Education Versus Crime Parker

20RUNNING HEAD: Education Versus Crime Parker

Chapter I: Introduction

The issue of education’s impact on crime can be advanced and far fetch from a privilege perspective, but the system of the basic understanding must be established to the average eye. The United States has one of the highest incarceration rates in the industrial world; its rate of spending on educational systems is among the lowest, considering this to be one of the major catalysts for ongoing increases in delinquent and violent behavior in America. The main area of discussion is how education can have an impact on crime as well as the criminal behavior. The abovementioned area is debatable, though there is disturbing agreement among public officials, teachers, academics as well as the parents that the post-secondary education is one of the methods of deterring crime cost, effectively and successful. The United States has only 5% of the world’s population yet more than 20% of the world’s incarcerated population. When the state level educational data and crime and the incarceration rates were compared, the results also support the fact that the states that are focusing more on education mostly have the lower rates of crime and incarceration. However, schooling can’t be seen as the cure all or ensure there is no crime in the countries, but the various research shows that investing in quality education can be one way of ensuring the country is free from violent criminal activities therefore achieving positive public safety.

Statement of the problem

The vast majority of U.S. correctional facilities offer some form of education and training for prisoners, with GED (General Educational Development) preparation courses. The extent that prison education programs help builds valuable market skills (in the same way traditional schools do), we would expect them to increase post-release earnings and reduce recidivism. Unfortunately, convincing empirical studies on this topic are scarce, primarily because prisoners who choose to enroll in prison education programs likely differ from those choosing not to enroll.

Purpose for the Study

Most states were struggling to keep education programs in the prisons and did not have the money for research needed to examine their correctional education programs. The U. S. Department of Education, Office of Correctional Education, saw the need for a study to assess whether or not correctional education programs were reducing the risk of recidivism for those inmates reentering their communities. Although many believe that there are numerous other social and economic benefits to be gained from educating inmates, this study focused primarily on the recidivism outcome (Lochner, 2004).

While not initially planned as part of the study, the focus of the research was extended to include wage and earnings data. Because of the difficulty associated with accessing wage and earnings data related to laws regarding confidentiality of social security numbers, this information has been rarely examined in the context of the impact of correctional education. In addition, a great deal of demographic/background data was 9 10 collected from the study participants to really look at carefully the characteristics and needs of incarcerated offenders who participated in correctional education and those incarcerated offenders who did not participate. This was done to gain information that could assist correctional education administrators in their strategic planning for correctional education programming.

Research Questions

1. Is there a relationship between education and crime?

2. Does education (as well as job training) develops formal labor market skills, which raises the opportunity costs of crime commission?

3. Can education also develop criminal skills?

4. Can education reduced re-arrest?

5. Does education reduce re-conviction?

6. Do education reduce re-incarceration, and in recidivists committing less serious offences?

7. Can education and post-release compliance with parole conditions as well as pro-social activities, and in higher employment and wages reduce crime?

Hypotheses

There are a number of reasons to believe that education can reduce criminal activity. If schooling increases the returns to legitimate work, while schooling may directly affect the financial or psychic rewards from crime itself, and then schooling may alter preferences in indirect ways, which may affect decisions to engage in crime.

Definition of Terms

· Crime : an action or omission that constitutes an offense that may be prosecuted by the state and is punishable by law

· The U. S. Department of Education: A department of the federal executive branch responsible for providing federal aid to educational institutions and financial aid to students, keeping national educational records, and conducting some educational research.

· Prisoners: a person legally held in prison as a punishment for crimes they have committed or while awaiting trial.

· Pell Grants:  is money the government provides for students who need it to pay for college. Grants, unlike loans, do not have to be repaid. Eligible students receive a specified amount each year under this program.

· GED (General Educational Development): is an internationally recognized test. If you pass the GED test, you will earn an Ontario High School Equivalency Certificate. It can help you get a job or admission to an educational or training program.

· Reduce: make smaller or less in amount, degree, or size.

· Meta-analysis: is a quantitative, formal, epidemiological study design used to systematically assess the results of previous research to derive conclusions about that body of research.

· Wage: a fixed regular payment, typically paid on a daily or weekly basis, made by an employer to an employee, especially to a manual or unskilled worker.

