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Racial Disparities in Imprisonment by Ed A. Muñoz, Ph.D. Research Report No. 22
Abstract A racial/ethnic analysis of total adult male admissions in six Nebraska Department of Correctional Services (DCS) facilities for a 5-year period, from 1987 to 1991, shows Latino admissions almost doubling. Interestingly, the majority of Latino males sentenced to Nebraska penal facilities enter the system from Panhandle County, a sparsely populated rural agricultural county. Census data indicate that Latino prison admissions in Nebraska and, even more so, in Panhandle County are highly disproportionate to respective 1990 state and county population figures. In addition, a comparison of Latino imprisonment rates in eight counties with Latino populations of 1,000 or more shows Latinos entering the prison system at higher rates from smaller rural counties. Finally, bivariate and multivariate analyses of Panhandle County district court records point to a double standard of justice in Panhandle County favoring Anglos over Latinos and Native Americans. This publication was presented to the Graduate College faculty at the University of Nebraska, Lincoln, in partial fulfillment of requirements for the Master of Arts degree. It was prepared under the supervision of Professor Jay Corzine, 1992.
About the Author: Dr. Ed A. Muñoz Dr. Muñoz, a faculty member of Iowa State University's
expanding Latino Studies Program, refers to himself as a "Nebrasqueno"
- a Chicano born and raised in the heartland state of Nebraska.
He earned his B.A., M.A., and Ph.D. in sociology and is an assistant
professor at ISU.
SUGGESTED CITATION Muñoz, Eddie A. (Ph.D.). "Racial Disparities in Imprisonment Rates in Nebraska: A Case Study of Panhandle County," JSRI Research Report #22, The Julian Samora Research Institute, Michigan State University, East Lansing, Michigan, 1999. The Julian Samora Research Institute is committed to the generation, transmission, and application of knowledge to serve the needs of Latino communities in the Midwest. To this end, it has organized a number of publication initiatives to facilitate the timely dissemination of current research and information relevant to Latinos. The Julian Samora Research Institute Research Report Series (RR) publishes monograph length reports of original empirical research on Latinos in the nation conducted by the Institute's faculty affiliates and research associates, and/or projects funded by grants to the Institute. Table Of Contents
There is increasing concern over the growing crime rate that threatens the well being of all citizens in this country. Yet the incidence of crime varies from region to region, making it the task of researchers to locate high crime areas in order to ameliorate the underlying factors. Nevertheless, there is considerable methodological debate as to defining the best measure of criminal activity. Pope reminds us that studies using:
Undoubtedly, a major issue in the study of crime is the disproportionate representation of non-White racial/ethnic minorities in official crime statistics. Some feel this is a result of racial bias in the criminal justice system, despite inconsistent empirical evidence for this phenomenon (Georges-Abeyie, 1989, 1992; Hagan, 1974; Kleck, 1981; Zatz, 1987). Indeed the dichotomization of race has been a questionable phenomenon in criminal justice research (e.g. Georges-Abeyie, 1989, 1992; Perry, 1980; Kleck, 1981; Gordon, et al. 1987; Zatz, 1987). For the majority of criminological studies it is unclear whether "Black" includes other non-White racial/ethnic groups such as Latinos1, Native Americans, or Asians. To further complicate matters, Latinos are as varied in terms of ethnic identification as racial identification. Mexicans, Puerto Ricans, Cubans, and other Central and South Americans can and do racially identify as White, Black, Asian, and Native American according to U.S. Census data (U.S. Bureau of the Census, 1990). This Black/White racial dichotomy continues to blur ethnic distinctions between and within groups questioning the validity of previous research on race and crime (Georges-Abeyie, 1989, 1992). Researchers must also focus more on situation and interaction variables, or the context-specific nature of crime, along with individual variables such as race, sex, age, and class to explain differential crime statistics (Georges-Abeyie, 1989; Jefferson, 1988; Tagaki, 1981). Particularly important is the socio-historical relationship between non-White racial/ethnic groups and the U.S. legal system. For instance, Acuña (1981) documents how law enforcement authorities, such as the Texas Rangers, brutally tortured and killed Chicanos along the imposed U.S.-Mexico border in the latter part of the 19th Century and the early part of the 20th Century. This produced a deep lasting mistrust of law enforcement officials, which negatively influenced, and continues to negatively influence, relations between Anglos and Chicanos in this area to this very day (Escobar, 1988; Mazón, 1984; Mirande, 1987; Morales, 1972). Bridges and Crutchfield (1988) further posit that social, economic, and legal characteristics of states contribute to racial disparities in imprisonment rates. Their national study found the greatest Black/White disparity in imprisonment rates in the predominantly White, agricultural North Central region of the country, small wonder considering previous research results indicating that a county's structural characteristics affect White and non-White imprisonment rates. Bridges, Crutchfield, and Simpson specifically argue that:
