Race Is Not Neutral: A National Investigation ofAfrican American and Latino Disproportionality
in School Discipline
Russell J. SkibaIndiana University
Robert H. HornerUniversity of Oregon
Choong-Geun Chung and M. Karega RauschIndiana University
Seth L. May and Tary TobinUniversity of Oregon
Abstract. Discipline practices in schools affect the social quality of each educa-tional environment, and the ability of children to achieve the academic and socialgains essential for success in a 21st century society. We review the documentedpatterns of office discipline referrals in 364 elementary and middle schools duringthe 2005–2006 academic year. Data were reported by school personnel throughdaily or weekly uploading of office discipline referrals using the Web-basedSchool-wide Information System. Descriptive and logistic regression analysesindicate that students from African American families are 2.19 (elementary)to 3.78 (middle) times as likely to be referred to the office for problem behavioras their White peers. In addition, the results indicate that students from AfricanAmerican and Latino families are more likely than their White peers to receiveexpulsion or out of school suspension as consequences for the same or similarproblem behavior. These results extend and are consistent with a long history ofsimilar findings, and argue for direct efforts in policy, practice, and research toaddress ubiquitous racial and ethnic disparities in school discipline.
The Supreme Court’s ruling in Brown v.Board of Education in 1954 set the nation ona path toward equalizing educational opportu-
nity for all children. The right not to be dis-criminated against on the basis of race, color,or national origin was explicitly guaranteed by
This research was supported in part by U.S. Department of Education Grant H326S980003. Opinionsexpressed herein do not necessarily reflect the policy of the Department of Education, and no officialendorsement by the Department should be inferred.
Correspondence regarding this article should be addressed to Russell J. Skiba, Center for Evaluation andEducation Policy, 1900 E. 10th St., Bloomington, IN 47401; e-mail: [email protected]
Copyright 2011 by the National Association of School Psychologists, ISSN 0279-6015
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Title VI of the Civil Rights Act of 1964(Browne, Losen, & Wald, 2002). Those pro-tections were expanded to students with dis-abilities in the Individuals with DisabilitiesEducation Improvement Act of 2004 and toeducational outcomes for all children in theElementary and Secondary Education Act (NoChild Left Behind, 2008). Yet continuing ra-cial and ethnic disparities in education rangingfrom the achievement gap (Ladson-Billings,2006) to disproportionality in special educa-tion (Donovan & Cross, 2002) to dropout andgraduation rates (Wald & Losen, 2007) haveled some to question the extent to which thepromises of Brown have been fulfilled(Blanchett, Mumford, & Beachum, 2005). Inparticular, over 30 years of research has doc-umented racial and socioeconomic disparitiesin the use of out-of-school suspension andexpulsion. The purpose of this article is todescribe a national investigation exploring theextent of, and patterns in, racial and ethnicdisparities in school discipline at the elemen-tary and middle school level.
Consistently DemonstratedDisproportionality
For over 25 years, in national-, state-,district-, and building-level data, students ofcolor have been found to be suspended at ratestwo to three times that of other students, andsimilarly overrepresented in office referrals,corporal punishment, and school expulsion(Skiba, Michael, Nardo, & Peterson, 2002).Documentation of disciplinary overrepresenta-tion for African American students has beenhighly consistent (see e.g., Gregory, 1997;McCarthy & Hoge, 1987; McFadden, Marsh,Price, & Hwang, 1992; Raffaele Mendez &Knoff, 2003; Skiba et al., 2002; Wu, Pink,Crain, & Moles, 1982). According to datafrom the U.S. Department of Education Officefor Civil Rights, disciplinary disproportional-ity for African American students appears tohave increased from the 1970s, when AfricanAmericans appeared to be at approximatelytwice the risk of out of school suspension to2002, when African American students riskfor suspension was almost three times as great
as White students (Wald & Losen, 2003). Al-though disciplinary overrepresentation of La-tino students has been reported in some studies(Raffaele Mendez & Knoff, 2003), the findingis not universal across locations or studies (seee.g., Gordon, Della Piana, & Keleher, 2000).
Possible Causative Mechanisms
A number of possible hypotheses havebeen proposed as mechanisms to account forrates of disciplinary disparity by race/ethnic-ity, including poverty, differential rates of in-appropriate or disruptive behavior in schoolsettings, and cultural mismatch or racial ste-reotyping. The possible mechanisms are dis-cussed in the following.
Poverty
Race and socioeconomic status (SES)are unfortunately highly connected in Ameri-can society (McLoyd, 1998), raising the pos-sibility that any finding of racial disparities inschool discipline can be accounted for by dis-proportionality associated with SES. Low SEShas been consistently found to be a risk factorfor school suspension (Brantlinger, 1991; Wuet al., 1982). Yet when the relationship of SESto disproportionality in discipline has beenexplored directly, race continues to make asignificant contribution to disproportionatedisciplinary outcomes independent of SES(Skiba et al., 2002; Wallace, Goodkind, Wal-lace, & Bachman, 2008; Wu et al., 1982).
Higher Rates of Disruption AmongStudents of Color
A related hypothesis might be that stu-dents of color, perhaps because they have beensubjected to a variety of stressors associatedwith poverty (see e.g., Donovan & Cross,2002), may learn and exhibit behavioral stylesso discrepant from mainstream expectations inschool settings as to put them at risk for in-creased disciplinary contact. Investigations ofstudent behavior, race, and discipline haveconsistently failed, however, to find evidenceof differences in either the frequency or inten-sity of African American students’ school be-
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havior sufficient to account for differences inrates of school discipline. Some studies havefound no significant differences in behaviorbetween African American and White students(McCarthy & Hoge, 1987; Wu et al., 1982),while others have reported that African Amer-ican students receive harsher levels of punish-ment for less serious behavior than other stu-dents (McFadden et al., 1992; Shaw &Braden, 1990). Skiba et al. (2002) comparedthe types of infractions for which AfricanAmerican and White middle school students ina large urban district were referred to the of-fice, and found no obvious differences in se-verity of behavior, but that African Americanstudents tended to be referred to the officemore often for offenses that required a higherdegree of subjectivity, such as disrespect orloitering.
Cultural Mismatch or RacialStereotyping
With a teaching force in most schooldistricts in this nation that is predominantlyWhite and female (Zumwalt & Craig, 2005),the possibility of cultural mismatch or racialstereotyping as a contributing factor in dispro-portionate office referral cannot be discounted.Townsend (2000) suggested that the unfamil-iarity of White teachers with the interactionalpatterns that characterize many African Amer-ican males may cause these teachers to inter-pret impassioned or emotive interactions ascombative or argumentative. In an ethno-graphic study of disciplinary practices at anurban elementary school, Ferguson (2001)documented the seemingly unconscious pro-cess whereby racial stereotypes may contrib-ute to higher rates of school punishment foryoung African American males.
There is some indication that teachersdo make differential judgments about achieve-ment and behavior based on racially condi-tioned characteristics. Neal, McCray, Webb-Johnson, and Bridgest (2003) found that stu-dents who engaged in a “stroll” style ofwalking more often associated with AfricanAmerican movement style were more likely tobe judged by teachers as being more aggres-
sive or lower achieving academically, whetherthe student was African American or White. Inan extensive study of teacher ratings, Zimmer-man, Khoury, Vega, Gil, and Warheit (1995)found evidence that African American stu-dents were more likely to be rated as havingmore extensive behavior problems by bothHispanic and non-Hispanic White teachers. Inaddition, teachers were more likely than par-ents to rate African American students as moreproblematic and less likely than parents to rateWhite students’ behavior as more problematic.In a more restricted sample set in a high-poverty inner-city setting, Pigott and Cowen(2000) found no evidence of a child–teacherrace interaction in teacher ratings of their stu-dents, but found that all teacher groups re-ported a higher incidence of race-related ste-reotypes for African American students.
