Determinants of State Innovations in American Sentencing and Corrections Policy

Abstract

Recently, government officials, policy makers, and practitioners are taking a closer look at present day sentencing and corrections approaches. State policy decisions have in large part determined how justice is administered, and a variety of contextual factors determine which policies states are likely to adopt. This review synthesizes the empirical literature on determinants of state sentencing and corrections policy innovations and discusses their relative value in predicting state policy adoptions across studies. Results indicate that sentencing and corrections policies are less likely to be predicted by functional explanations such as crime rates than by certain economic, political, and social variables. The most consistently predictive determinants of state policy adoptions are the external influences of other states and the federal government.

Keywords

justice correctional policy sentencing policy criminal justice policy

Extensive research across the social sciences seeks to explain and predict the process of public policy formation in the American states. Numerous studies identify variables which influence the policy-making process, either directly or indirectly. Researchers suggest that policy innovation at the state level varies widely, not only according to the environment but also along with the nature and type of policy under consideration (Gray, 1973; Makse & Volden, 2011; Nicholson-Crotty, 2009). Accordingly, a distinct focus has developed to explore the unique determinants of criminal justice policies, with even more specific explorations of policies directed at prosecution and defense, court reform, juvenile justice, criminalization, sentencing, and corrections (Bergin, 2011; Karch, 2007).

In recent decades, extensive changes in sentencing and corrections policies have provided fertile ground for targeted exploration of the unique determinants of these policies as researchers work to understand the complex forces underlying the rise and fall of mandatory sentencing guidelines, the privatization of prisons, and the evolution of innovative alternatives to traditional ways of responding to crime. This work has special relevance to criminal justice professionals and social workers as we seek to understand the social currents guiding the administration of justice and to intervene on behalf of marginalized and vulnerable populations, including offenders, victims, and victimized communities, through policy practice. In hopes of adding to this necessary understanding, this article synthesizes the empirical literature on factors influencing state legislation governing sentencing and corrections policies, identifies gaps in the literature, and suggests areas of focus for future practice and research.

Background

The earliest efforts to understand the determinants of state public policy adoption and diffusion offered competing views about the relative importance of functional, economic, political, and social factors and the relationship between them (Dawson & Robinson, 1963; Fenton & Chamberlayne, 1969; Walker, 1969). Walker’s (1969) study is considered by many to be the seminal study on policy diffusion or the spread of policies from one jurisdiction to another. A barrage of studies followed, each offering a unique model for the prediction of state policy innovations (see F. S. Berry & Berry, 2007; Nice, 1994). While Walker (1969) aggregated a multitude of policies and policy types, Gray (1973) advocated for the separate consideration of narrow policy areas, finding differential support for determinants of 12 individual welfare policies. F. S. Berry and Berry (2007) estimated that more than 40 studies were published on policy innovation and diffusion between 1990 and 2005 alone. Over time, the initial view of policy as a predictable response to problems gave way to more politicized and contextual hypotheses.

During the same time period that the literature on public policy formation was developing, dramatic shifts were occurring in federal and state responses to crime. Sentencing and corrections reforms were in the forefront of the discussion. Between 1972 and 2005, truth-in-sentencing laws, mandatory sentencing guidelines, three strikes laws, and movements toward prison privatization contributed to a 636% increase in the incarcerated population (King, Mauer, & Young, 2005). Anecdotal accounts abounded, ascribing sentencing and corrections policies to federal ideology and incentivizing (Harris, 1972), media hyping (Beale, 2006; Caldwell & Caldwell, 2011), shifts in public opinion (Shichor & Sechrest, 1996), and myriad other causes. Yet criminal justice and public policy researchers struggled to empirically understand the unique determinants of criminal justice policies within the framework of previously advanced ideas about the general study of public policy. Over the decades, studies evaluated the effect of social, economic, and political determinants on policies governing juvenile justice issues (Downs, 1976), rape laws (Berger, Neuman, & Searles, 1991), hate crimes (Grattet, Jenness, & Curry, 1998), capital punishment (Mooney & Lee, 2000), and due process standards (Worden & Davies, 2009), finding varying and often inconsistent levels of support for hypothesized determinants.

Decades later, the literature continues to observe that research on criminal justice policy formation is an underexplored area (Bergin, 2011; Ismaili, 2006). Ismaili (2006) suggested that criminologists are too intent on discovering policy outcomes to contribute to an adequate understanding of policy determinants and that political scientists overlook the criminal justice field as an area for targeted exploration. Regardless of the cause, there is work yet to be done toward developing a fuller picture of criminal justice policy formation, its relationship to the larger field of public policy research, and its many highly contextualized sub-fields.

