Journal of Contemporary Criminal Justice - SAGE - the natural home

http://ccj.sagepub.com

Criminal Justice Journal of Contemporary

DOI: 10.1177/1043986208319453 Jun 19, 2008;

2008; 24; 399 originally published onlineJournal of Contemporary Criminal JusticeBrenda Sims Blackwell, David Holleran and Mary A. Finn

Differences in SentencingThe Impact of the Pennsylvania Sentencing Guidelines on Sex

http://ccj.sagepub.com/cgi/content/abstract/24/4/399 The online version of this article can be found at:

Published by:

http://www.sagepublications.com

can be found at:Journal of Contemporary Criminal Justice Additional services and information for

http://ccj.sagepub.com/cgi/alerts Email Alerts:

http://ccj.sagepub.com/subscriptions Subscriptions:

http://www.sagepub.com/journalsReprints.navReprints:

http://www.sagepub.com/journalsPermissions.navPermissions:

http://ccj.sagepub.com/cgi/content/refs/24/4/399 Citations

at SAGE Publications on October 15, 2009 http://ccj.sagepub.comDownloaded from

http://ccj.sagepub.com/cgi/alerts

http://ccj.sagepub.com/subscriptions

http://www.sagepub.com/journalsReprints.nav

http://www.sagepub.com/journalsPermissions.nav

http://ccj.sagepub.com/cgi/content/refs/24/4/399


399

Journal of ContemporaryCriminal Justice

Volume 24 Number 4November 2008 399-418© 2008 Sage Publications

10.1177/1043986208319453http://ccj.sagepub.com

hosted athttp://online.sagepub.com

The Impact of the Pennsylvania Sentencing Guidelines on Sex Differences in SentencingBrenda Sims BlackwellGeorgia State University, AtlantaDavid HolleranThe College of New Jersey, EwingMary A. FinnGeorgia State University, Atlanta

Although it has been argued that sentencing guidelines reduce the favorable treatmentafforded female offenders, only one study has directly theoretically assessed the impactof guidelines on sentencing outcomes for men versus women. This study examines theinfluence of guidelines on the outcomes of male and female defendants sentenced inPennsylvania by examining three periods, including one period during which guide-lines were suspended. Results indicate that female, compared to male, offenders wereless likely to be incarcerated in jail or prison and received shorter sentences in all peri-ods; differences were not greatest when guidelines were suspended. Findings suggestthat Pennsylvania’s structured sentencing model has not affected the sex–sentencingrelationship in that state.

Keywords: sentencing; gender; sex; sentencing guidelines

Research on the impact of gender on criminal justice processing generally hasconcluded that women are treated more leniently than men throughout all

stages of the process (Daly, 1994; Kruttschnitt, 1996; Spohn & Beichner, 2000;Steffensmeier, Kramer, & Streifel, 1993). With the exception of violent crimes,women are less likely than men to be incarcerated and receive shorter terms of incar-ceration (Kruttschnitt, 1984; Kruttschnitt & Green, 1984; Steffensmeier et al., 1993).Beginning in the early 1980s, changes in female and male imprisonment rates indi-cated that the trend favoring female offenders was dissipating; the incarceration ratefor females was expanding at a rate almost double that of males (Chesney-Lind &Pollock, 1995; U.S. Department of Justice, 1999). Multiple explanations for theshifts were advanced. Some posited that changes in state-level sentencing, such asadoption of standardized decision-making models, which limited judicial and exe-cutive branch influences on sanction type and length (Steffensmeier et al., 1993) andmodification of criteria considered relevant for determining sanction type and length(Chesney-Lind, 1987), contributed to these changes.



400 Journal of Contemporary Criminal Justice

Since 1980, sentencing in the United States has grown increasingly punitive andmore bureaucratized (Clear, 1994). This is exemplified by the move of several statesto ensure greater certainty and uniformity in sentencing by the elimination of inde-terminate sentencing and implementation of structured sentencing models (Chesney-Lind, 1987; Daly & Tonry, 1997; Ulmer, 1997). State-level changes included theadoption of sentencing guidelines, determinate sentencing structures, mandatory mini-mum sentencing statutes, habitual offender laws, and truth-in-sentencing laws. Allintroduced formal legal rationality (Savelsberg, 1992) by limiting judicial discretionin sentencing, focusing the criteria for punishment on the severity of the currentoffense and the defendant’s prior record. Reforms were extensive; although everyjurisdiction in 1970 had indeterminate sentencing, by the mid-1990s only 27 statesand the District of Columbia retained such sentencing schemes (Spohn, 2002, p. 224).Reforms advanced both retributive and utilitarian goals. It was believed that throughsentencing reforms, reduction in racial and class sentencing disparities and desiresto “get tough on crime” could be simultaneously accomplished (Chesney-Lind,1987). Numerous scholars argued, however, that one consequence of this bureaucra-tization of sentencing, particularly sentencing guidelines that preclude considerationof defendant’s sex, could be less favorable sentences for women (Chesney-Lind &Pollock, 1995; Daly, 1994, Steffensmeier et al., 1993).

Little research has directly explored the validity of this claim. Rather, the claimhas been indirectly supported by documenting that female incarceration rates increasedfaster than those for males during the time frame of sentencing reforms (Chesney-Lind & Pollock, 1995; Daly, 1992). Research comparing sentence severity beforeand after enactment of guidelines reported that both percentages of offenders incar-cerated and mean sentence lengths increased (Spohn, 2002, pp. 264-271). To date,however, only one study (Koons-Witt, 2002) has had as its direct theoretical focusthe impact of sentencing guidelines on sex differences in sentencing.1 Because thisstudy was limited to a single jurisdiction, Minnesota, a need remains to explorewhether enactment of guidelines in additional jurisdictions differentially affectedmale and female offenders. This study examines sex disparity patterns in Pennsylvaniaacross three periods differentiated by the presence and the absence of sentencingguidelines to determine if guideline implementation affects the type and duration ofsentences imposed on males and females.

Offender Sex and Sentencing: Explanations for Disparity

The study of the impact of offender sex on criminal justice processing gainedpopularity in the 1970s, with research purporting that females were less criminal andwere treated more leniently in criminal justice processing than were males. Indeed,females were less likely to be arrested, convicted, and incarcerated than were theirmale counterparts (Daly, 1994; Daly & Bordt, 1995; Kruttschnitt, 1996; Steffensmeier



et al., 1993); moreover, when incarcerated, women received shorter sentences thandid men (Steffensmeier et al., 1993). Explanations for this differential treatment haveincluded paternalism (e.g., Ulmer, 1997) or chivalry, judicial focal concerns (e.g.,Steffensmeier, Ulmer, & Kramer, 1998; also see Albonetti, 1997), and bureaucrati-zation of sentencing (e.g., Koons-Witt, 2002).