There is some classroom observationaldata consistent with either a cultural mismatchor racial stereotyping explanation. Vavrus andCole (2002) analyzed videotaped interactionsamong students and teachers, and found thatmany ODRs were less the result of seriousdisruption than what the authors described as“violations of … unspoken and unwritten rulesof linguistic conduct” (p. 91), and that studentssingled out in this way were disproportion-ately students of color. In a study of officereferral practices in an urban high school,Gregory and Weinstein (2008) found that,among a sample of African American studentswith ODRs, differences in classroom manage-ment style significantly contributed to bothstudent attitudes toward classroom manage-ment and actual disciplinary outcomes. Fur-ther, even among students with multiple refer-rals to the office, only certain student–teachercombinations resulted in higher rates of officereferral.
Summary
A number of hypotheses might be ap-plied to explain the ubiquitous overrepresen-tation of African American students in a rangeof school disciplinary consequences. It seemslikely that, in the face of multiple hypotheses,the disproportionate representation of students
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of color in school discipline is complex andmultiply determined.
Risks of DisproportionateRepresentation in School Exclusion
Overrepresentation in out-of-school sus-pension and expulsion appears to place Afri-can American students at risk for a number ofnegative outcomes that have been found to beassociated with those consequences. First,given documented positive relationships be-tween the amount and quality of engaged timein academic learning and student achievement(Brophy, 1988; Greenwood, Horton, & Utley,2002), and conversely between school alien-ation/school bonding and subsequent delin-quency (Hawkins, Doueck, & Lishner, 1988),procedures like out-of-school suspension andexpulsion that remove students from the op-portunity to learn and potentially weaken theschool bond must be viewed as potentiallyrisky interventions. Second, a substantial da-tabase has raised serious concerns about theefficacy of school suspension and expulsion asa behavioral intervention in terms of eitherreductions in individual student behavior oroverall improvement in the school learningclimate (see e.g., American Psychological As-sociation, 2008). Finally, by removing stu-dents from the beneficial aspects of academicengagement and schooling, suspension andexpulsion may constitute a risk factor for fur-ther negative outcomes, including poor aca-demic performance (Skiba & Rausch, 2006),school dropout (Ekstrom, Goertz, Pollack, &Rock, 1986), and involvement in the juvenilejustice system (Wald & Losen, 2003). Thus,the overrepresentation of African Americanstudents in such high-risk procedures must beconsidered highly serious.
Gaps in Knowledge
There are substantial gaps in the re-search literature exploring racial and ethnicdisparities in school discipline, some extend-ing to basic descriptive information. Data con-cerning the representation of Hispanic/Latinostudents in school discipline are limited andhighly inconsistent. Few studies of school dis-
cipline have focused on school level as a vari-able (elementary vs. middle vs. high school)and fewer still have examined disproportion-ality across school levels (Skiba & Rausch,2006). Third, although the disciplinary processhas been recognized as a complex, multilevelprocess proceeding from office referral to ad-ministrative disposition (see e.g., Morrison,Anthony, Storino, Cheng, Furlong, & Morri-son, 2001), little attention has been paid to therelative contribution of office referrals andadministrative consequences to racial and eth-nic disparities in school discipline. Finally,few investigations have been both comprehen-sive and detailed. That is, empirical investiga-tions of school disciplinary processes appeareither to rely on national or state databases(e.g., U.S. Department of Education Office forCivil Rights data) that provide a comprehen-sive perspective on suspension or expulsion,but little detail concerning the initial offensethat led to referral; or to analyze local schoolor district databases of ODRs that provide aricher picture of student infractions, but mayor may not be generalizable to other locations.
Purpose and Assumptions
The purpose of this investigation was toexplore racial and ethnic disparities in officereferrals and administrative discipline deci-sions in a nationally representative sample.The schools in the sample had been involvedin efforts to reform their school disciplinarypractices using School-wide Positive BehaviorSupports (SWPBS) for at least one year.SWPBS is a whole-school approach to preven-tion of problem behavior that focuses on de-fining, teaching, and rewarding behavioral ex-pectations; establishing a consistent contin-uum of consequences for problem behavior;implementing a multitiered system of behaviorsupports; and the active use of data for deci-sion making (Sugai & Horner, 2006). A coreelement of the SWPBS implementation pro-cess is systematic data collection on occur-rence of problem behaviors that result in officereferrals and the discipline decisions associ-ated with those referrals.
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Although the data were drawn from asubsample of schools implementing SWPBS,the purpose of this investigation was not inany way to explore the effects or effectivenessof SWPBS as an intervention for reducingdisciplinary referrals or disproportionality inreferrals. Rather, to our knowledge, these dataprovide the most comprehensive and nation-ally representative sample for addressing someof the gaps in research knowledge regardingracial and ethnic disproportionality in schooldisciplinary procedures. We used descriptiveand logistic regression analyses to explore pat-terns of disproportionality in office referralrates, patterns of disciplinary decisions acrossdifferent racial/ethnic groups (African Ameri-can, Hispanic, White), and school level (ele-mentary vs. middle school).
The analyses make two assumptionsabout effective disciplinary practices andhence about the types of data that would pro-vide evidence of an effective and equitabledisciplinary system. First, we presume that themost effective disciplinary systems are gradu-ated discipline systems (American Psycholog-ical Association, 2008) in which minor infrac-tions produce less severe administrative con-sequences than more severe infractions. Thephilosophy and practice of zero tolerance hastended to emphasize an alternate model, inwhich both minor and major infractions aremet with more severe consequences, but asubstantial database has failed to support theefficacy of practices based on that perspective(American Psychological Association, 2008).Second, given that there is no evidence sup-porting a distribution of infractions that variesin severity by race, we presume that disciplin-ary outcomes will be proportional across ra-cial/ethnic categories.
Methods
Data Source
The subjects for this investigation weredrawn from data generated by the School-wideInformation System (SWIS: May et al., 2006),which was being used in over 4000 schoolsacross the nation during the 2005–206 aca-
demic year (cf. http://www.swis.org, January2007).
The SWIS is a three-component deci-sion system for gathering and using schooldiscipline data for decision making. The com-ponents of SWIS are (a) a data collectionprotocol that schools adopt that uses opera-tionally defined categories for problem behav-ior, school-wide standards defining whichproblem behaviors are addressed in class-rooms versus sent to the office, and a structurefor team meetings in which data are used; (b)a Web-based computer application for enter-ing ODR data and retrieving summary reportsin graphic and tabular formats (May et al.,2006), and (c) a facilitator-based training sys-tem to help teams use data for active decisionmaking.
The entry of data into the SWIS com-puter application requires that students beidentified by name, district identification num-ber, grade, Individualized Education Program(IEP) status, and ethnicity. The content of anoffice discipline referral includes informationabout (a) the type of problem behavior leadingto the referral; (b) the time of day, location,referring adult, and others present during theevent; (c) the presumed maintaining conse-quence (e.g., access to attention, escape fromwork, response to taunting from peers); and(d) the primary administrative decision (e.g.,conversation, detention, loss of privilege, par-ent report, suspension) resulting from the re-ferral. This information is summarized in aseries of reports that allow an administrator,specialist, team, or faculty member to monitorthe rate of office discipline referrals; the typeof behaviors leading to referrals; the time ofday, location, and presumed maintaining con-sequence; and the administrative decisionpatterns.
The SWIS system also provides the op-tion for a school to compute a summary ofODRs by race/ethnicity. Race/ethnicity withinSWIS is determined by the family designationwhen a child is enrolled in school, but islimited in specificity to the six federal racecategories: African American, Asian, NativeAmerican, Pacific Islander, Hispanic/Latino,and Caucasian.
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Selection of problem behavior for allschools using SWIS is based on a mutuallyexclusive and exhaustive list of 24 operation-ally defined “major problem behaviors” andthree operationally defined “minor problembehaviors.” School-based consequences forthese reported behaviors are coded into 14mutually exclusive and exhaustive categoriesof “administrative decisions.” Operationaldefinitions of both student behaviors and ad-ministrative decisions may be found on theSWIS Resources site at http://www.swis.org/index.php?page � resources;rid � 10121.
