The Discipline Gap: What’s Trust Got to Do With It?
by Lisa S. Romero - 2018
Background/Context: If we are serious about eliminating the racial achievement gap, we need to address the discipline gap as well. The scholarly literature generally paints a positive picture of the potential of trust to transform schools. Research on student trust has shown that students who trust their teachers and schools are suspended and expelled less frequently and have more positive academic outcomes. However, we know little about if or how the impact of trust may vary by race or gender.
Research Question: Do the benefits of trusting relationships accrue equally to all students? Do trusting student–teacher relationships pay off in less discipline and improved academic outcomes for all students, or do the benefits of trust depend on the race and gender of the student?
Research Design: Structural equation modeling was used to model the relationships between student trust, behavior, and high school outcomes, controlling for socioeconomic status, school size, and prior achievement. Data, drawn from the Educational Longitudinal Survey of 2002, includes responses from more than 6,000 public high school students (n = 6,352) who identify as African American or White. Comparisons are made between results for White, African American, and African American male students.
Findings/Results: Student trust is associated with fewer disciplinary incidents and better academic outcomes; however, the benefits of trust do not accrue equally to all students. Black students, particularly males, benefit less from trust. Controlling for trust, behavior, and standardized measures of math and reading ability, Black students are penalized multiple times for a single disciplinary incident: by the suspension (or other consequence), by missed instruction, and by the impact on their grades (and possibly their future course placement and postsecondary plans). In other words, there are unequal consequences of equal discipline.
Conclusions/Recommendations: This research found that Black and White students with roughly equivalent discipline records, scores on achievement tests, and levels of trust still have substantially different high school outcomes. Although efforts to implement restorative justice or positive behavior support programs are a step in the right direction, results suggest that they will not be enough. Schools must deal with implicit bias and the unequal consequences of equal discipline. To do this, we must scrutinize course placement practices, grading, and the messages that we send to students. Failure to do so will continue to leave us with a vast education debt and will continue to fuel the achievement gap.
Education is often called the civil rights issue of our time. And although this call typically is made in relation to the achievement gap, increasingly, attention is being called to another important, but too long ignored, problem: the discipline gap. African American students, both boys and girls, are suspended and expelled from schools and classrooms in far greater numbers and for more minor and subjective offenses than White students of the same gender (Fenning & Rose, 2007; Hoffman, 2014; Losen, Hewitt, & Toldson, 2014; Skiba, Michael, Nardo, & Peterson, 2002). Disciplinary sanctions that remove students from the classroom do more than just punish a student for poor behavior; they simultaneously deny students access to instruction and aggravate discrepancies, propelling Gregory, Skiba, and Noguera (2010) to call the achievement gap and the discipline gap two sides of the same coin (p. 59).
If we are serious about eliminating the achievement gap, we need to address the discipline gap as well (Gregory et al., 2010; Losen et al., 2014). The racial discipline gap is caused by a myriad of factors ranging from broad societal problems, such as institutionalized racism, to neighborhood and family issues of gangs and unemployment, to the quality of studentteacher interactions in the classroom. The focus of this inquiry is on the discipline gap as it is played out at the micro-levelin relationships and interactions between teachers and students. Why focus on the classroom level when there are clearly numerous macro-level factors at work? Classrooms are the core of public education (Mitchell & Romero, 2015). Students spend most of their day with teachers, and the majority of disciplinary referrals are initiated by teachers, pointing to the classroom and teacherstudent relationships as a leverage point for change (Gregory & Weinstein, 2008; Milner & Tenore, 2010; Skiba et al., 2002; Way, 2011).
Classroom climate, behavioral norms, and quality of relationships that exist between teachers and students are co-constructed through daily interactions in the classroom (Gregory & Weinstein, 2008; Hand, 2010; Way, 2011). Student behavior varies across classrooms and contexts, as do teacher styles of instruction, rules, and expectations. A student who is disruptive or defiant in one class may not act or be seen as a problem in another class with a different teacher (Gregory & Thompson, 2010). The same behavior (moving around the classroom or challenging the teacher) might be encouraged, acceptable, or ignored by one teacher but be a problem for a different teacher with different set of behavioral expectations. These factors conspire to produce, or reduce, studentteacher trust and quality relationships in the classroom, making classrooms an arena for the production of student opposition and resistance (Way, 2011, p. 350).
Quality trusting relationships do more than just make the time spent in a classroom pleasant (Ream, Lewis, Echeverria, & Page, 2014). Students who trust their teachers and schools are suspended and expelled less frequently and are more likely to view the teacher as a valid authority (Gregory & Ripski, 2008; Gregory & Weinstein, 2008; Kitzmiller, 2013; Way, 2011). They are more likely to identify with and be engaged with school, to be more motivated to achieve, and to have more positive academic outcomes (Forsyth, Adams, & Hoy, 2011; Romero, 2015; Tschannen-Moran, Bankole, Mitchell, & Moore, 2013; Van Maele, Forsyth, & Van Houtte, 2014). Though less tangible than books, buildings, or curriculum, trust is a valuable educational resourceand, though important for all students, it may be even more essential for African American students, especially males (Cohen & Steele, 2002; Gregory & Ripski, 2008; Gregory & Weinstein, 2008; McClain & Cokley, 2017; Murray & Zvoch, 2011; Yeager et al., 2014).
The scholarly literature generally paints a positive picture of the potential of trust to transform schools, but we know little about how the impact of trust may vary by race or gender. Some studies have looked at all students (Adams, 2014; Adams & Forsyth, 2009; Romero, 2015; Tschannen-Moran et al., 2013), whereas others focused on a single racial or ethnic group (Gregory & Ripski, 2008; Gregory & Weinstein, 2008; Ream et al., 2014). However, few studies in the field of education have explicitly compared how trust differs by race (Yeager et al., 2014; Yeager, Purdie-Vaughns, Hooper, & Cohen, 2017). This stands in marked contrast to other fields, where there have been numerous considerations of the interaction between race and trust (see for example, Glaeser, Laibson, Scheinkman, & Soutter, 2000; Shoff & Yang, 2012; Smith, 2010). Yet, there is ample reason to suspect that trust may not function in the same way for all students. Trust is a social phenomenon and, as such, is not immune to social problems such as unconscious or implicit bias. Therefore, we ask, do the benefits of trusting relationships accrue equally to all students? More specifically, do trusting studentteacher relationships pay off in less discipline and improved academic outcomes for all students, or do the benefits of trust depend on the race and gender of the student?
The goal of this inquiry is to begin to answer this question. To do so, we model the effect of student trust on behavior and academic outcomes, and compare the results for White students, African American students, and African American males. We focus on African American students, particularly males, because both the discipline gap and the achievement gap are consistently the greatest for Black males, and examinations of these gaps commonly use White students as the comparison group (see for example, Desimone & Long, 2010; Dixon-Román, Everson, & McArdle, 2013; Gosa & Alexander, 2007; Minor, 2014). This is not to suggest that the experiences of others, such as Latino, Asian, special education, gay and lesbian, or other students do not merit consideration, but that a BlackWhite comparison is an appropriate, and manageable, starting point. Before answering these questions, we begin by documenting the extent of the racial discipline gap and its relationship to achievement, and we briefly consider the role that implicit bias may play. After presenting the results of our analysis, we turn to theory and research on student trust. We end with a consideration of the implications of our findings for leadership and classroom practice.