Early explanations for lenient treatment of female offenders included paternalismor chivalry (Daly, 1989; Moyer, 1992). The chivalry hypothesis assumes that “ladies”do not share equal status with men and are considered less capable than men of com-mitting criminal acts, yielding leniency (Belknap, 2001). The paternalism thesis, incontrast, attributes lenient treatment of females to beliefs that females are weak,powerless, and dependent; in other words, females are less capable than males ofcommitting criminal acts, particularly by themselves. Most scholars referencingthese hypotheses have not distinguished between them (for exceptions, see Moulds,1978; Nagel & Hagan, 1983), primarily because such an outcome is difficult todetermine (Belknap, 2001), and the ultimate prediction is the same—women shouldbe less likely to receive a sentence of incarceration and, if incarcerated, shouldreceive a shorter sentence than men.2

More recently, generalized stereotypes regarding females have been incorporatedinto the focal concerns framework. Steffensmeier et al. (1998) noted that sex, as wellas race, age, and class, likely plays a role in sentencing decisions, albeit in an indi-rect manner as judges consider the defendant’s attributes and his or her offenseswhen rendering a sentencing decision. The focal concerns framework suggests thatwhen meting out justice, judges are concerned with the defendant’s degree of blame-worthiness, the threat posed by the defendant to the community, and the practicalconsequences of imposing various sanctions (Steffensmeier et al., 1993). When con-sidering these concerns, judges rely on the defendant’s current crime and priorrecord as well as generalized stereotypes based on the defendant’s race, gender, age,and/or social class. This framework offers numerous explanations for the lenienttreatment of women compared to men. Women are seen as less dangerous, henceposing a lower threat to public safety. Furthermore, when practical consequences forfemale incarceration are considered, costs are viewed as higher for females thanthose for males. Females, for example, are more likely to be the primary caretakersof their children. In sum, when considered individually or as a whole, focal con-cerns, based on stereotypes about female offenders, serve to lessen the need for themto be incarcerated. Research examining sentencing outcomes in Pennsylvania hasconsistently reported that females are treated more leniently in pretrial release(Demuth, 2002; Demuth & Steffensmeier, 2004) and sentencing decisions (Kramer& Ulmer, 2002; Steffensmeier et al., 1993); moreover, the sex effect is not attenu-ated by age (Kurlychek & Johnson, 2004) or race (Steffensmeier et al., 1998) and isconsistent across court contexts (Johnson, 2005).

Although chivalry and focal concerns frequently guide research on sex differ-ences in sentencing outcomes, this study examines the effect that bureaucratization,3

Blackwell et al. / Sex Differences in Sentencing 401



in the form of sentencing guidelines, plays in the sentencing process because it hasbeen largely unexplored, despite its importance in earlier sentencing research.Indeed, although bureaucratization and sentencing initially were linked to discus-sions of court size (e.g., Hagan, 1977; Tepperman, 1973), the impact of bureaucrati-zation on sex differences in sentencing was highlighted. Tepperman (1973) reportedthat small courts, which were less likely to exhibit bureaucratization than largecourts, were more likely to dismiss cases filed against female delinquents than casesof male delinquents and demonstrated more lenient treatment toward girls than boys.In contrast, large courts treated girls and boys in a remarkably similar manner, whichTepperman attributed to the standardization and formalization, as well as expedi-ency, of such courts.

Scholars have noted that bureaucratization of sentencing negatively affects femalesbecause such policies largely are founded on historical sentencing practices related tothe majority of defendants, who, by representation, were male (e.g., Daly, 1994). Stateand federal guidelines were developed to address problems present in the sentencingof male offenders, and the impact of such guidelines when applied to sentencingfemale offenders was not considered (Chesney-Lind & Pollock, 1995). Rather, guide-lines pointedly focused on the role of offense seriousness and prior record, factors thatare offense rather than offender based. As such, they generally omitted extralegalfactors, deeming consideration of factors such as race and sex inappropriate in thedecision-making process. The result is that guideline systems, by denying the “rele-vance of gender-related criteria,” may have “the effect of increasing punishment forwomen” (Daly, 1994, p. 15). As Tepperman (1973) concluded, if men and women enterinto crime because of different problems, such a bureaucratized system of decisionmaking will ignore these differences, leading to potentially greater harms.

However, this blanket generalization may be premature. Structured guidelinemodels are quite varied in their goals and structure. Thus, it is important to examinethe specific goals of a structured sentencing model and how guidelines are structuredto accomplish these goals before drawing conclusions about their effects on the sen-tencing of females. The bureaucratization of sentencing explanation provides a richcontext within which other factors, such as chivalry or paternalism or focal concerns,may have more or less of an impact on judicial decisions, depending on the degreeto which the guideline model reflects rational legal over substantive political ele-ments. Although frequently cited as a source of this trend, little research has directlyassessed the impact of bureaucratization, instead relying on indirect evidence.4

To date, only one study has specifically theoretically focused on and assessed sexdifferences in sentencing attributable to sentencing guideline implementation(Koons-Witt, 2002). Koons-Witt (2002) compared treatment of females across threeperiods: pre guidelines, early guidelines, and later guidelines. Her findings indicatedthat across all three periods, females were less likely than males to receive a sentenceof incarceration. In the preguideline period, sex only indirectly affected the incar-ceration decision through the presence of dependent children.5 This relationshipdisappeared during the early guideline period yet reemerged in the later guideline




period. Koons-Witt concluded that the patriarchal model of justice continued despitethe adoption of structured sentencing.

Minnesota and Pennsylvania sentencing guidelines markedly differ from oneanother. The different goals and structures in Minnesota and Pennsylvania guide-lines, which provide the data for this study, are described next to illustrate why adefendant’s gender may play a larger or smaller role in sentencing decisions withineach state’s guideline system.6

Minnesota and Pennsylvania: A Comparison of Sentencing Structures

Both Minnesota and Pennsylvania created structured sentencing processes thatwould reduce judicial discretion and unwarranted disparity (Kramer, Lubitz, &Kempinen, 1989). Both sentencing commissions were charged with developing pre-scriptive guidelines based on goals identified by each state (Kramer et al., 1989).7

Each developed a two-dimensional grid structure, with severity of current offensegiven primary weight and prior convictions secondary emphasis. Both provided forappellate review of sentences (Kramer et al., 1989). Although the two states’ guide-lines are similar, important differences between the systems also exist.