Participant Sample
As of January 2007, there were over4000 schools in the United States at varyingstages of SWIS adoption. During the fall of2007, we identified from this population ofschools a subset of 436 schools who (a) usedSWIS for the full 2005–2006 academic year,(b) reported ethnicity information, (c) hadgrade levels between kindergarten and sixthgrade (K–6) or sixth and ninth grade (6–9),and (d) agreed to share anonymous summariesof their data for evaluation purposes. Theseschools reported total enrollment of 120,148students in elementary grades (K–6)and 60,522 students in middle school grades(6–9). Spaulding et al. (2010), compared thedemographic features of the sample with73,525 comparable schools in the NationalCenter for Educational Statistics (NCES) sam-ple for 2005–2006 to assess bias in size, pro-portion of students with an IEP, SES, racial/ethnic distribution, and location (urban, sub-urban, or rural). They found the SWISdatabase to be within 5% of the NCES data inall categories except that the SWIS databasewas composed of fewer schools within thehigh SES category and had a larger number ofschools with high ethnic/racial diversity. Atthe K-6 and 6–9 levels, the sample did notdiffer from the NCES data in the percentage oflarge, midsized, or rural schools represented,but at the high school level there were moreschools with large enrollment.
It is important to note that schoolsadopting SWIS were self-nominated, and in
most cases were in varying stages of imple-menting school-wide positive behavior sup-port (Sugai et al., 2002; Lewis & Sugai, 1999).Adoption of SWIS does not require thatschools also adopt school-wide positive be-havior support, but often districts investing inadoptions of school-wide discipline systemsare more likely to also invest in adoption ofSWIS. Again, the purpose of this investigationwas not to explore any attributes, effects, oreffectiveness of the use of SWPBS in theseschools. No information was available withinthe SWIS database to indicate the length orfidelity of SWPBS adoption.
For purposes of analysis, the 436schools were organized into an elementarylevel (K–6) and a middle school level (6–9).Schools that overlapped to some extent (e.g.,Grades 5–9) were placed in the group with thelargest degree of overlap. Schools with a de-gree of overlap that did not permit sorting withconfidence (e.g., schools serving Grades K–8)were dropped from the sample. The final sam-ple included 272 K–6 level schools and 926–9 level schools.
Research Questions and Variables
The primary research questions focusedfirst on the pattern of ODRs by race and thenon the pattern of administrative decisions byrace. The following questions guided thestudy.
ODRs. Two questions were addressedthrough descriptive data and logistic regres-sion analyses.
1. To what extent does racial/ethnic statusmake a contribution to rates of ODR inelementary or middle schools?
2. In which categories of ODRs are racialor ethnic disparities evident?
The original SWIS data included 27 cat-egories of disciplinary infraction that could beentered as the reason for an ODR. For con-ceptual and analytic clarity, we categorizedthose infractions into the categories minormisbehavior, disruption, noncompliance,moderate infractions, major violations, use/possession, tardy/truancy, and other/unknown
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(Note: specific infractions included in eachcategory may be found in Table 3).
Administrative decisions. Three ques-tions were addressed through descriptive data,simply logistic regression, and multinomiallogit models.
3. To what extent does racial/ethnic statusmake a contribution to administrativedecisions concerning disciplinary con-sequences in elementary or middleschools?
4. In which categories of disciplinary con-sequence are racial or ethnic disparitiesevident?
5. What are the racial disparities in theinteraction of infraction types and ad-ministrative decisions regarding conse-quence? In which infraction/conse-quence pairs do such disparities occur?
The original SWIS data included 14 cat-egories of administrative decision regardingprimary disciplinary consequence. For con-ceptual and analytic clarity, we categorizedthose decisions into the categories of minorconsequences, detention, moderate conse-quences, in-school suspension, out-of-schoolsuspension and expulsion, and other/unknown.(Note: Specific administrative decisions com-prising each category may be found inTable 4.)
Data analyses. Descriptive analysesand a series of logistic and multinomial logitregression analyses (Greene, 2008) were usedto describe the extent of disproportionality instudent infractions, administrative decisions,and their interaction. The first logistic equa-tion addressing Research Question 2 (Table 2)was designed to test the extent to which raceproved a factor in the probability of an ODR.
The second analysis addressing Re-search Question 2 (Table 3) was a multinomiallogit model designed to explore the contribu-tion of race to referrals for specific types ofinfraction. The third regression, addressingQuestions 3 and 4, was a multinomial logitregression testing the influence of type of in-fraction and race on the probability of receiv-
ing a given consequence (Table 4). The finalmultinomial logit regression, addressing Re-search Question 5, was designed to test thespecific influence of race on the probability ofall possible infraction/consequence interac-tions (Table 5).
Early analyses showing differences inpatterns of results by school level led us toconduct separate analyses for K–6 and 6–9schools. The measure used to index dispropor-tionality throughout the analyses is the oddsratio (OR) drawn from the logistic and multi-nomial logit regression equations, with valuesgreater than 1.0 indicating overrepresentationand values less than 1.0 indicating underrep-resentation. In contrast to risk ratios, the ORmay offer a more stable and accurate estimateof disproportionality, because it accounts forboth occurrence and nonoccurrence of theevent being measured (Finn, 1982; Oswald,Coutinho, Best, & Singh, 1999). For all anal-yses involving racial/ethnic categories, the in-dex category was “White,” while the indexcategory for infractions or administrative de-cisions varied and is noted in the footnote ofthe table for that analysis. Finally, note thatdescription of the results refers to “overrepre-sentation” or “underrepresentation” of a givenracial/ethnic group with respect to a giveninfraction or disciplinary consequence. In de-scriptive results, presented as composition in-dices, proportionality is compared to thatgroup’s representation in the population.Across all logistic and multinomial logit anal-yses, disproportionality is framed in terms ofover- or underrepresentation in comparison tothe index group. This is not intended to con-vey any judgment concerning how frequentlya given consequence ought to be applied (e.g.,Latino students being underrepresented in de-tention does not in any way suggest theyshould be placed in detention more fre-quently), but rather is simply a numerical rep-resentation of the probability of occurrencerelative to the index group (White students).The Box Tidwell Transformation Test (Cohen,Cohen, West, & Aiken, 2003) was performedto test for the assumption that there is a linearrelationship between the independent vari-ables and the log odds (logit) of the dependent
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measure. Tests across all models failed toyield any significant results, indicating thatthere is no nonlinearity issue for this sample.
Results
Disproportionate representation inschool discipline can occur at either the pointof referral or administrative decision. To trackdisproportionality through these two points inthe disciplinary process, results are organizedinto two sections: ODRs and administrativedecisions.
ODRs
Table 1 presents the total enrollment,number of students referred to the office, andnumber of ODRs disaggregated by race forK–6 and 6–9 level schools. The percentagesin Columns 2, 4, and 6 are column percent-ages, reflecting the percent of enrollment, stu-dents referred, or total number of ODRs re-spectively for each racial/ethnic group. Eachpercentage in Column 4 or 6 therefore repre-
sents a composition index (Donovan & Cross,2002) that can be interpreted by comparing itto the percent overall enrollment in Column 2.Thus, at the K–6 level, African Americanstudents appear to be overrepresented, relativeto their proportion in the population, amongthose referred to the office, represent-ing 25.8% of total enrollment (Column 2),but 35.3% of those referred to the office (Col-umn 4). White and Hispanic/Latino studentsare underrepresented relative to their enroll-ment among those referred to the office at theK–6 level. At the 6–9 level, African Ameri-can students appear to be overrepresented, andWhite students appear to be underrepresentedin their rate of ODRs as compared to theirpercentage in the population. Hispanic/Latinostudents appear to be roughly proportionatelyrepresented in middle school ODRs. The levelof overreferral of African American studentsbecomes even more apparent if one examinesthe absolute number of referrals to the office(Column 6). The discrepancy between individ-
Table 1Enrollment, Number of Students Referred, and Number of Referrals
Disaggregated by Racial Ethnic Group
Group
Enrollment Students Referred Referrals
N % N % N %
K–6 Schools (N � 272)Hispanic/Latino 25,051 20.9 4,311 13.1 12,863 9.6African American 30,961 25.8 11,577 35.3 57,601 43.0White 54,690 45.5 11,703 35.7 45,900 34.3Unknown/all othersa 9,446 7.9 5,212 15.9 17,518 13.1
Total N of students 120,148 100.0 32,803 100.0 133,882 100.0
6–9 Schools (N � 92)Hispanic/Latino 10,332 17.1 4,245 16.9 18,419 14.5African American 13,228 21.9 8,024 32.0 52,894 41.7White 32,975 54.5 9,542 38.1 42,605 33.6Unknown/all others 3,987 6.6 3,260 13.0 12,842 10.1
Total N of students 60,522 100.0 25,071 100.0 126,760 100.0
Note. K–6 � kindergarten through Grade 6; 6–9 � Grade 6 through Grade 9.aUnknown/all others: American Indian/Alaskan Native, Asian, Pacific Islander/Native Hawaiian, Not Listed, andUnknown.