Therefore, when other factors are equal, non-Whites are more likely to be sentenced to prison terms in non-urbanized counties, particularly if the non-White population is relatively large. Given this Urban/ Rural disparity, it seems apparent that research on race and crime would produce more fruitful results if counties were used as units of analysis, because there may be large intra-state variations in percentages of minority populations (Hawkins and Hardy, 1989). With these issues in mind, this study will explore the nature and scope of male racial/ethnic disparities in imprisonment rates in Nebraska.2 In addition, case study analysis of criminal court data in Panhandle County will provide insight as to whether, and to what degree, such disparities are due to differential arrest rates, processing, and/or sentencing practices by criminal justice officials. The study will emphasize the Latino criminal justice experience for two reasons: with the continued growth of the Latino population (Garcia and Montgomery, 1991) in the United States - demographic forecasters predict that the Latino population will surpass the Black population as the largest minority population early in the next century - research dealing with Latina/os can no longer be ignored; most important, however, this exploratory analysis will determine if "gringo justice," or a double standard of justice favoring Anglos over Chicanos (Mirande, 1987), is evident in the rural heartland of Nebraska. Prison Admissions in Nebraska | Data and Measurements | Bivariate Findings and Discussion | Regression Results and Discussion | Conclusion | Endnotes | References | Appendix A | Appendix B
Percentages of the racial/ethnic composition of total adult
male admissions in six Nebraska Department of Correctional Services
facilities during a 5-year period from 1987 to 1991 are shown
in Table 1. Black admissions rose from 22.23% to 27.5% of the
total; Latino admissions rose from 3.5% to 6.11%; Native American
admissions declined These figures are striking when examining 1990 Nebraska population
percentages by race/ethnicity in Table 2. A word of caution concerning
the classification of race in official statistics is in order.
The United States census data categorizes race as White, Black,
Native American, Asian, and "Other" in their statistical
reports, and includes a separate designation for people of Spanish
Origin within these five categories. Nevertheless, in Nebraska,
Whites constitute 93.8% of the total Nebraska population, Blacks
3.6%, Native Americans 0.8%, and Asians/Other 1.8%. Within the
total population of Nebraska, people of Spanish origin constitute
2.3% of the population. The state of Nebraska is divided into 93 counties with almost half of the total state population living in the counties of Douglas, Lancaster, and Sarpy. (Nebraska Natural Resources Commission, 1990) During the 5-year period under investigation, 33 different counties had at least one Latino male sentenced to a DCS facility. Table 3 contains data on Latino male admissions for eight counties with a Latino population of 1,000 or more persons. Table 4 shows selected population characteristics for these eight counties. In 1990, the proportion of the population that was Latino
in Panhandle County was 16%. This figure is well below the percentage
of Latino admissions for each of the five years observed in Table
3. The data also reveals that Panhandle County had the highest
percentage of Latino admissions in the state by far for four
out of the five years: in 1987, the Latino admission percentage
for Panhandle County was 22.58% with Lincoln County next at 16.13%;
in the peak year of 1988, Panhandle County led all other counties
with 37.5% followed by Lancaster and Lincoln Counties with 12.5%
each; in 1989, Panhandle County admissions for Latinos decreased
to 26.09% followed by Douglas County with 19.57%. However, in
1990, Panhandle admissions Moreover, after converting the admissions and population data
into rates in Table 5, results show considerable support for
the previous work by Bridges, Crutchfield, and Simpson (1987)
who found that county structural characteristics affect White
and non-White imprisonment rates. As alluded to earlier, Douglas,
Lancaster, and Sarpy Counties located in the southeastern part
of the state, are the three most populous counties, and for that
matter are also the most urban. In fact, Omaha, the largest metropolitan
area in the state with a total population over 300,000, is situated
in Douglas County. (United States Bureau of the Census, 1990)
The rates for Latino male admissions from these three counties
range from 0.0 to 5.3 per 1,000 Latino males for the 5-year period.
