Race and Crime: Rushton's Analysis of INTERPOL Data

Independent Thinker, Raceology, October 2019.



Back in 1995 Dr. Philippe Rushton examined international differences in violent crime rates, and GDP per capita for which he used INTERPOL data as well as data from the CIA Facebook. He broke down the world population into three macro-races: Caucasoid, Negroid, and Mongoloid.  Keep in mind however that this is a gross oversimplification of racial classification. Dr. Lynn's later classification of the races into ten distinct groups following the work of Cavalli-Sforza are a much finer, and more accurate picture of race and race differences. Rushton looked at the differences in murder, rape, and serious assault per 100, 000, as well as GDP per capita. Unsurprisingly, the results found that in the aggregate East Asian nations had the lowest violent crime rates, Caucasoid countries were intermediate, and Negroid countries had the highest rates.  The paper was published in 1995, and followed up in 2002.

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.580.9145&rep=rep1&type=pdf

The abstract:

The paper goes on to explain the differences between groups in terms of r/K selection theory that was expounded by Wilson in his monumental work Sociobiology. From the article:

Drawn from sociobiology (Wilson, 1975), the r-K continuum defines a genetically-coor- dinated group of traits that evolved together to meet the trials of life—survi- val, growth, and reproduction. At one end of this scale, r-strategies are characterized by high fertility, low-investment parenting, fast maturation, and low intelligence and learning ability. K-strategies, on the other hand, are characterized by low fertility, high-investment parenting, slow matura- tion, and high intelligence and competitive ability. Typically, the K-strategy requires more complex nervous systems and bigger brains. It has been hy- pothesized that r-selected species are more adapted to non-competitive en- vironments of resource abundance whereas K-selected species are adapted to more competitive environments of resource scarcity. Because the com- ponents of life-history (differential fertility, rates of maturation, sexual be- havior, and parenting) are critical determinants of demography, r/K theory could have important implications for understanding human variation.

And it continues applying this concept to the different macro-races:

Rushton extended r/K theory to human race differences and found it predicts a wide spectrum of characteristics including fertility, infant mortal- ity, rates of physical maturation, IQ scores, brain size, dizygotic twinning, crime, sexual potency, sexual precocity, number of sexual partners, and hormone levels. Mongoloids tend toward the K end of the r-K gradient. On average, they devote resources to producing fewer children, invest more heavily in them, and provide them with greater parental care. Negroids, on average, lie more toward the r end of the gradient. They tend to devote resources to producing greater numbers of children, invest less heavily in them, and provide less parental care. Caucasoids tend toward being inter- mediate, though closer on the r-K gradient to Mongoloids than to Negroids.

And in regards to the crime rates within the US, Canada, and Britain:

Crime statistics within Britain, Canada, and the United States show that people of East Asian ancestry are disproportionately under-represented while those of African ancestry are disproportionately over-represented rel- ative to those of European ancestry. For example, in Canada, a government commission found that Blacks were five times more likely to be in jail than Whites and ten times more likely than Asians (Ontario, 1996). In Britain, the Home Office (1999) found that Blacks, who were 2% of the general population, made up 15% of the prison population. (No figures were re- ported for East Asians such as the Chinese, but Asians from the Indian sub- continent were 3% of the general population and 2% of the prison popula- tion.) In the U.S., Wilson and Herrnstein (1985) and Taylor and Whitney (1999) analyzed the FBI Uniform Crime Statistics and National Crime Vic- timization Surveys from the U.S. Department of Justice (e.g., 1997, 1998) and found that since record keeping began at the turn of the century, and throughout the 1960s, 1970s, 1980s, and 1990s, African Americans consis- tently committed proportionately more violent crime than did European Americans, while Asian Americans consistently committed proportionately fewer. Victim surveys tell a similar story. The proportional differences in arrest statistics cannot therefore be attributed to police prejudice.
Finer grained analyses within the United States also find race a factor. Whitney (1995) found that the best predictor of local murder rate is the percent of the population that is African American. Across 170 cities, Whit- ney (1995) found a correlation of r = 0.69 between the rate of murder and the percent of the population that was African American. Similarly, across the 50 states, Whitney (1995) found a correlation of r = 0.77 between the rate of murder and the percent African American. In a follow-up study, Hama (1999) found a correlation of r = 0.76 across the 50 states between violent crime (an aggregate of murder, non-negligent manslaughter, rape, robbery, and aggravated assault), and the percentage of the population that was African American.

Please also see The Color of Crime for a fuller analysis of race and crime statistics in the US. Also please see race differences in psychopathic personality by Richard Lynn where he goes onto examine all of the other correlates of psychopathic personality for the different races. 