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ual referrals and total referrals suggests ahigher rate of multiple referrals to the officefor African American students as opposed toWhite or Hispanic/Latino students at both theelementary and middle school levels.
Differences in ODRs across racial/eth-nic categories were more directly compared inthe ORs drawn from a logistic regression anal-ysis predicting the probability of at least oneODR (Table 2). The index group for all anal-yses is White students. All ORs in Table 2 aresignificant at the 0.01 level. At the K–6 level,African American students’ odds of being re-ferred to the office are 2.19 times that of Whitestudents; the overrepresentation of AfricanAmericans in ODRs relative to White studentsappears to increase (OR � 3.79) at the 6–9level.
A somewhat different pattern of dispro-portionality is in evidence for Hispanic/Latinostudents. At the K–6 level, Hispanic/Latino
students are underrepresented in their rate ofreferral to the office relative to White students(OR � 0.76). At the 6–9 level, however, His-panic/Latino students in this sample are over-represented (OR � 1.71) in their rate ofODRs. These results at the 6–9 level appear atfirst glance to be somewhat at odds with com-position indices (Table 1) that appear to showrates of ODRs for Hispanic/Latino studentsthat are roughly proportionate at the 6–9 level.Thus, significant Latino overrepresentationrelative to White students at the middle schoollevel appears to be from, not the absoluteoverreferral of Latino students, but rather tothe substantial underreferral to the office ofWhite students as compared to their represen-tation in the population.
The ORs associated with ODRs brokendown by infraction comparing African Amer-ican and Latino students with White studentsare presented in Table 3. With the exception ofTardy/Truancy, Major Violations, and Use/Possession for Hispanic/Latino students at theK–6 level, all ORs are significant at the p �.01 level. At both the K–6 and 6–9 levels,African American students are significantlyoverrepresented in ODRs across all infractiontypes, with the highest ORs compared toWhite students for the infraction types of Tar-dy/Truancy, Disruption, and Noncompliance.At the K–6 level, Hispanic/Latino students areunderrepresented as compared with White stu-dents in ODRs for Minor Misbehaviors, Dis-ruption, Noncompliance, and Moderate Infrac-tions. At the 6–9 level, in contrast, Hispanic/Latino students appear to be overrepresentedrelative to White students for all ODRcategories.
Administrative Decisions
Table 4 presents the results of a multi-nomial logistic regression predicting the like-lihood of a particular administrative decisionusing two models. In Model 1, the likelihoodof an administrative consequence is predictedsolely from type of infraction. In Model 2,race/ethnicity is added to type of infraction topredict the likelihood of an administrativeconsequence. For both Model 1 and Model 2,
Table 2Logistic Regression of the Influence
of Race/Ethnicity on Referrala
GroupReferred:
Odds Ratio
K–6 SchoolsHispanic/Latino 0.76*African American 2.19*Unknown/all others NANumber of cases 120,148Model �2 7,152Nagelkerke Pseudo R2 0.084% Correctly predicted 73.5
6–9 SchoolsHispanic/Latino 1.71*African American 3.79*Unknown/all others NANumber of cases 60,522Model �2 6,925Nagelkerke Pseudo R2 0.146% Correctly predicted 67.4
Note. K–6 � kindergarten through Grade 6; 6–9 �Grade 6 through Grade 9; NA � not available.aReference category is Not Referred for outcome and isWhite for Race/Ethnicity.*p � .05.
Disciplinary Disproportionality
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Tab
le3
Mu
ltin
omia
lL
ogit
Reg
ress
ion
ofth
eIn
flu
ence
ofR
ace/
Eth
nic
ity
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tion
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ajor
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latio
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se/P
osse
ssio
nT
ardy
/T
ruan
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ther
/U
nkno
wn
K–6
Scho
ols
His
pani
c/L
atin
o0.
66**
0.67
**0.
60**
0.77
**0.
911.
220.
840.
80**
Afr
ican
Am
eric
an1.
77**
3.96
**3.
32**
2.62
**2.
87**
2.96
**6.
58**
2.66
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nkno
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all
othe
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142,
451
Mod
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212
,848
Nag
elke
rke
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doR
20.
093
%C
orre
ctly
pred
icte
d61
.3
6–9
Scho
ols
His
pani
c/L
atin
o1.
50**
1.31
**1.
87**
1.76
**1.
80**
1.93
**2.
44**
1.30
**A
fric
anA
mer
ican
3.72
**5.
60**
5.43
**4.
76**
3.91
**2.
02**
4.40
**4.
55**
Unk
now
n/al
lot
hers
NA
NA
NA
NA
NA
NA
NA
NA
n89
,279
Mod
el�
212
,001
Nag
elke
rke
Pseu
doR
20.
129
%C
orre
ctly
pred
icte
d40
.5
Not
e.M
inor
Mis
beha
vior
s�
min
orin
appr
opri
ate
verb
alla
ngua
ge,
min
orph
ysic
alco
ntac
t,m
inor
defia
nce/
disr
espe
ct/n
onco
mpl
ianc
e,m
inor
disr
uptio
n,m
inor
prop
erty
mis
use,
othe
rm
inor
mis
beha
vior
s;D
isru
ptio
n�
disr
uptio
n;N
onco
mpl
ianc
e�
defia
nce/
disr
espe
ct/in
subo
rdin
atio
n/no
ncom
plia
nce;
Mod
erat
eIn
frac
tions
�ab
usiv
ela
ngua
ge/in
appr
opri
ate
lang
uage
,fig
htin
g/ph
ysic
alag
gres
sion
,ly
ing/
chea
ting,
hara
ssm
ent/b
ully
ing;
Maj
orV
iola
tions
�pr
oper
tyda
mag
e,fo
rger
y/th
eft,
vand
alis
m,
bom
bth
reat
/fal
seal
arm
,ar
son;
Use
/Pos
sess
ion
�us
e/po
sses
sion
ofto
bacc
o,al
coho
l,co
mbu
stib
leite
ms,
wea
pons
,dr
ugs;
Tar
dy/T
ruan
cy�
tard
y,sk
ipcl
ass/
trua
ncy,
dres
sco
devi
olat
ion;
Oth
er/U
nkno
wn
�ot
her
beha
vior
,un
know
nbe
havi
or;
K–
6�
kind
erga
rten
thro
ugh
Gra
de6;
6–9
�G
rade
6th
roug
hG
rade
9;N
A�
not
avai
labl
e.a E
ntri
esin
each
cell
repr
esen
tth
eod
dsra
tiodr
awn
from
the
mul
tinom
ial
logi
t,ho
ldin
gco
nsta
ntth
eco
ntri
butio
nof
all
othe
rva
riab
les.
Ref
eren
ceca
tego
ryis
Not
Ref
erre
dfo
rou
tcom
ean
dis
Whi
tefo
rR
ace/
Eth
nici
ty.
**p
�.0
1.
