained, any more than one's experience with a smoker who did not develop cancer shows that smoking doesn't cause cancer.

As Hsiao explains, one major pitfall of relying on personal "lived experience" is that it can't tell us whether the experience in question is representative. I myself have personal experience with a number of matters relevant to political debates, including poverty, anti-Semitism, immigration, and  online death threats. But it would be mistake to generalize based on these events, without knowing how typical they are. In my recent book on immigration, I briefly recounted part of my own story, but tried to emphasize only the parts that more systematic data shows are representative of broader trends. And, before I wrote the book, I spent years studying immigration-related issues. One person's necessarily limited and sometimes unrepresentative personal experience was no substitute for that.

The issue of representativeness is far from the only pitfall of privileging the views of those with lived experience. In many cases, people who have experienced some type of evil do not have any special insight on how to address. As I have pointed out previously, victims of school shootings don't necessarily have any special insight on how to prevent such events from recurring. The same is often true of victims of racism, anti-Semitism, and many other kinds of oppression and injustice.

Further, it's important to emphasize that  members of the groups in question often differ among themselves about how to address the wrongs they have suffered. The left can cite survivors of school shootings who say the solution is more gun control. The right, in turn, points to those who say the answer is more gun rights.

Barack Obama and Clarence Thomas are both black men who grew up in largely fatherless homes, and have experienced racism and discrimination (Thomas, perhaps more so, because he grew up in then-segregated Georgia). Both have written eloquent memoirs based on their experiences. Yet they also have drawn very different conclusions from them. If you credit the lessons Obama derived from his experience, you have to reject much of Thomas's—and vice versa. If there is a way to resolve the disagreement between them, it requires systematic analysis of evidence. Privileging either man's lived experience is of little help.

Perhaps the conundrum could be resolved by saying we should privilege the views of the majority within the group in question. The majority of African-Americans hold views closer to Obama's than Thomas's. So perhaps we should privilege former's lived experience over the latter's, when the two conflict. But majority public opinion is often influenced by ignorance, partisanship, and a variety of other biases. That's true of a wide range of groups. Thus, we cannot assume that majority opinion within a given group is necessarily the "correct" interpretation of that group's lived experience.

Admittedly, there are some situations where lived experience really does have great epistemic value. If someone claims that "X never happens," the claim can readily be refuted by citing someone who can credibly claim to have personally witnessed X. The testimony of Holocaust survivors is an important part of the evidence proving that the Holocaust actually happened (though there is a lot of other evidence, too). The testimony of former inmates of Chinese concentration camps for Uighurs gives the lie to Chinese government claims that such camps do not exist. At the same time, however, Holocaust survivors rarely have any special insight into how to prevent similar atrocities from occurring again.

It is also often true that only someone who has personally experienced a given event can fully grasp the subjective experience of what it was like to go through it. If you've never been incarcerated in a concentration camp, you may well never be able to understand how it feels.  The same is true if you've never been a victim of anti-Semitism, sexual assault, or racial profiling. But such subjective feelings are rarely enough to base policy decisions on. And a person who cannot grasp the subjective experience of being a concentration camp inmate or a victim of racial discrimination, can nevertheless still come to understand why these are grave injustices.

While Tsiao's article and other recent analyses of lived experience focus primarily non left-wing arguments for privileging the lived experiences of discriminated-against minority groups, the lived-experience trope is easily used for right-wing ends, as well. The 2016 Republican convention, for example, featured speeches by relatives of people killed by undocumented immigrants. Their experiences, however tragic, do not change the fact that immigrants, including undocumented immigrants, actually have much lower crime rates than native-born Americans.

Consider, also, such examples as white men who believe they have been victimized by affirmative action and various types of ethnic nationalists who believe their culture and economic prospects have been damaged by immigration. Crediting the "lived experience" of these people is likely to lead to conclusions few progressives would like. But if the perceived lived experience of women or racial minorities must be privileged when it comes to wrongs members of those groups believe they have suffered, the same logic applies to other groups, as well.

