Religion is a Mental Illness

‘Systemic Racism’ in the Justice System Does Not Exist | National Review

Researchers just found substantial evidence for something conservative scholars and criminal lawyers have long suspected.

National Review

Researchers just found substantial evidence for something conservative scholars and criminal lawyers have long suspected.

‘Systemic racism,” at least in the criminal-justice system, has been comprehensively measured. This, following my recent review of Cory Clark and Lee Jussim’s excellent analysis of academic censorship, to which I myself contributed the odd word, will be my second “academic findings” article in a row for National Review. Get excited!

This week’s topic is at least as important as last week’s. In a recent quantitative meta-analysis, Stetson University’s Christopher Ferguson and Sven Smith found substantial evidence for something conservative scholars and criminal lawyers have long suspected. Simply put, based on models that adjust for social class as a variable, there appears to exist little or no “systemic” racial bias in the U.S. criminal-justice system.

Overall, the pair’s meta-analytic review of some 51 studies — which, combined, included around 120 distinct effect tables — concluded that “neither class nor race biases for criminal adjudications for either violent or property crimes could be reliably detected.” For drug crimes such as crack sales, some evidence of bias was found, but “effect sizes were very small” — often on the order of a few percentage points — and may be primarily artifacts of the weaknesses of past studies.

Ferguson and Smith note that the “better quality studies” that were included in this complex analysis were “less likely to produce results supportive of [racial] disparities.” Studies with “citation bias” toward one side of the debate about whether racism exists in the modern criminal-justice system — generally, a bias in a liberal direction — were far more likely to find racism than were unbiased fair-test studies, and they “consistently produced higher effect sizes.” Only the innermost hearts of a few academics truly know why that is — although the findings of my last piece might provide a clue. Overall, the Stetson pair concludes: “Narratives of ‘systemic racism’ as relates to the criminal justice system do not appear to be a constructive framework from which to understand this nuanced issue.”

On some level, and this is not to minimize a top piece of work, these findings seem gobsmackingly obvious in 2023. As Ferguson and Smith put it, “the civil rights movement was successful in creating equality before the law.” Since then, they add, “evidence from psychological studies demonstrates major reductions in both explicit and implicit racial prejudice.”

More bluntly put, about 40 percent of Americans are now members of minorities, and 90-odd percent of whites do not test as racist when this is measured by any real metric such as opposition to interracial marriage. Hell, roughly 30 percent of cops are black and Hispanic — and so are more than 10 percent of lawyers (before we throw in Asian and Jewish Americans). Setting CRT mumbo jumbo to the side, where it belongs, there seems to be no reason to expect black or Irish-American big-city judges to treat (say) Puerto Rican teen goons differently from Italian or Bosnian ones. And, overall, they do not.

Serious analyses, of the kind that Ferguson and Smith conducted, frequently come to similar conclusions across a variety of sectors. Back in 1990, the economist June O’Neill took a look at the black–white income gap — then about 18 percent annually, and always attributed to racism. She concluded that fairly simple adjustments for variables such as age (the modal age of a black American is 27, versus 58 for a white Yank), region of residence, test scores, and years (rather than quality) of education shrink this gap to roughly 1 percent. Similarly, in policing, Harvard economist Roland Fryer’s multifactorial analysis, which included controls for the behavior of suspects and racial groups’ rate of contact with police, concluded that white suspects are actually 27 percent more likely than black suspects to be shot by cops . . . rebutting the entire Black Lives Matter narrative almost in passing.

This brings us to a key point. Life, much like good analysis, is multivariate. People who differ from one another in terms of a major factor such as race or religion are also very likely — indeed almost certain — to differ as well in terms of other characteristics, like those O’Neill studied. Racism occurs only when individuals are treated differently entirely and solely because of the single factor of their race.

It’s worth spelling this out. An analysis of mortgage-loan rates could be said to have uncovered racism only if large and statistically significant gaps in lending rates to racial groups remained after a statistical adjustment for black/Caucasian/Asian differences in age, region, income, wealth, credit score, and probably default rates. Similarly, any study of arrest rates (or crime rates) by race has failed to demonstrate the existence of bias — and therefore is pretty much useless for our purposes — if it has not made the obvious adjustments for age and social class.

By this standard, a rather amazing amount of past research — journalistic “studies” and some academic work — is pretty much useless. As Ferguson and Smith note, in a surprising number even of the better-known studies in their field of criminal justice, “control variables are comparatively lacking. . . . Many studies that examine race issues don’t control for class” (emphasis mine). “Most” studies control for “age and prior criminal record,” but not all.