As far as explaining the race differences we have two models, one of which includes a hereditarian component:

Two fundamentally different models have been put forth to explain why the races differ in average rate of crime and other socially valued out- comes: (1) the “discrimination” model, and (2) the “distributional” model (Herrnstein, 1990). The discrimination model focuses on social and institu- tional practices that discriminate against members of one group (or favor members of another), thus tilting the “playing field.” The crucial assumption of this model is that in the absence of such discrimination, crime rates would be about equal for all populations. Factors hypothesized under this model include relative poverty, anti-Black bias by police, a lack of access to legitimate channels of upward mobility, and inadequate family socializa- tion due to the legacy of slavery. On the other end of the model, criminolo- gists as early as the 1920s explained the under-representation of East Asians in U.S. crime statistics by hypothesizing the East Asian “ghetto.” This “ghetto” was seen as a response to external prejudice that protected mem- bers from the disruptive tendencies of the outside society. It was also claimed that bias against East Asian migration (“yellow peril”) resulted in only the wealthiest or hardest-working East Asians gaining entry into White-majority countries.
The alternative distributional model explains the overlapping of the populations and their differing averages in terms of differential population characteristics—for example, Rushton’s (2000) r-K life-history theory, or Sowell’s (1994) theory of socialization through subtle cultural traditions. Other factors hypothesized to underlie the distribution model include deep- rooted cultural values and family structures endemic to populations, as well as biological variables including body type, percent of age of cohort, hor- monal levels, exposure to toxic chemicals such as lead which may have different effects based on constitutional differences in metabolism, and per- sonality and temperament. Thus according to the distributional model, the population differences are expected to occur more universally. The two models may each be partially correct (Ellis & Walsh, 1999).

After Herrenstein and Murray using INTERPOL yearbooks, Rushton examined the violent crime rates and found statistically significant differences:

Summing the crimes, and averaging across years, Rushton (1990, 1995) found statistically significant differences per 100,000 population of: 44 (Pacific Rim), 74 (Eu- ropean), and 143 (Afro-Caribbean) total crimes, respectively. These results did not depend on the selection of countries because when only ethnically more homogeneous sets were chosen, for example, by limiting countries to those from northeast Asia, central Europe, and sub-Saharan Africa, the proportionate differences remained the same—or became even greater. Nor did the pattern alter for other sets of countries. For example, in the Caribbean data set, six mainly White/Amerindian countries averaged 72 per 100,000 whereas eight mainly Black countries averaged 449 violent crimes per 100,000 population (Rushton, 1995).

In reply to various critiques of Rushton's work in the 1990's we have:

He ignores the distributional model and holds that race cannot be primary be- cause it is only a “political construction resulting from social conflict” (p. 149). This position obscures more than it clarifies for his analyses confound the facts needing to be explained with explanations of those facts. For ex- ample, the social variables that Neapolitan used to make the higher homi- cide in African countries “disappear” have themselves been explained in terms of race-correlated genes for intelligence (leading to low income; Herrnstein & Murray, 1994; Rushton, 2000).
<b>A fundamental rule of science is that explanations must be based on the “totality of evidence.” </b> [My bolding] In this paper we use the 1993 to 1996 INTERPOL Yearbooks for homicide, rape, and serious assault to examine whether race is a more universal predictor variable. We also examine the role of Gross Domestic Product per Person on these variables both across and within ethnicities. If cross-nationally race is predictive of rape as well as homicide and serious assault, it places the hypothesis on firmer scientific ground. Moreover, although a case can be made that poverty leads men to commit murder and serious assault, the logic becomes weaker when extended to differences in committing rape.

Three crimes were used in the analysis using the INTERPOL definitions:

Murder, “Any act performed with the purpose of taking human life, in whatever circumstance. This definition excludes abortion but in- cludes infanticide;” Rape, (separate from other “Sex offences”); and Serious assault, “An injury whereby life could be endangered, including cases of injury involving the use of a dangerous instrument. Cases where instru- ments are used merely to threaten people without causing injury are to be excluded” (INTERPOL, 1996, front matter).

The CIA world Facebook for 1999 was used to obtain ethnic group data, and GDP per capita data.

74 countries were analyzed: 

7 East Asian, 45 European, and 22 African. The mean median and SD of the populations for each type of crime are displayed in the following table:

And it goes on:

As can be seen, for all four crime categories, the East Asian and European countries averaged about one-third the rates of African and Black Caribbean countries. Moreover, the predicted East Asian < European differences also generally occurred (for serious as- saults this was reversed but the SDs were very large in this category, espe- cially for Asian countries, and using the median, rather than the mean, again resulted in concordance with previous studies). For 7 East Asian, 45 European, and 22 African and Black Caribbean countries, the medians per 100,000 population were, respectively: Murder—1.6, 4.2, and 7.9; Rape— 2.8, 4.5, and 5.5; and Serious Assault—31.0, 33.7, and 135.6. Summing the medians resulted in a total of violent crimes per 100,000 of population: East Asians, 35; Europeans, 42; and Africans or Black Caribbeans, 149.

