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Test Score Gaps in California Increasingly Driven by Race, Not Class
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Screenshot 2015-10-27 20.06.18

It’s widely believed that racial gaps in test scores are just class gaps. And, if that’s not true, then it’s assumed that race is fading away in importance relative to class. But an important study shows that in multiracial California, race is becoming more influential in recent years.

THE GROWING CORRELATION BETWEEN RACE AND SAT SCORES: NEW FINDINGS FROM CALIFORNIA
October 2015
Saul Geiser
Center for Studies in Higher Education
University of California, Berkeley

This paper presents new and surprising findings on the relationship between race and SAT scores. The findings are based on the population of California residents who applied for admission to the University of California from 1994 through 2011, a sample of over 1.1 million students. The UC data show that socioeconomic background factors – family income, parental education, and race/ethnicity – account for a large and growing share of the variance in students’ SAT scores over the past twenty years. More than a third of the variance in SAT scores can now be predicted by factors known at students’ birth, up from a quarter of the variance in 1994. Of those factors, moreover, race has become the strongest predictor. Rather than declining in salience, race and ethnicity are now more important than either family income or parental education in accounting for test score differences. It must be cautioned that these findings are preliminary, and more research is needed to determine whether the California data reflect a broader national trend. But if these findings are representative, they have important implications for the ongoing debate over both affirmative action and standardized testing in college admissions.

… The regression results show a marked increase since 1994 in the proportion of variance in SAT scores that can be predicted from socioeconomic background factors largely determined at students’ birth. After falling slightly from 25% to 21% between 1994 and 1998, the proportion of explained variance increased each year thereafter, growing to 35% by 2011, the last year for which the author has obtained data. Remarkably, more than a third of the variance in SAT scores among UC applicants can now be predicted by family income, education, and race/ethnicity. This result contrasts sharply with that for high school GPA: Socioeconomic background factors accounted for only 7% of the variance in HSGPA in 1994 and 8% in 2011. …

Nevertheless, even without being able to observe those intermediating experiences directly, regression analysis enables one to assess the relative importance of different socioeconomic factors in predicting test performance. Figure 2 provides standardized regression coefficients, or “beta weights,” for predicting SAT scores conditional on family income, parents’ education, and race/ethnicity. The coefficients show the predictive weight of each factor after controlling for the effects of the other two, thereby providing a measure of the unique contribution of each factor to the prediction.

Screenshot 2015-10-27 20.09.47

In 1994, at the beginning of the period covered in this analysis, parental education was the strongest of the three socioeconomic predictors of test performance. (The standardized regression coefficient of 0.27 in that year means that, for each one standard deviation increase in parental education, SAT scores increased by 0.27 of a standard deviation, when income and underrepresented minority status were held constant.) The predictive weight for parental education has remained about the same since then. The weight for family income has shown a small but steady increase from 0.13 in 1998 to 0.18 in 2011. But the most important change has been the growing salience of race/ethnicity. By 2011, the predictive weight for underrepresented minority status, 0.29, was greater than that for either family income or parental education. When the regression results for the UC sample are pooled across applicant cohorts, race/ethnicity is the strongest predictor of SAT scores over the last four years.

A key implication of this finding is that racial and ethnic group differences in SAT scores are not simply reducible to differences in family income and parental education. At least for the UC sample, there remains a large and growing residual effect of race/ethnicity after those factors are taken into account.

Screenshot 2015-10-27 20.14.46

As shown in Figure 8, the test score gap in California is greatest between black and white SAT takers but has oscillated up and down and shows no consistent trend since 1998. If one were to draw inferences about racial and ethnic differences from the black-white gap alone, one might conclude that there has been little change in this respect.

But that conclusion would be wrong. For all other racial/ethnic comparisons, test score gaps between underrepresented minority and other students have been growing. The Black-Asian, Latino-White, and Latino-Asian test score gaps have increased almost every year since 1998.

 
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  1. One expects that the underlying explanation of these trends is that environmental differences are mostly gone, and we are seeing the pure effects of genetics.