DISPARATE IMPACT, DISCIPLINE AND ACHIEVEMENT
Exclusionary school disciplinary practices, including expulsions, suspensions, and in-school suspensions, have dramatically increased over the last few decades, especially since passage of the federal Gun-Free School Act of 1994 and wide embracement of zero-tolerance policies (Hoffman, 2014; Way, 2011). Zero tolerance policies are based on the premise that strong, unambiguous consequences will disincentivize poor behavior and serve as a deterrent (Way, 2011). However, there is little evidence that more severe punishment is effective (Hoffman, 2014; Skiba & Knesting, 2001). Racial disparities in suspension and expulsions are not new, but have grown dramatically since the mid-1990s policy shift.1
That school disciplinary policies disparately impact African American students, particularly males, has been well documented (Hoffman, 2014; Losen et al., 2014; Monroe, 2005; Skiba, Arredondo, & Rausch, 2014; Skiba et al., 2002). Black male students are suspended and expelled from schools at far greater rates and for more minor offenses than their White and Asian counterparts (Losen & Gillespie, 2012; Losen et al., 2014; Skiba et al., 2002; Wildhagen, 2012). According to a report by the Discipline Disparities Collaborative, Black high school and middle school students nationwide are suspended 17% more often than White students, and although Black students make up 16%18% of students, 39% of students expelled are African American. Incredibly, 70% of African American males have been excluded from school one or more times because of suspension or expulsion by the 12th grade (Losen et al., 2014). This problem is compounded by the fact that school infractions, in the past handled privately with families, now involve police, citations, arrest, and juvenile courts (Mitchell & Romero, 2015). Rather than serving as an effective behavioral intervention or deterrent, many scholars assert instead that this may place students on a path from school to the juvenile justice system and future incarceration, known as the school-to-prison pipeline (Kim, Losen, & Hewitt, 2010; Skiba, Arredondo, & Williams, 2014).
Examining the relationship between school discipline, race, socioeconomic status, and severity of behavior makes clear the racial nature of the problem. Although socioeconomic status is a predictor of school discipline and behavioral incidents for all students, even after controlling for socioeconomic status, African Americans still are suspended (and referred to the office) at higher rates (Skiba et al., 2002)and controlling for the severity of behavior does not eliminate the racial disproportionality (Skiba et al., 2011). To the contrary, data clearly demonstrate a de facto pattern in which African American students, most particularly males, are subject to more frequent and more severe disciplinary consequences for real or perceived transgressions, including subjective offenses such as disrespect, excessive noise, threat, and loitering (Skiba et al., 2002, p. 334). In other words, the disparity is not a reflection of either differential behavior or socioeconomic status.
Although there are now numerous studies that document the discipline gap, directly connecting discipline and achievement is more difficult. There is correlational evidence that students who are referred to the office, suspended, or expelled are more likely to perform poorly on achievement tests, to have lower grade point averages (GPAs), and to exhibit less growth in core academic competencies such as reading and math, and more likely to drop out of school (Arcia, 2006; Balfanz, Byrnes, & Fox, 2015; Losen & Martinez, 2013; Rumberger & Losen, 2016). However, more research is needed that directly examines this relationship (Arcia, 2006; Gregory et al., 2010). Nevertheless, we do know that instructional time and opportunity to learn are highly correlated with academic success, and that attendance is associated with higher test scores (Balfanz & Byrnes, 2006; Gottfried, 2010; Roby, 2004). Missed instruction due to referrals to the office, suspensions or expulsion, compound the problem (Gregory et al., 2010). Being suspended, even once, can have serious consequences for students, and doubles the probability that a student will drop out of high school (Balfanz et al., 2015).
In addition to missed instruction, excessively punitive practices are negatively associated with other factors important to learning. Students who are suspended and expelled have lower academic self-efficacy, are less engaged, and identify less with school (Skiba & Knesting, 2001; Toldson, McGee, & Lemmons, 2014). Furthermore, discipline policies and practices that overdepend on suspensions and expulsions may actually cause an increase in oppositional behavior (Gregory, Cornell, & Fan, 2011; Morris, 2005; Way, 2011). That is, rather than extinguishing undesirable behavior, discipline that students perceive as unfair or excessively punitive could increase defiant behavior (Kennedy-Lewis & Murphy, 2016; Way, 2011).
In short, we know that African American males are suspended, expelled, and face other disciplinary sanctions more often and for lesser offenses than any other demographic group and that these practices make success in school less likely. We also know that the racial discipline gap cannot be explained by either differential behavior or socioeconomic status.
What, then, is driving the discipline disparities? Many scholars point to implicit bias as at least partially contributing to the problem (Black, Garda, Taylor, & Waldman, 2013; Carter, Skiba, Arredondo, & Pollock, 2017; Fenning & Rose, 2007; Losen & Martinez, 2013; Nance, 2016; Okonofua & Eberhardt, 2015; Wald, 2014). Implicit bias is a subtle form of prejudice that acts below the level of conscious thought (Carter, et al., 2017; Nance, 2016). Even well-meaning people, who would not consciously condone racism, nonetheless have tacit beliefs, preferences, prejudices, and internalized stereotypes that unconsciously shape and inform their decision making and actions (Carter et al., 2017; Nance, 2016).
In schools, implicit bias may function via teacher, counselor, or administrator expectations. These may be expectations that appropriate behavior or discourse align with White, middle-class cultural norms. It can also take the form of lower expectations about student motivation or ability, sense of responsibility for student learning, or heightened perceptions of misbehavior triggered by stereotypes of Black males as dangerous (Carter et al., 2017; Diamond, Randolph, & Spillane, 2004; Downey & Pribesh, 2004; Milner, 2013; Monroe, 2005; Weinstein, Curran, & Tomlinson-Clarke, 2003). Much of what is known about implicit bias comes from experimental studies that are not focused on school discipline2 but that consistently show a small, negative bias toward Black subjects (Faulkner, Stiff, Marshall, Nietfeld, & Crossland, 2014; Losen & Martinez, 2013; Tenenbaum & Ruck, 2007). Though these effect sizes may be small, their cumulative effect is enough to account for the racial disparities observed in our school systems (Wald, 2014).
STUDENT TRUST AS AN EDUCATIONAL RESOURCE
TRUST, BEHAVIOR, AND LEGITIMATE AUTHORITY
Understanding how trust can function as an educational resource capable of impacting behavior and learning may be best understood by viewing effective teachers as authentic authorities and learning as sociocognitive. Classroom management, or the ability to control student behavior, is the most common problemand one of the most frustratingencountered by K12 teachers (Emmer, Sabornie, Evertson, & Weinstein, 2013; Milner & Tenore, 2010). How teachers respond to this challenge can make a difference in whether they leave teaching or stay in the profession; whether they are able to create an environment focused on learning, or a classroom mired in problems of behavior and control; whether and what students learn; and the quality of the learning experience. Teachers have formal power over students by virtue of their position. When faced with problems of managing the classroom, they may rely on their formal power to control (or coerce) student behavior using rewards or punishments such as disciplinary sanctions or grades. Positional power may be used to incentivize (or diminish) some behavior, but the power to punish or reward is not enough to control a classroom (Kitzmiller, 2013); if it were, far fewer teachers would struggle with classroom management.
Positional power does not automatically make teachers authentic or legitimate authorities in the eyes of students, and authentic authority cannot be established without trust (Kitzmiller, 2013; Mitchell & Spady, 1983). When students trust teachers and see them as authentic authorities, they are more likely to feel that teacher directions are legitimate, to willingly follow instructions, and to embrace the goals of the teacher (Gregory & Ripski, 2008; Kitzmiller, 2013; Mitchell & Spady, 1983; Smetana & Bitz, 1996). When teachers have earned student trust, the need for strategies to promote compliance is diminished, and discipline issues may be prevented (Gregory & Ripski, 2008) and conflict reduced (Gregory, Bell, & Pollack 2014; Kitzmiller, 2013).
Because learning is a sociocognitive process, trust also aids in learning. Learning is not solely a matter of individual ability and effort; learning in classrooms is inherently a social activity and dependent on context (Bandura, 2001; Davis, 2003; Goodenow, 1992; Zimmerman, 1989). In an environment of trust, students are more likely to risk being vulnerable by asking questions needed to clarify learning and to engage in help-seeking behavior key to achievement.
Authentic leadership and sociocognitive theory recognize the importance of relationships based on trust. Both make clear that classrooms have a social, relationship-based component. Taken together, they suggest that trust can act as an educational resource capable of leveraging or influencing student behavior and learning. This is not to suggest that trust alone is enough or is capable of overwhelming prior achievementbut it can have a meaningful effect on student performance.
