The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Sociodemographic Diversity, Correlated Achievement, and De Facto Tracking
Abstract
De facto tracking-the association between students' courses in disparate subjects, regardless of the decline of institutional mechanisms that organized de jure tracking-is a contested feature of secondary schools. Some analysts imply that de facto tracking arises simply because students who do well in one area often do well in other areas. Other analysts contend that pronounced tracking systems maintain racial, ethnic, and social-class segregation and thus that de facto tracking is driven, in part, by the sociodemographic composition of schools. This article investigates the school-level correlates of de facto tracking. An analysis of data from High School and Beyond suggests that the higher the correlation between students' achievements in different domains, the more pronounced the de facto tracking. However, racial-ethnic and socioeconomic diversity are also positively associated with de facto tracking, even though the achievement correlation is controlled. These findings suggest that de facto tracking may be maintained by both technical and demographic aspects of schools, both of which must be considered in any evaluation of tracking.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“students vary greatly in their academic ambitions, prior knowledge, and the environment in which learning is optimal”
From The Relationship of High School Curriculum Tracks to Degree Attainment and Occupational Earnings (2009) · cites this paper as Lucas & Berends, 2002
In the citing paper
“the primary rationale for tracking in schools is pedagogical”
From The Relationship of High School Curriculum Tracks to Degree Attainment and Occupational Earnings (2009) · cites this paper as Lucas & Berends, 2002
Citations
Cites
Men and Women of the Corporation.
Strauss, G., & Kanter, R. M. (1978) · Industrial and Labor Relations Review · doi:10.2307/2522922 · Cited by 7,292
Regression Models for Categorical and Limited Dependent Variables.
MTW, & Long, J. S. (1997) · Journal of the American Statistical Association · doi:10.2307/2965458 · Cited by 6,891
(1967) · Project Euclid (Cornell University) · Cited by 4,720
Kilzer, E., & Wolff, K. H. (1950) · The American Catholic Sociological Review · doi:10.2307/3707052 · Cited by 4,549
Keeping Track: How Schools Structure Inequality.
Oromaner, M. J., & Oakes, J. (1986) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2070941 · Cited by 3,425
The Struggle for the American Curriculum, 1893-1958
Kliebard, H. M. (2004) · Routledge eBooks · doi:10.4324/9780203339985 · Cited by 1,376
Yamaguchi, K. (1991) · Cited by 994
Generalized Linear Models and Extensions
Hardin, J. W., & Hilbe, J. M. (2012) · Cited by 853
Secondary School Tracking and Educational Inequality: Compensation, Reinforcement, or Neutrality?
Gamoran, A., & Mare, R. D. (1989) · American Journal of Sociology · doi:10.1086/229114 · Cited by 663
Tracking: From Theory to Practice
Hallinan, M. T. (1994) · Sociology of Education · doi:10.2307/2112697 · Cited by 433
Politics, Markets, and the Organization of Schools
Chubb, J. E., & Moe, T. M. (1988) · American Political Science Review · doi:10.2307/1961750 · Cited by 404
The Educational Decision-Makers.