    The moral/social paradox is that in a perfect meritocratic world, in which everybody has the same opportunity to succeed because their environments are in every key respect equivalent, it is genetics alone that engenders differences in outcome.

    Be careful what you wish for.

    • Replies: @Citizen of a Silly Country
    I was thinking the same thing. Better nutrition, more equal access to schooling, etc., may have severely reduced the differences in "shared environment" among various groups.

    That may be one of reasons that black test score improvement stalled after the early 1980s; they squeezed most of the juice out of environmental differences, leaving mainly innate IQ as the cause of the gap.
  2. I would say that’s racist, but it would eliminate all of the fun.

  3. For all other racial/ethnic comparisons, test score gaps between underrepresented minority and other students have been growing. The Black-Asian, Latino-White, and Latino-Asian test score gaps have increased almost every year since 1998.

    The fact that Black-White gaps have remained largely constant, whilst the gap between Black-Asian, Latino-White and Latino-Asian SAT scores have widened, prompts the search for causes.

    Possible candidate cause…

    Perhaps the cohort of Asians taking the SAT test now understand English better – because a higher proportion of them have been in the US longer and a higher proportion are second generation immigrants. This in turn prompts the obvious question – have the gaps widened because Asians are scoring better or because Blacks and Latinos are scoring worse, or a bit of both? Given that the Black-White gap has remained fairly constant, there is a hint that it may be Asians scoring better. What does the data tell us?

    Of course the term Asian is misleading – it covers all from Istanbul to Tokyo. I also suspect that Asian immigration is quite selective, this may also be a factor. Asian Immigration by Indian Brahmins and clever East Asians from well to do families may be pushing Asian scores up.

    The rise in the Latino-White Gap could be explained by the cohort of Latino SAT test takers scoring worse, because more of them are first generation immigrants with lower English skills. Again, given the broadly unchanging Black-White gap, there is a hint it may be due to falling Latino scores.

    It could also be because Latino immigrants are increasingly from the Latino lower orders.

    It should be possible to tease out further evidence from the data, supporting or falsifying these candidate causes.

    This would also explain the rise in the ‘Under-represented minority’ (gotta love that term) upturn, you’d expect it as an artifact of the above.

    • Replies: @unit472
    Its possible that the UC system no longer attracts the 'best' black applicants. Prop 209, to the extent UC adheres to it, passed in 1996 prohibited affirmative action admissions. This may have discouraged black students with good ( for black students) SAT scores from applying to UC as they could apply to other private Universities not subject to Prop 209. The tuition difference would likely be made up by loans and the willingness of private schools to eat the cost just to have more black students who met minimum admissions criterion.
  4. How in god’s name can the black/white ratio be higher than the black/asian?

    I thought most of the asians in California were from the “HBD approved” countries? You know, Japan, Asia, Korea,… Vietnam sorta.

    There a lot of Filipinos there? Enough to skew this?

  5. The Washington Post has a piece front and center on their website this AM about NAEP scores, with the subhead noting large difference in scores between white and minority students as well as between different income levels. Yet reading the article, nowhere does the reporter actually provide an actual number – not for the national averages, by race, or by income. Why would they omit that information?

    They did note an increase (again, no numbers provided) in DC’s scores…I think that would be relatively easy to figure out.

  6. I guess you’re only racist if you spell out that the explanation is genetic; if you leave open the possibility that the explanation is ‘systemic racism’, you’re ok. How much honking, in-your-face data can the mainstream explanation withstand? Probably, people are working out how to let it in from it in the dark ‘shadow’ parts of their minds. On the other hand we’ve had moments of shining HBD data clarity before and we’re still here.

  7. The expression “underrepresented minorities” seems rather odd.

    A better expression would be “non-European-and-non-Asian minorities”.

  8. @candid_observer
    One expects that the underlying explanation of these trends is that environmental differences are mostly gone, and we are seeing the pure effects of genetics.

    The moral/social paradox is that in a perfect meritocratic world, in which everybody has the same opportunity to succeed because their environments are in every key respect equivalent, it is genetics alone that engenders differences in outcome.