The purpose of this article is to discern a starting point for the further understanding of sentencing and corrections policy formation by conducting a systematic review of the empirical literature on this topic. After a description of methodology for this review, findings from identified studies are discussed within the context of relevant theories of public policy formation most frequently offered to explain the adoption of criminal justice policies. Afterward, gaps in the literature and areas for future research are identified.

Method

Databases and Search Terms

An exhaustive review of the empirical literature identifying social, political, and economic determinants of sentencing and corrections policy was conducted through a rigorous search strategy which included a comprehensive array of search engines and databases, carefully selected search terms, and well-defined inclusion criteria. Search engines including ProQuest, EBSCOHost, and Google Scholar were used to access multidisciplinary databases as well as databases representing the fields of political science, economics, sociology, psychology, and social work. Databases explored included Academic Search Complete, Criminal Justice Abstracts, EconLit, JSTOR, ProQuest Criminal Justice, ProQuest Dissertations & Theses, Psychology and Behavioral Sciences Collection, PsycARTICLES, PsycINFO, Public Affairs Information Service (PAIS) International, Social Services Abstracts, Sociological Abstracts, Social Work Abstracts, and Worldwide Political Science Abstracts. In addition, the Don M. Gottfredson Library of Criminal Justice Grey Literature Database was used to search the gray literature on criminal justice policy.

Initial broad search terms included any of the keywords criminal justice, sentencing, or corrections paired with either of the keywords policy (or policies) or legislation. These searches result in an unmanageable number of titles, but review of some of the most relevant abstracts prompted a second, more targeted search of all selected databases, this time including the original search terms along with any of the keywords innovation, diffusion, adoption, or influenc* and the keyword state (or states). From all databases, 978 titles were returned. Based on the relevance of titles, 146 abstracts were reviewed for inclusion in the study, and seven articles were selected for the study based on inclusion criteria. In addition to strategic search of the literature through topical databases, studies were identified for this review by tracing the references of other relevant studies, theoretical pieces, and one particularly salient literature review (Bergin, 2011). This process resulted in the addition of three more empirical articles to the study sample.

Inclusion Criteria

Abstracts returned by searches were carefully reviewed for a possible match with the inclusion criteria for this literature review: (a) selected articles must be published in a peer-reviewed journal, reputable periodical publication, or via a dissertation approved by an accredited college or university; (b) articles must describe the findings of an original empirical study; (c) articles must identify factors influencing the adoption of state sentencing or corrections policy affecting adult offenders in the United States; (d) the dependent variable of the study must be the passage of state legislation or otherwise formal, written state policy. Studies exploring an outcome other than policy adoption, such as sentencing rates, execution rates, corrections spending, or other indicators of policy implementation or outcomes did not meet the purpose of this review. In addition, studies including criminal justice policies in a multidisciplinary exploration of policy adoption were only included if results were reported separately for criminal justice legislation.

In recognition of widespread evidence that different types of policies have unique determinants, several useful explorations of criminal justice policy adoptions meeting other inclusion criteria for this review were excluded based on their distinctly separate nature from the topic being explored here: adult sentencing and corrections. Most notably, these include juvenile justice issues (Caldwell & Caldwell, 2011; Downs, 1976; Sutton, 1990), court reforms and due process (Scheb & Matheny, 1988; Worden & Davies, 2009), felony voting disenfranchisement (Murphy, Newmark, & Ardoin, 2006; Preuhs, 2001), hate crime laws (Grattet et al., 1998; Soule & Earl, 2001), rape laws (Berger et al., 1991; Call, Nice, & Talarico, 1991), and other laws defining the legality of specific behaviors.

In the interest of identifying the determinants with the greatest potential influence on general sentencing and corrections policy, a significant area of the literature focusing solely on capital punishment statutes has also been excluded (see Emmert & Traut, 2003; Erikson, 1976; Mooney & Lee, 2000; Nice, 1992, among others). While these laws are certainly related to corrections, the consensus of the literature on capital punishment policy decisions is that the determinants are uniquely social and moralistic in focus and likely to be quite different than the determinants of general criminal justice policies (Mooney & Lee, 2000).

Findings

Description of the Sample

An exhaustive review of the literature resulted in 10 empirical studies meeting the inclusion criteria for this review (see Table 1). The study of sentencing and corrections policies through a public policy framework has occurred mostly within the past 10 years, with 9 of the 10 studies being published in 2003 or later. The earliest study uncovered by this search is a 1986 study published by Justice Quarterly (Link & Shover, 1986); the most recent was published by Criminal Justice Policy Review in 2013 (Brown, 2013). Two dissertations represent the fields of law and political science. Of the remaining 8 studies, 4 were published by a political science or public policy journal, 3 were published by a criminal justice journal, and 1 was published by a law review.