In comparison, not one of the other five counties listed has
a total population of 50,000. And when focusing on Panhandle
County, a predominantly agricultural, rural area in the western
Reported city crime figures obtained from the Nebraska Crime Commission Uniform Crime Reports (1988-90) show that the city of Panhandle in Panhandle County, with a population of 14,308 in 1988, had the highest crime rate of 79 offenses per 1,000 population. In 1989, South Sioux City in Dakota County, with a population of 9,773, was first with a crime rate of 70 offenses per 1,000 population. The city of Panhandle tied for fourth at 65 per 1,000 population. But once again in 1990, Panhandle led the crime rate with 79 offenses per 1,000 population. Could racial disparities in imprisonment rates be due to the fact that some areas are just simply high crime areas? But with all things being "equal," would not logically then, male admission percentages into DCS very closely resemble population percentages of males 18 years or older for a county?
The fact that male admissions to the Department of Correctional Services are racially disproportionate in Panhandle County, and the significant size of the Latino population in Panhandle County, raise important questions regarding whether the criminal justice system has provided all convicted offenders a "fair trial?" On the one hand, it is impossible to determine the "true" crime rate due to undetected and/or unreported criminal activity. On the other hand, one can determine if racial differences in criminal justice processing occur. In order to answer this question, data from criminal court records were collected in order to determine whether or not there are differential practices by race/ethnicity of offender in court processing and sentencing. Prison Admissions in Nebraska | Data and Measurements | Bivariate Findings and Discussion | Regression Results and Discussion | Conclusion | Endnotes | References | Appendix A | Appendix B Data for the second part of this study were collected from the Panhandle District Court criminal case records by the author during the fall of 1991 and the winter of 1992. As these data are public information in the state of Nebraska, they were easily accessible by making a phone request to the Clerk of the District Court Office. Felony criminal cases tried by the District Court during the 5-year period 1987-1991 were necessarily chosen as units of analysis on the basis that only convicted felons are admitted to DCS. Inspection of the criminal court index, an approximately two-by-three foot binder, provided the volume and page number of felony criminal court cases referenced in appearance dockets. Appearance dockets then provided case file numbers for felony court proceedings on offenses such as murder, sex, drugs, assault, property violations, and a myriad of other crimes. Female felony convictions were omitted to their near absence in number. This selection process generated 453 individual cases for a 5-year period. Case files provided detailed information on types of offenses and number of charges for each specific offense; the type and amount of bond; whether the accused was represented by a private lawyer or public defender; whether the amount of bond had increased or decreased; the initial plea of the accused at arraignment; whether or not plea bargaining had occurred between the state and the defendant, and if so, the stipulations of the plea agreement; whether or not the case was forwarded to a jury; the final court verdict; whether or not a pre-sentence had been ordered by the court; and finally, terms of the sentence delivered. Unfortunately, previous criminal records of accused individuals were not available from the data. All the variables were readily recognizable through documents contained in the court files. The variable, race of the offender, was largely determined by the author and requires elaboration. The only official indication of race of an offender was found in an often difficult to read duplicate copy of a document stipulating the terms of the sentence found in the latter section of the case file. Whites and Latinos were categorized with either a "W" or a "C," meaning White or Caucasian in the court records. "B" was used for the very few Blacks involved, and "I" for Native Americans. It is important to note that this document, with the indicator of race, was not used in the year 1987, but was placed in use sometime in 1988. Therefore, the first criterion used by the author to categorize race was an offender's surname. Obvious Spanish surnames (e.g., Muñiz, Rivera) were categorized as Latino. In addition, individuals with traditional Native American names (e.g., Dances With Wolves, Spotted Owl) were categorized as Native American. As one might expect, surnames are not the most reliable indicator of race. Omission of proper accent marks could easily give a Spanish surname the appearance and subsequent resonance of an Anglo surname (Tarin vs. Tarín). In addition, other European surnames are very likely to be products of past and present biracial conjugal relationships, and as well, past attempts of forced assimilation of Native Americans by Whites. To compensate for these ambiguities, attention was given to other names listed in documents, particularly witness lists. If a witness list contained a considerable number of traditional Spanish or Native American surnames, then it was assumed that the offender was of Latino or Native American heritage. After the first day of data collection, the author devised a columnar tally sheet to aid in recording of data. Appendix A shows the