RESEARCH ON STUDENT TRUST
Seminal work led by Hoy (see, for example, Hoy & Kupersmith, 1985; Tschannen-Moran & Hoy, 1998) and Bryk and Schneider (2002) ignited interest in the importance of trust in high-functioning schools. These and ensuing studies documented the importance of trust between teachers, principals, parents, and other key players in educational settings (Beard & Brown, 2008; Forsyth et al., 2011; Goddard, 2003; Goddard, Salloum, & Berebitsky, 2009; Louis, 2007; Louis & Murphy, 2017; Mitchell, Forsyth, & Robinson, 2008; Moye, Henkin, & Egley, 2005; Murray & Zvoch, 2011; Tschannen-Moran, 2004; Van Maele et al., 2014; Walker, Kutsyuruba, & Noonan, 2011). However, interest in student trust, and high school students in particular, has been more recent (Schneider, Judy, Ebmeyer, & Broda, 2014), and only a handful of publications, including Gregory et al. (2008), Adams and Forsyth (2009), Yeager et al. (2014, 2017), and Romero (2015), have secondary students as their primary focus. Owens and Johnson (2009) and Görlich and Katznelson (2015) also provided insight into the role of trust for marginalized students who are recent high school graduates or young adults. Because few studies exist in this developing area, these articles are considered in some detail.
Several studies led by Gregory highlighted the close connection between trust, student behavior, and discipline (Gregory & Ripski, 2008; Gregory & Weinstein, 2008). Gregory and Ripski (2008) conceptualized trust, as it pertains to discipline, as made up of student beliefs about teachers fair use of power and their beliefs about respecting and following teacher requests. To measure student trust, they adapted items from Tyler and Dogoeys (1995) study of trust in government authority. Here students were asked questions such as whether the teachers rules worked well for everyone, if students could trust the way the teachers used their power and authority, and whether it was important that they obeyed the teacher. Thirty-two students (n = 32), the majority (n = 29) of whom were Black, participated in the study. The students, in Grades 9, 10, and 11, had all been suspended for defiance. Results showed that student trust in teacher authority had a positive impact on student behavior. Teachers who worked to establish relationships, engendering trust with students, were less likely to encounter student defiance.
In another study, Gregory and Weinstein (2008) focused on a small number of African American students who were assigned in-school suspension for defiance. The high school students, both males (n = 17) and females (n = 15), were in Grades 912. Most of the students had received disciplinary referrals from a small group of teachers. Interviews with students revealed that they did not see the referring teachers as trustworthy or as having legitimate authority. Results also showed a positive relationship between student trust, perceptions of teacher caring, and academic expectations. In short, students were more likely to trust teachers they viewed as caring and more likely to cooperate with teachers they trusted.
Whereas these studies by Gregory and others tended to have small sample sizes and focus on African Americans, other research on student trust employed larger samples that did not consider student race and that conceptualized trust somewhat differently. In 2008, Adams and Forsyth developed the Student Trust Scale (STS), which adopted Tschannen-Moran and Hoys (1998) definition of trust as the perception of benevolence, competence, reliability, honesty, and openness (Adams & Forsyth, 2009; Tschannen-Moran & Hoy, 1998). Surveys of 450 students in Grades 7, 8, and 9 were used to pilot the instrument. To assess their level of trust, students were asked a variety of questions, including, for example, whether teachers had high expectations for students and were good at teaching. Using this measure, Adams (2014) later demonstrated that collective student trust, or a school culture of student trust, acted as a social resource for urban elementary school students. In schools with trusting student cultures, students were more likely to identify with schools, were better at self-regulated learning, and scored better on state-mandated exams in reading and mathematics.
A study by Romero (2015) looked at the role of student trust using data from close to 15,000 high school students who participated in the Educational Longitudinal Study (ELS 2000). Drawing from Mayer, Davis, and Schoorman (1995), this study conceptualized trust as having three components: benevolence, competence, and integrity. Results documented a link between trust, discipline, and high school outcomes, finding that students with higher levels of trust in their teachers received fewer disciplinary referrals and had better academic outcomes in high school. However, as noted previously, neither the study by Adams (2014) nor the study by Romero (2015) differentiated the results by race or ethnicity.
Two studies by Yeager et al. (2014, 2017), both focusing on middle school students, did examine differences in trust by race. The first, an experimental study involving 44 seventh-grade students in a suburban middle-class school, examined the role that trust played in student receptivity to critical feedback by teachers. The authors found that deliberate feedback, designed to convey high expectations and mitigate distrust, was particularly important for African American students low in trust. In a more recent study, Yeager et al. (2017) used longitudinal data that tracked and compared White and African American students from sixth grade until college. They found that the Black students were less trusting of their schools than the White students and provided evidence that this trust gap could be attributed to student perceptions of racial bias in discipline. They also found that this lack of trust impacted both future student behavior and likelihood of college attendance.
In summary, there is a small but growing body of research on student trust. Although researchers have adopted different conceptualizations and measures of trust,3 taken together, these studies suggest that student trust is a social resource that plays a role in student behavior, schooling experiences, and outcomes. However, few studies have focused on high school students, or have explored whether trust is important for all students on an equal basis or if it differs by race and/or gender.
This study defines trust as the willingness to be vulnerable to another person, group, or organization based on the perception that the trusted party is benevolent, is competent, and behaves with integrity (Mayer et al., 1995; Mishra, 1996; Tschannen-Moran & Hoy, 2000). Benevolence may be perceived when a trustor acts kind and fostering and appears to have the trustees best interest in mind (Schoorman, Mayer, & Davis, 2007; Tschannen-Moran, 2004). When considered in a school setting, the trustee, or student, may infer that teachers are benevolent if they get along with students, do not put them down in class, demonstrate interest in them, and praise their efforts (Romero, 2015).
Competence may be perceived when a trustor is believed to have needed expertise, skills, or knowledge (Schoorman et al., 2007; Tschannen-Moran, 2004). Within schools, teachers may be perceived by students as competent when they set high expectations, expect their students to succeed, and make their classrooms and learning interesting and challenging (Adams & Forsyth, 2009; Ferguson, 2010; Romero, 2015).
Finally, integrity has to do with fairness, reliability, and adherence to acceptable principles (Mayer et al., 1995). In school settings, students often perceive teachers to have integrity when they exhibit fairness (Adams & Forsyth, 2009). When asked about the components of integrity, students may consider whether rules are fair, apply to everyone, and are consistently enforced (Romero, 2015).
We build on existing knowledge by examining if and how the impact of trust differs by race and gender, specifically comparing White, African American, and African American male students. The path diagram in Figure 1 displays the relationships of interest and is consistent with earlier research on student trust (Romero, 2015). Latent variables signifying trust, behavior, 10th-grade achievement, and high school outcomes are designated by ovals. School size and student socioeconomic status are manifest variables, represented by rectangles.
Viewing the diagram from left to right, school size and socioeconomic status (SES) control for the well-known effect of SES on achievement (Coleman, 1968; Reardon, 2011; Timar & Maxwell-Jolly, 2012) and for possible effects of SES and school size on trust (Lee & Ready, 2007; Meier, 2002). The literature asserts that there is a positive relationship between trust, behavior, and academic success. This is represented by the arrows from trust to behavior, from trust to 10th-grade achievement, and from trust to high school outcomes. The impact of behavior on achievement and schooling outcomes is shown by the arrows pointing from behavior to these constructs. The arrow from 10th-grade achievement to high school outcomes indicates the close connection between knowledge in 10th grade and high school outcomes two years later, and serves as a control. The model provides a visual representation of the relationships posited and also describes the structural equation model that will be used.
Figure 1. Structural model
Data are drawn from the Educational Longitudinal Study of 2002 (ELS). ELS is a nationally representative, longitudinal sample of approximately 15,000 students attending 750 public, private, and Catholic schools in the United States. Students were surveyed in three waves: in 2002, when students were in 10th grade; in 2004, when most students were seniors; and in 2006, two years postsecondary. This study examines a subsample (n = 6,352) of the ELS data, which includes public school students who identify as African American (n = 1,318) or White (n = 5,034). The sample included students who were members of the 10th-grade cohort in 2002 and completed surveys in either all three waves (2002, 2004, and 2006) or two of three waves (2002 and 2006), and responded to at least one of the items used to measure trust (detailed next). Responses were panel weighted to enable projection to the population of 10th-grade students in the spring of 2002 (Ingels et al., 2007). The weighted sample represents 1,923,267 African American and White public school students.
