Group 1

Disparities in Student Achievement in Portland Public High Schools

Motivations

        The initial motivation for choosing this topic stems from our group's general

understanding that disparities in student achievement exist within the population of students in

Portland Public Schools high schools. Within the public discourse, the problems are often

attributed to problems in financial resource allocation by the city.  The problem is a lack in

funding, which reduces the amount of support for students, and negatively impacts their

academic performance and likelihood of graduation. We would like to explore how these

financial resources are divided in the Portland Public School districts. Specifically, we would

like to uncover how the school demographics vary by district in the areas of racial composition

and socioeconomic class.  We feel our research could be applied to the ongoing public discourse

and has the potential to impact public policy.

Aims of Research

        We intend to find maps of the Portland Public School district boundaries that best

represent district boundaries and racial composition of the districts. We also intend to find data

on graduation rates, advanced placement program participation and availability, standardized

testing scores, dropout rates, and academy class sizes.  We would also like to see how many

students are on free and reduced lunches.  The income of parents will be measured by looking at

students who are eligible for free lunches and reduced lunches. Another factor that we wish to

incorporate into our research is looking at individual schools within the Portland Public School

District student to teacher ratios. These ratios are a contributing factor when looking how

resources are allocated within the Portland Public Schools.

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Literature Review

        Each group member was assigned his or her own independent variables to find existing

research.  Group members spent time individually researching their assigned variables, and

selected the most relevant articles to bring to the group for further examination. The independent

variables assigned included extracurricular activities, race, gender, school funding, juvenile

delinquency, and parental involvement. All of these variables were paired with student

achievement as a dependent variable. Our group was able to compile a large body of research for

use in focusing the aim and scope of our own research. Drawing from the existing literature, we

have noticed that much of the research has been conducted outside of the Pacific Northwest.

In the existing literature that our group has collected, race has been accounted for using

the categories of black, white, and other; with Hispanic and non-Hispanic not being addressed

specifically. Furthermore, there have been few articles written about the correlation between race

and educational achievement in the Portland, Oregon area specifically. The literature gap that we

are going to focus on is how there is no literature written about the Portland area.

Summary of Articles

Home Influence on School Learning: Direct and Indirect effects of Parental

Involvement on High School Grades, written by Paul Fehrmann, Timothy Keith, and Thomas

Reimers from the University of Iowa in 1987, mainly encompasses parent's involvement with

students and the effects on that student's grades. The independent variable is the parent's

involvement and the dependent variable is the student’s grades. There are also two other

variables taken into consideration, which are time spent on homework and time spent watching

television. Since parent involvement is such a broad term they used the parent's expectation of

school performance, verbal encouragement or interactions regarding school work, general

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academic guidance and support, direct reinforcement of improved academic performance in

order to measure it. This study consisted of 28,051 high school seniors from the (1980) National

center for education statistics high school and beyond longitudinal study (HSB).

The article entitled Teachers and the Gender Gaps in Student Achievement, written by

Thomas S. Dee, looks at data sets from a number of previous studies addressing student gender,

teacher gender, and student’s academic achievement.  He used data from the National

Assessment of Educational Progress (NAEP) from 1999, which studied 9, 13, and 17-year-old

students test scores, their gender and the gender of their instructor.  Dee also used data from the

National Education Longitudinal Study: 1988, which was a two-stage longitudinal study that

began in 1988 with a sample of 24, 599 eighth grade students from 1,052 public and private

schools across the country.  The dependent variable in this study is the student test and

assessment scores, the independent variable is teacher gender.  The results of the study show that

assignment to a same-gender teacher significantly improves the achievement of both girls and

boys as well as teacher perceptions of student performance and student engagement with the

teacher’s subject.

               This article Perceived Parental Investment in School as a Mediator of the Relationship

Between Socioeconomic Indicators and Educational Outcomes in Rural America, takes rural

America and discusses the socio-economic status of parents children who are attending high

school. The purpose of the study was to see if the same patterns that happen in urban areas

happen in rural areas. The results were similar, children that have parents with higher

socioeconomic status are generally going to be more successful at graduating high school then

those that have lesser socio-economic status. The article also found that parental investment is

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key at the district level and on the individual level. Concluding that investment from parents on

both levels impacts graduation rates positively.