For every left-wing life experience narrative, there is a right-wing one that can be used to bolster the other side—and vice versa. If we want to get at the truth, we cannot give a privileged status to either. Rather, we must always  consider whether the experience in question is true, whether it's representative, and whether the policy recommendations derived from it are backed by logic and evidence.

 

 

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  1. I hope people link this every time someone starts talking about their “lived experience” as a justification for one public policy or another.

    1. One of the proposed remedies to the failure of the lawyer profession is to require some prelaw subjects. One should be a course in Critical Thinking to inoculate the student against the idiocy of law school, and its brain damaging effects.

      One would learn about fallacies, which are replete in all subjects of the law, enforced at the point of a gun, the sole validation of the lawyer profession.

      Anecdotal Fallacy reviewed:

      https://fallacyinlogic.com/anecdotal-fallacy-definition-and-examples/

      Sorry. The Holocaust survivor is the least helpful to prevent such a recurrence. He allowed it to happen, after all.

      The other remedy proposed is to go beyond 4th grade math, that needed to count money, and have some 5th grade math. It includes fractions, and the idea of the denominator.

      A career criminal is killed by the police after acting the fool. Yet, the police answered 21 million 911 calls by those people, and provided good service. That is the denominator.

      1. Even when looking at fractions, they should be big enough to feel. It is tough to feels a fraction smaller than 30%.

        Smoke 2 packs a day for 50 years, for 100 pack years, the chance of getting lung cancer is 1 in 7.

        1. I enjoyed this joke. In Paper Chase, law prof Kingsfield tells his students, “You come into here with a skull full off mush and leave thinking like a lawyer.”

          Leave with supernatural beliefs. Impose massive fallacies on the nation at the point of a gun. Be in utter failure in every self stated goal of every law subject. Leave and join the most toxic occupation in the country, 10 times more toxic than organized crime.

          Kingsley needs an ass kicking and to stand in the corner with a tall dunce cap, the idiot.

          1. In fairness, lived experience is preferred in the policy maker under the math leaning utilitarianism. That is my preferred method of decision making. That should have been mentioned in the post, to present all sides.

    2. Me too. 🙂

      Professor, I enjoy your occasional articles at ToI.

    3. Great article Ilya. Credit where credit is due.

    4. The plural of anecdote isn’t data.

    5. My “lived experience ” includes being robbed by a black kid. Does that qualify as a basis for making public policy?

  2. Statistics is a kind of whiteness. The world needs less of it.

    1. This kind of comment is the epitome of racism. The world needs less of it

  3. We should acknowledge that a lot of our policy understanding is informed by our own life. And that such information will often have a level of detail you can’t get elsewhere.

    That being said, we should not privilege people who connect their positions to something they experience over those with a more academic understanding.

    Actually, both have value, and a good policy will have both sorts of people in the room.

    1. We should acknowledge that a lot of our policy understanding is informed by our own life.

      Yes, and we call that “bias”.

    2. We should acknowledge that a lot of our policy understanding is ill-informed and based far more on (non-religious) faith/intuition than actual rigorous analysis of cause/effect. “Common Sense” is as ill-informed as “lived experience”.

      It’s simply wrong to base public policy on “I’ve seen it happen!” I can both believe that and ask for that “lived experience” to be substantiated across the polity.

  4. “And, before I wrote the book, I spent years studying immigration-related issues. One person’s necessarily limited and sometimes unrepresentative personal experience was no substitute for that.”

    Pot, kettle.

    1. Research is not “lived experience”.

      1. It is if it is driven by pre-conceived notions.

        1. It isn’t. Words have meaning.

  5. This article makes me think of a story I heard on NPR recently about how professional psychological associations recognized a psychological malady in slaves wanting to run away from their masters. I can see runaway slaves being lectured about how their ‘lived experience’ shouldn’t be taken to negate that….