coding scheme for the variables derived from the raw data. Upon completion of data collection, the raw data were then transformed into computer readable form for analysis. The data file includes 20 independent variables and seven dependent variables for analysis. For the sake of simplicity in interpreting results, Appendix B lists the variables under analysis after data transformation, and reflects the collapsing of selected continuous and/or categorical variables. Grouping the 199 total possible charges derived from the raw data into six offense types created categories for the independent variables most serious offense (MSERIOUS) and next most serious offense (NSERIOUS). The category "other crimes," consisting of charges dealing with insufficient funds, forgery, carrying a concealed weapon, stolen cattle, etc., is coded 1. The category "property offense" is coded 2, "assault and other personal offense" is 3, "drug offense" is 4, "sexual offense" is 5, and, finally, "murder" is 6. There may be some issue as to the rank of severity assigned to the categories. Choices were subjectively based upon which crimes would more likely result in admittance into one of the six DCS male facilities, and the severity of the crime for the victim and/or the accused. Lizotte (1978, p. 569) argues that judges' perceptions are influenced by the seriousness of the crime which:
For example, murder and sexual crimes are severely damaging to the physical wellbeing of the victim, hence, a need for harsher sentencing for the accused if found guilty. Drug offenses, while "victimless" crimes, have an enormous potential for physical damage and, within the current "War on Drugs" campaigns, are perceived by society as the leading contributor to violent crimes. Assault and property crimes are evaluated by severity depending on the amount of physical and financial damage incurred. Assuming that the total number of offenses will have an effect on sentencing, and in order to limit confusion among variables, a total number of charges (TOTOFF) variable was created by adding COUNTS1, COUNTS2, and COUNTS3 from the raw data, and then collapsing the resulting numbers into four categories. NBNDAMT and NCREDIT are collapsed continuous variables respectively for bond amount and for days credit for time served. Values for TOTOFF, NBNDAMT, NCREDIT, and the remaining independent categorical variables (RACE, BOND, BONDCHGE, PLEA, NEWDEAL, and JUDGE) are listed in Appendix B.4 A final note concerning the reporting of race for the study is necessary. The author chose to expand the scope to include analyses of Native American sentencing patterns because of the extraordinarily high Native American imprisonment rate in Panhandle County (see Table 6). After collecting and tabulating racial data from Panhandle District Court criminal cases, Native Americans constituted almost 10% of the cases. The extremely minimal number of cases involving Blacks and Asians were included in the Native American and White categories, respectively.5 Dummy variables for whether or not an interpreter was employed (BILING), whether or not a plea bargain was negotiated (BARGAIN), whether or not the case was tried by jury (JURY), and whether or not a pre-sentence investigation was ordered by the court (EVAL), were coded 0 = Yes and 1 = No. This was based on the assumptions that having an interpreter (if necessary), entering into plea negotiations, having a jury trial, and having a pre-sentence evaluation conducted, would lessen chances of incarceration, as well as the severity of the sentence. Along similar reasoning, final verdict (FINAL), was coded 0 = Not Guilty and 1 = Guilty, while defense attorney (ATTORNEY) was coded 0 = Private Lawyer and 1 = Public Defender. Dependent variables for the study were operationalized and
ranked by the type and severity of the punishment delivered by
the two judges of the Panhandle District Court. For instance,
if probation (SENTI) was the only type of punishment delivered,
then the length of probation in years is reported. Next, assuming
that having to pay a fine and/or restitution would be more serious
than only probation, NSENTII is categorized by amount of fine
and/or restitution in dollars. A sentence of intensive probation
constituted the next dependent variable SENTIII. As with SENTI,
SENTIII is reported as duration of probation in years. However,
the difference is that SENTIII involves a combination of probation,
fine and/or restitution, community service, and/or electronic
monitoring. Finally, in order to interpret bivariate crosstabulations more easily, ALBOTE, JAIL, and PRISON were created by whether or not SENTIV, SENTV, NSENTVI, and NSENTVII were meted out as punishment. If jail time (SENTIV or SENTV) or prison (NSENTVI or NSENTVII) are reported, then ALBOTE, or incarceration to either county jail or Department of Correctional Services (DCS), is recorded as "yes." If, however, only incarceration into Panhandle County Jail (SENTIV or SENTV) is reported, then JAIL is "yes." Similarly, if incarceration into DCS (NSENTVI or NSENTVII) is reported, then PRISON is recorded as "yes." Prison Admissions in Nebraska | Data and Measurements | Bivariate Findings and Discussion | Regression Results and Discussion | Conclusion | Endnotes | References | Appendix A | Appendix B Bivariate Findings and Discussion