The article by Deslardins et. al. discusses the effect that race has on student graduation

rates. Other mediating variables that the study included were income, age, and overall high

school performance. The study consisted of sampling 12,628 students. The sample was collected

from students in 1984, 1986 and 1991 and the students were studied for six years. The

researchers found empirical evidence to support that Asian Americans have the highest

graduation rate. Whites have the second highest graduation rates followed by Latinos, American

Indians/other with the third highest graduation rates. African Americans have the lowest

graduation rates. The results also showed that those coming from families with higher income

have higher graduation rates overall.

The article Comparison of the educational deficiencies of delinquent and non-

delinquent students discusses how the researchers in this study wanted to look at how education

could possibly prevent and deter delinquent behavior by comparing non-delinquents with

delinquents. They rounded up a sample size of 5,187 delinquent and 5,187 non-delinquent

students and matched them based on age, race, gender, socioeconomic status, exceptionality

status, and school type by creating a case control design. The two groups were then compared in

terms of academic achievement, attendance, and disciplinary problems.  They found that

delinquent students experience disproportionate educational deficiencies. Juvenile delinquents

were found to have lower attendance records, lower GPA, and more likely to be retained in the

same grade, and receive more disciplinary actions than their counterparts. This study also shows

how students who attend schools without proper funding or perhaps a lack of teachers or

educational support immediately find themselves at a higher risk to “act out”. It also explains

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how early intervention and prevention of at-risk youths could deter students from delinquent

actions.

The research entitled Extracurricular Activities and High School Dropouts, by Ralph

B. Mcneal Jr., uses a secondary data analysis design, using statistics that were taken from the

Center for Educational Statistics. A multilevel cluster sampling method was used to draw 735

regular public high schools, with an oversample of selected subgroups. This produced a high

school student sample of 14,249. Using a series of regression models and controlling for

variables such as race, SES, gender, and others, it can be concluded that there is a strong

correlation between extracurricular activities and student dropouts. Students who participate in

extracurricular activities have significantly reduced chances of dropping out of high school

(McNeal).

Variables

After collecting data on a variety of variables pertaining to student educational

achievement the variables that our group is going to focus on for our research are race as an

independent variable and high school graduation as our dependent variable. Our mediating

variables which we wish to include in our study are gender and socio-economic class.  The best

measure available as an indicator for socioeconomic status of students in the Portland Public

School District is found in data collected by the US Department of Education, focusing

specifically on student participation in free and reduced lunch programs.

Research Plan

Research Question

From the research that was collected we found empirical evidence that minority high

school students are disadvantaged in the United States compared to white students.  Looking at

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incidences of graduation, there is evidence that minority students graduate less than white

students.  Our group is interested in finding out if this same pattern occurs within the Portland

Public School District's high schools.  Do minority high school students in the Portland Public

School system graduate at lower rates than white students?

Hypothesis

Existing research puts forth evidence revealing that African Americans are the most

disadvantaged group within the United States.  In other cities around the country, African

American high school students experience the lowest graduation incidences compared to any

other minority group.  Based on the findings of existing research showing evidence of racial

disparity among other high schools around the United States, we suspect that this same pattern is

true for the Portland Public School system’s high school's.  We wish to examine if this dynamic

is present within the Portland Public Schools high schools or if there are other disadvantaged

minority groups within the Portland Public School District.  Furthermore, mediating

relationships exist between the student’s socioeconomic statuses and graduation incidences in

other places, and this most likely holds true for Portland.  In examining this relationship, we are

defining socioeconomic status as students who are eligible to receive free lunches or reduced

lunches and also the average household income per school zone.

Research Design

The research design is going to be secondary data analysis. The motivations for our group

choosing secondary data analysis is based on the time constraints of this class. With secondary

data analysis our group feels we will be able to obtain more accurate data pertaining to our

variables that will better suit us in our analysis.  Along with the data being more accurate than

collecting our own data, the data is recent data pertaining to the Portland Public School District.

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This data also gives our group insight into other variables that we would have possibly

overlooked if we were collecting data from a survey.

The data set that our group has found that we are interested in using in our secondary

data analysis was collected by the Oregon Department of Education. The data set has

information about different variables specifically for the Portland Public School District. The

data is collected annually and is aggregate level information. The data set is the most relevant for

the information in which we wish to obtain in order to find empirical evidence to support our

hypothesis.

Extended Literature Review

For the extended literature review all members of the group researched the same

independent variable (race) and dependent variable (graduation from high school). Through

researching the same independent and dependent variables our group was able to examine

different studies which included a variety of mediating variables to further give us a better idea

of what variables we will include in our secondary data analysis.