    1. This article makes me think

      If only that was possible.

    2. And slaves drove antebellum public policy decisions?

  6. Really, cites to “lived experience” is just the elevation of bigotry over reality. After all, every bigot will tell you that their lived experience is that all X are Y, for whatever values of X and Y they’re bigoted about. Now, personally, I would question the bigot’s assumptions, but for those who to defer to “lived experience,” they have little choice but to grant it the same weight as other lived experiences.

    1. Might want to look phenomenology. Nasty Critical Race Theory Marxist thing!

  7. To put it gently, statistics can miss things that experience catches. Statistics mostly concerns itself with averages and what happens in ghe middle. But social problems often involve extremes, what happens at the tails. Statistics can completely miss that. Similarly, statistics requires stability, assuming the future is similar ro the past. But singular, rare events can cause abrupt changes and be fundamental drivers of our reality. The archives of journals are full of useless papers predicting an entirely different future from the one we have by taking a sample of then-current people or extrapolating from the previous five or ten or twenty years.

    If science could reliably predict, Marxism and planned economics would work. The whole critique of such things comes from the idea that our state of knowledge is much humbler than that and our ability to reliably prefict the future is very limited.

    Finally, statistics when it works addresses clearly formulated hypotheses. But what hypotheses should we formulate? Statistics cannot answer that problem. It cannot help us with what question to ask. That generally comes from personal observation and experience. Similar, statistics cannot tell us if the method of observation actually addresses the real matter of concern. Often it doesn’t, or simply misses something of importance. We have to look under the hood, using experience, to address that.

    Experience is of course limited as well. But sometimes we cannot help but project our limited experience into a future and onto a scale where no reliable inference can be supported, making a decision without adequate evidence because we have to. We often have no other choice.

    Experience and personal observation aren’t everything. But denigrating them as nothing and thinking that scientific method and statistics can solve all problems and obtain all knowledge reflects an arrogance and a hubris that represents a fundamental misunderstanding of what science is about – both its strengths and its limitations. It reflects an attitude that thinks that we know far, far more than we actually do. One doesn’t understand something until one understands its limits. The person who thinks something is all-powerful is thinking magically, not maturely. To think that science is all-powerful is to think of it as a kind of magic, even a kind of deity, which is to say not to understand it at all. This is true about science as anything else.

    Indeed, to use scientific terms and concepts to support essentially magical thinking is the very fefinition of pseudoscience.

    We have no other choice but to try to integrate our different ways of knowing about the world, accept that each has strengths and limitations, and none can tell us even close to everything we need to know. Sometimes statistics catches something experience misses. But sometimes the reverse is true.

    1. This is an excellent comment.

      Finally, statistics when it works addresses clearly formulated hypotheses. But what hypotheses should we formulate? Statistics cannot answer that problem. It cannot help us with what question to ask. That generally comes from personal observation and experience. Similar, statistics cannot tell us if the method of observation actually addresses the real matter of concern. Often it doesn’t, or simply misses something of importance. We have to look under the hood, using experience, to address that.

      Of course. “Lived experience” is not the end of research, but it is a critical part of the beginning.

      1. It is not an excellent comment, as it misunderstand statistics completely.
        Statistics does not care about individuals, it models populations – and it is quite aware that individual things (people or objects) differ. The majority of statistics deals with attempting to compensate for these errors, in fact.

        As for “lived experience”, that’s just another word for anecdote. It isn’t data, and should not be treated as such.

        1. That’s note either of the theses of the comments you reply to.

          I will make it easy:
          “It cannot help us with what question to ask.”

        2. I don’t think it misunderstands statistics at all. I don’t think ReaderY is saying that you talk to a few people, or even a fair number, and then announce your conclusion, rather you get an idea of what the issues are.

          Before you can start gathering data for your statistical analysis you have to decide what question you are addressing, what data to gather. That’s where talking to people helps. It gives you insight into what might be happening.