Friedenberg, E. Z., Cicourel, A. V., & Kitsuse, J. I. (1964) · American Sociological Review · doi:10.2307/2091445 · Cited by 367
The Variable Effects of High School Tracking
Gamoran, A. (1992) · American Sociological Review · doi:10.2307/2096125 · Cited by 345
Tracking Inequality: Stratification and Mobility in American High Schools
Grusky, D. B., & Lucas, S. R. (2001) · Contemporary Sociology A Journal of Reviews · doi:10.2307/3088991 · Cited by 328
Self-citationWells, A. S., & Serna, I. (1996) · Harvard Educational Review · doi:10.17763/haer.66.1.274848214743t373 · Cited by 311
Race Differences in Sexual Activity Among Adolescent Women: The Role of Neighborhood Characteristics
Brewster, K. L. (1994) · American Sociological Review · doi:10.2307/2095941 · Cited by 308
Curriculum Tracking and Educational Stratification: Some Further Evidence
Alexander, K. L., Cook, M., & McDill, E. L. (1978) · American Sociological Review · doi:10.2307/2094761 · Cited by 234
Crossing the tracks: how "untracking" can save America's schools
(1993) · Choice Reviews Online · doi:10.5860/choice.30-2819 · Cited by 217
Students, Courses, and Stratification
Garet, M. S., & Delany, B. (1988) · Sociology of Education · doi:10.2307/2112265 · Cited by 146
More Than Misapplied Technology: A Normative and Political Response to Hallinan on Tracking
Oakes, J. (1994) · Sociology of Education · doi:10.2307/2112698 · Cited by 127
The tracking wars: state reform meets school policy
(2000) · Choice Reviews Online · doi:10.5860/choice.37-4023 · Cited by 123
The Struggle for the American Curriculum: 1893-1958
Useem, E. L., & Kliebard, H. M. (1987) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2071630 · Cited by 114
Riehl, C., Pallas, A. M., & Natriello, G. (1999) · American Journal of Education · doi:10.1086/444209 · Cited by 68
Conant, J. B. (1960) · Cited by 67
The New Improved Sorting Machine.
Moore, D. R., & Davenport, S. (1988) · Cited by 67
Tracking the Middle Grades: National Patterns of Grouping for Instruction.
Braddock, J. H. (1990) · Phi Delta Kappan · Cited by 43
Ingels, S. J., Scott, L. A., Taylor, J. R., Owings, J. A., & Quinn, P. (1998) · Cited by 24
Curricular Differentiation in Public High Schools. Fast Response Survey System. E.D. Tabs.
Carey, N. (1994) · Cited by 6
Kelley, F. M. (1903) · The Annals of the American Academy of Political and Social Science · doi:10.1177/000271620302100308 · Cited by 2
Cited by
Sorted by citations
Gonzales, R. G. (2011) · American Sociological Review · doi:10.1177/0003122411411901 · Cited by 848
What Do Test Scores Miss? The Importance of Teacher Effects on Non–Test Score Outcomes
Jackson, C. K. (2018) · Journal of Political Economy · doi:10.1086/699018 · Cited by 462
Bouchey, H. A., & Harter, S. (2005) · Journal of Educational Psychology · doi:10.1037/0022-0663.97.4.673 · Cited by 259
Mickelson, R. A. (2003) · Teachers College Record The Voice of Scholarship in Education · doi:10.1111/1467-9620.00277 · Cited by 235
An International Comparison of Achievement Inequality in Within- and Between-School Tracking Systems
Chmielewski, A. K. (2014) · American Journal of Education · doi:10.1086/675529 · Cited by 228
Metadata
- Authors
- Lucas, S. R., & Berends, M.
- Venue
- Sociology of Education
- Publisher
- JSTOR
- Published
- 2002-10
- Volume
- 75
- Issue
- 4
- Pages
- 328
- ISSN
- 0038-0407 (ISSN-L)
- OpenAlex
- W1971754158
- Cited by
- 216
- References
- 30
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 22 · 2023: 6 · 2022: 7 · 2021: 9 · 2020: 10 · 2019: 14 · 2018: 11 · 2017: 7 · 2016: 18 · 2015: 12 · 2014: 10 · 2013: 11 · 2012: 11
- FWCI
- 22.32
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Sociology of Education (publishedVersion)
- Topics
- Social Sciences › Education › School Choice and Performance
- Social Sciences › Sociology and Political Science › Critical Race Theory in Education
- Social Sciences › Sociology and Political Science › Intergenerational and Educational Inequality Studies
- Keywords
- educational tracking, sociodemographic diversity, racial and ethnic diversity, socioeconomic diversity, school composition, secondary schools, High School and Beyond, school segregation
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