    Be careful what you wish for.

    I was thinking the same thing. Better nutrition, more equal access to schooling, etc., may have severely reduced the differences in “shared environment” among various groups.

    That may be one of reasons that black test score improvement stalled after the early 1980s; they squeezed most of the juice out of environmental differences, leaving mainly innate IQ as the cause of the gap.

  9. @NickG

    For all other racial/ethnic comparisons, test score gaps between underrepresented minority and other students have been growing. The Black-Asian, Latino-White, and Latino-Asian test score gaps have increased almost every year since 1998.
     
    The fact that Black-White gaps have remained largely constant, whilst the gap between Black-Asian, Latino-White and Latino-Asian SAT scores have widened, prompts the search for causes.

    Possible candidate cause...

    Perhaps the cohort of Asians taking the SAT test now understand English better - because a higher proportion of them have been in the US longer and a higher proportion are second generation immigrants. This in turn prompts the obvious question - have the gaps widened because Asians are scoring better or because Blacks and Latinos are scoring worse, or a bit of both? Given that the Black-White gap has remained fairly constant, there is a hint that it may be Asians scoring better. What does the data tell us?

    Of course the term Asian is misleading - it covers all from Istanbul to Tokyo. I also suspect that Asian immigration is quite selective, this may also be a factor. Asian Immigration by Indian Brahmins and clever East Asians from well to do families may be pushing Asian scores up.

    The rise in the Latino-White Gap could be explained by the cohort of Latino SAT test takers scoring worse, because more of them are first generation immigrants with lower English skills. Again, given the broadly unchanging Black-White gap, there is a hint it may be due to falling Latino scores.

    It could also be because Latino immigrants are increasingly from the Latino lower orders.

    It should be possible to tease out further evidence from the data, supporting or falsifying these candidate causes.

    This would also explain the rise in the 'Under-represented minority' (gotta love that term) upturn, you'd expect it as an artifact of the above.

    Its possible that the UC system no longer attracts the ‘best’ black applicants. Prop 209, to the extent UC adheres to it, passed in 1996 prohibited affirmative action admissions. This may have discouraged black students with good ( for black students) SAT scores from applying to UC as they could apply to other private Universities not subject to Prop 209. The tuition difference would likely be made up by loans and the willingness of private schools to eat the cost just to have more black students who met minimum admissions criterion.

  10. This looks to me like it is just a mechanical effect of the Asian population growing and getting sharper at gaming the system. They are not an ‘underrepresented minority’, their population is growing fast, and their scores are going up. So that increases the gap between underrepresented minorities and non-underrepresented minorities.

    I bet these charts would look totally different, with much less change, if it was just blacks and whites.

  11. Probably the contribution to R2 of race is rising because the variation in race is rising. If the population is 90% white and 10% hispanic, race won’t explain as much as if the population is 50% white and 50% hispanic. Of course, once it gets to 10% white nad 90% hispanic the R2 will decline again.

    • Agree: International Jew
    • Replies: @International Jew
    Good point.

    Another thing is, did they try fitting more than that one model (and btw I hope they didn't really leave out the constant term...) Their "trend" could very well be an artifact of one particular model.
    , @AnotherDad

    Probably the contribution to R2 of race is rising because the variation in race is rising.
     
    Eric--exactly right, nailed it.

    There's absolutely zero surprising here: There's more racial diversity, so more of the total test score variance comes from racial diversity.

    In the old 90-10 America--or for California 90-5-3-2 or whatever it was--the mean is close to the white mean, and most of the variance of any *individual* score from that mean is mostly going to be individual genetics and luck, with parental class\income capturing\explaining some of genetic variation.

    But when you start adding more and more diversity, then more and more individual variation is explained simply by the large score gaps between the various racial groups.

    ~~~

    This is just simply a statistical example of something that is crystal clear to anyone not soaked through the gills in multi-culti propaganda:

    Diversity generates stark differences in outcome and creates conflict.