School Psychology Review, 2011, Volume 40, No. 1
94
the odds of receiving a suspension/expulsionfor committing a minor infraction are very lowat both the K–6 and 6–9 levels, and appear toincrease proportionally as the seriousness ofinfraction increases. Thus, the odds of receiv-ing a suspension or expulsion for Use/Posses-sion are very high at both the K–6(OR � 16.60) and 6–9 (OR � 53.01) level.
Model 2 in Table 4 adds race/ethnicityto the model, and results in little change to theORs or significance for type of infraction ascompared to Model 1. Race/ethnicity entersthe equation significantly for most administra-tive decisions. Both African American andLatino students are overrepresented in suspen-sion/expulsion relative to White students atboth K–6 and 6–9 levels. African Americanstudents are underrepresented in the use ofdetention at the K–6 level, and underrepre-sented in all administrative consequences ex-cept suspension/expulsion at the 6–9 level. Incontrast, Hispanic/Latino students are under-represented relative to White students in theuse of moderate consequences, but overrepre-sented in detention at both the K–6 and 6–9levels. The continuing significance of race/ethnicity in Model 2 even after controlling fortype of behavior indicates that race/ethnicitymakes a contribution to administrative deci-sions regarding discipline independent of typeof infraction, above and beyond any prior dis-parity in classroom referral.
Table 5 presents the ORs for receivingvarious administrative consequences brokendown by race and type of infraction drawnfrom a series of multinomial logit regressionanalyses at the K–6 and 6–9 levels, testing forthe presence of differential administrativetreatment for the same offense. The resultsdescribe a complex pattern of variation acrosstype of infraction, race/ethnicity, and schoollevel. At the elementary level, African Amer-ican students were more likely than Whitestudents to receive out-of-school suspension/expulsion for all types of infractions tested(note that tardiness/truancy and use/possessioncould not be estimated in the model becausezero cells). In particular, results indicated thatAfrican American elementary school studentswere more likely than White students to be
suspended out-of-school for minor misbehav-ior (OR � 3.75, p � .01). They were also lesslikely to receive in-school suspension for dis-ruption or noncompliance, less likely to re-ceive moderate consequences for noncompli-ance, and less likely to receive detention forminor misbehavior or moderate infractions.Latino students at the elementary level weremore likely to be suspended/expelled thanWhite students across all infractions exceptdisruption, and also more likely to receivedetention than White students for minor mis-behavior, noncompliance, and moderate in-fractions. Finally, Latino students were morelikely than White students to receive in-schoolsuspension for minor misbehavior, and lesslikely to receive in-school suspension fornoncompliance.
A slightly different pattern of infraction/consequences appears at the middle schoollevel. The overrepresentation of AfricanAmerican students in suspension/expulsion forspecific offenses is less consistent at the 6–9level, with ORs significantly greater than 1.00for only disruption, moderate infractions, andtardy/truancy. The pattern of African Ameri-can underrepresentation in less serious conse-quences was more pronounced at the 6–9level, however, with ORs significantly lessthan 1.00 for almost all less serious conse-quences across most types of infractions. His-panic/Latino disproportionality in suspension/expulsion at the 6–9 level appeared to be moreconsistent with elementary level findings, withORs significantly greater than one across alltypes of infractions except use/possession.Significant underrepresentation of Hispanic/Latino students was found in the use of mod-erate consequences for disruption and moder-ate infractions, and in in-school suspension forminor misbehavior and tardy/truancy.
Discussion
We conducted a disaggregated analysisof a detailed, nationally representative data setin order to provide a more comprehensivepicture of disproportionality in disciplineacross racial/ethnic categories and school lev-els. The results indicate that, across an exten-
Disciplinary Disproportionality
95
Tab
le4
Mu
ltin
omia
lL
ogit
Reg
ress
ion
ofth
eIn
flu
ence
ofB
ehav
ior
and
Rac
eon
Adm
inis
trat
ive
Dec
isio
ns:
Odd
sR
atio
sa
Var
iabl
e
Mod
el1
Mod
el2
Det
entio
nM
oder
ate
Con
sequ
ence
In-S
choo
lSu
spen
sion
OSS
and
Exp
ulsi
onO
ther
/U
nkno
wn
Det
entio
nM
oder
ate
Con
sequ
ence
In-S
choo
lSu
spen
sion
OSS
and
Exp
ulsi
onO
ther
/U
nkno
wn
K–6
Scho
ols
Infr
actio
nsb
Min
orM
isbe
havi
ors
0.96
0.64
0.17
**0.
02**
0.03
**0.
880.
660.
17**
0.03
**0.
03**
Dis
rupt
ion
0.76
*1.
400.
790.
59**
0.01
**0.
73*
1.41
0.78
0.63
**0.
01**
Non
com
plia
nce
0.88
1.51
0.88
0.78
0.01
**0.
841.
530.
880.
850.
01**
Mod
erat
eIn
frac
tions
1.04
1.42
1.28
1.55
**0.
01**
0.96
1.44
1.28
1.73
**0.
01*
Maj
orV
iola
tions
1.19
2.53
**1.
44*
1.14
0.01
**1.
072.
60**
1.44
*1.
270.
01**
Use
/Pos
sess
ion
0.94
1.84
4.34
**16
.60*
*0.
02**
0.82
1.91
4.35
**18
.82*
*0.
02**
Oth
er/U
nkno
wn
1.33
*2.
25*
1.19
1.32
0.02
**1.
202.
30**
1.19
1.48
**0.
02**
Rac
eb
His
pani
c/L
atin
o1.
24**
0.71
**1.
011.
52**
0.64
**A
fric
anA
mer
ican
0.78
**1.
030.
991.
64**
1.03
Oth
er/U
nkno
wn
NA
NA
NA
NA
NA
Nof
case
s13
3,88
213
3,88
2M
odel
�2
33,8
9935
,681
Nag
elke
rke
Pseu
doR
20.
240
0.25
1%
Cor
rect
lypr
edic
ted
57.5
57.5
School Psychology Review, 2011, Volume 40, No. 1
96
Tab
le4
Con
tin
ued
Var
iabl
e
Mod
el1
Mod
el2
Det
entio
nM
oder
ate
Con
sequ
ence
In-S
choo
lSu
spen
sion
OSS
and
Exp
ulsi
onO
ther
/U
nkno
wn
Det
entio
nM
oder
ate
Con
sequ
ence
In-S
choo
lSu
spen
sion
OSS
and
Exp
ulsi
onO
ther
/U
nkno
wn
6–9
Scho
ols
Infr
actio
nsb
Min
orM
isbe
havi
ors
0.48
**0.
27**
0.27
**0.
27*
1.06
0.49
**0.
27**
0.27
**0.
28**
1.07
Dis
rupt
ion
0.30
**0.
38**
0.58
**1.
030.
20**
0.33
**0.
40**
0.59
**1.
090.
20**
Non
com
plia
nce
0.29
**0.
41**
0.74
**1.
40**
0.24
**0.
31**
0.43
**0.
75**
1.45
**0.
24**
Mod
erat
eIn
frac
tions
0.30
**0.
67**
1.20
**6.
40**
0.33
**0.
31**
0.66
**1.
22**
6.70
**0.
34**
Maj
orV
iola
tions
0.38
**2.
04**
1.04
**6.
59**
0.50
**0.
38**
1.93
**1.
44**
6.89
**0.
50**
Use
/Pos
sess
ion
0.27
**1.
97*
2.05
**53
.01*
*0.
61*
0.25
**1.
74*
1.98
**55
.65*
*0.
58*
Oth
er/U
nkno
wn
0.49
**1.
20*
1.04
2.95
**0.
49**
0.51
**1.
19*
1.05
3.13
**0.
50**
Rac
eb
His
pani
c/L
atin
o1.
06*
0.77
**0.
991.
58**
0.90
**A
fric
anA
mer
ican
0.58
**0.
53**
0.82
**1.
12**
0.73
**O
ther
/Unk
now
nN
AN
AN
AN
AN
AN
ofca
ses
126,
760
126,
760
Mod
el�
228
,905
31,1
23N
agel
kerk
ePs
eudo
R2
0.21
10.