Interestingly, very few papers on criminal sentencing control for what may be the most critical variable of all — whether your lawyer was a public defender or private counsel and how good he was. Criminal justice is hardly unique in this regard: Conservative éminence grise Thomas Sowell devoted an entire book to debunking scholars’ and reporters’ cross-disciplinary trend of simply attributing any disparity between groups — black vs. white maternal mortality, for example — to racism. But that particular dragon even the great man could not slay.

Why is the univariate problem that Ferguson and Smith and Sowell describe so well, and which I have been known to gripe about myself, so prevalent? There are many reasons, one suspects. Many writers, especially in the journalistic sector, are almost certainly well intentioned but unskilled with advanced statistical tools such as Stata. Others likely notice real racism in today’s online public squares, jump to the premature conclusion that this kind of tawdry stuff explains serious decisions that adults such as bankers make, and don’t test for much else.

But it is hard not to notice a potential third factor. An entire sector of the economy — within which fall most left-aligned think tanks and lobbying groups and more than a few academic departments (“postcolonial studies,” anyone?) — is dependent on the continued existence of old-school bigotry in the United States. Old warhorses such as Jesse Jackson’s Rainbow Push and Al Sharpton’s National Action Network never really went anywhere, and they have been joined at the trough by more than 100 BLM groups led by Patrisse Cullors’s Black Lives Matter Global Network Foundation. Even sexual-rights groups now host seven-figure fundraisers centered on professional-looking white papers (I responded to the Human Rights Campaign’s claims of “trans genocide” here). This lucrative grift is quite hard to defend in the near absence of real and serious bias — and it might often be tempting for smart activists or even ideologically inclined academics to go out and create some.

The rest of us, however, shouldn’t go along with the radicals (or Thuh Science™) if their ideas and methods are simply bad and unscientific. To quote Ferguson and Smith one more time, when it comes to understanding at least the major and nuanced issue they study, “narratives of ‘systemic racism’ . . . do not appear to be a constructive framework.”

Race, class, and criminal adjudication: Is the US criminal justice system as biased as is often assumed? A meta-analytic review

It is widely reported that the US criminal justice system is systematically biased in regard to criminal adjudication based on race and clas

sciencedirect.com

• It is commonly believed ethnicity predicts criminal justice outcomes in the US.
• For most crimes, evidence for racial disparities is weak.
• Very small disparities appear to persist for drug crimes only.
• Academia has often worryingly overstated the evidence for racial disparities in the US criminal justice system.

It is widely reported that the US criminal justice system is systematically biased in regard to criminal adjudication based on race and class. Specifically, there is concern that Black and Latino defendants as well as poorer defendants receive harsher sentences than Whites or Asians or wealthier defendants. We tested this in a meta-analytic review of 51 studies including 120 effect sizes. Several databases in psychology, criminal justice and medicine were searched for relevant articles. Overall results suggested that neither class nor race biases for criminal adjudications for either violent or property crimes could be reliably detected. For all crimes, effect sizes (in terms of r) for Black vs White comparisons were.054, for Latinos vs Whites, 0.057 and for Asians vs Whites −0.028. There was significant heterogeneity between studies, particularly for Asian vs White comparisons. Effect sizes were smaller than our evidentiary threshold, indicating they are indistinguishable from statistical noise. For drug crimes, evidentiary standards were met, although effect sizes were very small. Better quality studies were less likely to produce results supportive of disparities. Studies with citation bias produced higher effect sizes than did studies without citation bias suggesting that researcher expectancy effects may be driving some outcomes in this field, resulting in an overestimation of true effects. Taken together, these results do not support beliefs that the US criminal justice system is systemically biased at current. Negativity bias and the overinterpretation of statistically significant “noise” from large sample studies appear to have allowed the perception or bias to be maintained among scholars, despite a weak evidentiary base. Suggestions for improvement in this field are offered. Narratives of “systemic racism” as relates to the criminal justice system do not appear to be a constructive framework from which to understand this nuanced issue.

The ‘Intersectionality’ Canard | National Review

Many studies that purport to find giant residual effects of race or sex are flawed from the outset.

National Review

Many studies that purport to find giant residual effects of race or sex are flawed from the outset.

‘Intersectionality” is just a badly done “woke” version of regression analysis.

The old feminist idea of intersectionality has been popping up across the mainstream media of late, as the latest round of the national debate over “DEI” (and CRT, ESG, SEL, NU-HR, and the rest of today’s insufferable corporate alphabet soup) rages on. Its resurgence seems like a worthwhile topic, while I am on a 3–4-week run of discussing academic issues for the gentle readers of National Review.