First, Pennsylvania guidelines incorporated a variety of sentencing philosophies,including rehabilitation, deterrence, retribution, and incapacitation (Koons-Witt,2002; Kramer & Ulmer, 1996). In contrast, Minnesota moved sharply away fromdeterrence and rehabilitation philosophies, focusing instead on retribution (Koons-Witt, 2002). This philosophical change yielded the adoption of determinate sentencingin Minnesota (Pennsylvania retained its indeterminate system) and much narrowerranges for the determined lengths of incarceration within their guidelines when com-pared to Pennsylvania (Koons-Witt, 2002; Kramer et al., 1989; Kramer & Ulmer,1996; Miethe & Moore, 1985).

Second, Minnesota “expressly prohibited” departures from guidelines based onsocial contextual factors (e.g., sex and race); in Pennsylvania, there was no explicitdiscussion of such factors (Kramer et al., 1989; Kramer & Ulmer, 1996). Instead,Pennsylvania judges continued to be bound by extant statutes and case law mandat-ing consideration of character and attitude to determine rehabilitation potential.Furthermore, Minnesota’s sentencing commission was expected to consider existingprison capacities in the development of its guidelines (Miethe & Moore, 1985), withan eye toward limiting prison population growth. Kramer et al. (1989) noted thatalthough the Pennsylvania sentencing commission did consider the correctional capac-ity issue, ultimately correctional resources were not referenced in the guidelines.

The overall impact of these differences is that judges retained greater discretionin Pennsylvania than in Minnesota. Researchers have noted, as a result, that caseprocessing in Pennsylvania should not be significantly affected by guidelines, par-ticularly in comparison to Minnesota (Kramer at al., 1989).




An ideal test of the impact of guidelines on sex differences in sentencing wouldutilize data collected prior to and after passage of guidelines, using the same method-ology and the same variables. Unfortunately, with the exception of Minnesota(Koons-Witt, 2002; Miethe, 1987; Miethe & Moore, 1985), direct tests of the impactof guidelines have not occurred in jurisdictions that passed guidelines, primarilybecause of methodological differences created by different data-collection formatsin periods preceding and following guideline passage. Prior to the passage of guide-lines, most data collection was not formalized, yielding inconsistent inclusion ofinformation on variables (both legal and extralegal) that may influence sentencingdecisions (Daly & Tonry, 1997; Hofer, Blackwell, & Ruback, 1999). A commonfeature of sentencing guidelines is the requirement that sentences be reported, alongwith additional information, to sentencing commissions or agencies. This improvedthe ability of agencies to more accurately assess the impact of legal and extralegalvariables in sentencing (Daly & Tonry, 1997; Hofer et al., 1999). Solely throughretroactive, extensive collection of data can enough information be obtained toexamine the impact of guidelines over time.

The Present Study

We recognize the important contribution that Koons-Witt (2002) made to sentenc-ing research by specifically focusing on the role of gender and how its impact may varyunder the presence and absence of guidelines. However, given differences betweenstate guideline structures, we stress that it is necessary to examine Koons-Witt’s frame-work in other jurisdictions, particularly those with considerably different guidelinestructures. By exploring the impact of sentencing guidelines on changing rates offemale imprisonment under the Pennsylvania guidelines system, which is more looselystructured and allows much more judicial discretion, this study builds on Koons-Witt’s research. Prior literature has posited that bureaucratization influenced thesex–sentencing relationship in a manner harmful to female offenders. However, asfocal concerns suggest, within this constriction gender stereotypes may continue toplay a role. Specifically, variation in the effect of guidelines on differential sentencingof male versus female defendants may depend on sentencing goals and guideline struc-tures. Hence, we explore the argument that bureaucratization has a negative impact onwomen in a jurisdiction where judges have greater discretion than found in otherguideline systems to determine if this position is upheld.

Data and Method

As Steffensmeier et al. (1993) noted, Pennsylvania guideline data are ideal forexploring the role of gender in sentencing decisions.8 The guidelines are structured




so that prior record and offense severity are considered, yielding data that more likelyreflect the true role of these variables in the sentencing decision (Steffensmeier et al.,1993, p. 417). The data are collected across the state of Pennsylvania, ensuring thata large number of cases and a wider social context are sampled (Steffensmeier et al.,1993). Consistent with most guidelines, Pennsylvania has a reporting requirement,promising consistency of data—with a range of legal and extralegal variables—across time as well as place. Moreover, data are collected on both felony and misde-meanor sentences (Kramer & Kempinen, 1995; Kramer & Ulmer, 1996), increasingthe likelihood that women are represented in the data.

For this study, the most important aspect of the Pennsylvania data is that they pro-vide a unique opportunity to test the influence of guidelines on limiting judicial dis-cretion. On July 22, 1982, guidelines were instituted (Kramer & Kempinen, 1995).On October 7, 1987, in Commonwealth v. Sessoms, the Pennsylvania Supreme Courtinvalidated the guidelines;9 the Sentencing Commission and Legislature quicklyaddressed the issue and new guidelines became effective April 25, 1988 (DelSole, 1992). These circumstances allow for a test of the impact of the guidelines ongender differences in sentencing. For this research, data were obtained from thePennsylvania Commission on Sentencing for all offenders sentenced betweenJanuary 1, 1986, and December 31, 1990 (N = 176,685). Two issues, however, hadto be addressed.

First, when the guidelines were suspended, judges were not required to reportsentencing decisions to the Sentencing Commission. Thus, it is possible that caseswhere judges reported in the presuspension and the postsuspension period were inreality cases where a judge was imposing sentences during the suspension of theguidelines but chose not to report. As a result, this time frame frequently was omit-ted from research using Pennsylvania Sentencing Guidelines data (Kramer & Ulmer,1996) because of concerns that inclusion of decisions during this period would adderror into analyses. To control for error introduced if judges did not report duringsuspension of guidelines, we retained only judges who reported across all three periods,yielding a conservative test of guideline influences and a reduced analytical sample(n = 134,536).

Second, there were changes in mandatory sentencing requirements for particulardrug offenses during the suspension period (Del Sole, 1992; Kramer & Kempinen,1995). To control for possible bias introduced by these changes, control variables foroffense type were included.