opportunity. Nonetheless, with the current "War On Drugs" campaign throughout the nation, this could be a major contributor to the dramatic increase of Latino admissions into DCS. An alarming picture is portrayed by the data in regards to Native Americans and the criminal justice system. Not one Native American arraigned on felony criminal charges in Panhandle County District Court had a jury trial or a private attorney for their defense (p < .001). Furthermore, about one-fourth of the Native Americans processed in the 5-year period entered a plea of guilty at arraignment (p < .10). While this information may suggest a state of hopelessness for Native Americans, it surely suggests the lack of economic resources for the best legal defense possible. Not surprisingly, Whites (31%) have better economic resources for legal defense, as indicated by the high proportion of individuals employing private attornies. Interestingly, Latinos have the highest proportions of individuals choosing jury trials (17.6%) and pleading not guilty at arraignment (84.7%). Regardless, Latinos have the highest proportion of individuals receiving jail or prison sentences (68.9%) as shown by the variable ALBOTE in Table 8. But when disaggregating county JAIL sentences from PRISON sentences, Native Americans (50%) have the highest proportion of individuals receiving county jail sentences, while Latinos (39.1%) have the highest proportion of individuals receiving prison sentences. Thus far, support for a double standard of justice in Panhandle County based on race/ethnicity is moderately strong. Let us turn to multivariate regression analyses to more appropriately determine the strength and direction of statistical associations. Prison Admissions in Nebraska | Data and Measurements | Bivariate Findings and Discussion | Regression Results and Discussion | Conclusion | Endnotes | References | Appendix A | Appendix B Regression Results and Discussion Previous research has found that the race/ethnicity of an
accused, the judge, the seriousness of the crime, the type of
attorney (public defender vs. private lawyer), and the amount
of bail affect the length of sentencing given to convicted offenders
(Lizotte, 1978). I propose that the total number of offenses
a person is charged with could also have an effect on the perceived
seriousness of the crime, thereby affecting incarceration and
length of sentence. For the purpose of this study, race of an
offender was transformed into two dummy variables LATINO and
NATIVE AMERICAN (0 = no; 1 = yes) with White offenders excluded
as the comparison group. The Latino population in Panhandle County
is relatively large and a number of cases indicated the use of
an interpreter designated by the variable BILING. Hence, the
independent variables BILING, LATINO, NATIVE AMERICAN, JUDGE,
TOTOFF (total offenses), MSERIOUS (crime type), ATTORNEY, JURY,
and NBNDAMT (bond amount) were entered into regression models.
Because the focus is on imprisonment, whether or not an accused receives incarceration into either the county jail or prison (ALBOTE) is the first dependent variable selected for analysis. In addition, the length of sentence into the county jail (SENTIV), and the length of sentence into prison (NSENTVI) will also be used as dependent variables for the equations. ALBOTE is a dichotomous dependent variable, and "When the probability of falling to either of the two groups represented by the values of the dependent variable lies within the range of .25 to .75, the relationship between the log-odds and probability is approximately linear and a linear function yields reliable information concerning the relative importance of predictor variables" (Cleary and Angel 1984, p. 343). The frequency distribution for ALBOTE is 37.1% "no" and 62.9% "yes."
Table 10 shows the effects of independent variables on the
length of county jail time (SENTIV). Only plea-bargaining can
account for the significantly longer jail sentences in non-jury
cases (p < .005). Defendants in Panhandle County must view
county jail time as less severe than prison time, which could
lend to a more cooperative In contrast, race variables have no significant effects on the length of prison time as depicted in Table 11. Also in contrast to previous results, having Judge Y hear your case significantly increases the length of a prison sentence (p < .005). However, the amount of bond (NBNDAMT) has the strongest significant effect (beta = .235, p < .005) on length of prison time, implicating the severity of crimes punished. Further support for this contention manifests in significantly increased prison sentences for more serious crimes (MSERIOUS p < .005). Earlier plea-bargaining arguments can also explain less prison time for non-jury cases (p < .01). And just as having a public defender for legal defense significantly increases the chance of incarceration, it also significantly increases prison time (p < .01). Prison Admissions in Nebraska | Data and Measurements | Bivariate Findings and Discussion | Regression Results and Discussion | Conclusion | Endnotes | References | Appendix A | Appendix B Previous sentencing research shows that criminal adjudication may be more capricious for non-White racial/ethnic minorities in non-urbanized counties where they comprise a relatively large proportion of the population (Bridges and Crutchfield 1988; Bridges, Crutchfield, and Simpson 1987; Hawkins and Hardy 1989). Nebraska Department of Correctional Services data for the years 1987-1991 provide support for this contention, as Latinos from sparsely populated non-urban counties account for the majority of Latino prison admissions in the state. In addition, 1990 Nebraska census figures demonstrate a high degree of disproportionality with respect to Latino prison admissions and their total state and county male populations.
In contrast, Latinos are more dispersed throughout the state.