Per Merriam-Webster, which updated its definition of the term November 30, 2023 — the major dictionaries have been doing that kind of thing a lot lately — intersectionality is “the complex, cumulative way in which multiple forms of discrimination (such as racism, sexism, and classism) combine . . . especially in the experiences of marginalized individuals or groups.” The United Nations’ Global Citizenship initiative has, also within the past year or two, adopted this concept as a primary analytical framework, and defines “intersectionality” as “how multiple identities interact to create unique patterns of oppression.”

“In the United States,” author and Global Citizen Sarah El Gharib declaims, “Women earn 83 cents for every dollar a man earns.” But, the situation is even worse for black women, who pull in “a mere 64 cents for every dollar a white man earns.” The reason for all of this? Obviously, oppression: The analysis almost invariably stops there.

The problem with all of this, which needs to be discussed if radical-feminist analysis — intersectionality as a concept was first outlined by UCLA’s Kimberlé Crenshaw in the late 1980s, and traces its roots back to “a Black lesbian social justice collective formed in Boston in 1974” — is now prevalent in the United Nations and around the Fortune 500, is fairly basic. The idea that multiple independent variables can influence a dependent variable like income is not exactly a new one. And, the actual range of potential “IVs” that can do so extends well beyond race and sex to include: age, the regions where people and groups live, test and IQ scores, patterns of study time, crime rates, desire to work at all (in the context of men vs. women), and so on down the line.

Simply put, racism or sexism can only be said to exist where we find that pretty much identical people, who differ only in terms of the characteristic of race or sex, are still being treated differently — after all of the other factors which might explain performance differences between them have been accounted for. This sort of real bigotry is, today, fairly rare. Many “intersectional” studies that purport to find giant residual effects of race or sex on some specific thing — individuals’ chances of going to prison, let’s say — literally just consist of unadjusted comparisons between citizens in two or more different groups.

This, however, is not how serious people conduct this sort of analysis. The pay gap between men and women, in fact, provides one of the best examples of an apparently giant gulf which vanishes almost as soon as anything but sex is competently adjusted for. As it turns out, one major reason that women make so little money relative to men — less than 70 cents per dollar, in some analyses — is that 39 percent of women “prefer a home-maker role” and about one-third are housewives . . . who often earn almost no money, but have access to all of the resources of what is usually a middle-class household.

Even if we focus only on working men and working women, it remains the case that males and females prefer to work different jobs, men work slightly longer hours, men took virtually no time off from work for pregnancy and child care until quite recently, and so forth. When the quantitative team at the PayScale business website took all of this into account and ran some models, they found that any actual gap in same-job wages which could be attributed to sexism would be on the order of –(1 percent). At some level, this is not even surprising: American corporate business is ruthless, and any trading floor or shark-tank start-up that could actually save 17–31 percent on labor costs by hiring only women would do so immediately.

Pay gaps between white and black guys, for that matter, do not survive serious analysis. As I have noted elsewhere, the labor economist June O’Neill attempted, back in the 1990s, to distinguish the impact of racism from that of plain human capital on the B/W wage gap. What she found was stunning, almost remarkable. An initial gap of 15–18 percent, which has been attributed to “racism” by almost everyone to write about it during the modern era, in fact shrunk to about 1 percent when adjustments were made for basic variables like the mean age of each racial population, region of residence, and IQ- or aptitude-test scores.

O’Neill and a co-author found almost exactly the same pattern to still hold more than a dozen years later, in 2005. As both she and I have pointed out, groups that are different as re very major traits such as race and religion also invariably vary in terms of other characteristics — and any effects of racism simply cannot be parsed out without adjusting for all of these important differences. Simply put, there is no reason to expect a 27-year-old black man living in Mississippi to earn anything like as much as a 58-year-old white dude with a residence in mid-town Manhattan.

What is true in the critical context of money is true almost everywhere else. For years, the “Black Lives Matter” movement argued that young African Americans are being “murdered” or “genocided” by police officers, because members of this group are more likely to be shot by law enforcement than members of the general public. Again, however, there is an elephant in the room. As the Manhattan Institute’s Heather MacDonald has pointed out for decades now, the crime rate for black Americans — certainly before we adjust for age, or sex ratios, or living in mile-spire cities instead of Green Acres — is about two to 2.5 times that for whites. As an obvious result, we tend to encounter on-duty cops about that much more often.