Summary of Articles

In the article Measuring High School Graduation Rates at the State Level: What

Difference Does Methodology Make? it discusses how there are problems when looking at

graduation numbers from high school when focused on the state level. The authors, Warren and

Halpern-Manners, bring up many different arguments as to why looking at different data

collected through different means can be problematic. The first sample that they analyzed was

collected from the Current Population Survey along with census data of individuals between the

ages of 16 to 24 years old. Through this survey, along with the Digest of Education Statistics,

which is collected by the U.S. Department of Education, the numbers report that close to 90% of

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students graduated in the year 2000. The authors then looked towards another data set collected

by the State Nonfiscal Survey where only 65-75% of students graduated in the year 2000. The

authors discuss arguments for both sides of the article saying that yes there is an idea of there

being exaggerated dropouts at the state level. Although many believe this argument to be true

Warren and Halpern-Manners found empirical evidence to show that graduation numbers are

much lower than what is actually reported due to errors occur with differences between GED

certification, migration issues across state and the lack of including the youth prison population.

In the article Losing Our Future: How Minority Youths are Being Left Behind by the

Graduation Rate Crisis the authors addressed three main questions; How deep and widespread

are the racial disparities that exist at the state and district levels? Second, how has the misleading

and incomplete reporting of this issue obscured both the magnitude of the crisis and its racial

dimensions? Finally, focusing primarily on the No Child Left Behind (NCLB) legislation, we ask

whether state and federal accountability systems, as implemented, are appropriately structured to

improve high school graduation rates, especially among children of color.  The study done

compares data from two major sources, the Center for Educational Statistics and the Current

Population Survey, with "a more accurate method for calculating graduation rates" conducted by

the Urban Institute.  The Urban Institute also conducted a 50 state statistical profile, breaking the

statistics down by race, gender, as well as additional statistics for the ten largest districts in the

state.  The authors conclude that graduation rates are as low as 30% in some parts of the country,

that there are large numbers of “missing” students that go completely unaccounted for in either

official dropout or graduation rate reports and that the accountability systems in place are not

effective and require much more rigorous regulations.                            

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Sociological researchers Kyle Crowder and Scott J. South published an article entitled

Spatial and Temporal Dimensions of Neighborhood Effects on High School Graduation, which

investigates the relationship between a person's exposure to advantaged socio-economic

neighborhoods and high school graduation likelihood. Using a secondary data analysis research

design, the authors look at longitudinal data gathered by the Panel Study of Income Dynamic.

The data includes a sample of 2,254 black and white people born between 1968 and 1980 whom

were tracked over a 25-year period. Their dependent variable is whether these people received a

high school diploma or GED by age 25. Their independent variable was socioeconomic

advantaged neighborhoods, which they found data for in the United States Census records.

Gender was analyzed as a possible mediating variable. The authors have two major findings in

this research. First, for both blacks and whites alike, high school graduation is positively

correlated with exposure to advantaged socioeconomic residential areas. Second, this correlation

more pronounced for whites than for blacks. When gender is factored in, the authors found that

very little disparity existing between genders.

In the article Who graduates? Who doesn’t? A statistical portrait of high school

graduation, class of 2001 offers valuable insight and research into recent trends of high school

graduates across the nation as well as breaking down the results by individual states and by the

four main regions in the United States; Northeast, South, Midwest, and West. The author used

secondary data analysis by using information gathered by the Common Core of Data (CCD),

which was conducted by the U.S. Department of Education. The researcher then used a

Cumulative Promotion Index (PMI) which includes factors like the No Child Left Behind Act

(NCLB), enrollment vs. diploma counts, and uses a two year period of data collecting as opposed

to a typical four year collecting period to help define, discuss and measure high school

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graduation rates across the nation, region and state respectively. The researcher focused on race

and gender as well as multivariate analysis to determine linkages in socio-economic segregation

and disadvantage. Of the 14,935 school districts across the United States this study used

information gathered from 11,110 districts due to some schools being temporarily closed, shut

down, or district lines being redrawn creating overlapping or inaccurate data. The most notable

and shocking find was the disparity among majority and minority high school graduates. The

results show that Whites and Asian Americans far exceed the graduation rates of their Black,

Hispanic, and Native American peers by roughly 20-25% with Whites and Asian Americans

graduating at a rate of 75-77%. When focusing on specific regions the gap between majority and

minority increased in the Midwest and Northeast with majority students graduating at rates of up

to 50% more than their minority peers. The South and West, with generally overall lower

graduation rates due to lower socio-economic districts and school funding, saw a slightly smaller

disparity among graduating students. When looking at gender gaps of graduation rates the data

shows that female students graduate at 72% while males around 64% with a disparity of 8% that

only varies slightly when looking at U.S. regions specifically. The researcher found that there are

notable and definitive differences in high school graduates and race and socio-economic status

are the key factors in determining a students scholastic success.