Table 1.

Empirical Studies Exploring Determinants of Adult Sentencing and Corrections Policies.

Author(s), date	Policy arena	Method	States	Dates sampled
Allen, Pettus, and Haider-Markel (2004)	Truth in sentencing	EHA	50	1985-2000
Brown (2013)	Corrections (decarceration)	Logistic regression	50	2009
Dharmapala, Garoupa, and Shepherd (2010)	Determinate sentencing	Logistic regression	50	1960-2000
Grossback, Nicholson-Crotty, and Peterson (2004)	Sentencing guidelines	EHA	50	1981-1994
Link and Shover (1986)	Sentencing various	Multiple regression	50	1971-1982
Makse and Volden (2011)	27 Criminal justice policies	EHA	50	1973-2002
Nicholson-Crotty (2004a)	Corrections privatization	Cox Hazard	50	1987-1998
Nicholson-Crotty (2004b)	Sentencing guidelines	EHA	50	1981-1996
Stemen (2007)	Sentencing various	Cox Hazard	50	1970-2002
Williams (2003)	Sentencing various	Logistic regression	48	1997

Note. EHA = event history analysis.

Review of Methodologies

Within the vast literature on prediction of state policy adoption, as well as within the study cohort identified by this literature review, the primary statistical methods used are time hazard models and, secondarily, logistic regressions. Four studies identified herein describe their method as Event History Analysis (EHA); three, logistic regression; two, the Cox hazards model; and one, multiple regression (see Table 1). EHA, widely considered the standard model for studying policy innovation, is a discrete time hazard framework in which the variable being studied is the hazard rate or the risk that a state will adopt a given policy in any given year (F. S. Berry & Berry, 1990). The Cox probability hazard model is also a discrete time hazard framework. Logistic regression is used most frequently where multiple points in time are not a feature of the dependent variable, but the dichotomous variable of policy adoption is considered in 1 year only (see Brown, 2013; Williams, 2003). In this sense, logistic regression is used to predict the likelihood, based on an array of independent variables, that a state will adopt a policy by or within the year under study.

All selected studies with the exception of Williams (2003), who excluded Alaska and Hawaii, sampled from all 50 states. Sampled dates ranged from 1960 through 2002, observing substantial reforms to sentencing and corrections policies in the United States during the later half of the 20th century. Half of the selected studies examined the diffusion of policies across states over a 10- to 15-year time period, while three sampled periods of 30 or more years and two examined policy changes within a single year or point in time (see Table 1).

Frequency and Operationalization of Dependent Variables

Walker (1969) defined a policy innovation as a “program or policy which is new to [the state] adopting it” (p. 881). In accordance with the inclusion criteria for this review, all selected studies use some measure of state policy adoption. Sentencing and corrections policies explored in the literature include legislation governing truth-in-sentencing or determinate sentencing, sentencing guidelines, three strikes laws, general (multiple) sentencing reforms, corrections privatization, decarceration, and general (multiple) criminal justice laws including those related to sentencing and corrections (see Table 1).

Operationalization of variables in most cases was dependent on the statistical method of analysis employed, with the majority of studies coding adoption of legislation through a dichotomous dummy variable indicating adoption by a given state within a given year. While most policies were easily identified in state legal codes, Brown (2013) coded the purpose of correctional policies to identify those “reducing reliance on incarceration” and measured the adoption of 95 such policies adopted across all states in 2009. An outlier, Link and Shover (1986) created an 8-point scale, assigning a point value for each of seven sentencing reforms adopted by states in the study period.

Frequency and Operationalization of Independent Variables

Within the literature on criminal justice public policy, three overarching areas can be used to categorize the vast array of predictive variables that have been offered and tested. These areas include (1) internal state characteristics including (a) the functional features of the problem environment, (b) economic capacity, (c) political influences, and (d) social characteristics; (2) external factors which influence the state environment including diffusion of ideas from the federal government, from geographically proximal states, and from ideologically similar states; and (3) attributes of the policies themselves. The following sections provide a synthesis of the predictive variables explored in the identified literature on sentencing and corrections policies described within the context of relevant theories contributing to model specification.

Internal determinants

The earliest explored predictors of state policy making were the internal characteristics of the state environment (Walker, 1969). The explanatory power of functional, economic, political, and social variables at the state level have been tested extensively in the literature on criminal justice public policy. Selection of variables is determined by one or more of several guiding theories of policy development.