226
%C
orre
ctly
pred
icte
d32
.533
.3
Not
e.D
eten
tion
�de
tent
ion;
Min
orC
onse
quen
ces
�tim
ein
offic
e,lo
ssof
priv
ilege
s,co
nfer
ence
with
stud
ent,
pare
ntco
ntac
t,in
divi
dual
ized
inst
ruct
ion;
Mod
erat
eC
onse
quen
ces
�Sa
turd
aysc
hool
,bu
ssu
spen
sion
,re
stitu
tion;
In-S
choo
lSu
spen
sion
�in
-sch
ool
susp
ensi
on;
OSS
and
Exp
ulsi
on�
out-
of-s
choo
lsu
spen
sion
,ex
puls
ion;
Oth
er/U
nkno
wn
�ot
her
adm
inis
trat
ive
deci
sion
,un
know
nad
min
istr
ativ
ede
cisi
on;
K–
6�
kind
erga
rten
thro
ugh
Gra
de6;
6–9
�G
rade
6th
roug
hG
rade
9;N
A�
not
avai
labl
e.a R
efer
ence
cate
gory
isM
inor
Con
sequ
ence
sfo
rou
tcom
e.bR
efer
ence
cate
gory
isT
ardy
/Tru
ancy
for
Infr
actio
ns,
Whi
tefo
rR
ace/
Eth
nici
ty.
*p�
.05.
**p
�.0
1.
Disciplinary Disproportionality
97
Tab
le5
Mu
ltin
omia
lL
ogit
Reg
ress
ion
ofth
eIn
flu
ence
ofR
ace
onA
dmin
istr
ativ
eD
ecis
ion
sin
Indi
vidu
alIn
frac
tion
:O
dds
Rat
iosa
Rac
eb
K–6
Scho
ols
6–9
Scho
ols
Det
entio
nM
oder
ate
Con
sequ
ence
sIn
-Sch
ool
Susp
ensi
onO
SSan
dE
xpul
sion
Oth
er/
Unk
now
nD
eten
tion
Mod
erat
eC
onse
quen
ces
In-S
choo
lSu
spen
sion
OSS
and
Exp
ulsi
onO
ther
/U
nkno
wn
Min
orM
isbe
havi
ors
His
pani
c/L
atin
o1.
22**
0.85
3.01
**2.
06*
0.51
**1.
050.
800.
36**
1.83
**0.
27*
Afr
ican
Am
eric
an0.
58**
1.24
*1.
76**
3.75
**1.
030.
70**
0.46
**0.
52**
0.95
0.62
*U
nkno
wn/
All
Oth
ers
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
N56
,884
23,1
81M
odel
�2
1,67
31,
209
Nag
elke
rke
Pseu
doR
20.
033
0.05
4
Dis
rupt
ion
His
pani
c/L
atin
o1.
271.
030.
781.
281.
361.
080.
63*
0.99
1.59
**1.
12A
fric
anA
mer
ican
0.94
0.94
0.83
*1.
54**
0.84
0.54
**0.
53**
0.93
1.35
**1.
19**
Unk
now
n/A
llO
ther
sN
AN
AN
AN
AN
AN
AN
AN
AN
AN
AN
8,20
318
,570
Mod
el�
252
498
Nag
elke
rke
Pseu
doR
20.
007
0.02
8
Non
com
plia
nce
His
pani
c/L
atin
o1.
30**
0.72
0.72
**1.
24*
1.06
1.09
0.82
1.05
1.25
**0.
94A
fric
anA
mer
ican
1.04
0.70
**0.
81**
1.22
**0.
920.
47**
0.44
**0.
88**
0.99
0.90
*U
nkno
wn/
All
Oth
ers
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
N21
,374
34,6
42M
odel
�2
141
887
Nag
elke
rke
Pseu
doR
20.
007
0.02
6
School Psychology Review, 2011, Volume 40, No. 1
98
Tab
le5
Con
tin
ued
Rac
eb
K–6
Scho
ols
6–9
Scho
ols
Det
entio
nM
oder
ate
Con
sequ
ence
sIn
-Sch
ool
Susp
ensi
onO
SSan
dE
xpul
sion
Oth
er/
Unk
now
nD
eten
tion
Mod
erat
eC
onse
quen
ces
In-S
choo
lSu
spen
sion
OSS
and
Exp
ulsi
onO
ther
/U
nkno
wn
Mod
erat
eIn
frac
tions
His
pani
c/L
atin
o1.
27**
0.48
**0.
891.
59**
1.08
1.01
0.72
*1.
031.
74**
1.34
**A
fric
anA
mer
ican
0.91
*1.
32**
0.98
1.84
**1.
14*
0.52
**0.
59**
0.88
**1.
13**
1.28
**U
nkno
wn/
All
Oth
ers
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
N34
,792
24,5
20M
odel
�2
504
481
Nag
elke
rke
Pseu
doR
20.
015
0.02
0
Maj
orV
iola
tions
His
pani
c/L
atin
o1.
121.
010.
691.
87**
1.03
1.47
1.11
0.94
1.93
**0.
96A
fric
anA
mer
ican
0.85
0.73
0.90
2.02
**0.
870.
52**
0.45
**0.
801.
301.
14U
nkno
wn/
All
Oth
ers
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
N2,
978
2,12
0M
odel
�2
4784
Nag
elke
rke
Pseu
doR
20.
017
0.04
0
Use
/Pos
sess
ionc
His
pani
c/L
atin
o1.
420.
391.
002.
320.
67A
fric
anA
mer
ican
0.34
0.33
0.29
**0.
550.
38U
nkno
wn/
All
Oth
ers
NA
NA
NA
NA
NA
N1,
015
Mod
el�
240
Nag
elke
rke
Pseu
doR
20.
047
Disciplinary Disproportionality
99
Tab
le5
Con
tin
ued
Rac
eb
K–6
Scho
ols
6–9
Scho
ols
Det
entio
nM
oder
ate
Con
sequ
ence
sIn
-Sch
ool
Susp
ensi
onO
SSan
dE
xpul
sion
Oth
er/
Unk
now
nD
eten
tion
Mod
erat
eC
onse
quen
ces
In-S
choo
lSu
spen
sion
OSS
and
Exp
ulsi
onO
ther
/U
nkno
wn
Oth
er/U
nkno
wn
His
pani
c/L
atin
o1.
320.
550.
62*
2.12
**0.
990.
940.
710.
933.
99**
1.70
**A
fric
anA
mer
ican
1.10
0.83
1.38
**1.
69**
0.61
**0.
57**
1.19
1.00
1.67
**0.
81*
Unk
now
n/A
llO
ther
sN
AN
AN
AN
AN
AN
AN
AN
AN
AN
AN
4,50
66,
328
Mod
el�
218
640
3N
agel
kerk
ePs
eudo
R2
0.04
20.
064
Tar
dy/T
ruan
cyc
His
pani
c/L
atin
o1.
34**
1.06
1.86
**1.
66**
2.28
**A
fric
anA
mer
ican
0.63
**0.
48**
0.62
**1.
37**
0.38
**U
nkno
wn/
All
Oth
ers
NA
NA
NA
NA
NA
N16
,384
Mod
el�
282
3N
agel
kerk
ePs
eudo
R2
0.05
1
Not
e.D
eten
tion
�de
tent
ion;
Mod
erat
eC
onse
quen
ces
�Sa
turd
aysc
hool
,bus
susp
ensi
on,r
estit
utio
n;In
-Sch
oolS
uspe
nsio
n�
in-s
choo
lsus
pens
ion;
OSS
and
Exp
ulsi
on�
out-
of-s
choo
lsu
spen
sion
,exp
ulsi
on;O
ther
/Unk
now
n�
othe
rad
min
istr
ativ
ede
cisi
on,u
nkno
wn
adm
inis
trat
ive
deci
sion
;K–
6�
kind
erga
rten
thro
ugh
Gra
de6;
6–9
�G
rade
6th
roug
hG
rade
9;N
A�
not
avai
labl
e.E
ach
OD
R/s
choo
lle
vel
com
bina
tion
inth
isan
alys
isre
pres
ents
ase
para
tem
odel
.Thu
s,w
ithse
para
teN
valu
esfo
rea
chm
odel
,it
isim
port
ant
tono
teth
atth
eod
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sive national sample, significant disparities ex-ist for African American and Latino studentsin school discipline. Patterns are complex andmoderated by type of offense, race/ethnicity,and school level. Nevertheless, the overall pat-tern of results indicates that both initial refer-ral to the office and administrative decisionsmade as a result of that referral significantlycontribute to racial and ethnic disparities inschool discipline.