· Adult Basic Education: Education provided for adults at the elementary level (through grade 8), usually with emphasis on communicative, computational, and social skills

· Correctional Education: Educational programs provided for adults or youth in correctional institutions

· Correctional Institutions:  used to detain persons who are in the lawful custody of the government (either accused persons awaiting trial or convicted persons serving a sentence) pen, penitentiary. A correctional institution for those convicted of major crimes.

· Correctional Rehabilitation:  includes a broad array of programs including mental health, substance abuse, and educational services. In addition, specialty programs have been developed for women, sex offenders, and parolees.

· Criminal: a person who has committed a crime.

· Data Collection: Generating or bringing together information that has been systematically observed, recorded, organized, categorized, or defined in such a way that logical processing and inferences may occur

· Employment: the condition of having paid work.

· High School Equivalency Programs: adult educational activities concerned with the preparation for and the taking of tests which lead to a high school equivalency certificate, e.g., General Educational Development programs

· Multivariate Analysis: study of the relationships among three or more variables that are either dependent or neither dependent nor independent

· Outcomes of Education: results or consequences of education

· Parole Officers:  focus on working only with adults or juveniles, though occasionally they may work with both. Before an inmate is even released from prison, a parole officer will usually develop a plan for him or her.

· Recidivism: tendency to relapse into previous criminal or delinquent behavior habits

· Role of Education: functions of education, real or expected, in regard to the individual and the society at large

· Statistical Bias: characteristics of an experimental or sampling design, or the mathematical treatment of data, that systematically affects the results of a study so as to produce incorrect, unjustified, or inappropriate inferences or conclusions

· Surveys: a general view, examination, or description of someone or something.

· Vocational Rehabilitation: process of developing, restoring, or preserving the ability to engage in suitable employment through such services as diagnosis, guidance, counseling, physical restoration, education, training, and placement

Limitations

There were three main study limitations for this project. First, randomization of the study participants was not possible. To address this limitation, a release cohort was used to select the treatment and control groups to be studied. Second, the findings cannot be generalized to other settings. The study groups were selected from three states Maryland, Minnesota, and Ohio. Other states may have characteristics that could impact recidivism and employment outcomes differently than the three states in the study. Third, the extent of educational involvement by months or hours is not absolutely known for the entire study group. Although some data was collected on month’s involved correctional education for a number of different programs, it was only for a portion of offenders in the study, thus making it difficult to assess the impact of length of time of participation in correctional education on recidivism.

Record-keeping for these data elements was inadequate in all three states for a number of different reasons: (1) failure by education staff to maintain data in a systematic manner that could be reported with any confidence at the institutions (attempts to figure hours based on good/gain time credits given to inmates were rejected by the researchers); (2) movement of offenders to different institutions for security/custody purposes which meant attendance records were often lost in the process of files being moved with the inmate; and (3) inadequate 13 14 management information systems at the central offices. Since the study was conducted, the three states have implemented better management information systems for correctional education programs utilizing computer-based reporting either through the World Wide Web or through their own network systems.

Chapter 2: Literature Review

In an attempt to counter the efforts at cutting back or eliminating correctional education there have been a variety of studies conducted since 1990 to measure the value of correctional education including GED participation, vocational training, cognitive 8 9 skills programs, and post-secondary/college participation (Flanagan, 1994; Eisenberg, 1991; Saylor and Gaes, 1991; Menon, et al., 1992; Jenkins, Pendry, and Steurer, 1993; Smith and Silverman, 1993; Porporino and Robinson, 1992; Little, et al., 1991; Gainous, 1992). Most of these occurred in the early 1990’s with little being done during the last five years (1996-2001). Texas, however, has consistently examined the impact of their correctional education programs and has provided the most comprehensive studies with large sample sizes (Fabelo, 2000).