They are more likely to be visible in rural areas due to the
fact that Nebraska, for the most part, has an agriculturally
based economy. There is a great deal of seasonal farm work, along
with livestock producing and processing, occupations often filled
by Latinos. There are certain pockets in the state where many
Latino families settled after years in the migrant farm labor
stream and through employment with railroad companies. This is
the case for Panhandle County, where the highest proportion of
Latinos resides. Peculiar, however, is the high crime rate per
1,000 population during a portion of the time period investigated
(Nebraska Crime Commission, 1988-1990), which could in part account
for the exorbitantly high proportion of Latino prison admissions
from the county. However, case study analysis of Panhandle District Court records suggest bias in criminal sentencing decisions. Although Latinos were arraigned on a fewer number of charges than their White counterparts, the types of offenses were more severe. Of special interest is the higher proportion of Latinos pleading not guilty at arraignment and choosing to have their case heard by a jury, rather than plea-bargaining. Yet Latinos have higher proportions of individuals receiving a sentence of incarceration, and more specifically, state prison rather than county jail sentences, when convicted of felony charges. Multivariate regression analyses provide a clearer picture of sentencing processes. That Latinos were significantly more likely to receive a sentence of incarceration rather than probation when convicted on felony charges, even when controlling for a number of legal variables supports the contention of a double standard of justice for Latinos and Anglos. However, Native Americans received significantly longer county jail sentences than Latinos or Whites. Race did not factor significantly in the length of prison sentences. Regression results also showed that there are significant differences in sentencing decisions between judges and that having a private lawyer significantly decreased punishment severity. The seriousness of the crime had significant positive effects on the length of prison sentences, as one expects. What seems to be at issue and worthy of more attention in sentencing decisions is the plea-bargaining process. Findings indicate that having a jury trial is disadvantageous in the adjudication process, suggesting that an accused should cooperate during criminal processing in order to insure leniency in punishment (i.e., plead guilty and/or provide information to investigators for leniency). Although case study results cannot be generalized to represent the overall criminal justice experience, they do provide a stepping point for future research. Namely the respecification of regression models to better account for the variance in sentencing decisions. Logistic regression models should also include controls for plea-bargaining in order to determine the risk of incarceration for those found guilty of felony offenses. The same can be said of ordinary least square regression models on length of sentence variables. Models should also test for interaction effects between ethnicity and type of offense variables. It could be that Latinos are specifically targeted for crimes that warrant severe punishment. Perhaps, in the long run, Bridges, Crutchfield, and Simpson (1987) are right in arguing that Latinos are starting to pose a threat to the political and economic hegemony of the dominant White population in some areas. Given the nature of the numbers uncovered in this project, it seems logical to speculate that if this is so, Native Americans compound this threat even more. If Latinos and Native Americans are perceived to be a threat in Panhandle County, are criminal justice officials using the courts to keep Latinos and Native Americans in their place? In-depth interviews with male prison inmates from Panhandle County would perhaps be a good place to look for insights into the context-specific nature of Panhandle County criminal justice. Prison Admissions in Nebraska | Data and Measurements | Bivariate Findings and Discussion | Regression Results and Discussion | Conclusion | Endnotes | References | Appendix A | Appendix B 1. Unless otherwise specified, Latino and Latinos will be used interchangeably with Hispanic and Hispanics. They are umbrella terms for individuals of Mexican, Cuban, Puerto Rican, and other Latin American heritages. Likewise, Chicano and Chicanos will be used interchangeably with Mexican and Mexican Americans. Feminine forms of these nouns (i.e., Latina, Chicana, etc.) will be used when appropriate. 2. While crime by females is a growing concern, their omission from the study is based on their low numbers of admissions into the Nebraska Department of Correctional Services (DCS) institutions. DCS admissions data show only 20 females were admitted from Panhandle County for the fiscal years 1987-1991. 3. Judy Eggers, data programming specialist at the Nebraska Department of Correctional Services (DCS) central office, provided admissions data from the six DCS male facilities for the fiscal years 1987-1991. 4. PLEA is a defendant's plea at arraignment, while NEWDEAL is the outcome of plea negotiations. 