Across a national sample, AfricanAmerican students have twice the odds com-pared to White students of receiving ODRs atthe elementary level, and almost four times theodds of being referred to the office at themiddle school level. A different pattern ofdisproportionality emerges for Hispanic stu-dents, with significant overrepresentation(OR � 1.71) at the middle school level, butsignificant underrepresentation (OR � 0.76) atthe elementary school level. These results areconsistent with previous research indicatingubiquitous overrepresentation in school disci-pline for African American students, but in-consistent evidence of disparities for Latinostudents (Gordon, Della Piana, & Keleher,2000; Skiba & Rausch, 2006). It is possiblethat the striking shift found in the currentstudy from Hispanic under- to overrepresenta-tion in ODRs as one moves to the middleschool level may help explain some of theinconsistency in previous findings.
For African American students at theelementary school level, and for both AfricanAmerican and Latino students at the middleschool level, disparities in rates of referralwere widespread across referral types. Oneexplanation for racial and ethnic dispropor-tionality in school discipline is that such dis-parities are primarily a result of socioeco-nomic disadvantage (National Association ofSecondary School Principals, 2002); that is,African American students, overexposed tothe stressors of poverty, are more likely to beundersocialized with respect to school normsand rules. Yet previous research has found noevidence that disciplinary disproportionalitycan be explained to any significant degree bypoverty (Wallace et al., 2008; Wu et al.,1982). More important, there appears to be
little support for a hypothesis that AfricanAmerican students act out more in similarschool or district situations (McFadden et al.,1992; McCarthy & Hoge, 1987; Wu et al.,1982). The current results at the middle schoollevel, that the most likely types of ODR lead-ing to disparate African American disciplineare disruption and noncompliance, are consis-tent with a growing body of previous researchin suggesting that the types of referrals inwhich disproportionality is evident are mostlikely to be in categories that are more inter-active and subjectively interpreted, such asdefiance (Gregory & Weinstein, 2008) anddisrespect (Skiba et al., 2002).
One important premise of the presentresearch is that effective disciplinary systemsare more likely to have at their core a gradu-ated model, in which more serious conse-quences are reserved for more serious infrac-tions. Although zero tolerance disciplinaryphilosophy and practice has focused on “send-ing a message” to potentially disruptive stu-dents by applying relatively harsh punish-ments for both minor and more serious infrac-tions (Skiba & Rausch, 2006), reviews of theevidence regarding school discipline havefound little evidence supporting the effective-ness of such an approach (American Psycho-logical Association, 2008). Rather, a gradu-ated discipline model whereby the severity ofconsequences are scaled in proportion to theseriousness of the infraction, often in conjunc-tion with a tiered model of discipline (Sugai,2007), appears to hold far more promise as aneffective and efficient method for organizingschool disciplinary policy and practice.
Prior to disaggregation of the data(Model 1 in Table 4), the current data seem toshow some evidence of such a pattern of grad-uated discipline. That is, the odds for all stu-dents in this sample of receiving a suspensionor expulsion for minor misbehavior are ex-tremely low at both the elementary and middleschool levels, and gradually increase such thatit becomes highly likely that use and posses-sion of weapons or drugs will result in a sus-pension or expulsion. Although given the ab-sence of information on the extent of imple-mentation of SWPBS for this sample it is
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impossible to know whether SWPBS imple-mentation was related to that finding, thesedata do suggest that many of the school disci-plinary systems in the current sample are ingeneral organized in a way that could be ex-pected to be efficient and effective.
In the logistic regressions regarding stu-dent infraction, consequence, and race/ethnic-ity (Table 4), both the various types of infrac-tions and the racial/ethnic categories enter theequation significantly at both the elementaryand middle school level. The failure of race tosignificantly affect the pattern of ORs for in-fractions means that the nature of the recordedinfraction is an important contributor to theseverity of consequences received, regardlessof student race or ethnicity. At the same time,the significance of race in predicting suspen-sion and expulsion even after the inclusion ofinfraction means that, regardless of the type ofinfraction, race/ethnicity makes a significantcontribution to the type of consequence cho-sen for a given infraction.
The pattern of differential treatment iseven more clearly articulated by the pattern ofadministrative decisions for various infrac-tions (Table 5). At the elementary schoollevel, African American students were morelikely than White students to be suspended orexpelled for any offense, and Latino studentsmore likely to be suspended for all offensesexcept disruption. In particular, African Amer-ican students have almost four times the odds,and Hispanic students twice the odds, of beingsuspended or expelled for a minor infraction atthe elementary school level. Although the pat-tern of overrepresentation in out-of-schoolsuspension/expulsion is somewhat less pro-nounced at the middle school level, there isstill substantial evidence of differential treat-ment. African American students were signif-icantly more likely than White students to besuspended or expelled for disruption, moder-ate infractions, and tardy/truancy, while La-tino students were more likely to be suspendedor expelled in Grade 6–9 schools for all in-fractions except use/possession. In addition,underrepresentation in the use of minor ormoderate consequences appears to be morepronounced at the middle school level, espe-
cially for African American students. Al-though specific patterns differ by race/ethnic-ity and school level, these findings are againconsistent with previous investigations (e.g.,McFadden et al., 1992; Shaw & Braden, 1990)that have found evidence of differential pro-cessing (Gregory et al., 2010) at the adminis-trative level.
In summary, these results suggest thatboth differential selection at the classroomlevel and differential processing at the admin-istrative level make significant contributionsto the disproportionate representation of Afri-can American and Latino students in schooldiscipline. For African American students,disproportionality at both the elementary andmiddle school levels begins at referral, mostparticularly in the areas of tardiness/truancy,noncompliance, and general disruption; forLatino students, disparities in initial ODRsemerge at the middle school level. Yet regard-less of previous disproportionality at referral,the type of infraction, or the school level, thefindings from this study indicate that studentsof different races and ethnicities are treateddifferently at the administrative level, withstudents of color being more likely to receivemore serious consequences for the same in-fraction. An investigation of extant data, thisstudy was able to identify the existence ofdisproportionate outcomes at the classroomand administrative level, but without local ob-servation, was unable to specify the classroomor school variables that create such imbal-ances. Further research, in particular ethno-graphic or observational studies that can iso-late specific teacher–student or administrator–student interactions, are essential forincreasing understanding of the variables con-tributing to racial and ethnic disparities inschool discipline.
The focus of this article was not onintervention per se, but these results may holdimportant implications for monitoring the ef-fects of interventions intended to address dis-ciplinary disproportionality. Although the ef-ficacy of SWPBS in reducing rates of ODRshas been well demonstrated (Barrett, Brad-shaw, & Lewis-Palmer, 2008; Bradshaw,Koth, Thornton, & Leaf, 2009; Bradshaw,
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Mitchel, & Leaf, 2009 Horner et al., 2009;Nelson, Martella, & Marchand-Martella,2002; Safran & Oswald, 2003 Taylor-Green &Kartub, 2000), few investigations (Jones et al.,2006) have explored the issue of PBS andcultural variation, or sought to explore howthe application of such school-wide systemswill affect rates of disciplinary disproportion-ality. Kauffman, Conroy, Gardner, and Os-wald (2008) have argued that there is no evi-dence that behavioral interventions operatedifferently based on ethnicity, gender, or reli-gion, but also noted that differential effectsbased on race and ethnicity have been under-studied in the behavioral literature, and that“many studies in leading behavioral jour-nals. . . do not report sufficient detail about thecultural identities of participants” (p. 255).Until such time as a sufficient database hasbeen accumulated on interventions for reduc-ing disproportionate representation in schooldiscipline outcomes, it seems logical that im-plementations of interventions designed to af-fect student behavior in school should disag-gregate their results, in order to empiricallyexplore the extent to which those interventionswork equally well for all groups.