In the article Neighborhood Effects in Temporal Perspective: The Impact of Long-

Term Exposure to Concentrated Disadvantage on High School Graduation discusses how certain

neighborhoods have an impact on High School graduation. The article focuses over a seventeen-

year period including a little over four thousand children. Looking at specific aspects of

gentrification the article reflects on how specific neighborhoods have a high dropout rate. The

purpose of the study was to collect long-term data to look at a generation of high school students

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in specific disadvantaged neighborhoods. Specifically a disadvantaged neighborhood contains

lack of social services, jobs, and a lower socio-economic status level. The study concludes that

race plays an important role in this equation but, the disadvantaged neighborhood seems to be the

determining factor of high school graduation.

High school Graduation Rates in the United States: Implications for the Counseling

Profession by Rebecca Powell Stanard (article written in 2003, but research conducted by J.P.

Green in 2001). This report tries to show that graduation rates are actually quite lower than we

are lead to believe. He also points out that the top four schools in graduation rates, are

predominantly white, but at the same time those same schools had some of the lowest minority

graduation rates. The data was collected from the 50 largest school districts in the country.

Through his methods he shows that schools like to skew the facts to make it seem like they are

doing far better than they really were. In 1998 the National Center for Educational Statistics

(NCES) showed an 86% high school completion rate whereas in Greene’s study it was 74%. For

Greene’s research he did not accept GEDs towards his formula insisting that GEDs are not the

equivalent to a regular high school diploma because it does not show the “success of  high

schools at graduating students”. When those who had graduated with GED’s were removed

Greene also found that the numbers of whites and Latinos were similar to the statistics that

NCES had, but that those for African Americans were quite different. He attributes this by

saying that NCES gets information from the Current Population Survey (CPS) and that coverage

bias and self-report bias. There was also discrepancy with the event dropout rate (the percentage

of students who drop out within a given year) and he found that 37 out of 50 states reported this

information and that out of those 37 only 27 adhered to the standards definition and collection

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procedures set by the NCES. He also noted that quite often data was missing and that it could not

be used to calculated dropout rate.

List of Variables  

Independent Variable

Race

Dependent Variable

Graduation from high school

Mediating Variables

Socio-economic class:

o Students who are eligible to receive free lunches

o Students who are eligible to receive reduced lunches

o Student to teacher ratio

Data Description

Data

The target population for our study is high school students enrolled in Portland Public

High Schools. The data set our group will be conducting secondary data analysis with was

collected by the Oregon Department of Education.  Faculty from each school in the Portland

Public School district are required to submit annual information describing the performance of

their students.  The data collected is then compiled into a “report card” system which determines

whether schools meet requirements at the state and federal levels.  The data set we are looking at

is from the 2010-2011 school year.  The data includes all individuals who were enrolled in a high

school within the Portland Public School District. There are eight high schools in the Portland

Public School District:  Benson, Cleveland, Franklin, Grant, Jefferson, Lincoln, Madison and

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Wilson.  Benson student body was 952 students in 2010-2011. Cleveland total number of

students 1,593 in 2010-2011. Franklin student body was 1,011 students in 2010-2011. Grant

student body was 1,567 students in 2010-2011. Jefferson student body was 573 students in 2010-

2011. Lincoln student body was 1,387 students in 2010-2011. Madison student body was 576

students in 2010-2011. Wilson student body was 1,407 students in 2010-2011. The total number

of students enrolled in the eight Portland Public High Schools is 9,066 students from the 2010-

2011 school year.

Portland Public High Schools

Benson Cleveland Franklin Grant Jefferson Lincoln Madison Wilson

Total Number of Student (2010-2011)

952 1,593 1,011 1,567 573 1,387 576 1,407

Measures

The independent variable we are focusing our main research question and hypothesis

around is race. Our data set defines race into different categories, which include American

Indian/Alaskan Native, Asian/Pacific Islander, Black (not of Hispanic origin), Hispanic, White

(not of Hispanic origin), and Multi-Racial/Multi Ethnic. Our dependent variable is whether or

not students graduate from high school within four years of attending. The cohort graduation

rates are recorded from students who entered into a Portland Public high school in the years

2006-2007 and graduated within four years from the given school they were attending.

