The University of California Was Wrong to Abolish the SAT: Admissions When Affirmative Action Was Banned
Open accessAbstract
I study student characteristics and academic performance at the University of California, where consideration of an applicant's ethnicity has been banned since 1996 and SAT scores were used in admitting students to the university until fall 2021. I show the following: (1) SAT scores were more important than high school grades in predicting first‐year university GPA; (2) the use of SAT scores alone or with high school grades in determining admission is biased in favor of admitting underrepresented minorities and students who are socioeconomically disadvantaged; (3) SAT scores are more important and high school grades are less important in predicting GPA for underrepresented minorities and/or those students from low‐income families than they are for those students who are white and/or from high‐income families; and (4) the University of California found ways to admit a significant number of underrepresented minorities despite many of them having low SAT scores.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Examinations for differential prediction by socioeconomic status are rare, and the few available studies suggesting overprediction have relied on narrow SES components.
“While overprediction for Black students has been consistently observed, examinations for differential prediction by socioeconomic status (SES) are rare and the few available studies which suggest overprediction have relied on narrow SES components (Rothstein, 2004;Wittman, 2024).”
From An Omitted Variables Approach to Disentangling Differential Prediction in College Admissions (2026) · cites this paper as Wittman, 2024
In “Admissions Based on SAT Scores Are Biased in Favor of Students Who Are SED” (page unavailable), Wittman describes a “long and varied empirical literature” using socioeconomic characteristics, contrary to the claim that such examinations are rare. He also says Rothstein used a long list of student and high-school variables, including parental income, rather than only narrow SES components. The paper does report overprediction for disadvantaged students, but its account of the literature contradicts the claim’s main qualifications. (LLM, conf=0.86)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Berry, C. M., & Sackett, P. R. (2009) · Psychological Science · doi:10.1111/j.1467-9280.2009.02368.x · Cited by 68 · see citing works
Flagged first, then by citations
Research works printed but not linked: 17
- Achen, A., & Courant, P. (2009). What are grades made of. Journal of Economic Perspectives, 23(3), 77-92.
- Arcidiacono, P., Aucejo, E. M., & Spenner, K. (2012). What happens after enrollment? An analysis of the time path of racial differences in GPA and major choice. IZA Journal of Labor Economics, https://izajole. springeropen.com/articles/10.1186/2193-8997-1-5 · DOI
- Bleemer, Z. (2023). Affirmative action and its race-neutral alternatives. Journal of Public Economics, 220, 104839. https://doi.org/10.1016/j. jpubeco.2023.10483 · DOI
- Cleary, T. A. (1968). Test bias: Prediction of grades of Negro and white students in integrated colleges. Journal of Educational Measure- ment, 5(2), 115-124.
- Fischer, F. T., Schult, J., & Hell, B. (2013). Sex-specific differential pre- diction of college admission tests: A meta-analysis. Journal of Edu- cational Psychology, 105(2), 478-488.
- Geiser, S. (2017). Norm-referenced test and race blind admissions. In Joseph Soares (Ed.), The Scandal of standardized tests: Why we need to drop the SAT & ACT. Teachers College Press.
- Geiser, S., & Studley, R. (2002). UC and the SAT. Predictive validity and differential impact of the SAT I and SAT II at the University of Cali- fornia. Educational Assessment, 8(1), 1-25
- Goodman, J., Gurantz, O., & Smith, J. (2020). Take two! SAT retak- ing and college enrollment gaps. American Economic Journal: Eco- nomic Policy, 12(2), 115-158.
- Hanushek, E., Light, J., Peterson, P. E., Talpey, L. M., & Woessmann, L. (2022). Long-run trends in the U.S. SES achievement gap. Education Finance and Policy, 17(4), 608-640.
- Keiser, H. N., Sackett, P. R., Kuncel, N. R., & Brothen, T. (2016). Why women perform better in college than admission scores would pre- dict: Exploring the roles of conscientiousness and course-taking pat- terns. Journal of Applied Psychology, 101(4), 569-581. https://doi. org/10.1037/apl0000069 · DOI
- Lee, V., & Burkam, D. (2002). Inequality at the starting gate: Social background differences in achievement as children begin school. Economic Policy Institute. Washington D.C. Long, M. C. (2015). Is there a "workable" race-neutral alternative to affirmative action in college admissions? Journal of Policy Analysis and Management, 34(1), 162-183.
- Rothstein, J. M. (2004). College performance predictions and the SAT. Journal of Econometrics, 121(1-2), 297-317. https://doi.org/ 10.1016/j.jeconom.2003.10.003 · DOI
- Sackett, P. R., & Kuncel, N. R. (2018). Eight myths about standard- ized testing. In J. Buckley, L. Letukas, & B. Wildavsky (Eds.), Measuring success: Tests, grades, and the future of admissions testing (pp. 13-39). Baltimore, MD: Johns Hopkins University Press.
- Tomkin, J. H. D., & West, M. (2022). STEM courses are harder: Evalu- ating inter-course grading disparities with a calibrated GPA model. International Journal STEM Ed, 9(1), Article 27. https://doi.org/10. 1186/s40594-022-00343-1 · DOI
- Wittman, D. (2022) Average rank and adjusted rank are better measures of college student success than GPA. Educational Measurement: Issues and Practice, 41(4), 23-34. https://doi.org/10.1111/emip. 1252 · DOI
- Wodtke, G. T., Harding, D. J., & Elwert, F. (2011). Neighborhood effects in temporal perspective: The impact of long-term exposure to con- centrated disadvantage on high school graduation. American Socio- logical Review, 76(5), 713-736.
- Zwick, R., & Green, J. G. (2007). New perspectives on the correlation of SAT scores, high school grades, and socioeconomic factors. Journal of Educational Measurement, 44(1), 23-45.
Cited by
Sorted by citations
An Omitted Variables Approach to Disentangling Differential Prediction in College Admissions
Demeke, S., Sackett, P. R., Kuncel, N. R., & Lee, S. D. (2026) · Educational Measurement: Issues and Practice · doi:10.1111/emip.70048
- Authors
- Wittman, D.
- Affiliations
- University of California, Santa Cruz (US)
- Corresponding author
- Wittman, Donald
- ORCID
- Wittman, Donald
- Venue
- Educational Measurement: Issues and Practice
- Publisher
- Wiley
- Published
- 2024-02-09
- Volume
- 43
- Issue
- 2
- Pages
- 55-63
- ISSN
- 0731-1745 (ISSN-L)
- 1745-3992
- OpenAlex
- W4391677978
- Cited by
- 1
- References
- 1
- Citations by year
- 2026: 1
- FWCI
- 1.26
- Type
- journal article
- Language
- en
- Open access
- hybrid
- dx.doi.org
- Licence
- Locations
- Educational Measurement Issues and Practice (publishedVersion, cc-by-nc-nd)
- Topics
- Social Sciences › Education › Higher Education Research Studies
- Social Sciences › Education › School Choice and Performance
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Medical Education and Admissions
- Keywords
- SAT, university admission, affirmative action, University of California, underrepresented minorities, socioeconomic deprivation, high school grades, first-year GPA
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