          Suppose you are interested in sex discrimination in employment. Before building your models and digging into databases, go talk to some women to find out what kinds of discrimination they feel they have experienced – hiring, promotion, wages, working conditions, evaluation, assignments, etc.

          Then go ahead.

    2. “If science could reliably predict, Marxism and planned economics would work”

      Bzzt. Thank you for playing

      Science can and does reliably predict that individuals, en mass, have more information available to them than central authorities ever can, so “central planning” is doomed to failure.

    3. “Experience and personal observation aren’t everything. But denigrating them as nothing and thinking that scientific method and statistics can solve all problems and obtain all knowledge reflects an arrogance and a hubris that represents a fundamental misunderstanding of what science is about”

      Bzzt again.

      “Experience and personal observation” are only valuable if you’re capable of being honest about the reality of events. I was recently reading about a black female TSA agent who had moved to Vegas, and now “was being harassed by racist cops”, and “weighed down with massive fines for traffic infractions”!!11! (Was that here?)

      You look down into the details, and you find that she’d been doing a lot of speeding and reckless driving, and when pulled over she also got tickets for expired license / registration / no insurance.

      Which she just couldn’t be bothered to renew. Or bothered to pay her fines, before more fines were stacked on top.

      Oh, and that when she was wearing her TSA jacket while pulled over, she usually got let off with a warning.

      But it was all racism!!11!

      “Wah, the cops routinely pull us over for driving while black!” Hmm, we’re looking at the statistics, and black drivers are getting pulled over no more often than white.

      “Lived experience” is bullshit you pull out when there’s not logic or reason behind your claims

      1. GregJ, do you see what you just did? Confronted with a policy issue, you chose to analyze experience, instead of relying on logic or reason. That turned your comment into a better contribution to a policy-making dilemma than either of the other two methods could have delivered.

        1. Stephen,

          Logic and reason have already proved the Left to be completely in the wrong.

          And the person I directed my comments at isn’t going to care about that “lived experience”, wont’ in any way respond to it.

          Because the POINT of “lived experience” is to say “I don’t care abotu facts, reason, logic, or opposing data. I have my story and that’s the only thing that matters.”

    4. Experience and personal observation aren’t everything. But denigrating them as nothing and thinking that scientific method and statistics can solve all problems and obtain all knowledge reflects an arrogance and a hubris that represents a fundamental misunderstanding of what science is about – both its strengths and its limitations. It reflects an attitude that thinks that we know far, far more than we actually do. One doesn’t understand something until one understands its limits. The person who thinks something is all-powerful is thinking magically, not maturely. To think that science is all-powerful is to think of it as a kind of magic, even a kind of deity, which is to say not to understand it at all. This is true about science as anything else.

      Bravo!

    5. I think you’re attacking a strawman. You also seem to fundamentally misunderstand how science works.

      Yes, any given research program starts from anecdotes. But those anecdotes will quietly disappear as the data comes in. You don’t go back to anecdotes once you have real data – you use the data. If those anecdotes end up being outliers, a scientist accepts the anecdotes were not typical. They don’t continue to insist those anecdotes are evidence of something for which they can’t collect collaborating data. It’s a type of magical thinking to believe that processes are governed by an interpretation of anecdote despite being unable to document it more generally.

      Science is not ‘all powerful’. I’m not even sure what that would mean. Science is a method, not a thing. But science is the *only* method that gives us reliable information about what is *not* true, and thus (by ruling out alternatives) some idea of what is true.

      We’re all in plato’s cave, looking at shadows cast on a wall. If you rely on anecdote, you’re taking one view of the wall, and relying on someone’s interpretation of that view – a just-so story. Science not only demands multiple views of the shadows on the wall, but attempts to cast shadows in different shapes to see how you would create a particular shadow-casting. It’s not perfect – we’re still flailing about in a dark cave – but it’s a lot better than relying on just-so stories.