    When everyone is white your low score just means you're stupid--that's life. (And no big deal when you can run a punch press or swing a hammer and make a living.)
    With diversity your low score means "racist society is screwing me and my people!"--a social and political problem.

    Or short form: "Diversity Sucks"
    , @Anon
    I can understand how greater ethnic diversity leads to race being a stronger explanatory variable, simply by dint of mathematics, if you were comparing individuals to the multi-ethnic state average. But if you are comparing the white average to the Hispanic average, and ignoring the combined state average, I don't see why a 90,000 white / 10,000 Hispanic sample should look any different than a 50,000 white / 50,000 Hispanic sample, just based on statistical artifacts. The study here seems to be doing the latter.
  12. “New and surprising findings”. Amazing how easily surprised these folks always are. I don’t know how their “easily surprised” genes got carried down to them, since you would think their early ancestors would have been weeded out of the genetic pool by being ambushed by leopards, dire wolves, enemy tribesmen and so forth.

  13. @Eric Rasmusen
    Probably the contribution to R2 of race is rising because the variation in race is rising. If the population is 90% white and 10% hispanic, race won't explain as much as if the population is 50% white and 50% hispanic. Of course, once it gets to 10% white nad 90% hispanic the R2 will decline again.

    Good point.

    Another thing is, did they try fitting more than that one model (and btw I hope they didn’t really leave out the constant term…) Their “trend” could very well be an artifact of one particular model.

  14. This is pretty puzzling to me. Why the increase of almost 50% in the explanatory power of race since 1999? That’s only 15 years. It corresponds to the cohort born starting in 1981.

    It looks like the BW gap is fairly steady, but the Black/Asian gap has widened.

    Maybe an influx of smart Asians to Silicon Valley, where the high paying jobs would also drive up the explanatory power of income? The smart Asians/tech workers in the valley have a high income and smart children. Is the SV population large enough to drive these effects? I wonder if you could break it out the data by region.

  15. Parental education has lost comparative power as a predictor of achievement because college degrees are given away for the asking.

    Race (a less varying variable) has thus increased in predictive power.

    Implications?

    • Replies: @MarkinLA
    Implications?

    Yeah, more need to hunt down and out the insidious racism in every white and make up for it with more affirmative action.
    , @Boomstick
    I'd think that that would have been the case, but the predictive power of a parental college degree seems to have been flat, maybe declining a little.
  16. @Langley
    Parental education has lost comparative power as a predictor of achievement because college degrees are given away for the asking.

    Race (a less varying variable) has thus increased in predictive power.

    Implications?

    Implications?

    Yeah, more need to hunt down and out the insidious racism in every white and make up for it with more affirmative action.

  17. @Langley
    Parental education has lost comparative power as a predictor of achievement because college degrees are given away for the asking.

    Race (a less varying variable) has thus increased in predictive power.

    Implications?

    I’d think that that would have been the case, but the predictive power of a parental college degree seems to have been flat, maybe declining a little.

  18. They changed the SAT in 2005, making it easier and shorter, which gives a big assist to those kids preparing 80 hours or more.

    I haven’t read the study, was Geiser only using California residents, or UC applicants?

    • Replies: @Boomstick
    But about half the change was already in place by 2005.
  19. @education realist
    They changed the SAT in 2005, making it easier and shorter, which gives a big assist to those kids preparing 80 hours or more.

    I haven't read the study, was Geiser only using California residents, or UC applicants?

    But about half the change was already in place by 2005.

  20. The Black/Asian gap went from about 178 to 215, and the Latino/Asian gap from 140 to 200.

    The Black/White gap closed slightly, while the Latino/White gap went from 175 to 200.

    No info on White/Asian.

    It looks to me like Latinos got a little dumber (thanks, illegal immigration), Whites and Blacks stayed about the same, and Asians did a lot better. The explanatory power of the “Underrepresented minority” category increased as a result because their status increasingly explains that they’re not Asian.