The mediating variables we are going to include in our study are measured in the

following ways. For defining socio-economic class we are going to look at how many students

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are eligible for free lunches, how many students are eligible for reduced lunches, average

household income, and student to teacher ratio. The state requirements for students who are

eligible for free lunches must be living in a household who earns $14,157 or less per child. With

each additional child the family must add $4,966. The state requirements for students who are

eligible for reduced lunches must be living in a household who earns $20,147 or less per child.

With each additional child the family must add $7,067. The student to teacher ratio is collected

by taking the total number of students at a given school and divided by the number of teachers at

the same school.

Children from households whose income is at or below the following levels are eligible for free

or reduced price meals or free milk:

Reduced Price Meals

Household Size Annual Monthly Twice Per Month

Every Two Weeks

Weekly

-1- 20,147 1,679 840 775 388

-2- 27,214 2,268 1,134 1,047 524

-3- 34,281 2,857 1,429 1,319 660

-4- 41,348 3,446 1,723 1,591 796

-5- 48,415 4,035 2,018 1,863 932

-6- 55,482 4,624 2,312 2,134 1,067

-7- 62,549 5,213 2,607 2,406 1,203

-8- 69,616 5,802 2,901 2,678 1,339

For each additional family member add

7,067 589 295 272 136

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Free Meals/Free Milk

Household Size Annual Monthly Twice Per Month

Every Two Weeks

Weekly

-1- 14,157 1,180 590 545 273

-2- 19,123 1,594 797 736 368

-3- 24,089 2,008 1,004 927 464

-4- 29,055 2,422 1,211 1,118 559

-5- 34,021 2,836 1,418 1,309 655

-6- 38,987 3,249 1,625 1,500 750

-7- 43,953 3,663 1,832 1,691 846

-8- 48,919 4,077 2,039 1,882 941

For each additional family member add

4,966 414 207 191 96

Data Analysis Part One

Coding Variables

Total Number of Students: TOTSTUD

Number of Teachers: NTEACH

Student to Teacher Ratio: STRAT

Students eligible for reduced lunches:

REDLUN

Students eligible for free lunches: FRELUN

American Indian/Alaskan Native: AIAN

Asian/Pacific Islander: ASPI

Black (not of Hispanic origin): BLACK

Hispanic: HISPAN

White (not of Hispanic origin): WHITE

Multi-Racial/Multi Ethnic: MRME

The data that we took for all these variables are compiled into the follow table:

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Benson Cleveland Franklin Grant Jefferson Lincoln Madison Wilson

Total # students 952 1593 1011 1567 573 1387 576 1407

# of teachers 51.9 69.5 52.6 68 44.1 63.6 48.9 63

Ratio 18.343 22.921 19.221 23.044 12.993 21.808 11.779 22.333

Reduced Lunch 99 80 104 65 45 28 91 52

Free Lunch 501 337 373 307 394 145 493 245

American Indian/Alaskan Native

80 44.4 60 25 * 100 33.3 40

Asian/Pacific Islander

83.5 61.1 70.7 72.2 50 69.2 60.7 80

Black (non-hispanic)

72.5 37 70 70.5 54.8 60 40.6 63.6

Hispanic 69.7 53.2 76.7 63.3 35.3 64.3 45.2 62.1

White (non-hispanic)

79.7 72.3 66.2 85.1 35.7 84.3 60.2 76.2

Multi-Racial/Multi-Ethnic

75 78.6 71.4 81.8 100 75 33.3 57.1

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Mean and Standard Deviations of Averaged Student Cohort Graduation Rates by Racial Categories for the eight Portland Public High Schools

Cohort graduation rates by Race (All Schools)

Frequencies (n) Mean S.D.

American Indian/Alaskan Native 7 54.6714 27.0262

Asian/Pacific Islander 8 68.425 10.91575

Black (non-hispanic) 8 58.625 13.61058

Hispanic 8 58.725 13.46495

White (non-hispanic) 8 69.9625 16.28882

Multi-Racial/Multi-Ethnic 8 71.525 19.49306

Total # students 9066 1133.25 415.9398

# of teachers 461.6 57.7 9.48894

Ratio 152.442 19.0553 4.46262

Reduced Lunch 564 70.5 27.44865

Free Lunch 2795 349.375 119.988

The frequencies is the total number (n) of how many data numbers we have for each

racial category. Since we pulled aggregate level information for the eight Portland Public High

School there are 8 frequencies for each racial category. For American Indian/Alaskan Native the

frequency is only 7 because of one missing data number. The reason for there only being 7 is

because one school did not disclose the racial information for American Indian/Alaskan Native

to ensure the student’s confidentiality.