The Impact of Schooling on Incarceration Rates

3.1 Data and OLS Estimates

We begin by analyzing the impact of education on the probability of incarceration for men using U.S. Census data. The public versions of the 1960, 1970, and 1980 Censuses report the type of group quarters and, therefore, allow us to identify prison and jail inmates, who respond to the same Census questionnaire as the general population. We create a dummy variable equal to 1 if the respondent is in a correctional institution, we include in our sample males ages 20-60 for whom all the relevant variables are reported. Summary statistics are provided in Table 1. Roughly 0.5-0.7% of the respondents are in prison during each of the Census years we examine. Average years of schooling increase steadily from 10.5 in 1960 to 12.5 in 1980. 7Unfortunately, the public version of the 1990 Census does not identify inmates. The years under consideration precede the massive prison build-up that began around 1980. 10 Table 2 reports incarceration rates by race and educational attainment. The probability of imprisonment is substantially larger for blacks than for whites and this is the case for all years and education categories. Incarceration rates for white men with less than twelve years of schooling are around .8% while they average about 3.6% for blacks over the three decades. Incarceration rates are monotonically declining with education for all years and for both blacks and whites.

The Effects of Education on Crime

Empirically, there is a strong negative correlation between educational attainment and various measures of crime. Freeman (1996) points out that more than two-thirds of all incarcerated men in 1993 had not graduated from high school. In the 1980 wave of the National Longitudinal Survey of Youth (NLSY), 34% of all men ages 20-23 with 11 or 12 years of completed schooling self-reported earning some income from crime, compared with 24% of those with a high school degree, and only 17% of those with more than twelve years of school (Lochner 2004).

A Human Capital-Based Model of Crime

This section develops a time allocation model of crime, work, and human capital investment. Following Becker (1964) and Ben-Porath (1967), assume that skills can only be acquired through costly time investments (e.g. education and job training) and that those skills increase the return to work. Market skills may or may not raise the net return to crime. Individuals optimally choose how much time to allocate each period to investment in human capital, legitimate work, and crime with the goal of maximizing their expected lifetime income. If they engage in crime, they face some probability of future incarceration. If incarcerated, they are provided a minimal level of consumption and cannot invest, work, or engage in crime again until they are released. (Lochner 2004).

Lochner and Moretti (2004) use changes in state-specific compulsory schooling laws over time as an instrumental variable for completed schooling to estimate the effects of education on arrest rates and the probability of incarceration among adult men. Intuitively, they measure the extent to which an increase in a state’s compulsory schooling age leads to an immediate increase in educational attainment and reduction in subsequent crime rates for affected cohorts. This identifies the causal effect of schooling on crime as long as the changes in compulsory schooling laws are not related to changes in the underlying propensity to commit crime. Lochner and Moretti’s (2004) analysis suggests that changes in compulsory schooling laws are exogenous and not related to prior trends in schooling or state expenditures on law enforcement, so it appears to be a valid instrument.

The Effects of Arrest and Incarceration on Education

Hjalmarsson (2006) empirically examines the effects of juvenile arrests and incarceration (through age 16) on high school completion by age 19. Her main specifications control for youth cognitive achievement, juvenile criminal activity, and family background. She also considers additional models that account for state or family fixed effects to account for differences in state-level juvenile law enforcement and education policies as well as differences in family (and, therefore, neighborhood) environments. Her regression-based estimates suggest substantial effects of both arrest and incarceration on subsequent schooling attainment; however, she finds that her estimated effects for arrest may be largely due to unobserved heterogeneity across youth. Her findings for juvenile incarceration are more robust and suggest that youth who become incarcerated, holding their juvenile criminal activity and arrest rates constant, are roughly 25 percentage points less likely to complete high school by age 19 than similar youth who are not arrested.

Education and Training in Prison

The vast majority of U.S. correctional facilities offer some form of education and training for prisoners, with GED (General Educational Development) preparation courses the most 11 common. To the extent that prison education programs help build valuable market skills (in the same way traditional schools do), we would expect them to increase post-release earnings and reduce recidivism. Unfortunately, convincing empirical studies on this topic are scarce, primarily because prisoners who choose to enroll in prison education programs likely differ from those choosing not to enroll. Tyler and Kling (2006) attempt to account for these differences through a rich set of prisoner characteristics (e.g. sentence length, marital status and number of dependents, employment status prior to arrest, offense type, and a measure of cognitive ability), comparing the post-release earnings of prisoners who received a GED in prison with similar high school dropout prisoners who did not. They further account for prisoner differences by controlling for pre-prison earnings. Their findings suggest that a GED earned in prison offers no post-release earnings benefit for white offenders, but it does increase the earnings of minority offenders for the first two years after release (by about $800 per year). The earnings benefits for minorities fade quickly after the second year and are no longer statistically significant.