Just adjusting for this one variable entirely removes the gap in rates-of-shooting. In the fairly representative year of 2015, which I select for analysis in my brilliant and best-selling book Taboo, there were 999 fatal police shootings nationwide — out of tens of millions of police/citizen encounters — of which 250 (25.1 percent) involved African Americans. That figure, which is 1.92 times the nation’s black population percentage, is almost exactly what any reasonably intelligent person would expect to see after taking a single glance at the crime statistics — if anything, a bit on the low side.

Entertainingly, the Reilly Rule about the impacts of the real, multi-variate version of “intersectionality” on day-to-day life applies even in the context of “white privilege.” As it happens, there exist several scales that attempt to measure personal privilege — such as this popular but quite empirical example, which several hundred thousand people have taken (a little bird tells me the average score is 43). When I have administered the 100-item ordinal survey, which includes Yes/No questions ranging from “I have never gone to bed hungry” to “I went to private school,” to sizable groups as a learning exercise, I do find that being white does have a small effect on ease-of-life: about two–three points, with all else adjusted for.

However, almost everything else has a bigger one. Other more influential variables recorded by myself and others to work with the test include female sex (yes, sure) — but also where people live (the suburbs as vs. the “hood or the “holler,” the North vs. the South), being gay rather than straight, and most notably plain social class. The largest chunk of “privilege” appears to be pure socio-economic status: crudely put, how much money a test taker and his or her family happen to make in a year. Across the aforementioned 100 questions, poor Appalachian or immigrant respondents often post “have not experienced” scores on the order of 17, while well-off ones “achieve” 69s and 73s.

At some level, none of this is particularly surprising, to the average human being with eyes. Of course, having wealthy parents, or not committing crimes, or not living on an isolated farm, or being a 6’4” blonde or black jock might sometimes help you along in life. However, this empirical point is a useful rebuttal to the much simpler standard idea of intersectionality — that what matters is race, or sex alone, or perhaps something like “being non-binary.”

In reality, conservatives don’t make fun of that simplistic concept because we are too unsophisticated to understand it, some pack of rubes who believe that only hard work and lovin’ America predict life outcomes. Instead, we do so because we recognize that many, many factors predict those outcomes. And, in the end, if dozens or hundreds of things predict where each singular human being will end up in life, we should turn our focus back to that smallest and most vulnerable of minorities: the individual.

Thread by @wil_da_beast630 on Thread Reader App

@wil_da_beast630: I'll do a quick response here, since this is my article. Obviously, no one argues that "racism does not exist." The point

threadreaderapp.com

I'll do a quick response here, since this is my article.

Obviously, no one argues that "racism does not exist." The point is that you do not DETERMINE the existence of racism simply by pointing out "performance gaps" re something like income or police encounters - which is literally the level of a lot of 'woke' research....or by adjusting for sex as well as race (whee!).

As J. O'Neill pointed out 20+ years ago, most such gaps close or vanish after basic adjustments for things like age, region, any aptitude test score, etc.

(2) At some very basic level, it makes no sense to argue that, if a 27-year old Black Mississippian with a community college degree makes less money than a 58-year old white Bostonian who went to BU, the reason is "racism."

These are the sort of gaps political scientists often look at between large groups. More whites DO live in the US North (the boats landed further South). That IS the gap in at least modal average/most common ages between Blacks and whites...

The most common age among whites in U.S. is 58 – more than double that of racial and ethnic minorities

The most common age was 11 for Hispanics, 27 for blacks and 29 for Asians as of last July. Multiracial Americans were by far the youngest ra

Pew Research Center

(3) A common response from smart left-slanting stats folX, including Kareem, is that these other variables (age?!) could themselves just be measures of racism.

But, especially given that we can easily test for multi-collinearity and covariance, there is almost never any evidence presented of this. Aptitude test scores, for example, are higher for white kids from families making $40,000 per year than for Black kids from families making $200K per year.......and don't vary at all with reported racism. The obvious actual predictor here (attached) is study time.

The core point of my article () is quite simple - the "intersectional" idea that TWO or even THREE variables can affect a dependent variable is not very novel or original.

Of course both sex and race can influence your life outcomes - but so can social class (!!!), IQ, prey drive, attractiveness and fitness, age, level of education, being gay or lesbian, being from the country, hailing from the South, being white in the academic job market, just etc. Figuring all this out is the basic idea of multi-variate analysis.

We have to take some basic precautions as re how we model these things, but a researcher who finds that Black women earn 'just' 73 cents for every dollar white men do has not in fact "gotten to the bottom of the matter."