Functional determinants

Functionalism, also termed rational or democratic response theory, suggests that crime policy is a logical reaction to observable features of the problem environment such as crime rates (Bennett, Dilulio, & Walters 1996; Ismaili, 2006). “Problems, dramatic or not, spur innovation by encouraging decision makers to search for new and better ways of doing things” (Nice, 1994, p. 21). In addition to crime rates, recidivism rates, sentence lengths, and incarceration rates may also indicate the need for reforms to sentencing or corrections policies. Support in the criminological literature for functionalist perspectives of crime is inconclusive, with rational explanations often superseded by political and economic forces (Link & Shover, 1986; Meier, 1994; Nicholson-Crotty, Peterson, & Meier, 2003).

Eighty percent of the studies identified for this review explored at least one functional explanation of criminal justice policy. Eight included either general or violent crime rates from the Uniform Crime Report in their model specification (see Table 2), though only Dharmapala, Garoupa, and Shepherd (2010); Stemen (2007); and Williams (2003) found statistically significant support for a predictive effect of high crime rates on sentencing and corrections reforms. Hoping to capture the influence of rising crime rates, Link and Shover (1986) operationalized crime as the change in violent crime rates during the 5 years prior to policy adoption; however, this was not associated with the extensiveness of criminal sentencing reform as measured in their study.

Table 2.

Functional Determinants of State Sentencing and Corrections Policy Making.

Functional determinant	Operationalization (source)
Crime rates	Crime rates per 100,000 (Allen, Pettus, & Haider-Markel, 2004)
	Crime rates per 100,000 (Brown, 2013)
	Violent crime rates per 100,000 (Dharmapala, Garoupa, & Shepherd, 2010)*[+]
	Crime rates per 1,000 (Grossback, Nicholson-Crotty, & Peterson, 2004)
	Change in level of violent crime during 5 years prior (Link & Shover, 1986)
	Violent crime rates per 1,000 (Nicholson-Crotty, 2004b)
	Index crime rate and violent crime rates per 100,000 (Stemen, 2007)*[+]
	Crime rates per 100,000 (Williams, 2003)*[+]
Incarceration rates	Incarceration rate per 100,000 (Brown, 2013)
	Prisoners per 100,000 (Dharmapala et al., 2010)
	Incarceration rate per 100,000 (Stemen, 2007)
Other functional	Percent of population under correctional supervision (Brown, 2013)
	Percentage of sentences served (Williams, 2003)
	Mean maximum sentence length (Williams, 2003)

[+]Indicated by author as a statistically significant predictor within the specified model.

Three studies tested incarceration rates as a determinant of decarceration policies (Brown, 2013) and sentencing reforms (Dharmapala et al., 2010; Stemen, 2007), but found no significant relationship. Neither were the percent of the population under correctional supervision (Brown, 2013), the percentage of sentences served, or the mean maximum sentence length (Williams, 2003) useful in predicting the adoption of decarceration or sentencing reforms, respectively. Like previous literature, studies exploring the determinants of sentencing and corrections policies find only partial support for a functionalist view of criminal justice policy making.

Economic capacity determinants

An alternate but related view of public policy making is that policies are adopted in response to state economic capacity. Theorists proffer that a state’s lack of fiscal capacity, structural capacity, or otherwise limited resource environment may induce pressure to reduce costs and overcrowding (Gordon, 1989; Nice, 1994; Nicholson-Crotty et al., 2003). Recently, the state of California has received national attention over a Supreme Court mandate to reduce prison overcrowding, resulting in a variety of innovative sentencing and corrections reforms (“The Magic Number,” 2013). Similarly, lack of fiscal or system capacity may lead states to adopt policies which result in cost reductions or, alternatively, prevent states from adopting new policies which are viewed as cost inducing.

All but one of the identified studies tested at least one economic capacity variable as a possible predictor of state sentencing and corrections policy making (see Table 3). The most widely explored determinants were fiscal health, state fiscal capacity, prison overcrowding, and corrections spending. Only Stemen (2007) identified a statistically significant effect of fiscal health, most frequently operationalized as a ratio of state revenues to expenditures, on criminal justice policy making in his study of sentencing reform policy adoptions. Explorations of state fiscal capacity were more promising. State revenues were found to be negatively correlated with the likelihood of adoption of both decarceration policies (Brown, 2013) and policies governing changes in probation and parole fees (Stemen, 2007), both policies likely to reduce state costs. As a result, Brown (2013) found partial support for her hypothesis that the national economic recession of the past decade had resulted in policies seeking to reduce reliance on incarceration as a cost reduction strategy. Likewise, Williams (2003) found that limited capacity as indicated by the presence of greater prison overcrowding resulted in states being less likely to adopt truth-in-sentencing or three strikes laws. However, Nicholson-Crotty (2004a) did not find support for his hypothesis that prison overcrowding would increase the likelihood of state legislation enabling prison privatization.