      1. Let me give an example of a case where you had to go back to anecdotes after you had real data.

        The consumer price index, the standard measure of inflation, was created in the 1950s. The index weighted prices based on how consumers in the 1950s spent their money, creating a fixed basket of goods and services and giving consistent weighting to permit an apples-to-apples comparsion across years.

        Over more than a half century, consumer spending priorities changed. Housing, education, and other needs started occupying a much higher percentage of budgets. New products and services that didn’t exist before became necessities.

        At some point people started arguing that the 1950s basket and its weighting simply didn’t reflect reality any more. It had so little to do wifh how consumers soent their money that its estimates of inflation were basically useless.

        So people went in, resurveyed consumer habits, and came uo with new baskets with new weights.

        This is an example of where anecdotes trumped data. In order for the question of whether the datais talking about the right things to arise, you have to be willing to look at the research endeavor and its data critically. This requires using lived experience to ask whether the research makes sense, whether it is pointed in the right direction and whether there might be something important it might be missing.

        If we simply discount lived experience because we have data, the basket would never get rewrightrd. After all, goods and services invented after the basket was created don’t even included in the survey! Your data can’t tell you that your data is incomplete. It can’t tell you that there are a lot of goods and sevices, or a lot of consumers, that your survey method is missing entirely. Only lived experience can do that.

        1. I disagree that’s an example of anecdote trumping data. The original data (on consumer preferences) were from a particular point in time. There was no reason to think consumer preferences should be constant with respect to time. It wasn’t new anecdotes that were needed, but new data about consumer preferences. Anecdotes would be useless – because anecdotes don’t generalize to a whole population.

          (And to do it properly, such data collection should be continuous, because consumer preferences are going to change over shorter timespans than decades. Which doesn’t mean you can change the CPI definition that often since you want to compare across years, but that gives you the ability to know *when* you need to change it).

          But it’s not really a triumph of lived experience, because you could have had someone living in the very year CPI was codified where the CPI assumptions didn’t match up with their lived experience, and you could have had someone 30 years later for whom the 1950s CPI assumptions did roughly match up to their lived experience. Lived experience is fickle – data tells you how typical that lived experience is, and thus data is key either way.

          What it is an example of is a badly conceived project where data was poorly applied by people who apparently sucked at understanding economic history. (Even in the 1950s, it should have been clear that consumer preferences change. It would have been within the lifetimes of some professional economists that horse and buggy was the dominant mode of transportation).

          It would be like assuming that a biodiversity survey from the 1980s for a patch of forest was still applicable today, without even bothering to check if there was still a forest there, much less doing a new survey.

          1. Therein lies the problem. Prediction requires making assumptions that features relevant to ones model will remain constant over time. Even when things change, they have to change according to the mdel, so that the model remains valid over time.

            If one can’t assume that, one can’t assume ones prediction model is reliable.

            There are many situations where one can’t. Human history in general, economic or otherwise, is one of them. Historical knowledge is based on documenting and analyzing experience, not on science of the predictive sort.

            And in general, in order to tell that your model is or has become invalid or you are not collecting the right data, you have to use knowledge that comes from outside the model and outside the data you are collecting. That knowledge comes from, or at least begins with, experience.

            Only experience can give you the idea that something is wrong which then enables you to begin checking systematically.

            In your biodiversity example, if you check that the forest is still there, you do so by personal observation. That’s lived experience right there. It’s exactly what it is. You are checking the model against your lived experience, and using your lived experience to tell you something is wrong with the model. I think your example supports, rather than contradicts, the idea that statistics cannot completely replace personal observation and lived experience. We cannot rely on statistics alone. Lived experience remains relevant.

    6. If science could reliably predict

      That statement betrays a fundamental ignorance of what “science” is. Making reliable predictions is the very essence of scientific models. Theories (and groups thereof) like quantum mechanics, biological evolution, et al make predictions that have proven to be amazingly reliable (with exceptions, of course…nothing is perfect). In fact a great many technological advances you rely on every day are possible only because of that sort of predictive reliability.