Take note of this for statistical significance:

With each country taken as an independent entry, the results of one- way analyses of variance showed significant differences among the popula- tions in each of the crime categories (Murder, F2,71 = 4.52, p < 0.01; Rape,F2,71 = 9.22, p < 0.001; Serious assault, F2,71 = 10.45, p < 0.001; Sum of all three crimes, F2,71 = 10.11, p < 0.001). Some might question the application of parametric analyses to these ratio figures. However, the exact probability of getting this particular median ranking three times in a row is 1/6 × 1/6 ×1/6 = 0.01.

Same brain size, IQ differences found as well as the finding that wealthier countries had less crimes, but for Blacks the results show a different trend:

It was highest in East Asian countries ($12,600), intermediate in European countries ($7,400), and lowest in African and Black Caribbean countries ($1,900). Following the prescriptive advice of Lubinski and Humphreys (1996) to correlate group means when predicting the behavior or status of groups, and the example of Jensen (1998, pp. 442–443) who found an “ecological correlation” of 0.998 across the three racial groups between brain size and IQ scores, we calculated a similar correlation of −0.96 between crime and wealth across the three major geographic races (wealthier races had less crime). Calculat- ing the correlations between GDP and crime across all 76 countries found the association to be weaker but still significant, again showing the wealth- ier the country, the less the crime. More perplexing, however, is the findingthat the correlations with the GDP are positive for the 22 African and Black Caribbean countries (Murder, r = 0.33, ns; Rape, r = 0.65, p < 0.05; and Serious assault, r = 0.63, p < 0.01), suggesting that in those regions and among those populations, it is the wealthier, more urbanized countries that have the most social disruption.

The discussion goes on to explain that the results confirm Rushton's r-K selection model. Crime rate differences between races within countries are generalizable to some extent to crime rate differences internationally for particular countries or even groups of countries. 

But also:

More- over, the crime differences cannot simply be attributed to “poverty” for such an explanation does not fit the finer-grained analyses found withinAfrican countries where violent crime increased with GDP. This could be because only wealthier nations have the infrastructure to gather and report crime statistics comparable to those for East Asia and Europe. It is also possible that there are some gene-culture interactions when opportunities become available for engaging in behavior not otherwise affordable. In Africa, for example, there is a link between wealth and AIDS: wealthier males turn their resources into sexual partners (Rushton & Bogaert, 1989).

It goes on to conclude that:

Taken together, these results support the distributional model rather than the discrimination model of why the races differ in average rate of crime and other socially valued outcomes. However, we do not suggest that racial differences are 100% genetic, but rather that they are due to genes, cultures, and their interactions. Genetic factors involve brain size and intelligence (Jensen, 1998; Rushton & Ankney, 2000), and hormone levels like testosterone (Ellis & Nyborg, 1992). Cultural factors involve soialization practices, including of deep-rooted values transmitted by families (Sowell, 1994).

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Now first to address non-arguments, or simply fallacies:

This is all "racist": LMAO. Name-calling when confronted with uncomfortable facts. 
These people are all racists: LMAO. More name-calling when confronted with uncomfortable facts.

Now onto some actual arguments:

Argument:

But there is so much variation between groups of the different races, e.g. some East Asian groups have higher levels of crime than White groups, or White groups have higher crime levels than some Black groups.  

Counterargument:

First of all, variation within groups is to be expected.  It is "racist" to assume that if there are race differences on average then it must mean that all black individuals, and black groups are higher in crime than all white individuals and groups, etc. A genetic difference in propensity does not mean determination, rather it means influence on these traits. Thus, there will be overlapping on these traits between White, Black, and East Asian groups.  That in no way means that the differences are not genetic in origin, it implies simply that there is a genetic influence which is one important component of explaining the different crime rates. 

The fact that there is great variation within racial groupings is to be expected. Genes don't solely determine crime rates, they influence them. It is expected that between all racial groupings there will be overlap, though the difference in the means is statistically significant. 

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Thus we have it, race differences in aggressive crimes occur within countries, and between them when one considers race. Poverty does not explain the differences in crime rates. Using Ockham's razor we are led to conclude that there must be genetic differences that account for some of the variation of crime rates between the races, not only because of these facts, but that racial differences of other correlates of psychopathic personality have been found for these racial groupings.  The aggregate of the data strongly suggests that there is a simple component that explains much of the variation, a genetic one, though obviously for complex behaviors there is a host of factors that play a role.