The data were divided into three separate periods for analytical purposes. Thepresuspension period, beginning January 1, 1986, ending September 30, 1987, con-tained 48,885 cases. The suspension period, ranging from October 1, 1987, throughApril 30, 1988, contained 13,828 cases. Finally, the postsuspension period, betweenMay 1, 1988, and December 31, 1990, contained 71,823 cases. Summary statisticsfor all variables by period are in Table 1.





Table 1Summary Statistics by Period

Presuspension Suspension Postsuspension (n = 48,885) (n = 13,828) (n = 71,823)

% % %

GenderMale 85.64 84.16 83.93Female 14.19 15.77 16.01Missing 0.17 0.07 0.06

RaceWhite 61.61 62.53 60.12Black 31.13 30.81 33.00Missing 7.26 6.66 6.87

Type of offenseViolent 21.53 20.20 19.27Drugs 13.94 14.75 19.18Property 46.24 44.04 41.54Other 18.28 21.02 20.00Missing 0.00 0.00 0.00

Guilty plea enteredTrial 23.61 27.81 27.76Plea 76.39 72.19 72.24Missing 0.00 0.00 0.00

Guidelines departureNo 89.56 74.61 84.52Yes 10.39 13.17 13.31Missing 0.05 12.22 2.17

Multiple convictionsNo 71.20 71.28 69.61Yes 28.80 28.72 30.39Missing 0.00 0.00 0.00

Type of sentenceProbation 41.16 41.48 38.41Jail 33.02 32.84 33.12Prison 18.62 17.75 20.75Missing 7.21 7.93 7.72

% % % M SD Missing M SD Missing M SD Missing

Offense gravity score 3.85 2.025 0.02 3.70 2.10 6.2 3.63 2.06 17.12Prior record score 1.197 1.95 0.08 1.12 1.92 13.8 1.30 2.00 2.03Prior record score × 5.117 9.69 0.08 4.76 9.60 16.01 5.58 10.11 18.50

offense gravity scoreAge 29.143 9.31 0.00 29.54 9.03 0.00 29.53 9.12 0.00Percentage urban 72.59 25.64 0.00 72.35 24.87 0.00 72.07 24.86 0.00



Dependent Variables

The decision to incarcerate was modeled in this study by differentiating amongprison sentences, jail sentences, and probation sentences (e.g., Holleran & Spohn,2004). The sentence length decision also was considered using the minimum lengthof incarceration (in months) separately for prison and jail.

Independent Variable

The key independent variable was the offender’s gender (female = 1, male = 0).

Control Variables

We controlled for the offender demographic variables of race (Black = 1, non-Black = 0) and age (measured in years), as well presence of multiple convictions in thecurrent case (yes = 1, no = 0), case disposal (guilty plea = 1, trial = 0), prior recordscore, and the offense gravity score.10 The most serious conviction offense was classi-fied into violent, property, drug, or other (reference category).11 Guidelines departurecaptured whether a sentence imposed was outside of the guidelines’ recommendedrange (outside range = 1, within range = 0).12 Finally, percentage urban, obtained fromthe U.S. Bureau of Census, was included as a county contextual variable.

Analytical Protocol

The analytical protocol occurs in two stages. First, the decision to incarcerate ismodeled using multinomial logistic regression because prison and jail sentencesconstitute distinct outcomes (see Holleran & Spohn, 2004; Ulmer, 1997). Conditionalprobabilities from the multinomial logistic regression estimates for males and femalesare then presented.

Second, the sentence length decision is estimated. Consistent with most sentencingstudies (except see Bushway & Piehl, 2001), we consider the decision makingprocess as twofold, including incarceration and length as separate components. Thesampling scheme employed in multinomial regression precludes the ability to ana-lyze length equations for prison sentences and jail sentences corrected for sampleselection bias.13 Hence, length decisions for prison and jail sentences are modeleduncorrected for the selection bias that may have resulted from an offender beingselected for some type of incarceration in the first-stage regression estimates.14

Further comments about the results of the regression models presented herein arenecessary. These regression models are descriptive, not inferential (for a discussion,see Berk, 2004). Although we follow convention and report p values for all of theregression estimates, we do not look to these probability values associated with thechi-square distributed Wald statistic for each regression parameter to draw conclusions




about the effects of the independent variables. The data in this study are viewed asthe apparent population of cases collected during the noted periods. As Berk (2004)noted, “If the data are a population, there is no sampling, no uncertainty because ofsampling, and no need for statistical inference. Indeed, statistical inference makes nosense” (p. 42).

Results

The Decision to Incarcerate

Table 2 presents the multinomial logistic regression parameters for the decisionto incarcerate. Across all three periods, female offenders were less likely than maleoffenders to receive a prison sentence relative to probation or a jail sentence relativeto probation; there were no differences between men and women in any period forreceiving a prison sentence relative to a jail sentence. The conditional probabilitiesfor the decision to incarcerate by sex and period, depicted in Figure 1, yield no sub-stantial fluctuations in the difference between male and female offenders across thethree periods. Thus, the suspension of the sentencing guidelines did not have anappreciable effect on how male and female offenders were sentenced.

Incarceration Length Decision

Results for the incarceration length decision are reported in Table 3.15 The (uncor-rected) sentence length parameters reveal that male offenders received longer prisonterms for the presuspension (3.6 months) and postsuspension (4.9 months) periods.Male offenders were sentenced to jail approximately 1 additional month overfemales for all three periods. There is no evidence that female offenders receivedsubstantially shorter sentences when guidelines were suspended.

Discussion

Our main objective was to explore the viability of bureaucratization of sentencing,specifically through the role of guidelines, as an explanation for the increasing simi-larity in how women and men are punished. This study built on prior research inMinnesota (Koons-Witt, 2002) by examining gender effects on sentencing outcomesin a single state across three periods, including suspension of guidelines. UnlikeMinnesota’s system, Pennsylvania’s permits judges to consider the rehabilitativepotential of defendants. Thus, this research examined the impact of guidelines on sen-tences for men and women under a guidelines system that affords judges greater flex-ibility. In contrast to Koons-Witt (2002), the decision to impose a sentence of prison




incarceration, jail incarceration, or a probation term was examined. As well, this studyexamined if the effect of gender was conditioned by type of commitment offense.