5. If an error was made in categorizing, it would be in favor of Whites and diminish the impact of results found for Latinos and Native Americans. 6. ALBOTE is a Spanish contraction (a el bote) which literally means to the can. Figuratively, ALBOTE means to go to jail or prison. 7. See Lizotte (1978) also for a discussion on operationalization of variables. 8. Whether an accused chose to plea bargain (BARGAIN) was left out of the equation because of the high correlation whith JURY (-0.686). Prison Admissions in Nebraska | Data and Measurements | Bivariate Findings and Discussion | Regression Results and Discussion | Conclusion | Endnotes | References | Appendix A | Appendix B Acuña, Rodolfo. 1981. Occupied America A History of Chicanos, Second Edition. New York: Harper & Row. Bridges, George S., and Robert S. Crutchfield. 1988. "Law, Social Standing, and Racial Disparities in Imprisonment." Social Forces 66: 699-724. Bridges, George S., Robert D. Crutchfield, and Edith E. Simpson. 1987. "Crime, Social Structure and Criminal Punishment: White and Nonwhite Rates of Imprisonment." Social Problems, 34: 345-361. 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"Defining Race, Ethnicity, and Social Distance: Their Impact on Crime, Criminal Victimization, and the Criminal Justice Processing of Minorities." Journal of Contemporary Criminal Justice 8(2): 100-113. Gordon, Randall A., Thomas A. Bindrim, Michael L. McNicholas, and Teresa Waldon. 1987. "Perceptions of Blue-Collar and White-Collar Crime: The Effect of Defendant Race on Simulated Juror Decisions." The Journal of Social Psychology 128: 191-197. Hagan, John. 1974. "Extra-Legal Attributes and Criminal Sentencing: An Assessment of a Sociological Viewpoint." Law and Society 8: 357-383. Hawkins, Darnell. 1986. "Black and White Homicide Differentials: Alternatives to an Inadequate Theory." Homicide among Black Americans, edited by Darnell Hawkins, Pp. 109-135, Lanham, MD: University Press. Hawkins, Darnell F., and Kenneth A. Hardy. 1989. "Black-White Imprisonment Rates: A State by State Analysis." Social Justice. 16: 75-94. Jefferson, Tony. 1988. "Race, Crime, and Policing: Empirical, Theoretical and Methodological Issues." International Journal of the Sociology of Law, 16: 521-539. Kleck, Gary. 1981. "Racial Discrimination on Criminal Sentencing: A Critical Evaluation of the Evidence with Additional Evidence on the Death Penalty." American Sociological Review, 46: 783-805. Lizotte, Charles. 1978. "Extra-Legal Factors in Chicago's Criminal Courts: Testing the Conflict Model of Criminal Justice." Social Problems, 25: 564-580. Mazón, Mauricio. 1984. The Zoot-Suit Riots. Austin: University of Texas Press. Mirandé, Alfredo. 1987. Gringo Justice. Notre Dame: University of Notre Dame Press. Morales, Armando. 1972. Ando Sangrando (I Am Bleeding). La Puente, California: Perspectiva Publications. Nebraska Crime Commission. 1988-1990. Crime in Nebraska. Uniform Crime Reports. Lincoln, Neb. Nebraska Natural Resources Commission. 1990 Nebraska Census Data. Lincoln, Neb. Perry, Ronald W. 1980. "Social Status and the Black Violence Hypothesis." The Journal of Social Psychology 111: 131-137. Pope, Carl E. 1979. "Race and Crime Revisited." Crime and Delinquency 25: 347-357. Radelet, Michael L. 1989. "Executions of Whites for Crimes against Blacks: Exceptions to the Rule?" Sociological Quarterly 30: 529-544. Sampson, Robert J. 1987. Urban Black Violence: The Effect of Male Joblessness and Family Disruption." American Journal of Sociology 93: 341-382. Tagaki, Paul. 1981. "Race, Crime, and Social Policy: A Minority Perspective." Crime and Delinquency 27: 48-63. Tierney, John. 1988. "Viewpoint-Romantic Fictions: The Re-Emergence of Crime as Politics Debate." Sociological Review 36: 133-145. Trujillo, Larry. 1983. "Police Crimes in the Barrio." History, Culture and Society: Chicano Studies in the 1980's, edited by M. Garcia et al. Ypsilanti, Michigan: Bilingual Press. Pp. 199-242. 1974. "La Evolución del 'Bandido' al 'Pachuco': A Critical Examination and Evaluation of Criminological Literature on Chicanos." Issues in Criminology, 9: 43-67. United States Bureau of the Census. 1990. "1990 Census of Population and Housing Summary Tape File 1A." C 3.282:990, Green Disk No. 12. Zatz, Marjorie S. 1987. "The Changing Forms of Racial/Ethnic Biases in Sentencing." Journal of Research in Crime and Delinquency 24(1): 69-92. Prison Admissions in Nebraska | Data and Measurements | Bivariate Findings and Discussion | Regression Results and Discussion | Conclusion | Endnotes | References | Appendix A | Appendix B
Prison Admissions in Nebraska | Data and Measurements | Bivariate Findings and Discussion | Regression Results and Discussion | Conclusion | Endnotes | References | Appendix A | Appendix B Appendix B
Prison Admissions in Nebraska | Data and Measurements | Bivariate Findings and Discussion | Regression Results and Discussion | Conclusion | Endnotes | References | Appendix A | Appendix B JSRI Home | JSRI Research & Publications | Institute Research Reports |
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Even though Pope (1979) warns
of the selection bias in official crime data statistics, prison
admission rates are one of the most reliable indicators of criminal
activities, and even more so, of criminal justice system activities.