Student trust. Student trust was measured using 10 items from the ELS 10th-grade survey. Responses were based on 4-point Likert scales, ranging from strongly agree to strongly disagree. Sample items included teachers are interested in students, teachers praise my efforts, teachers expect me to succeed, and school rules are fair. Consistent with theory, trust was measured as a multifaceted construct involving the perception of benevolence, competence, and integrity (Makiewicz & Mitchell, 2014; Mayer et al., 1995; Romero, 2015; Schoorman et al., 2007). These first-order factors demonstrated internal consistency with Benevolence (α = .73), Competence (α = .61), and Integrity (α = .64). These factors were loaded on Trust, a second-order factor. Descriptive statistics for these and the remaining measures are provided in the appendix.
Behavior. The behavior factor consisted of four items from the 10th-grade survey, which asked the number of times the student got in trouble, received in-school suspension, was suspended or put on probation, or cut class. Responses ranged from 1 (never) to 5 (ten or more times). Cronbachs alpha was calculated to verify that the four items tapped into the same latent construct. The score (α = .69) demonstrated that the items are related.
High school outcomes. Four items were used to broadly gauge high school outcomes, including students’ graduation status, postsecondary plans, GPA, and highest math class taken. Graduation status ranged from 1 (dropout or nongraduate), to 4 (graduated with a regular high school diploma). Postsecondary plans ranged from 1 (does not plan to continue education), to 6 (early graduate already attending a postsecondary institution). Final cumulative GPA was calculated on a traditional 4-point scale, with A = 4.0 and F = 0.0. Highest math class taken in high school had six possible values ranging from 1 (no math) to 6 (calculus).
Controls. Prior achievement was controlled for using standardized scores on tests of math and reading administered in 10th grade. SES status was measured using an ELS composite variable made up of a combination of parents level of education, income, and occupational prestige. School size figures reported in ELS were standardized because of the vast differences in size, with schools ranging from about 50 students to over 4,000 students.
Structural equation modeling (SEM) was used to model the relationships between trust, behavior, achievement, and race and gender.4 SEM is especially well suited for this analysis because of its ability to simultaneously measure multiple latent factors, examine the relationships among these factors, and consider multivariate outcomes. MPlus 7.2 was used to analyze data because of its ability to handle the complex structure of the ELS data.5 Weighted least squares estimation was used because of the presence of categorical variables (Finney & DiStefano, 2006). Missing data were handled using full information maximum likelihood estimation.
Results include data from more than 6,000 high school students in the United States (n = 6,352) who identified as African American (n = 1,318) or White (n = 5,034). A total of 627 (n = 627) responses were from African American males. Consistent with extant research, descriptive statistics provide evidence of race-based differences in achievement and discipline. African Americans scored approximately 13 points lower than White students in math and about 8 points lower in reading on standardized achievement tests administered in 10th grade. As seniors, White students had higher GPAs (M= 2.71) than Black students (M = 2.05) and Black males (M = 1.91). In terms of graduation, 91% of Whites, 83.4% of Blacks, and 81.8% of Black males had graduated from high school with a diploma.
Looking at behavior and discipline, African American males got in trouble, received in-school suspensions, and were suspended from school or placed on probation more frequently than other students. Although large numbers of students had never been in trouble, this too varied by race, with 60.3% of White students, 55.0% of Black students, 46.4% of African American males reporting that they had never been in trouble. Most students also reported that they never, or rarely, skipped class, and this too varied by race, with 89.0% of White students, 85.1% of Black students, and 83.9% of Black males reporting that they had never skipped class or skipped class only once or twice. Variable means and standard deviations can be found in the appendix.
Results also revealed some interesting discrepancies on variables reflective of student trust. African Americans were less likely than White students to report that teachers were interested in students (63.8% of African American males, 67.0% of all African Americans, and 75.0% of Whites); that teachers got along with students (68.0%, 61.6%, and 77.8%, respectively); and that the teaching was good (73.4%, 75.3%, and 81.0%). However, they were more likely to report that their teachers expected success (66.5%, 67.2%, and 58.1%) and that classes were interesting and challenging (62.4%, 63.0%, and 52.3%). There was also a marked difference in perceptions about whether the rules were fair (39.2%, 41.5%, 57.9%); see Table 1.
Table 1. Percentage of Students Who Agree or Strongly Agree
TRUST, BEHAVIOR, AND SUCCESS IN SCHOOL
Next, structural equation modeling was used to model the relationships between student trust, behavior, and high school outcomes, controlling for socioeconomics, school size, and prior achievement. The same model was run with data from Black students and White students, and then with data from Black males only. Fit statistics, including the CFI, TLI, and RMSEA, are provided in Table 2 and demonstrate a good fit. Standardized coefficients for the measurement models are provided in the appendix.
Turning to the structural model, Figure 2 provides the standardized path coefficients between the principal latent constructs. Each path has three coefficients; the squares represent White students, the circles represent Black students, and the triangles represent Black males. The number in parentheses is the standard error of the estimate.
Table 2. Model Fit Statistics
Looking first at the relationship between trust and student behavior, results are consistent with previous research (Gregory et al., 2008; Romero, 2015; Yeager et al., 2017), showing an inverse relationship between student trust and discipline. That is, students with higher levels of trust in their teachers have fewer disciplinary incidents. However, racial differences in the magnitude of the effect are striking. For Whites, the standardized coefficient (r =-.46) is almost twice that of African Americans (r =-.24) or African American males (r = -.25). Standardized results are analogous to regression beta (β) weights, which are interpreted in units of standard deviation; a one-standard-deviation change in the latent variable will result in a standard deviation change the size of the path coefficient on the corresponding variable. In this case, a one-unit increase in trust is associated with almost half (-.46) a standard deviation improvement in behavior and disciplinary incidents for White students, compared with a quarter (-.24) for Black students. In short, results show that although trust is beneficial to all students, White students benefit more.
As expected, behavior is inversely related to both 10th-grade achievement and high school outcomes. Negative behavior, whether it is self-reported incidents of getting in trouble, choosing to ditch class, or being suspended or expelled, leads to demonstratively lower scores on standardized measures of math and reading ability. The magnitude of this is fairly consistent across race and gender (r = -.28 White; -.24 Black; -.27 Black male). Likewise, behavior and discipline have a detrimental effect on outcomes such as GPA, graduation status, and postsecondary plans. However, the impact of poor behavior on high school outcomes differs by race and is magnified for African American students, particularly for males (r = -.24 White; -.39 Black; -.48 Black males). This suggests that when the impact of behavior is assessed against standardized measures of academic proficiency, there is a generally equally negative effect for all students. However, when the impact of behavior is measured against outcomes such as grades or courses students are enrolled in, there is a greater penalty for Black students, and worse, for Black males. As opposed to the standardized tests, these measures allow for greater subjectivity. For example, teacher grades reflect more than just student mastery of content and include more subjective assessments of student behavior, participation, and effort (Bowers, 2011). Likewise, course placement may be influenced by counselor and teacher expectations, including Pygmalion effects and implicit bias (Ansalone, 2009; Faulkner et al., 2014; Rosenthal & Jacobson, 1968; Tenenbaum & Ruck, 2007; Van den Bergh, Denessen, Hornstra, Voeten, & Holland, 2010). This may be consistent with findings by Minor (2104), who documented that the behavior of young Black students has a greater impact on teacher perceptions of student ability than it does for White students.
Figure 2. Structural model with standardized coefficients (standard error)
Looking next at the impact of SES, as would be expected, results show an inverse relationship between SES and behavior, with students from lower socioeconomic households having more behavioral incidents than students from higher SES families, and this difference is fairly consistent across race. The impact of SES on trust is less clear. For White students, SES has a small positive impact on trust. In contrast, for Black students, SES has a small negative impact, suggesting that Black students from low-SES families might be slightly more trusting of their teachers and schools than higher SES families. To be clear, the effect size is very small but may be in line with results from a qualitative study by Beard and Brown (2008), which found that some high-income African American mothers were distrustful of their childrens schools, and this may merit future investigation. Turning next to SES and achievement, as anticipated, we find that students from higher SES families score higher on 10th-grade achievement tests, and this is true regardless of race. However, the impact of SES on achievement is stronger for White students (r = .64) than for Black students (r = .42 for all Black students, r = .41 for Black males).