Chapter 3: Research Design (Plan)

A Research Design used in Criminal Justice research often precludes, for legal and ethical reasons, randomization for selection of experimental and control groups. The OCE/CEA Recidivism Study utilized a quasi-experimental design which is an accepted methodology commonly used in criminal justice/corrections research. The main distinction between experimental and quasi-experimental designs is the lack of random assignment to a treatment or control group. Therefore when randomization is not possible, using a quasi-experimental design with close attention to procedures for selection of the study groups, techniques for measuring dependent variables, and utilization of other controls are methods that can reduce threats to the validity of the research and increase the rigor of the study (Maxfield and Babbie, 2001, p. 176)

In this research, we used a release cohort (a group of inmates being released from incarceration during a certain time frame) for our study population. A cohort study is a methodology employed in quasi-: experimental designs for nonequivalent groups where there is a belief that the treatment group does not systematically differ from the comparison group on important variables. Only after the release cohort is selected would data that would identify the cohort participants as either the treatment or comparison group be collected. This design takes advantage of the natural flow of cases through the criminal justice process with an assumption that the treatment group and the comparison group are similar on key variables known to impact recidivism and employment. Part of the research can also be categorized as a longitudinal study since the release cohort was followed for a three-year period following release from incarceration for measures of recidivism and employment.

Population

The study group was comprised of the entire population of a cohort of inmates released from incarceration during 1997 and 1998 in Maryland, Minnesota, and Ohio. After the release cohort was identified, the cohort was separated into two groups education participants and a comparison group of non-participants. As stated earlier, the selection of a release cohort is a method used for non-equivalent “treatment” and comparison groups with an assumption of comparability. However, to further ensure the comparability of the two groups, significance tests were conducted for several key characteristics to see if the two groups differed on important variables that might impact the recidivism and employment results. Table 2 provides the characteristics and 15 9 6 description of the two groups (education participants and non-participants) and indicates whether or not they were significantly different on any of these variables (Lochner, 2004).

Sampling Procedure

Originally Maryland, Alabama, and Ohio volunteered to participate in the study but the logistics could not be worked out in Alabama. With Alabama unable to participate a third state was sought for the research, and consequently Minnesota volunteered. This gave us an opportunity to examine correctional education in a small prison population (Minnesota), a medium-size prison population (Maryland) and a large prison population (Ohio). We wanted a large enough sample to look at a number of different variables so we decided to select 1000 inmates from each state for a total of 3,000 inmates in the study group. To generate a release cohort, we selected the entire population of inmates being released within a specified time period rather than a sampling. In order to identify the release cohort, each state’s Department of Corrections was asked to generate a list of inmates who were going to be released during the next several months until a list of 1200 from each state was reached. Information included the inmates’ projected release date and the institutions from which they were being released. Over sampling was done to address those who might be released early and would not be available for the study. This list with the pertinent information was provided to the data collectors for each state. Table 1 shows that overall there were 3170 in the release cohort: 1373 (43.3%) correctional education participants and 1797 (56.7%) nonparticipants. Each state’s sample size is as follows: Maryland – 275 (31.1%) 14 15 participants and 610 (68.9%) non-participants; Minnesota 574 (54.6%) participants and 477 (45.4%) non-participants; and Ohio 524 (42.5%) participants and 710 (57.5%) nonparticipants. Having the opportunity to include over 3,000 offenders in the study, makes this research one of the largest and most comprehensive studies ever conducted assessing the impact of correctional education on post-release behavior.