The current data demonstrate a markeddiscrepancy between the aggregated data, inwhich the severity of infraction and conse-quence are relatively well matched, and thedisaggregated data, showing that AfricanAmerican and Latino students receive moresevere punishment for the category “minormisbehavior.” Such a pattern of results isconsistent with emerging research on cultur-ally responsive pedagogy and classroommanagement (e.g., Harris-Murri, King, &Rostenberg, 2006; Serpell, Hayling, Steven-son, & Kern, 2009; Utley, Kozleski, Smith,& Draper, 2002) in suggesting that it cannotbe assumed that interventions intended toimprove behavior will be effective to thesame degree for all groups. Existing racialand ethnic differences in the use of currentdisciplinary interventions strongly indicatethat, for any intervention strategy aimed atreducing such disparities, disciplinary out-come data should be disaggregated, in orderto explicitly evaluate whether SWPBS, or
indeed any general intervention, is equallyeffective for all racial/ethnic groups.
Limitations
The present investigation was not ableto explicitly test the influence of SES on thetested relationships. Despite widespread be-liefs to the contrary, there is no previous evi-dence that the overrepresentation of AfricanAmerican or Latino students in school disci-plinary outcomes can be fully explained byindividual or community economic disadvan-tage (Skiba et al., 2002; Wallace et al., 2008;Wu et al., 1982). Further investigation isneeded, however, to parse the relative contri-bution of individual, classroom, and schoolcharacteristics to disciplinary disproportional-ity, including both SES and the complex ef-fects of gender (see e.g., Wallace et al., 2008).In addition, although we were able to explorevariations for different educational levels orracial/ethnic categories to arrive at a morecomplex rendering of disciplinary dispropor-tionality, we were not able to analyze the databy geographic location or school locale. Itseems highly likely that the variables contrib-uting to racial and ethnic disparities will varyconsiderably by location and locale, especiallyfor groups such as Hispanic students that haveshown inconsistency in previous research. Itmay well be that the specific causes of racialdisparities are regionally unique, requiring lo-cal analysis of causes and conditions (Skiba etal., 2008), in much the same way that func-tional behavior analysis is used at the individ-ual level in order to develop individualizedbehavior plans tailored to the needs of eachchild in each situation.
Finally, using school as the unit of anal-ysis restricted our ability to investigate thecontribution of prior infractions, a variablethat might well be expected to have a signifi-cant effect on administrative decisions regard-ing disciplinary consequences. It is importantto note, however, that there is no previousresearch we are aware of that explores theassociation of students’ prior record of schoolinfraction with racial and ethnic disproportion-ality in school discipline. There is an excep-
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tionally long history in this nation of acceptinga stereotype of African Americans, especiallyAfrican American males, as being more proneto disordered behavior or criminality (see e.g.,Muhammed, 2010), often with little or no sup-porting evidence. With no evidence that sup-ports the notion that there are concurrentlyhigher levels of disruption among AfricanAmerican students, we see no reason to pre-sume that disparate rates of discipline betweenracial and ethnic groups can be explained bydifferential behavioral histories.
Summary and Recommendations
The fact of racial/ethnic disproportion-ality in school discipline has been widely and,we would argue, conclusively demonstrated.Across urban and suburban schools, quantita-tive and qualitative studies, national and localdata, African American and to some extentLatino students have been found to be subjectto a higher rate of disciplinary removal fromschool. These differences do not appear to beexplainable solely by the economic status ofthose students, nor through a higher rate ofdisruption for students of color.
Opportunity to remain engaged in aca-demic instruction is arguably the single mostimportant predictor of academic success. Inthe absence of an evidence-based rationalethat could explain widespread disparities indisciplinary treatment, it must be concludedthat the ubiquitous differential removal fromthe opportunity to learn for African Americanand Latino students represents a violation ofthe civil rights protections that have developedin this country since Brown v. Board of Edu-cation. We propose here that the existing em-pirical evidence for disproportional school dis-cipline by race, and the severe effect of exclu-sionary discipline on educational success,make disproportional application of exclusion-ary discipline an issue in need of immediateand substantive response. At the school level,(a) data on discipline by race should be re-ported regularly (monthly) to faculty, (b) pol-icies focused on prevention and culturally re-sponsive practice should be encouraged, and(c) investment in developing appropriate so-
cial behaviors should be made before resortingto exclusionary consequences. At the districtand state level, (a) disaggregated data on dis-cipline patterns should be available and dis-seminated, (b) policies addressing disciplinaryinequity and promoting equity should be es-tablished, and (c) personnel development op-tions should be made available to minimizethe disproportionate application of discipline.At the federal level, (a) research funding isneeded to move beyond mere description ofdisproportionality to clear documentation ofcausal mechanisms and functional interven-tions for reducing disparate outcomes; (b) re-sources are needed to document the technicalassistance and implementation strategies thatwill allow state- and district-wide responses todisproportionate use of discipline; and (c) as iscurrently the case for disproportionality inspecial education, federal monitoring practicesshould regularly require disaggregated report-ing of discipline patterns, and mandate thedevelopment and implementation of correctiveaction plans where disparities are found.
Racial and ethnic disparities that leavestudents of color behind remain ubiquitous inAmerican education. The national reportBreaking Barriers (Caldwell, Sewell, Parks, &Toldson, 2009; Toldson, 2008) found thatwhile personal, family, and community factorsall make a contribution to such disparities, sodo school and teacher characteristics, such asstudent perceptions of being respected andsupported by teachers, and perceptions ofschool safety. To the extent that the policiesand practices of schools maintain or widenracial gaps, it is imperative that policy makersand educators search for school-based solu-tions that can contribute to reducing racial andethnic disparities in important educationaloutcomes.
All children deserve access to effectiveeducational settings that are predictable, pos-itive, consistent, safe, and equitable. Access toeducational achievement requires the supportneeded to be socially successful in school.This typically involves not simply ensuringthat problem behavior is addressed equitably,but investing in building school cultures whereappropriate behavior is clearly defined, ac-
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tively taught, and consistently acknowledged.For race to become a socially neutral factor ineducation, all levels of our educational systemmust be willing to make a significant invest-ment devoted explicitly to altering currentlyinequitable discipline patterns, to ensure thatour instructional and disciplinary systems af-ford all children an equal opportunity forschool learning.
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Date Received: September 23, 2009Date Accepted: January 6, 2011
Action Editor: George Bear �
Russell J. Skiba is Professor in the School Psychology Program and Director of the EquityProject at Indiana University. His current research focus includes racial and ethnicdisproportionality in school discipline and special education, and developing effectiveschool-based systems for school discipline and school violence.
Robert H. Horner is Almuni-Knight Endowed professor of Special Education at theUniversity of Oregon. His research focuses on severe disabilities, instructional design,positive behavior support, and implementation science.
Choong-Geun Chung is Statistician at the Center for Evaluation and Education Policy atIndiana University in Bloomington. His research interests are analytical issues in racialand ethnic disproportionality in special education and in school discipline, and statisticalmodels for access and persistence in higher education.
M. Karega Rausch currently serves as the Director of the Office of Education Innovationfor Indianapolis Mayor Greg Ballard. He is currently completing his doctorate in schoolpsychology at Indiana University-Bloomington. Rausch’s research interests include eq-uity in school discipline and special education.
Seth L. May is a research assistant and software developer at Educational and CommunitySupports in the University of Oregon’s College of Education. His efforts currently focuson developing research databases and large software systems for managing, collecting,and reporting on student behavior.
Tary J. Tobin is a Research Associate and an Adjunct Assistant Professor of SpecialEducation at the University of Oregon. Her current research interests include staffdevelopment, cultural and linguistic diversity, and use of prevention science and tech-nology in school and community interventions.
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