Not surprisingly, the strongest relationship observed in the model is between 10th-grade achievement and high school outcomes two years later. However, the size of the coefficient varies by race and gender and is higher for White students (r = .85) than for Black students (r = .74) or Black males (r = .65). Stated differently, 72% of the variance (r2 = .72) in high school outcomes is explained by 10th-grade test scores for White students, but this number drops to 55% (r2 = .55) for Black students and to 42% (r2 = .42) for Black males. Math and reading ability in 10th grade is more indicative of outcomes for Whites than Blacks, and even less for Black males, and this is true when controlling for key variables such as behavior and family SES.
This study began by asking about the links between student trust, behavior, and educational outcomes by race, exploring whether the benefits of trusting relationships accrue equally to all studentspaying off in less discipline and improved academic outcomesor if the benefits of trust may depend on the race and gender of the student.
Results show not only that benefits of trust do not accrue equally to all students, but also a clear pattern of differences by race and gender. Although we speculate that implicit bias may be implicated, it is not possible to determine this from the data. However, it is clear that for African American students, especially Black males, trust is less convertible into disciplinary gains. Black students who trust their teachers and schools have fewer disciplinary incidents than their less trusting peers, but they have more disciplinary incidents than White students with similar positive relationships. This remains true after adjusting for SES and other key variables.
As would be expected, disciplinary incidents, such as suspension and expulsion, that exclude students from the classroom and learning opportunities have a negative effect on educational attainment. The magnitude of this effect varies little by race or gender on objective indicators of learning. In other words, students with similar disciplinary histories pay the same academic penalty on standardized tests of math and reading ability, regardless of race or gender. However, the impact of discipline on educational outcomes, which include more subjective measures, shows a clear racial bias, especially for African American males. This includes grades, course placement in mathematics, and postsecondary plans, all key to postsecondary opportunities. This is consistent with other research showing that grades reflect not just subject matter mastery but also perceived student behavior (Bowers, 2011). This implies that Black students are penalized multiple times for a single disciplinary incident: by the suspension (or other consequence), by missed instruction, and by impact on their grades (and possibly their future course placement and postsecondary plans). In other words, there are unequal consequences of equal discipline.
Equally concerning is that what should be a close relationship between 10th-grade measures of cognitive achievement and high school outcomes two years later varies greatly by race and gender. Tenth-grade achievement tests are quite predictive of high school outcomes for White students, but they are less predictive for Black students, and even less so for Black males. For White students, these scores explain 70% of the variance in high school outcomes, but for Black males, this drops to 42%. This is true when controlling for SES, disciplinary histories, and tests of math and reading acquisition.
What does this mean? It suggests that the discipline gap and the achievement gap are reverse sides of the same coin, but the coin is weighted differently for African American students, and most especially for African American males. As numerous studies have clearly documented, Black males are more likely to be disciplined, suspended, and expelledbut thats not the end of the story. Not only are Black males more likely to be singled out for discipline, but the effect on ultimate schooling outcomes is also more severe. That is, the bias seen in school discipline ripples through the system, manifesting itself in course placement, GPA, and other important schooling outcomes.
This does not mean that student trust does not matter; it does. But it is a social resource, and as such, it is not immune to structural problems of bias and racism embedded in our social system. Research on student trust has been promising; however, the findings of this study are troubling. Trust may be a vital resource for school improvement (Bryk & Schneider, 2002), but racial bias, whether intended or unintended, may dilute its effects. The findings of this study may be interpreted as a cautionary tale to future research on trust in schools. Trust may be an important ingredient in school improvement, but more research needs to be done to investigate the interplay of trust, race, and gender.
Data for this study were drawn from the National Educational Longitudinal Study of 2002 (ELS). ELS provides data that would otherwise be difficult or impossible to obtaina large, nationally representative sample that follows high school students over multiple years. However, there are limitations worth noting. Although ELS provides a wealth of information about students and was designed to study a broad range of educational topics, some of the variables used in this study are not ideal measures. For example, discipline data provide the number of times a student was suspended or expelled but does not indicate the length of the suspension (1 day, 5 days, a full semester?) or type or severity of the offense. This may mean that suspensions and other disciplinary actions are undercounted and could compress actual group differences. Another variable reflects students responses to the number of times they got in trouble. However, it is not possible to know from the survey question exactly what students consider getting in trouble. For instance, it is possible that for one student, getting in trouble means being warned by the teacher about inappropriate behavior, whereas another may interpret it as being suspended.
Additionally, as noted earlier, this investigation was limited to a comparison of White and Black students and did not consider students of other races or ethnicities. Research is needed to investigate how these findings might differ for other groups of students. Finally, future research is also needed to untangle interactions between race and gender, enabling comparison between Black and White females and males.
SIGNIFICANCE/IMPLICATIONS FOR PRACTICE
As the discipline gap and the school-to-prison pipeline have increasingly gained attention, there have been some limited policy responses. In 2014, the Office of Civil Rights issued discipline guidance to schools across the nation with an admonishment reminding schools that federal law requires them to administer school discipline without discriminating on the basis of race, color or national origin, and it warned of possible consequences for disciplinary sanctions with racially disparate impacts (U.S. Department of Education, 2014). There have been some state-level responses as well. For example, in 2014, California amended the state education code to limit suspensions and prohibit expulsions for minor offenses such as disruptions or defiance (California Education Code 48900). In 2015, the State of Illinois passed legislation to limit the use of suspensions and mandated that other appropriate interventions be exhausted before a student is removed from school (Illinois Public Act 099-0456).
At the local level, more schools and districts have been implementing restorative justice or positive behavioral interventions and support (PBIS) (González, 2015; McCluskey et al., 2008). These types of approaches aim to shift the focus and practice of discipline. Instead of reactive practices focused on punishment and exclusion, they focus on setting clear, positive behavior expectations, changing the behavior of teachers and staff, reinforcing community, and developing positive, trusting relationships (Gregory, Allen, Mikami, Hafen, & Pianta, 2015). In essence, this is a move from controlling student behavior by overreliance on the power to punish, to developing authentic authority based on relationships and community that students recognize as legitimate, thereby averting or diminishing conflict.
To be successful, these approaches will require a sweeping paradigm change from focusing on student behavior to focusing on how educators react to student behavior, from coercion and exclusion to cohesion and inclusion, from reaction to prevention, from distrust to trust and relationship building. This type of change will not be easy, nor will it happen overnight. To be successful, schools will need to invest in PBIS training for faculty, staff, and administration, consistently implement supportive policies, and continuously teach and reteach students about positive behavioral expectations (Gregory et al., 2015). Training in classroom management, typically neglected in schools of education, is also called for. Here, investing in culturally responsive classroom management practices would be wise (Milner & Tenore, 2010; Weinstein et al., 2003). In schools marked by high student mobility rates and faculty turnover, typical in many urban schools, this effort will be all the more difficult. Schools and districts must plan for this by continually investing in staff and student development.
Additionally, training in implicit bias recognition may be not only essential but also the most fundamental action required (Devine, Forscher, Austin, & Cox, 2012; Wald, 2014). If researchers are right about disparities being driven by implicit bias, then implicit bias needs to be recognized and its effect extinguished for other programs to be effective. Intervention programs, whether restorative justice or PBIS, are not immune to implicit bias, and failure to account for it can be expected to undermine these new efforts.
Recent data show a drop in suspensions and expulsions where these policies and practices are being implemented (Cohn, 2015; González, 2015; Gregory et al., 2015). Although these developments are promising, and necessary, they will not be enough. This research found that Black and White students with roughly equivalent discipline records and scores on achievement tests still have substantially different high school outcomes. Schools must deal with the unequal consequences of equal discipline. To do this, we must scrutinize course placement practices, grading, and the messages that we send to students. Failure to do so will continue to leave us with a vast education debt (Ladson-Billings, 2006) and will continue to fuel the achievement gap.