In order to be admitted into a state correctional facility, an
individual must have been convicted of a crime in a district
court. Therefore, an analysis of the racial composition of adult
male admissions in six Nebraska Department of Correctional Services
(DCS) facilities for the fiscal years 1987-1991 was performed
to determine the character of racial/ethnic disparity in imprisonment.
In addition, 1990 Nebraska census data is employed to determine
extent of racial/ethnic disproportionality. Latino county population
figures are then used to ascertain the existence of gringo justice.
from
4.51% to 3.88%; and Anglo admissions declined from 69.19% to
62.01%. Latino admissions witnessed the greatest proportional
increase, nearly doubling in five years.
climbed
back to 30.0% followed by Douglas once again with 18.57%; finally,
in 1991 Panhandle County's 21.62% Latino male admission percentage
was narrowly surpassed by Douglas County's 22.97%.
part of the state, the Latino
admission rate ranges from 4.7 (in 1987) to 14.2 (in 1989 and
1990) per 1,000 Latino males during the five-year period. In
addition, Dakota - the county with the second highest percentage
of Latinos in the state seems to be experiencing a similar increase
in Latino admissions with a rate of 0.0 in 1987 and 17.8 in 1991.
This is far from the case when
isolating Panhandle County individually. Data for the 5-year
period in Table 6 shows that White males accounted for 82.5%
of the total male population 18 years and older, but only accounted
for 50.7% of admissions into DCS. In contrast, Latino males accounted
for 10.8% of the male population 18 years and older, however,
they accounted for 35.9% of male admissions into DCS. This pattern
is consistent for all other minority populations in the county.
Finally, after once again converting the data into rates, the
disparities are even more pronounced. The White admission rate
is 9.8 per 1,000 White adult males, while the Latino admission
rate is 52.9 per 1,000 Latino males. An interesting finding to
note in the data is the Native American admission rate of 171.2
per 1,000 adult Native American males in Panhandle County!
Bivariate crosstabular analyses
were performed on various combinations of the variables described
above. Significant relationships were found between the extra-legal
variable race and six of the legal variables. Results in Table
7 show that Whites have higher proportions of individuals being
charged with multiple offenses (p < .05). In fact, over 56%
of White felony defendants were originally charged with two or
more offenses, compared to 45% of Latino defendants and 39.1%
of Native American defendants (p < .05). This finding fails
to support the contention of racial/ethnic bias in arrest procedures.
However, Latinos (51%) have a significantly higher combined proportion
(p < .05) of individuals charged with crimes more serious
than "other," and property crimes, in comparison to
Whites (36.7%) and Native Americans (26.1%). Perhaps the seemingly
high Latino involvement in drug related activity is an indication
of limited economic 
As shown in Table 9, Latinos
are significantly more likely to receive a sentence of incarceration
(ALBOTE) for the conviction of a felony offense in comparison
to Whites or Native Americans (p < .005). Having Judge Y (coded
2) rather than Judge X (coded 1) hear your case significantly
decreases the chances for incarceration (p < .01). Having
a public defender for defense in criminal court significantly
increases the likelihood for incarceration (p < .05). Interestingly,
not having your case tried by a jury significantly increases
the likelihood of incarceration (p < .05). In addition, as
the seriousness of the crime increases the likelihood of incarceration
decreases (p < .05). Plea-bargaining may be mediating these
two paradoxical findings.
adjudication
process - plead guilty and don't do prison time. Consistent with
findings on incarceration, having Judge Y hear your case decreases
the length of jail time (p < .05). However, Native Americans
receive significantly longer jail sentences than both Latinos
and Whites (p < .005), though Latinos receive significantly
longer jail sentences than Whites (p < .005).
To further illustrate these findings,
let us consider a few characteristics of the state. The population
of the state is almost 95% White, with Blacks and Latinos constituting
the two largest minority groups in the state. However, their
population distribution within the state is very different: the
majority of the Black population is concentrated in Omaha, the
largest urban center in the state, with a smaller concentration
in Lincoln, the capital and home of the University of Nebraska.
Other than these two eastern cities in Nebraska, the Black population
is sparse throughout the rest of the state. Naturally, Black
admissions are almost exclusively from these large urbanized
counties.