  21. @Eric Rasmusen
    Probably the contribution to R2 of race is rising because the variation in race is rising. If the population is 90% white and 10% hispanic, race won't explain as much as if the population is 50% white and 50% hispanic. Of course, once it gets to 10% white nad 90% hispanic the R2 will decline again.

    Probably the contribution to R2 of race is rising because the variation in race is rising.

    Eric–exactly right, nailed it.

    There’s absolutely zero surprising here: There’s more racial diversity, so more of the total test score variance comes from racial diversity.

    In the old 90-10 America–or for California 90-5-3-2 or whatever it was–the mean is close to the white mean, and most of the variance of any *individual* score from that mean is mostly going to be individual genetics and luck, with parental class\income capturing\explaining some of genetic variation.

    But when you start adding more and more diversity, then more and more individual variation is explained simply by the large score gaps between the various racial groups.

    ~~~

    This is just simply a statistical example of something that is crystal clear to anyone not soaked through the gills in multi-culti propaganda:

    Diversity generates stark differences in outcome and creates conflict.

    When everyone is white your low score just means you’re stupid–that’s life. (And no big deal when you can run a punch press or swing a hammer and make a living.)
    With diversity your low score means “racist society is screwing me and my people!”–a social and political problem.

    Or short form: “Diversity Sucks”

    • Replies: @gcochran
    Right. On the other end, people would publish something about how race didn't explain much of the variation in North Dakota. The racial difference was about the same as everywhere else, but there were very few blacks in N.D. Since the authors were journalism majors or sociologists, you can hardly accuse them of lying - it ain't a lie if you're too dumb to know better.
  22. @AnotherDad

    Probably the contribution to R2 of race is rising because the variation in race is rising.
     
    Eric--exactly right, nailed it.

    There's absolutely zero surprising here: There's more racial diversity, so more of the total test score variance comes from racial diversity.

    In the old 90-10 America--or for California 90-5-3-2 or whatever it was--the mean is close to the white mean, and most of the variance of any *individual* score from that mean is mostly going to be individual genetics and luck, with parental class\income capturing\explaining some of genetic variation.

    But when you start adding more and more diversity, then more and more individual variation is explained simply by the large score gaps between the various racial groups.

    ~~~

    This is just simply a statistical example of something that is crystal clear to anyone not soaked through the gills in multi-culti propaganda:

    Diversity generates stark differences in outcome and creates conflict.

    When everyone is white your low score just means you're stupid--that's life. (And no big deal when you can run a punch press or swing a hammer and make a living.)
    With diversity your low score means "racist society is screwing me and my people!"--a social and political problem.

    Or short form: "Diversity Sucks"

    Right. On the other end, people would publish something about how race didn’t explain much of the variation in North Dakota. The racial difference was about the same as everywhere else, but there were very few blacks in N.D. Since the authors were journalism majors or sociologists, you can hardly accuse them of lying – it ain’t a lie if you’re too dumb to know better.

  23. Do the beta weights here depend on relative population size? I don’t think they do. I’d have to look at it more closely, but I think the beta weight would be the same whether the Latino population is 10% or 40%, assuming the population makeup remains constant.

    I suspect the increasing beta weights reflect a decline in the quality of the Latino population due to the influx of illegal, uneducated Mexican immigrants (often indigenous), and the increase in the academic quality of Asians.

  24. Anon • Disclaimer says:
    @Eric Rasmusen
    Probably the contribution to R2 of race is rising because the variation in race is rising. If the population is 90% white and 10% hispanic, race won't explain as much as if the population is 50% white and 50% hispanic. Of course, once it gets to 10% white nad 90% hispanic the R2 will decline again.

    I can understand how greater ethnic diversity leads to race being a stronger explanatory variable, simply by dint of mathematics, if you were comparing individuals to the multi-ethnic state average. But if you are comparing the white average to the Hispanic average, and ignoring the combined state average, I don’t see why a 90,000 white / 10,000 Hispanic sample should look any different than a 50,000 white / 50,000 Hispanic sample, just based on statistical artifacts. The study here seems to be doing the latter.

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