1. Racial disparities in discipline have been documented since the 1960s (Hoffman, 2014). The enactment of the Gun Free Schools Act of 1994, as part of the 1994 reauthorization of the Elementary and Secondary Schools Act, mandated that states adopt policies to expel students for bringing weapons to school. Subsequent policy changes in many states expanded this mandate to include zero-tolerance policies for weapons and for many other categories of offenses, including drugs, alcohol, fighting, and repeated offenses (Hoffman, 2014). The zero-tolerance movement resulted in a staggering increase in exclusionary discipline and amplified existing racial disparities (Skiba & Knesting, 2001).
2. For example, see Baron and Banaji (2014), Greenwald and Krieger (2006), Jacoby-Senghor, Sinclair, and Shelton (2016), and Gilliam, Maupin, Reyes, Accavitti, and Shic (2016).
3. Although the literature agrees that trust has multiple components, their exact number and nature have been debated. See for example, Bryk and Schneider (2002), Butler (1991), Kramer, (1999), Makiewicz and Mitchell (2014), Mayer et al. (1995), Mishra (1996), Romero (2010, 2015), and Tschannen-Moran and Hoy (1998).
4. A model-generating approach, as described Raykov and Marcoulides (2006), was used in this analysis. A model drawn from Romero (2015) was proposed a priori, and tested and evaluated for goodness of fit. Fit statistics, factor loadings, residuals, and modification indices were examined and, guided by theory, used to refine the model. The final model is presented in this article.
5. ELS data are selected using stratified cluster sampling, violating the assumption of independence. Failure to take into account the complex, hierarchical nature of the data could result in incorrectly computed standard errors (Stapleton, 2006).
Adams, C. M. (2014). Collective student trust a social resource for urban elementary students. Educational Administration Quarterly, 50(1), 135159.
Adams, C. M., & Forsyth, P. B. (2009). Conceptualizing and validating a measure of student trust. In W. K. Hoy & M. DiPaola (Eds.), Studies in school improvement (pp. 263279). Charlotte, NC: Information Age.
Ansalone, G. (2009). Tracking, schooling and the equality of educational opportunity. Race, Gender & Class, 16, 174184.
Arcia, E. (2006). Achievement and enrollment status of suspended students: Outcomes in a large, multicultural school district. Education and Urban Society, 38(3), 359369.
Balfanz, R., & Byrnes, V. (2006). Closing the mathematics achievement gap in high-poverty middle schools: Enablers and constraints. Journal of Education for Students Placed at Risk, 11(2), 143159.
Balfanz, R., Byrnes, V., & Fox, J. (2015). Sent home and put off track: The antecedents, disproportionalities, and consequences of being suspended in the 9th grade. In D. J. Losen (Ed.), Closing the school discipline gap: Equitable remedies for excessive exclusion (pp. 151165). New York, NY: Teachers College Press.
Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52, 126.
Baron, A. S., & Banaji, M. R. (2006). The development of implicit attitudes: Evidence of race evaluations from ages 6 and 10 and adulthood. Psychological Science, 17(1), 5358.
Beard, K. S., & Brown, K. M (2008). Trusting schools to meet the needs of African American students? Suburban mothers perspectives. International Journal of Qualitative Studies in Education, 21(5), 471485.
Black, D. W., Garda, R. A., Taylor, J. E., & Waldman, E. G. (2013) Education law: Equality, fairness, and reform. WVU Law Research Paper No. 2013-10. http://dx.doi.org/10.2139/ssrn.2270078
Bowers, A. J. (2011). What's in a grade? The multidimensional nature of what teacher-assigned grades assess in high school. Educational Research and Evaluation, 17(3), 141159.
Butler, J. K. (1991). Toward understanding and measuring conditions of trust: Evolution of a conditions of trust inventory. Journal of Management, 17(3), 643666.
Bryk, A. S., & Schneider, B. L. (2002). Trust in schools: A core resource for improvement, New York, NY: Russell Sage Foundation.
Carter, P. L., Skiba, R., Arredondo, M. I., & Pollock, M. (2017). You cant fix what you dont look at: Acknowledging race in addressing racial discipline disparities. Urban Education, 52(2), 207235.
Cohn, C. (2015). Expulsions and suspensions decline as schools shift strategies. EdSource. Retrieved from http://edsource.org/2015/expulsions-and-suspensions-decline-as-california-shifts-strategies/74890
Cohen, G. L., & Steele, C. M. (2002). A barrier of mistrust: How negative stereotypes affect cross-race mentoring. In J. Aronson (Ed.), Improving academic achievement: Impact of psychological factors on education (pp. 303327). San Diego, CA: Emerald Publishing Group.
Coleman, J. (1968). The concept of equality of educational opportunity. Harvard Educational Review, 38(1), 722.
Davis, H. A. (2003). Conceptualizing the role and influence of student-teacher relationships on children's social and cognitive development. Educational Psychologist, 38(4), 207234.
Desimone, L. M., & Long, D. (2010). Teacher effects and the achievement gap: Do teacher and teaching quality influence the achievement gap between Black and White and high- and low-SES students in the early grades? Teachers College Record, 112(12), 30243073.
Devine, P. G., Forscher, P. S., Austin, A. J., & Cox, W. T. (2012). Long-term reduction in implicit race bias: A prejudice habit-breaking intervention. Journal of Experimental Social Psychology, 48(6), 12671278.
Diamond, J. B., Randolph, A., & Spillane, J. P. (2004). Teachers' expectations and sense of responsibility for student learning: The importance of race, class, and organizational habitus. Anthropology & Education Quarterly, 35(1), 7598.
Dixon-Román, E. J., Everson, H. T., & McArdle, J. J. (2013). Race, poverty and SAT scores: Modeling the influences of family income on Black and White high school students SAT performance. Teachers College Record, 115(4).
Downey, D. B., & Pribesh, S. (2004). When race matters: Teachers' evaluations of students' classroom behavior. Sociology of Education, 77(4), 267282.
Emmer, E., Sabornie, E., Evertson, C. M., & Weinstein, C. S. (2013). Handbook of classroom management: Research, practice, and contemporary issues. London, England: Routledge.
Faulkner, V. N., Stiff, L. V., Marshall, P. L., Nietfeld, J., & Crossland, C. L. (2014). Race and teacher evaluations as predictors of algebra placement. Journal for Research in Mathematics Education, 45(3), 288311.
Fenning, P., & Rose, J. (2007). Overrepresentation of African American students in exclusionary discipline: The role of school policy. Urban Education, 42(6), 536559.
Ferguson, R. (2010). Student perceptions of teaching effectiveness (Discussion Brief). National Center for Teacher Effectiveness and Achievement Gap Initiative, Harvard University, Cambridge, MA.
Finney, S. J., & DiStefano, C. (2006). Non-normal and categorical data in structural equation modeling. In G. R. Hancock & R. O. Mueller (Eds.), Structural equation modeling: A second course (pp. 269314). Greenwich, CT: Information Age.
Forsyth, P. B., Adams, C. M., & Hoy, W. K. (2011). Collective trust: Why schools cant improve without it. New York, NY: Teachers College Press.
Gilliam, W. S., Maupin, A. N., Reyes, C. R., Accavitti, M., & Shic, F. (2016). Do early educators implicit biases regarding sex and race relate to behavior expectations and recommendations of preschool expulsions and suspensions? Research Study Brief. Yale University, Yale Child Study Center, New Haven, CT.
Glaeser, E. L., Laibson, D. I., Scheinkman, J. A., & Soutter, C. L. (2000). Measuring trust. The Quarterly Journal of Economics, 115(3), 811846.
Goddard, R. D. (2003). Relational networks, social trust, and norms: A social capital perspective on students' chances of academic success. Educational Evaluation and Policy Analysis, 25(1), 5974.
Goddard, R. D., Salloum, S. J., & Berebitsky, D. (2009). Trust as a mediator of the relationships between poverty, racial composition, and academic achievement: Evidence from Michigan's public elementary schools. Educational Administration Quarterly, 45(2), 292311.
González, T. (2015). Socializing schools addressing racial disparities in discipline through restorative justice. In D. J. Losen (Ed.), Closing the school discipline gap: Equitable remedies for excessive exclusion (pp. 151165). New York, NY: Teachers College Press.
Goodenow, C. (1992). Strengthening the links between educational psychology and the study of social contexts. Educational Psychologist, 27(2), 177196.