Overall, our results did not support assertions that sentencing guidelines reducesex disparity. Women were less likely than men to be incarcerated in prison (relativeto probation) or jail (relative to probation), regardless of presence or absence ofguidelines and type of commitment offense. Results did, however, support the notionthat because Pennsylvania’s guideline system confers greater discretion to judgesthan do guidelines in other jurisdictions (specifically Minnesota), the presence orabsence of guidelines does not alter the impact of sex on sentencing decisions. UnderPennsylvania’s system, judges are required to consider the defendant’s character andrehabilitation potential; thus, it is not surprising that the effect of sex was invariantto presence or absence of guidelines. We conclude, in part, that broad claims about


Table 2Multinomial Logistic Regression Estimates by Period

for the Decision to Incarcerate

Prison vs. Probation Jail vs. Probation Prison vs. Jailb b b

(p > ⏐z⏐) (p > ⏐z⏐) (p > ⏐z⏐)

Presuspension period (n = 42,041)Female (male = 0) –0.587 –0.506 –0.081

(.000) (.000) (.437)Offense gravity score 0.876 0.445 0.430

(.000) (.000) (.000)Prior record score 0.584 0.328 0.255

(.000) (.000) (.000)Suspension period (n = 10,031)

Female (male = 0) –0.599 –0.569 –0.030(.000) (.000) (.844)

Offense gravity score 0.703 0.412 0.291(.000) (.000) (.000)

Prior record score 0.547 0.309 0.238(.000) (.000) (.004)

Postsuspension period (n = 50,898)Female (male = 0) –0.624 –0.557 –0.067

(.000) (.000) (.578)Offense gravity score 0.694 0.403 0.291

(.000) (.000) (.002)Prior record score 0.573 0.370 0.203

(.000) (.000) (.002)

Note: The following control variables were also included in the regression equation: offender’s race,offender’s age, prior record score × offense gravity score, drug offenses, violent offenses, property offenses,other offenses, departure from the guidelines, multiple convictions, and the percentage of people living inurban areas in the county. The regression estimates for the control variables are available on request.




Prison Sentences

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

A

Females Males Females Males Females Males

Presuspension Suspension Postsuspension

p

B Jail Sentences

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00



p

Figure 1Conditional Probabilities for the Decision to Incarcerate

by Gender and Period

Probation Sentences

0.00

0.10

0.200.30

0.40

0.50

0.60

0.700.80

0.90

1.00

C



p



the negative impact of guidelines on female offenders should be cautiously inter-preted. These data highlight the importance of recognizing that sentencing goalsaccomplished through various structures may permit consideration of factors thatcontinue to favor women. Indeed, these findings, considered with those of Koons-Witt(2002), suggest that the impact of guidelines should be assessed on a state-by-statebasis. Moreover, blanket statements about guidelines may impugn systems that donot generate the previously identified problems, such as negatively affecting womenin sentencing.16


Table 3Uncorrected Ordinary Least Squares Regression Estimates by Period and

Type of Incarceration for the Minimum Length of Incarceration

Prison Sentence Length Jail Sentence Lengthb b

(p > ⏐t⏐) (p > ⏐t⏐)

Presuspension periodFemale (male = 0) –3.619 –0.823

(.003) (.000)Offense gravity score 3.348 1.136

(.000) (.000)Prior record score 0.668 0.958

(.000) (.000)n 8,404 14,795R2 .431 .250

Suspension periodFemale (male = 0) –1.098 –0.882


(.010) (.000)Prior record score –0.690 0.762

(.092) (.000)n 1,940 3,458R2 .383 .222

Postsuspension periodFemale (male = 0) –4.891 –0.701


(.158) (.000)Prior record score –0.010 0.799

(.846) (.000)n 10,620 17,296R2 .358 .282

Note: The following control variables were also included in the regression equation: offender’s race,offender’s age, prior record score × offense gravity score, violent offenses, property offenses, drug offenses,other offenses, guilty plea, departure from the guidelines, multiple convictions, and the percentage residingin an urban area. The regression estimates for these variables are available on request.



Spohn (2002), in a recent review of research on sentencing outcomes in federaland state courts where guidelines operate, observed,

Although it would be inappropriate to conclude that there is a causal relationshipbetween the adoption of sentencing guidelines and more punitive sentences, the factthat these evaluations consistently revealed that sentences became more severe suggeststhat the guidelines did have an effect. (p. 271)

One cannot dispute the fact that the past 20 years, marked by enactments of varioussentencing reforms, have seen greater numbers of offenders incarcerated and forlonger periods of time. However, our results and the results of other research on sen-tencing guidelines conducted in Minnesota (Koons-Witt, 2002; Kruttschnitt & Green,1984), Oregon (Mosbaeck, 1993), and Washington (Fallen, 1987) suggest that withinstructured sentencing processes, women continue to experience a lower probabilityof incarceration. Thus, more punitive treatment of women does not appear to be thedirect effect of limiting judicial discretion through sentencing guidelines; rather, itlikely is because of guidelines being formulated within political contexts that demandharsher responses to anyone convicted of a crime. Increased use of incarceration nega-tively affects both men and women and does not occur only in states with sentencingguidelines (U.S. Department of Justice, 1996).

It is important to note that sentencing guidelines were not the only reforms enactedin this period. By 1994, all 50 states had enacted some form of mandatory minimumsentencing (U.S. Department of Justice, 1996, p. 22). The U.S. Sentencing Commission(2001) observed that the lack of uniform application in mandatory minimum sen-tences compromises the ability of guideline-driven sentencing systems to reduceunwarranted disparity. Given current knowledge about the effects of guidelines onsentence severity and likely impacts of other sentencing policies, we assert that it ispremature to claim that women are disproportionately affected by guidelines. Rather,we conclude that future research should attempt to disentangle the effects of distinctsentencing reforms to more accurately understand their impact and whether suchreforms differentially, and, more important, negatively, affect women.

This research highlights the need to collaborate with criminal justice agencies.Although prior research has found that defendant’s family status (Daly, 1987, 1989)and social class (Kruttschnitt, 1980-1981; Worrall, 1990) interact with sex to influencesentencing decisions, we were precluded from analytical consideration of these vari-ables because data were unavailable.17 Consistent collection of data would enable moreaccurate assessments of sentencing policies.

Finally, we recognize that the effect of gender on earlier decision points (i.e., arrest,bail, prosecutorial charging) was not captured here. To date, scant research has exam-ined the “hydraulic displacement effect” (the shifting of discretion from the judge tothe prosecutor, who has the ability to gain plea agreements; Miethe, 1987; Savelsberg,1992; Ulmer, 1997, pp. 31-32).