Data Collection Instruments and Measures

There were five sources of data for this study three main data collection instruments and offender criminal histories and offender employment data. The three main instruments included the Pre-Release Survey, the Educational/Institutional Data Collection Form, and the Parole/Release Officer Survey

Inmate Pre-Release Survey

The pre-release survey is a self-report instrument which included questions designed to gather information on inmate demographics, family information, prior employment data, adult and juvenile criminal histories, educational experiences both prior to and during incarceration, participation in programs other than education, motivation questions, and release plans including post-release residence, employment and criminal justice information. The pre-release survey was comprised of sixty questions chosen to elicit information pertinent to recidivism factors and participation in educational programming. The questions covered the following areas:

a. Participant demographics including DOC number (used as the study participant identifier, age, gender, race, and area lived in prior to incarceration;

b. Family background including 12 questions on such topics as prior and current government assistance, marital status, number of dependents, number of children, visitation questions, and family criminal history;

c. Employment information, including six questions to determine the inmate’s prior work and wage history;

d. Criminal history, including eight questions on both juvenile and adult arrests and incarcerations including the age at first arrest, and types and numbers of commitments/incarcerations;

e. Educational experiences both prior to and during current incarceration, including seventeen questions on academic and vocational education and questions to assess satisfaction with correctional education programming;

f. Participation in other programs, including questions about involvement in substance abuse or sex offender treatment, institutional job assignments, and prison industry participation; 27 28

g. Motivation questions which included a series of 16 questions with Likert scale responses to find out why people participate or should participate in correctional education programs;

h. Release information, including seven questions about the inmate’s plans after release, employment prospects, housing arrangements, and documents needed for employment such as a photo id and legal social security number.

Educational/Institutional Data Collection Form

An instrument was developed to collect institutional/educational information about each inmate in the study sample. The data collected included the crime and sentence length of current incarceration, basic demographic information (race, gender and age), number of felony arrests and convictions, major institutional infractions as a measure of institutional adjustment, programming and employment while incarcerated, and prerelease information. While much of this information was requested of the inmates in the pre-release survey, we wanted to crosscheck as much of the data as possible for accuracy. We were also looking for any factors that might impact recidivism such as long-term substance abuse, mental illness, and unstable family backgrounds. Thus questions about the inmate’s involvement in these types of programs were part of this data collection instrument. We also included questions about the inmate’s participation in education programs/activities. The education records, for those subjects enrolled in academic and vocational education programs, included information about types of educational programs in which the inmate was enrolled (ABE, GED, Life Skills, Vocational Training, etc.), level of participation from first date of entry into the program to final exit from the program, the number of diplomas and/or certificates received, and whether enrollment was mandatory, court ordered, or voluntary. A Test of Adult Basic Education (TABE) score from the beginning of the inmate’s incarceration and an exit TABE score if 28 29 available was collected as well. Data for this instrument were collected for all study participants whether or not they were enrolled in correctional education programming. The educational/institutional data was collected by research assistants, teachers and/or caseworkers either at the institution or at the central offices of the states’ Department of Corrections. Each state was provided a scantron form with the questions described in the previous section (Data Instruments). Comment sections were included so that information not listed on the scantron form could be included. Training was provided to the various states on how the data was to be collected, how to read important information in the files, and how to report the data on the scantron form. In addition, the project’s director and researcher were available to answer questions during data collection. Some data elements were available electronically and were entered into an SPSS database, which was forwarded to the project researcher. All scantron forms were reviewed to collect information from the comment sections for later data entry.

Data Analyses

An SPSSpc database was created for the research. This database was designed with the ability to analyze the data for each state independently of one another or analyze data combined for all three states. The ability to combine all three states’ data elements allowed the researchers an opportunity to conduct more sophisticated multivariate analyses in addition to simple significance tests (t-tests and chi-square) by producing a larger sample needed for such tests. We set the alpha level at .01 rather than .05 to provide stronger evidence for making inferences about the data (Agresti and Finlay, 1986, p.147).

Data Collection Procedures

Inmate Pre-Release Survey

The pre-release survey was piloted with a group of inmates in Maryland to test the readability and clarity of the questions. The Flesch-Kincaid readability test had been conducted which showed a reading level of 6.1 for the survey instrument. While most of the questions posed no difficulty for the inmates, there were a few questions that were revised to address inmate concerns. The pilot study was also used to determine the length of time needed for inmates to complete the survey instrument. A video administration of the survey was also used to assist inmates with low reading skills, but inmates who did not experience any difficulty in reading the questions on the survey found the video administration much more of a hindrance than a help.