After imputing the data from the Oregon Department of Education our group found the

mean and standard deviation for the different racial categories. We took the cohort graduation

rates from the eight different Portland Public High Schools and found the average for the

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individual racial categories. From the descriptive statistics we can see that the racial group with

the highest cohort graduation rate within the Portland Public High Schools are those who identify

as being multi-racial/multi-ethnic. The mean for multi-racial/multi-ethnic is 71.525%. What this

means is that the average number of students who identify as multi-racial/multi-ethnic graduate

from high school in four years is 71.525% of the time. The racial category with the lowest cohort

graduation rate is those who are American Indian/Alaskan Native. American Indian/Alaskan

Native students who graduated in four years from a Portland Public High School graduated

54.67%.

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Data Analysis Part Two

Model 1 Model 2 Model 3

Coefficient S.E. sig. Coefficient S.E. sig. Coefficient S.E. sig.

Constant 63.246 10.143 0.001 63.395 10.585 0.002 97.887 148.212

0.545

REDLUN -0.624 1.186 0.618

REDLUN 1.094 2.702 0.702

FRELUN -0.327 0.457 0.507

REDLUN 1.453 3.373 0.689

FRELUN -0.6 1.277 -1.195

STRAT -1.384 5.929 -0.454

R-Square 0.044 0.133 0.144

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References:

Crowder, Kyle and South, Scott J. “Spatial and temporal dimensions of neighborhood effects on high school graduation”  Social Science Research. , 40, pp. 87-109 (2011).

Dee, Thomas S. "Teachers and the Gender Gap in Student Achievement" The Journal of Human Resources, pp. 528-554. (1999)

       DesJardins, Stephen L; Ahlburg, Dennis; McCall, Brian. “The Effects of interrupted enrollment

on graduation from college: Racial, income, and ability differences” (2004)

Fehrmann, Paul G.; Keith, Timothy Z.; Reimers, Thomas M.. “Home influence on School Learning: Direct and Indirect Effects of Parental Involvement on High School Grades” The Journal of Educational Research. Vol. 80, No. 6 (1987) http://www.jstor.org/stable/27540261

Henry, Kimberly; Cavanagh, Thomas; Oetting, Eugene. “Perceived Parental Investment in School as a Mediator of the Relationship Between Socio-Economic Indicators and Educational Outcomes in Rural America” Journal of Youth Adolescence. Vol. 40, No. 9. (2011)

McNeal Jr., Ralph B. Extracurricular activities and high school dropouts. Sociology of Education, Vol. 68, No. 1 (1995) pp. 62-80

Orfield, G., Losen, D., Wald, J., Swanson, C. (2004). "Losing Our Future: How Minority Youth are Being Left Behind by the Graduation Rate Crisis" The Civil Rights Project at Harvard University, The Urban Institute, Advocates for Children of New York, The Civil Society Institute. http://www.urban.org/UploadedPDF/410936_LosingOurFuture.pdfof cthwjlosearyo

Stanard, Rebecca P. "High School Graduation Rates in the United States: Implications for the Counseling Profession." Journal of Counseling and Development 81.2 (2003): 217-21. Print.

Swanson, C.B. (2004). “Who graduates? Who doesn’t? A statistical portrait of high school graduation, class of 2001.” The Urban Institute, The Educational Policy Center. http://www.urban.org/publications/410934.html

Wang, X. , Blomberg, T.G., & Spencer, D.L. (2005). “Comparison of the educational deficiences of delinquent and nondelinquent students”. Evaluation Review. 29 (4). DOI:             

10.1177/0193841X05275398

Warren, John Robert; Halper-Manners, Andrew. “Measuring High School Graduation Rates at the State Level: What Difference Does Methodology Make?” Sociological Methods and Research, Vol. 38, No. 1 (2009)

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Wodtke, G. T. (2011). Neighborhood Effects in Temporal Perspective: The Impact of Long-Term Exposure to Concentrated Disadvantage on High School Graduation. American Sociological Review, 713-736

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