In sum, this research adds to the gender and sentencing literature, highlightingkey considerations for the creation of correctional policies. Although guidelines weredeveloped to redress inequities based on race and class, less attention was given to thepossibility that such policies could have hidden consequences for other offenders—specifically women. Reformers should consider the debate between those arguing infavor of equal versus “special” treatment in sentencing. It is possible that sentencingreforms may yield what Chesney-Lind (1998) refers to as “vengeful” equity—outcomes that ultimately are more punitive for women than men as they are metedout. States contemplating guidelines must contemplate the degree of discretion madeavailable to judges to allow for the consideration of the circumstances surroundingthe offense and the offender, including level of culpability, amenability to rehabili-tation, and offender’s family status. As Daly and Tonry (1997) noted, such a focusallows policy makers to transform their focus from equity in sentencing to develop-ment of a “justice-based” framework.

Notes

1. Although some have explored sex differences in sentencing outcomes under guidelines (Albonetti,1998; Steffensmeier, Kramer, & Streifel, 1993), a pre–post comparison of these differences has been thedirect theoretical focus of only Koons-Witt (2002). There have been studies that have explored the impactof the passage of guidelines in numerous jurisdictions in a pre–post setting, but gender was included as acontrol variable, and it was not the theoretical focus (e.g., Miethe & Moore, 1985).

2. The chivalry hypothesis may be contingent on sex role stereotypes (Daly, 1987, 1989; Nagel &Hagan, 1983). The “evil woman thesis,” a corollary of the chivalry hypothesis, posits that leniency isextended only to women who display expected, traditional “female” behaviors; women who are minori-ties, in the lower class, or accused of violent crimes are treated more harshly than those who are White,middle class, or accused of nonviolent crimes (Moyer, 1992).

3. As one reviewer noted, we use the term bureaucratization broadly, to represent a myriad ofprograms that have introduced a rational-legal approach and have led to increasingly bureaucratizedapproaches to decision making, decentralizing the decision-making role by removing it from individuals—specifically judges—in an effort to formalize the punishment process. We note that this term has beenrather loosely employed empirically; as noted by Dixon (1995), early research on bureaucratization didnot employ direct measures of bureaucratization but rather employed urbanization (Hagan, 1977; but seealso Tepperman, 1973) or caseload size (Myers & Talarico, 1986) as proxies for the concept. Dixon(1995) argued in favor of using measures of divergent characteristics of court structure and centrality ofjudicial and prosecutorial decision making. We agree that a “true” measure of bureaucratization wouldencompass numerous components of organizational qualities; however, such measures were not available.Our reference to their presence and absence as reflecting some degree of bureaucratization is, we argue,consistent with discussions of how guidelines are affecting the sentencing process.

4. Chesney-Lind (1987), for example, supported her claim that bureaucratization of sentencing led toharsher penalties for female offenders by noting that “between 1974 and 1984 the number of women inprison jumped 258% (steeper than the male increase of 199%)” (p. 124). Meierhoefer (1992) reported thatincreasing incarceration rates of women were significantly affected by mandatory minimum terms set infederal guidelines for offenses involving drugs and firearms. Neither, however, presented a direct test oftheir claims.

5. Although this finding is notable, representing support for the family status perspective (see Daly,1994), this information, unfortunately, is not collected in the Pennsylvania guideline data.




6. A comparison across the multitude of guidelines that exist today, focusing on the guiding princi-ples of their design and resultant structures, is beyond the scope of the present study. We focus on the dif-ferences between the Minnesota and Pennsylvania guidelines primarily because we are exploring howguidelines have affected the effect of gender on sentencing decisions under different guideline systems. Asnoted in the article, although other studies examining the impact of guidelines across time have includedgender as a variable in the model, to date Koons-Witt (2002) provided the clearest theoretically focusedassessment of this question, using data from Minnesota. We identify the marked differences between guide-lines in Minnesota and those in Pennsylvania, which provide the data for this study, to illustrate the poten-tial for different findings. We believe that because of their different goals and structure, defendant’s gendermay play a larger or smaller role in sentencing decisions with these guideline systems. We then note thepotential for generalizing our findings to other guideline jurisdictions in the discussion section.

7. Prescriptive guidelines, as a forward-looking approach, are designed to accomplish particular sen-tencing goals and are authorized by a legislature; judges must sentence within guideline ranges or pro-vide justification for departures. Descriptive guidelines, by contrast, reflect past sentencing practices(U.S. Department of Justice, 1996).

8. Steffensmeier et al. (1993) presented a comprehensive review of the data and their benefits forexploring the question of gender differences in sentencing. The material presented here represents areview of their arguments as well as consideration of other factors.

9. Because the original guideline plan was not presented to the governor for approval, passage of theguidelines violated technical requirements. The invalidation was therefore a procedural issue, not a con-tent issue (see the annual report of the Pennsylvania Commission on Sentencing, 1997).

10. The offense gravity score was assigned by the Pennsylvania Sentencing Commission and used byjudges in decision making. This reduces the likelihood that we are introducing measurement error yetincorporates a guideline-based definition of seriousness that makes such a measure incomparable to otherguidelines using a different severity measure (Dixon, 1995).

11. Fifteen dummy variables for offense types (e.g., Steffensmeier, Ulmer, & Kramer, 1998) were cre-ated as more distinct offense type groupings than found in the four offense type groupings often used (i.e.,violent, drug, property, other) to examine their potential inclusion in the regression models. A fewoffenses lacked sufficient data representation for meaningful regression estimates; kidnapping cases, forexample, constituted .07% of the offense types in the presuspension period. Thus, we present the regres-sion estimates obtained with the four offense type groupings.

12. A greater percentage of cases were missing on the departure variable during the suspension period(12.22%) compared to the presuspension (0.05%) and postsuspension periods (2.17%). To examine theimpact of this difference, a multinomial logistic regression model was performed to determine if casesmissing departure information (12.22%) differed on key variables (gender, race, offense gravity score,prior record score, and multiple convictions), compared to cases in which departure information wasavailable. Results indicated that gender was not significantly related to whether a case was missing orreported as a departure. Cases with lower offense gravity scores and lower prior record scores were morelikely to be reported as falling within guidelines than to be missing, suggesting that departure informa-tion on less serious cases was consistently reported when guidelines were suspended. Because casesinvolving female defendants consistently are reported across all three periods and our statistical modelscontrol for both prior record and offense gravity scores, the impact of this slight overrepresentation of lessserious cases does not threaten the integrity of the findings.