On average the survey took approximately 45 minutes for inmates to complete. 32 33 All data collection began with training the data collectors responsible for administering the pre-release survey. Training included question and answer sessions, demonstration of the video, a walkthrough of the questions on the survey, and a written detail of the protocol for collecting the data. Data collectors were encouraged to present the survey and provide explanations in a positive and enthusiastic manner in order to reduce the number of refusals. In addition, the video provided a short presentation by two inmates about the importance of the study and to encourage their fellow inmates to participate in the research. Teachers or Department of Corrections personnel administered most of the surveys in the three states. In Minnesota and Ohio, individuals were assigned as research assistants specifically to complete this task. In Maryland, because one institution was temporarily closed, teachers from that facility were used to collect the data from the other institutions. We made sure that no teachers were giving the pre-release survey to their own students. In addition the primary investigators for this study were on site at various times to ensure that the protocol was being followed and to monitor the administration of the survey instrument. The list of releasees and the institutions where they were located were obtained from each state’s Department of Corrections and provided to the data collectors. These data collectors traveled to the various institutions and requested from correctional staff that the list of releasees be brought to the area where the survey was to be administered.

The pre-release survey was administered in small group settings at the institutions where the inmates were being released. Each state released inmates from a number of different sites. Only those inmates who were mentally unstable or who were critically ill were not included as part of the release cohort. The decision was made that if the refusal rate were higher than 20% at any site additional data would be collected to compare the refusals with the study sample. Refusals were defined as those who did not want to participate 33 34 once the study and survey were explained to them. Most all sites provided some refreshments for those participating in the study. All potential participants were advised that the survey was strictly voluntary and that no sanctions would be used against those who did not want to participate (verbal informed consent). The time required to administer the surveys varied from state to state since the number of inmates being released each month was different for all three states. It took approximately two months to collect the data from Ohio, four months for Maryland, and one year for Minnesota.

References

Aizer, A., & Doyle Jr, J. J. (2015). Juvenile incarceration, human capital, and future crime: Evidence from randomly assigned judges. The Quarterly Journal of Economics130(2), 759-803.

Dodge, K. A., Bierman, K. L., Coie, J. D., Greenberg, M. T., Lochman, J. E., McMahon, R. J., … & Conduct Problems Prevention Research Group. (2014). Impact of early intervention on psychopathology, crime, and well-being at age 25. American journal of psychiatry172(1), 59-70.

Fella, G., & Gallipoli, G. (2014). Education and crime over the life cycle. The Review of Economic Studies81(4), 1484-1517.

Hjalmarsson, R., Holmlund, H., & Lindquist, M. J. (2015). The Effect of Education on Criminal Convictions and Incarceration: Causal Evidence from Micro‐data. The Economic Journal125(587), 1290-1326.

Lochner, L. (1999), Education, Work, and Crime: Theory and Evidence. Rochester Center for Economic Research Working Paper No. 465.

Lochner, L. and Moretti, E. (2001), The Effect of Education on Crime: Evidence from Prison Inmates, Arrests, and Self-Reports. NBER Working Paper No. 8605.

Lynch, J. et al. (1994), Profile of Inmates in the United States and in England and Wales, 1991, U.S. Department of Justice, Washington, DC

Moretti, E. (1999), Estimating the Social Return to Education: Evidence from Longitudinal and Cross-Sectional Data. Center for Labor Economics, University of California, Berkeley, Working Paper No. 22.

Petrosino, A., Turner, H., Hanson, T., Fronius, T., Campie, P., & Cooke, C. (2017). The Impact of the Safe and Successful Youth Initiative (SSYI) on City-Level Youth Crime Victimization Rates. Journal of MultiDisciplinary Evaluation13(29), 8-15.

Schuck, A. M. (2017). Evaluating the impact of crime and discipline on student success in postsecondary education. Research in Higher Education58(1), 77-97.

Steurer, Stephen J.; Smith, Linda G (2003) Education Reduces Crime: Three-State Recidivism Study. Executive Summary. Correctional Education Association. Retrieved: https://files.eric.ed.gov/fulltext/ED478452.pdf

U.S. Department of Education NCES (2007). Retrieved:

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