      1. Not all science is predictive.

        Cosmology, for instance, is largely descriptive given the timescales on which it is operating.

        1. Evolution is another example. We can explain past evolutiok. But we can’t predict which direction future evolution will go in, especially not over any long period of time. Like human history, that too depends on no small part in fundamentally unpredictable, “butterfly effect” type events.

          1. Well, we can predict some directions in evolution, at least in the short term. (Changes in species coloration for species that live in proximity to humans and for which camoflauge is important, for example. Or, as habitats fragment and populations of some species end up living on effectively islands, island effects in terms of the mechanisms and outcomes of evolution are increasingly likely).

            No, we can’t predict exactly all changes which will happen. Partly that’s because evolution is ultimately probabilistic, partly that’s because evolution leverages existing genetypic and phenotypic variation, which is poorly surveyed within most populations, and partly because evolution is a response to selective forces operating over long timespans, which are themselves hard to predict.

            It doesn’t help that most evolution happens over long timescales, much longer than evolutionary biology has been around.

            But we can predict some evolution. The rise of antibiotic resistant infections was predictable, and tools to estimate the likelihood of the emergence of new resistant strains were being discussed over a decade ago (see, for example, https://www.nature.com/articles/nrmicro1796 ).

            And we can predict the modes by which evolution will operate at various scales. I guess it partly depends on what you think it is you’re trying to predict. A short term evolutionary prediction that could be made would be, given a particular selective gradient this year (low rainfall in some area, for example), how will that impact the survival probabilities of different phenotypes within a species. Making predictions like that is certainly possible for some habitats and species therein. (Darwin’s Finches would be doable in that example).

            Now, as soon as you can predict rainfall centuries in advance (and other similar things), scientists could start hazarding guesses at longer term evolutionary trends with some accuracy.

        2. Climatology, too.

      2. Glendower: I can call spirits from the vasty deep.
        Hotspur: Why so can I, or so can any man! But will they come when you do call for them?

        —William Shakespeare, Henry IV, Part I,
        Act III, Scene1.

        If I understand your argument, the problem here is that Hotspur doesn’t understand what spirit-summoning is. The very definition of spirit-summoning is calling spirits. And this definition provides all the logical proof needed to prove that they will come when called. If critic casts doubt on that, spirit-summoners can simpy look down at yhe critic’s ignorance, remind thag spirit-summoning iscalling soirits BY DEFINITION, it’s exactly what it is, and thereby assure that everything is indeed in order.

        Science can’t reliably predict human history, at least beyond a very short term and a cery limit scope. It’s too irregular. Isolated rare events regularly have huge butterfly-like effects.

        That was one of Karl Popper’s most important points. And he wasn’t the only one to say this.

  8. There’s a fine line here. It’s true that lived experience is subjective and is not necessarily the basis for sound public policy. But it’s also true that someone born with a silver spoon in their mouths does not understand what life is like for someone who grew up in poverty, and should not pontificate to those who did. Drawing that line is not always easy.

    1. ” But it’s also true that someone born with a silver spoon in their mouths does not understand what life is like for someone who grew up in poverty, and should not pontificate to those who did”

      Great. So every single leftist who did not personally grow up in poverty will STFU about the subject, right?

      No? yeah, that’s what I thought

    2. Tell that to every non-white/female who feels qualified to lecture about white male privilege.

      1. White privilege is something nonwhite people experience, and white people don’t notice.

        1. … and a perfect example of the anecdotal crap discussed in the article.

          Yeah, yeah I get it. The same guy who is so quick to dismiss anecdote when brought up by others is the first to adopt it when it suits his narrative. It’s not important that its anecdote only that it forward the narrative. I suppose its “lived experience” when convenient and anecdote otherwise.

          1. You don’t think there are any studies on white privilege?

            There are countless studies. About housing, about hiring, about perceived aggression.