Görlich, A., & Katznelson, N. (2015). Educational trust: Relational and structural perspectives on young people on the margins of the education system. Educational Research, 57(2), 201215.
Gottfried, M. A. (2010). Evaluating the relationship between student attendance and achievement in urban elementary and middle schools: An instrumental variables approach. American Educational Research Journal, 47(2), 434465.
Gosa, T. L., & Alexander, K. L. (2007). Family (dis)advantage and the educational prospects of better off African American youth: How race still matters. Teachers College Record, 109(2), 285321.
Greenwald, A. G., & Krieger, L. H. (2006). Implicit bias: Scientific foundations. California Law Review, 94(4), 945967.
Gregory, A., Allen, J. P., Mikami, A. Y., Hafen, C. A., & Pianta, R. C. (2015). The promise of a teacher professional development program in reducing racial disparity in classroom exclusionary discipline. In D. J. Losen (Ed.), Closing the school discipline gap (pp. 166179). New York, NY: Teachers College Press.
Gregory, A., Bell, J., & Pollock, M. (2014, March). How educators can eradicate disparities in school discipline: A briefing paper on school-based interventions. Discipline Disparities Series: Interventions. The Equity Project at Indiana University. Retrieved from http://www.indiana.edu/~atlantic/wp-content/uploads/2014/03/Disparity_Interventions_Full_031214.pdf
Gregory, A., Cornell, D., & Fan, X. (2011). The relationship of school structure and support to suspension rates for Black and White high school students. American Educational Research Journal, 48(4), 904934.
Gregory, A., & Ripski, M. B. (2008). Adolescent trust in teachers: Implications for behavior in the high school classroom. School Psychology Review, 37(3), 337353.
Gregory, A., Skiba, R. J., & Noguera, P. A. (2010). The achievement gap and the discipline gap: Two sides of the same coin? Educational Researcher, 39(1), 5968.
Gregory, A., & Thompson, A. R. (2010). African American high school students and variability in behavior across classrooms. Journal of Community Psychology, 38(3), 386402.
Gregory, A., & Weinstein, R. S. (2008). The discipline gap and African Americans: Defiance or cooperation in the high school classroom. Journal of School Psychology, 46(4), 455475.
Hand, V. M. (2010). The co-construction of opposition in a low-track mathematics classroom. American Educational Research Journal, 47(1), 97132.
Hoffman, S. (2014). Zero benefit estimating the effect of zero tolerance discipline policies on racial disparities in school discipline. Educational Policy, 28(1), 6995.
Hoy, W. K., & Kupersmith, W. J. (1985). The meaning and measure of faculty trust. Educational and Psychological Research, 5(1), 110.
Ingels, S. J., Pratt, D. J., Wilson, D., Burns, L. J., Currivan, D., Rogers, J. E., & Hubbard-Bednasz, S. (2007). Education Longitudinal Study of 2002 (ELS: 2002): Base-year to second follow-up data file documentation (NCES 2008-347). Washington, DC: National Center for Education Statistics.
Jacoby-Senghor, D. S., Sinclair, S., & Shelton, J. N. (2016). A lesson in bias: The relationship between implicit racial bias and performance in pedagogical contexts. Journal of Experimental Social Psychology, 63, 5055.
Kennedy-Lewis, B. L., & Murphy, A. S. (2016). Listening to frequent flyers: What persistently disciplined students have to say about being labeled as bad. Teachers College Record, 118(1), 140.
Kim, C. Y., Losen, D. J., & Hewitt, D. T. (2010). The school-to-prison pipeline: Structuring legal reform. New York, NY: NYU Press.
Kitzmiller, E. M. (2013). You can't control me!": Cultivating authority in a struggling urban high school. Teachers College Record, 115(12), n12.
Kramer, R. M. (1999). Trust and distrust in organizations: Emerging perspectives, enduring questions. Annual Review of Psychology, 50(1), 569598.
Ladson-Billings, G. (2006). From the achievement gap to the education debt: Understanding achievement in U.S. schools. Educational Researcher, 35(7), 312.
Lee, V. E., & Ready, D. D. (2007). Schools within schools: Possibilities and pitfalls of high school reform. New York, NY: Teachers College Press.
Losen, D. J., & Gillespie, J. (2012). Opportunities suspended: The disparate impact of disciplinary exclusion from school. New York, NY: Teachers College Press.
Losen, D., Hewitt, D., & Toldson, I. (2014, March). Eliminating excessive and unfair exclusionary discipline in schools: Policy recommendations for reducing disparities. Discipline Disparities Research to Practice Collaborative. The Equity Project at Indiana University. Retrieved from http://www.indiana.edu/~atlantic/wp-content/uploads/2014/03/Disparity_Policy_Full_031214.pdf
Losen, D. J., & Martinez, T. E. (2013). Out of school and off track: The overuse of suspensions in American middle and high schools. K-12 Racial Disparities in School Discipline. Los Angeles, CA: The Civil Rights Project/Proyecto Derechos Civiles, UCLA. Retrieved from http://escholarship.org/uc/item/8pd0s08z
Louis, K. S. (2007). Trust and improvement in schools. Journal of Educational Change, 8(1), 124.
Louis, K. S., & Murphy, J. (2017). Trust, caring and organizational learning: The leaders role. Journal of Educational Administration, 55(1), 103126.
Makiewicz, M., & Mitchell, D. (2014). Teacher trust in the principal: Factor structure and effects. In D. Van Maele, P. B. Forsyth, & M. Van Houtte (Eds.), Trust and school life: The role of trust for learning, teaching, leading, and bridging (pp. 99118). Dordrecht, Netherlands: Springer Netherlands.
Mayer, R. C., Davis, J. H. & Schoorman, F. D. (1995). An integrative model of organizational trust. The Academy of Management Review, 20(3), 709734.
McCluskey, G., Lloyd, G., Kane, J., Riddell, S., Stead, J., & Weedon, E. (2008). Can restorative practices in schools make a difference? Educational Review, 60(4), 405417.
McClain, S., & Cokley, K. (2017). Academic disidentification in Black college students: The role of teacher trust and gender. Cultural Diversity and Ethnic Minority Psychology, 23(1), 125133.
Meier, D. (2002). In schools we trust: Creating communities of learning in an era of testing and standardization. Boston, MA: Beacon Press.
Milner, H. R., IV. (2013). Why are students of color (still) punished more severely and frequently than White students? Urban Education, 48(4), 483489.
Milner, H. R., & Tenore, F. B. (2010). Classroom management in diverse classrooms. Urban Education, 45(5), 560603.
Minor, C. M. (2014). Racial differences in teacher perception of student ability. Teachers College Record, 116(10), 122.
Mishra, A. K. (1996). Organizational responses to crisis: The centrality of trust. In R. M. Kramer & T. R. Tyler, Trust in organizations: Frontiers of theory and research (pp. 261287). Thousand Oaks, CA: SAGE.
Mitchell, D. E., & Spady, W. G. (1983). Authority, power, and the legitimation of social control. Educational Administration Quarterly, 19(1), 533.
Mitchell, R. E., & Romero, L. S. (2015). Responsibility at the core of public education: Students, teachers, and the curriculum. In Professional responsibility (pp. 1137). Dordrecht, Netherlands: Springer International Publishing.
Mitchell, R. M., Forsyth, P. B., & Robinson, U. (2008). Parent trust, student trust and identification with school. Journal of Research in Education, 18,116124.
Monroe, C. R. (2005). Why are "bad boys" always Black? Causes of disproportionality in school discipline and recommendations for change. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 79(1), 4550.
Morris, E. W. (2005). Tuck in that shirt!: Race, class, gender, and discipline in an urban school. Sociological Perspectives, 48(1), 2548.
Moye, M. J., Henkin, A. B., & Egley, R. J. (2005). Teacher-principal relationships: Exploring linkages between empowerment and interpersonal trust. Journal of Educational Administration, 43(3), 260277.
Murray, C., & Zvoch, K. (2011). The inventory of teacher-student relationships: Factor structure, reliability, and validity among African American youth in low-income urban schools. The Journal of Early Adolescence, 31(4) 493525.