13. The correction for sample selection bias discussed in Berk (1983) assumes bivariate normality forthe error structure from the decision to incarcerate equation and the sentence length equation. The bivariatenormality assumption arises from the fact that the decision to incarcerate equation is modeled using the bino-mial probit regression model, which assumes a normally distributed error term, and that the sentence lengthequation is modeled using the ordinary least squares regression model, which also assumes a normally dis-tributed error term. As one recent study has shown, many previous sentencing studies have incorrectly incor-porated the predicted probability from either a logistic (or probit) regression model as a “correction” forsample selection in the decision to incarcerate stage (see Bushway, Johnson, & Slocum, 2007).




14. An analog to the correction for sample selection when the first stage assumes a multinomial sam-pling scheme could not be found in the statistical, econometric, or social science literatures. Although a“two-part model,” which does not correct for sample selection, has been shown to produce biased esti-mates in the second stage (see Bushway et al., 2007), the decision was made to “live with the selectionbiases because the statistical cure can be worse than the statistical disease” (Berk, Azusa, & Hickman,2005, pp. 368-369).

15. Selection of cases for the sentence length decision on the basis of prison or jail artificially con-strained the variability in the prior record score. The lack of variability on the prior record score, coupledwith the inclusion of the interaction term for prior record score and the offense gravity score, induced illconditioning among the independent variables. The interaction term was therefore mean centered to treatthe ill conditioning among the independent variables.

16. The Supreme Court ruled in the case of Blakely v. Washington (2004) that sentences departingabove the standard range of guidelines are in violation of the Sixth Amendment if the facts supporting thesentencing decision were not found at trial beyond a reasonable doubt or were not admitted by a defen-dant in the entering of a plea. This decision led to great discussion about how jurisdictions with guide-lines will be affected, acknowledging that jurisdictions designed their guidelines differently based ondifferent concerns (Wool & Steman, 2004). Notably, there is considerable agreement that Pennsylvania’sguidelines scheme will fair well, as they retained indeterminate sentencing, and only the minimum termis affected by findings of aggregating circumstances, with the maximum term set at the statutory maxi-mum (Skove, 2004; but also see Commonwealth v. Pugh, 2004). These discussions support our contentionthat broad claims about the impact of guidelines are to be taken cautiously, as guideline frameworks mayyield very different outcomes.

17. The inability to control for family status raises the issue of omitted variable bias. Hence, estimatesin this study should be viewed with the knowledge that family status variables were previously found tocorrelate with sentencing outcomes.

References

Albonetti, C. A. (1997). Sentencing under the federal sentencing guidelines: Effects of defendant charac-teristics, guilty pleas, and departures on sentence outcomes for drug offenses, 1991-1992. Law &Society Review, 31, 789-822.

Albonetti, C. A. (1998). The role of gender and departures in the sentencing of defendants convicted of awhite-collar offense under the federal sentencing guidelines. Sociology of Crime, Law and Deviance,1, 3-48.

Belknap, J. (2001). The invisible woman. Belmont, CA: Thomson/Wadsworth.Berk, R. (1983). An introduction to sample selection bias in sociological data. American Sociological

Review, 48, 386-398.Berk, R. A. (2004). Regression analysis: A constructive critique. Advanced quantitative techniques in the

social sciences. Thousand Oaks, CA: Sage.Berk, R., Azusa, L., & Hickman, L. J. (2005). Statistical difficulties in determining the role of race in

capital cases: A re-analysis of data from the state of Maryland. Journal of Quantitative Criminology,21, 365-390.

Blakely v. Washington, 542 U.S. 296 (2004).Bushway, S., Johnson, B. D., & Slocum, L. A. (2007). Is the magic still there? The use of the

Heckman two-step correction for selection bias in criminology. Journal of Quantitative Criminology,23, 151-178.

Bushway, S., & Piehl, A. M. (2001). Judging judicial discretion: Legal factors and racial discriminationin sentencing. Law and Society Review, 35, 733-764.




Chesney-Lind, M. (1987). Girls and violence: An exploration of the gender gap in serious delinquentbehavior. In D. H. Crowell, I. M. Evans, & C. R. O’Donnell (Eds.), Childhood aggression and vio-lence (pp. 207-229). New York: Plenum.

Chesney-Lind, M. (1998). Women in prison: From partial justice to vengeful equity. Corrections Today,60, 66-73.

Chesney-Lind, M., & Pollock, J. M. (1995). Women’s prisons: Equality with a vengeance. In A. V. Merlo& J. M. Pollock (Eds.), Women, law & social control (pp. 155-175). Boston: Allyn & Bacon.

Clear, T. (1994). Harm in American penology: Offenders, victims, and their communities. Albany: StateUniversity of New York Press.

Commonwealth v. Pugh, 67 Pa. D. & C., 4th 458 (2004).Commonwealth v. Sessoms, 516 Pa. 365, 532 A.2d 775 (1987).Daly, K. (1987). Structure and practice of familial-based justice in a criminal court. Law and Society

Review, 21, 267-290.Daly, K. (1989). Rethinking judicial paternalism: Gender, work-family relations, and sentencing. Gender &

Society, 3, 9-36.Daly, K. (1992). Women’s pathways to felony: Feminist theories of lawbreaking and problems of repre-

sentation. Southern California Review of Law and Women’s Studies, 2, 11-52.Daly, K. (1994). Gender, crime and punishment. New Haven, CT: Yale University Press.Daly, K., & Bordt, R. L. (1995). Sex effects and sentencing: An analysis of the statistical literature. Justice

Quarterly, 12, 143-177.Daly, K., & Tonry, M. (1997). Gender, race and sentencing. In M. Tonry (Ed.), Crime and justice: A

review of research (Vol. 22, pp. 201-252). Chicago: University of Chicago Press.Del Sole, J. A. (1992). Appellate review in a sentencing guidelines jurisdiction: The Pennsylvania experi-

ence. Unpublished master’s thesis, University of Virginia, Charlottesville.Demuth, S. (2002). Racial and ethnic differences in pretrial release decisions and outcomes: A comparison

of Hispanic, Black, and White felony arrestees. Criminology, 41, 873-908.Demuth, S., & Steffensmeier, D. (2004). The impact of gender and race-ethnicity in the pretrial release

process. Social Problems, 51, 222-242.Dixon, J. (1995). The organizational context of criminal sentencing. American Journal of Sociology, 100,

1157-1198.Fallen, D. L. (1987). Sentencing practices under the Sentencing Reform Act. Olympia: Washington State

Guidelines Commission.Hagan, J. (1977). Criminal justice in rural and urban communities: A study of the bureaucratization of

justice. Social Forces, 55, 597-613.Hofer, P. J., Blackwell, K. R., & Ruback, B. R. (1999). The effect of the federal sentencing guidelines on

inter-judge sentencing disparity. Journal of Criminal Law & Criminology, 90, 239-306.Holleran, D., & Spohn, C. (2004). On the use of the total incarceration variable in sentencing research.