            1. I’m sure there are “countless studies”

              And I’m sure they’re all total garbage

              But, I subscribe to reason and logic, so I’m willing to be proved wrong.

              What’s the best study proving “white privilege”? By best I mean a combination of “rigorously done” and “actual impact”.

              IOW, if you have a really rigorous study that shows that people smile more at white women than at black women, and that’s the best you can come up with, I’m not going to care.

  9. Never heard the phrase “lived experience” before, but the quote about the grandfather who smoked reminded me of the simpler explanation: people who say only victims of racism can advise on how to cure racism are in effect saying that only victims of cancer can advise on how to cure cancer.

    1. The victims of cancer had the risk factors and got cancer. Least useful to prevent cancer.

  10. There have been quite a lot of posts on this blog which would not have been written if the writer had a nonwhite/ female/ nonaffluent/ practicing lawyer person available to bounce ideas off first.

    1. Of course that only works the one way, right? Wokies who right nonsense would never ever have changed their mind if they’d had a sane practicing lawyer person available to bounce ideas off first.

      Usually it’s a good idea to reverse your thoughts and see if they still apply, before committing them to the rotating rusty silicon of archives.org.

    2. What a racist and sexist thing to say

  11. “Activists, politicians, commentators, and others often say that we should judge policy issues based on the “lived experience” of members of various groups”

    I’m all for valuing “lived experience”.

    I am human, I have lived, I have experience. And my experience is diametrically opposite of what the Left wants.

    So, by all means, let’s go by “lived experience.” Mine.

    Their only response to that is to engage in racist and / or sexist babbling that boils down to “you have the wrong skin color, so you don’t matter.”

    And I’m happy to make that the focus of the discussion, so long as they attempt to push their “lived experience” BS.

    And if they want to make it a matter of numbers, that’s even better. Because that’s an argument that the trans and their desires, for example, simply don’t matter at all. Neither do gays, or any other small minority that they Left wants to use as an excuse to push their insane policies.

    So let’s play

  12. Choosing policy is a problem, because policy is always about the future. No method anyone has come up with delivers reliable predictions about the future on any scale commensurate with significant policy problems. Among 4 alternatives commonly relied upon, which to choose? Here they are:

    1. Statistical analysis.

    2. Estimates of plausible consequences.

    3. Rationalism.

    4. Experience, lived or otherwise.

    Statistical Analysis — In principle, statistical analysis has an edge on the others—the edge being rigor. But achieving rigor in a socially-relevant context is hard, almost impossible. Even when limiting analysis to math-related topics like economics, statistical predictions about future outcomes fail routinely, often notoriously, and, over time, almost universally. If anyone had ever found a way to made statistical predictions reliable for policy purposes, no one would be debating these questions today. On the plus side, statistical analysis at least creates the impression of delivering useful information about the past. It fails utterly when tested against future results.

    Estimates of Plausible Outcomes — Relying on plausibility amounts to playing hunches. Some folks are much better at that than others. Politicians quickly become specialists in guessing social consequences consequent to plausible-sounding proposals. They stake careers on their ability to do it. Problem is, no one has found any way to make politicians stake their careers on taking a guess each time the nation requires a policy choice. Mostly, politicians sensibly distrust their own abilities, don’t like the career consequences implied by uncertainty, and duck every question they can. Consequently, policy challenges chronically outnumber plausible proposals to deal with them politically. Folks on the sidelines, without a personal stake in being right or wrong, have no trouble offering plausible-sounding proposals. Those get ignored by policy-making political professionals, who prefer to make choices based on more reliable criteria, such as which donors will give them money.