Nance, J. P. (2016). Over-disciplining students, racial bias, and the school-to-prison pipeline. University Richmond Law Review, 50, 1063. Retrieved from http://scholarship.law.ufl.edu/facultypub/749/
Okonofua, J. A., & Eberhardt, J. L. (2015). Two strikes race and the disciplining of young students. Psychological science, 26(5), 617-624.
Owens, M. A., & Johnson, B. L. (2009). From calculation to courtships to contribution: Cultivating trust among urban youth in an academic intervention program. Education Administration Quarterly, 45(2), 312347.
Raykov, T., & Marcoulides, G. A. (2006). A first course in structural equation modeling. Mahwah, NJ: Erlbaum.
Ream, R. K., Lewis, J. L., Echeverria, B., & Page, R. N. (2014). Trust matters: Distinction and diversity in undergraduate science education. Teachers College Record, 116(5).
Reardon, S. F. (2011). The widening academic achievement gap between the rich and the poor: New evidence and possible explanations. In G. J. Duncan & R. J. Murnane (Eds.), Whither opportunity? Rising inequality, schools, and children's life chances (pp. 91116). New York, NY: Russell Sage Foundation.
Roby, D. E. (2004). Research on school attendance and student achievement: A study of Ohio schools. Educational Research Quarterly, 28(1), 3.
Romero, L. (2010). Student trust: Impacting high school outcomes (Unpublished doctoral dissertation). University of California Riverside.
Romero, L. S. (2015). Trust, behavior, and high school outcomes. Journal of Educational Administration, 53(2), 215236.
Rosenthal, R., & Jacobson, L. (1968). Pygmalion in the classroom. The Urban Review, 3(1), 1620.
Rumberger, R. W., & Losen, D. J. (2016). The high cost of harsh discipline and its disparate impact. Civil Rights Project-Proyecto Derechos Civiles. Retrieved from https://www.civilrightsproject.ucla.edu/resources/projects/center-for-civil-rights-remedies/school-to-prison-folder/federal-reports/the-high-cost-of-harsh-discipline-and-its-disparate-impact/UCLA_HighCost_6-2_948.pdf
Schneider, B., Judy, J., Ebmeyer, C. M., & Broda, M. (2014). Trust in elementary and secondary urban schools: A pathway for student success and college ambition. In D. Van Maele, P. B. Forsyth, & M Van Houtte (Eds.), Trust and school life: The role of trust for learning, teaching, leading, and bridging (pp. 3756). Dordrecht, Netherlands: Springer Netherlands.
Schoorman, F. D., Mayer, R. C., & Davis, J. H. (2007). An integrated model of organizational trust: Past, present, future. Academy of Management Review, 32, 344354.
Shoff, C., & Yang, T. (2012). Untangling the associations among distrust, race, and neighborhood social environment: A social disorganization perspective. Social Science & Medicine, 74(9), 13421352.
Skiba, R. J., Arredondo, M. I., & Rausch, M. K. (2014). New and developing research on disparities in discipline. Bloomington: The Equity Project at Indiana University.
Skiba, R. J., Arredondo, M. I., & Williams, N. T. (2014). More than a metaphor: The contribution of exclusionary discipline to a school-to-prison pipeline. Equity & Excellence in Education, 47(4), 546564.
Skiba, R. J., Horner, R. H., Chung, C. G., Rausch, M. K., May, S. L., & Tobin, T. (2011). Race is not neutral: A national investigation of African American and Latino disproportionality in school discipline. School Psychology Review, 40(1), 85.
Skiba, R. J., & Knesting, K. (2001). Zero tolerance, zero evidence: An analysis of school disciplinary practice. New Directions for Youth Development, 2001(92), 1743.
Skiba, R. J., Michael, R. S., Nardo, A. C., & Peterson, R. L. (2002). The color of discipline: Sources of racial and gender disproportionality in school punishment. The Urban Review, 34(4), 317342.
Smetana, J. G., & Bitz, B. (1996). Adolescents' conceptions of teachers' authority and their relations to rule violations in school. Child Development, 67(3), 11531172.
Smith, S. S. (2010). Race and trust. Annual Review of Sociology, 36, 453475.
Stapleton, L. M. (2006). An assessment of practical solutions for structural equation modeling with complex sample data. Structural Equation Modeling, 13(1), 2858.
Tenenbaum, H. R., & Ruck, M. D. (2007). Are teachers' expectations different for racial minority than for European American students? A meta-analysis. Journal of Educational Psychology, 99, 253273.
Timar, T. B., & Maxwell-Jolly, J. (2012). Narrowing the achievement gap: Perspectives and strategies for challenging times. Cambridge, MA: Harvard Education Press, Cambridge Press.
Toldson, I. A., McGee, T., & Lemmons, B. P. (2014). Reducing suspensions by improving academic engagement among school-age Black males. In D. J. Losen (Ed.), Closing the school discipline gap (pp. 107117). New York: Teachers College Press.
Tschannen-Moran, M. (2004), Trust matters: Leadership for successful schools, San Francisco, CA: Jossey-Bass.
Tschannen-Moran, M., & Hoy, W. (1998). Trust in schools: A conceptual and empirical analysis. Journal of Educational Administration, 36(4), 334352.
Tschannen-Moran, M., & Hoy, W. K. (2000). A multidisciplinary analysis of the nature, meaning, and measurement of trust. Review of Educational Research, 70(4), 547593.
Tschannen-Moran, M., Bankole, R. A., Mitchell, R. M., & Moore, D. M. (2013). Student academic optimism: A confirmatory factor analysis. Journal of Educational Administration, 51(2), 150175.
Tyler, T. R., & Degoey, P. (1995). Collective restraint in social dilemmas: Procedural justice and social identification effects on support for authorities. Journal of Personality and Social Psychology, 69, 482−497.
Van den Bergh, L., Denessen, E., Hornstra, L., Voeten, M., & Holland, R. W. (2010). The implicit prejudiced attitudes of teachers: Relations to teacher expectations and the ethnic achievement gap. American Educational Research Journal, 47(2), 497527.
Van Maele, D., Forsyth, P. B., & Van Houtte, M. (Eds.). (2014). Trust and school life: The role of trust for learning, teaching, leading, and bridging. Dordrecht, Netherlands: Springer Netherlands.
Wald, J. (2014). Can de-biasing strategies help to reduce racial disparities in school discipline? Summary of the literature. Institute for Race and Justice, Harvard Law School. Retrieved from http://www.indiana.edu/~atlantic/wp-content/uploads/2014/03/Implicit-Bias_031214.pdf
Walker, K., Kutsyuruba, B., & Noonan, B. (2011). The fragility of trust in the world of school principals. Journal of Educational Administration, 49(5), 471494.
Way, S. M. (2011). School discipline and disruptive classroom behavior: The moderating effects of student perceptions. The Sociological Quarterly, 52(3), 346375.
Weinstein, C., Curran, M., & Tomlinson-Clarke, S. (2003). Culturally responsive classroom management: Awareness into action. Theory Into Practice, 42(4), 269276.
Wildhagen, T. (2012). How teachers and schools contribute to racial differences in the realization of academic potential. Teachers College Record, 114(7), 127.
U.S. Department of Education. Office of Civil Rights (2014). School climate and discipline. Retrieved from http://www2.ed.gov/policy/gen/guid/school-discipline/index.html
Yeager, D. S., Purdie-Vaughns, V., Garcia, J., Pebley, P., Master, A., Hessert, W., . . . Cohen, G. L. (2014). Breaking the cycle of mistrust: Wise interventions to provide critical feedback across the racial divide. Journal of Experimental Psychology,143(2), 804824.
Yeager, D. S., Purdie-Vaughns, V., Hooper, S. Y., & Cohen, G. L. (2017). Loss of institutional trust among racial and ethnic minority adolescents: A consequence of procedural injustice and a cause of life-span outcomes. Child Development, 88(2), 658676.http://www2.ed.gov/policy/gen/guid/school-discipline/index.html
Zimmerman, B. J. (1989). A social cognitive view of self-regulated academic learning. Journal of Educational Psychology, 81(3), 329339.
Measurement Model Standardized Coefficients
*Correlated error terms: math IRT with reading IRT, in-school suspension with suspend/probation, grade point average with graduation status, and postsecondary plans with highest math class taken.