Criminology, 42, 211-240.Johnson, B. D. (2005). Contextual disparities in guidelines departures: Courtroom social contexts, guide-

lines compliance, and extralegal disparities in criminal sentencing. Criminology, 43, 761-797.Koons-Witt, B. A. (2002). The effect of gender on the decision to incarcerate before and after the intro-

duction of sentencing guidelines. Criminology, 40, 297-328.Kramer, J. H., & Kempinen, C. A. (1995). Reassessment and remaking of Pennsylvania’s sentencing

guidelines. Federal Sentencing Reporter, 8, 74-79.Kramer, J. H., Lubitz, R. L., & Kempinen, C. A. (1989). Sentencing guidelines: A quantitative comparison

of sentencing policies in Minnesota, Pennsylvania, and Washington. Justice Quarterly, 6, 565-587.Kramer, J. H., & Ulmer, J. T. (1996). Sentencing disparity and departures from guidelines. Justice Quarterly,

13, 81-106.Kramer, J. H., & Ulmer, J. T. (2002). Downward departures for serious violence offenders: Local court

“corrections” to Pennsylvania’s sentencing guidelines. Criminology, 40, 897-923.




Kruttschnitt, C. (1980-1981). Social status and sentencing of female offenders. Law and Society Review,15, 247-265.

Kruttschnitt, C. (1984). Sex and criminal court dispositions: The unresolved controversy. Journal ofResearch in Crime and Delinquency, 2, 213-232.

Kruttschnitt, C. (1996). Contributions of quantitative methods to the study of gender and crime, or boot-strapping our way into the theoretical thicket. Journal of Quantitative Criminology, 12, 135-161.

Kruttschnitt, C., & Green, D. E. (1984). The sex-sanctioning issue: Is it history? American SociologicalReview, 49, 541-551.

Kurlychek, M. C., & Johnson, B. D. (2004). The juvenile penalty: A comparison of juvenile and youngadult sentencing outcome in criminal court. Criminology, 42, 485-517.

Meierhoefer, B. S. (1992). The general effect of mandatory minimum prison terms. Washington, DC:Federal Judicial Center.

Miethe, T. D. (1987). Charge and plea bargaining practices under determinate sentencing: An investi-gation of the hydraulic displacement of discretion. Journal of Criminal Law and Criminology, 78,155-176.

Miethe, T. D., & Moore, C. A. (1985). Socioeconomic disparities under determinate sentencing systems: A comparison of pre-guideline and post-guideline practices in Minnesota. Criminology,23, 337-363.

Mosbaeck, C. (1993). Third year report on implementation of sentencing guidelines, 1992. Portland:Oregon Criminal Justice Council.

Moulds, E. F. (1978). Chivalry and paternalism: Disparities of treatment in the criminal justice system.Western Political Quarterly, 31, 416-430.

Moyer, I. L. (1992). The changing roles of women in the criminal justice system: Offenders, victims andprofessionals (2nd ed.). Prospect Heights, IL: Waveland Press.

Myers, M. A., & Talarico, S. M. (1986). The social contexts of racial discrimination in sentencing. SocialProblems, 33, 236-251.

Nagel, I. H., & Hagan, J. (1983). Gender and crime: Offense patterns and criminal court sanctions. InM. Tonry & N. Morris (Eds.), Crime and justice: An annual review of research (Vol. 4, pp. 91-144).Chicago: University of Chicago Press.

Pennsylvania Commission on Sentencing. (1997). Pennsylvania Commission on Sentencing annualreport. State College: Author.

Savelsberg, J. J. (1992). Law that does not fit society: Sentencing guidelines a neoclassical reaction to thedilemmas of substantivized law. American Journal of Sociology, 97, 1346-1381.

Skove, A. E. (2004). Blakely v. Washington: Implications for state courts. Retrieved October 4, 2004, fromhttp://www.ncsonline.org/WC/Publications/KIS_SentenBlakely.pdf

Spohn, C. (2002). How do judges decide: The search for fairness and justice in punishment. ThousandOaks, CA: Sage.

Spohn, C., & Beichner, D. (2000). Is preferential treatment of female offenders a thing of the past: A multi-site study of gender, race and imprisonment. Criminal Justice Policy Review, 11, 149-184.

Steffensmeier, D., Kramer, J., & Streifel, C. (1993). Gender and imprisonment decisions. Criminology,31, 411-446.

Steffensmeier, D., Ulmer, J. T., & Kramer, J. (1998). The interaction of race, gender and age in criminalsentencing: The punishment cost of being young, Black and male. Criminology, 36, 763-797.

Tepperman, L. (1973). The effects of court size on organization and procedure. Canadian Review ofSociology and Anthropology, 10, 346-365.

Ulmer, J. T. (1997). Social worlds of sentencing: Court communities under sentencing guidelines. Albany:State University of New York Press.

U.S. Department of Justice. (1996). National assessment of structured sentencing. Washington, DC:Office of Justice Programs.

U.S. Department of Justice. (1999). Prisoners in 1998. Washington, DC: Bureau of Justice Statistics.




U.S. Sentencing Commission. (2001). Special report to the Congress: Mandatory minimum penalties in thefederal criminal justice system. Retrieved August 22, 2006, from http://www.ussc.gov/reports.htm

Wool, J., & Steman, D. (2004). Aggravated sentencing: Blakely v. Washington: Practical implications forstate sentencing systems. Retrieved October 4, 2004, from http://www.vera.org/ssc

Worrall, A. (1990). Offending women: Female law-breakers and the criminal justice system. London:Routledge.

Brenda Sims Blackwell is an associate professor of criminal justice at Georgia State University. Herresearch agenda focuses on causes of gender differences in crime and responses of criminal justice agen-cies to female offenders and victims.

David Holleran is assistant professor and department chair in the Department of Criminology at TheCollege of New Jersey. His research interests include correlates of sentencing outcomes and factorsassociated with sexual assault case prosecution.

Mary A. Finn is professor of criminal justice at Georgia State University. Her research interests includeviolence against women and children and evaluation of policies and interventions designed to addresssuch violence.




Documents

Journal of Contemporary Criminal Justice - SAGE - the natural home