    Rationalism — Rationalism is, hands down, the worst of the 4 methods—but, for some reason, the overwhelming favorite of ideologues of all stripes. Marxists love rationalism. Libertarians love rationalism. Rationalism is thought short-circuited. Axioms are bruited, and reason deployed. Predicting the future becomes a simple matter of reasoning from the axioms to discover facts. Experience, if it intrudes, gets tested. If it is found to flatter the axioms, the experience is embraced—otherwise, rejected as irrelevant or mistaken. The axioms remain, ever and always, impervious. Nothing delivers closed-minded policy stasis as reliably as rationalism.

    Experience, Lived or Otherwise — Experience has the disadvantage of being the loosest, least organized, most-readily contested, all-around messiest guide to policy choices. The history of policy making teaches that rarely if ever will a policy maker enjoy any clear-cut, agreed-upon consensus for what experience has actually been, let alone for what it implies about policy and the future. That makes it the best of the 4 methods. Choosing experience as the right policy guide forces acknowledgment of uncertainty about future outcomes. It implies a need to test them continuously. That frees policy makers to un-commit, and instead experiment, test results, and change course based on what the future actually delivers. Policy makers may not have the wisdom to do that, but relying on experience at least frees them to do it if they are wise. Experience works best because its lack of rigor makes it paradoxically the best-structured method to match policy to an unpredictable future.

    Beginning with an acknowledgment that the future will always remain massively unpredictable is the only way to think sensibly about policy making. Policy-making methods which do not accommodate that premise, or which purport to counter it, should be rejected out of hand.

    1. “Choosing experience as the right policy guide forces acknowledgment of uncertainty about future outcomes.”

      Wrong.

      The people who push “lived experience” are doing so from a space of “there is only one truth: ours. And we will ignore everything else while we shove our truth down everyone else’s throats.”

      That is the reality of the situation. Please stop pretending otherwise

  13. Rather, we must always consider whether the experience in question is true, whether it’s representative, and whether the policy recommendations derived from it are backed by logic and evidence.

    Aren’t these factors where the fight currently exists: true, representative, backed by logic and evidence?

    Off topic…Professor Somin, I enjoyed your comments in ‘Fair Weather Federalism’ but the sunlight coming through the window behind you obscured seeing you clearly. If you do Zoom classes/meetings, I’d suggest covering that window with a heavy drape.

  14. On a recurring basis, when arguing for a particular policy action, I want to provide a statistical explanation of what is or isn’t a good policy. But I am told by those seeking to influence the policy that politicians are not interested in abstract arguments. They want personal stories that they can use to argue the point.

    I don’t like it but I accept the reality that that is how it works.

    1. Yep. And this has a lot to do with why politicians are amazingly bad at governing.

      1. That’s not something unique to politicians. It’s something all humans share. It’s why a news story about a particular problem will always start with an anecdote about a person who experienced the problem before segueing into statistical claims.

  15. As I’ve said above, “lived experience” is just lookijg around and seeing things with your own wyes. And sometimes there’s just no substitute for looking around and seeing things with your own wyes if you want to understand what’s going on.

    This means in particular that sometimes people on the other side of the culture war might be right. For example, if data on police-civilian interactions are collected by police, it’s entirely possible that this data might be biased. Anecdotes from a different perspective might help uncover this possibility. “Lived experience” might indeed tell you something that’s missing in the data.

    The purpose of the academy is to discover the truth, not just to defend the correct ideological principles. Ideological principles are bright and clean; the truth is often murky and messy and hard to uncover. No single method, no single theory, no single principle, no single size fits all.

    1. “For example, if data on police-civilian interactions are collected by police, it’s entirely possible that this data might be biased. Anecdotes from a different perspective might help uncover this possibility”

      Nope. “Anecdotes from a different perspective” are meaningless trash.

      If you don’t like the data the police are collecting, then establish your own data collecting platform, let us know what safeguards you will impose on yourself so that we can trust your data, and go for it.

      There are over 300 million people in this country. If you can’t find anecdotes to support your claims, that just means your claims are beyond pathetic.

      The insistence on “anecdotes” is solid proof that even you don’t believe your side is honestly correct. And, even worse, you don’t care

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