Table 3.

Capacity-Related Determinants of State Sentencing and Corrections Policy Making.

Capacity-related determinant	Operationalization (source)
Fiscal health	State deficit as percent of general budget (Brown, 2013)
	Balanced budget (Y/N; Brown, 2013)
	Ratio change in state expenditures to national average change (Link & Shover, 1986)
	Ratio of state revenues to expenditures/expenditures (Stemen, 2007)*[+]
	State revenues over expenses (Williams, 2003)
State fiscal capacity	Gross state product per capita (Allen, Pettus, & Haider-Markel, 2004)
	State revenue per capita (Brown, 2013)*[−]
	State generated revenue (Nicholson-Crotty, 2004b)
	State revenue Per 100,000 (Stemen, 2007)*[−]
Prison overcrowding	Percent of inmates over capacity (Nicholson-Crotty, 2004a)
	Prison population as percent of prison capacity (Williams, 2003)*[−]
Corrections spending	Corrections spending per capita (Allen et al., 2004)*[−]
	Corrections spending as percent of general budget (Brown, 2013)
	Corrections spending as percent of general budget (Makse & Volden, 2011)
	Corrections spending as percent total spending (Nicholson-Crotty, 2004a)
	Corrections spending per 100,000 (Stemen, 2007)*[+]
Spending limitations	Taxing/spending limits (Nicholson-Crotty, 2004a)
	Capital debt restrictions (Nicholson-Crotty, 2004a)

[ ]Indicated by author as a statistically significant predictor within the specified model.

Corrections spending is another indicator of justice system capacity. Measures of corrections spending as a percentage of general state expenditures were not predictive of the adoption of decarceration policies (Brown, 2013), prison privatization statutes (Nicholson-Crotty, 2004a), or general criminal justice policies (Makse & Volden, 2011). However, measures of greater corrections spending per capita were predictive of decreased adoptions of truth-in-sentencing laws (Allen, Pettus, & Haider-Markel, 2004) and increased adoptions of mandated increases to parole and probation fees (Stemen, 2007), supporting the hypotheses that an overtapped corrections environment may render the state unlikely to legislate the expenditure of additional resources but likely to pass policies which garner resources. While divided, the existing literature supports the notion that state economic capacity helps predict the adoption of state-level sentencing and corrections policies. Studies by multiple authors lend credence to the theory that a scarce resource environment is particularly predictive of policy adoptions that alleviate strain on systems as well as failure to adopt policies which increase financial burden.

Political determinants

Underneath the surface, political variables which are unrelated to the actual problem environment or resource environment are also at work in public policy formation (Ismaili, 2006). Political theories of policy making suggest that party affiliation, interest groups, media coverage, and public opinion contribute at some level to decisions about public policy (Bergin, 2011; F. S. Berry & Berry, 2007; Karch, 2007). Historically, the Democratic Party has been associated with less punitive criminal justice goals, and four studies identified for this review explore party control of the state legislature, the governorship, or both as a predictive determinant of policy adoptions (see Table 4). Of these, two find at least partial support for a party hypothesis: Brown (2013), that the percent of Republican legislators will reduce the likelihood of adoption of decarceration policies, and Makse and Volden (2011), that Democratic control of the governorship will increase general criminal justice policy reforms.

Table 4.

Political Determinants of State Sentencing and Corrections Policy Making.

Political determinant	Operationalization (source)
Legislative party	Democratic Control of State Legislature (Allen, Pettus, & Haider-Markel, 2004)
	% Republican (Brown, 2013)*[−]
	Proportion Democrats in house/senate (Makse & Volden, 2011)
	Party control of lower house (Stemen, 2007)
Governor party	Democratic control of governorship (Allen et al., 2004)
	Republican control of governorship (Brown, 2013)
	Democratic control of governorship (Makse & Volden)*[+]
Party competition	Holbrook and Van Dunk’s (1993) measure (Allen et al., 2004)*[+]
	Legislative races lost with 40+% of the vote (Williams, 2003)*[+]
Divided government	Number of years with divided legislature and governor (Dharmapala, Garoupa, & Shepherd, 2010)*[+] [Rep Leg More)
	Unified government (Y/N; Stemen, 2007)
Public responsiveness	Whether judges face re-election (Dharmapala et al., 2010)
	Governor election year (Y/N; Stemen, 2007)
	Existence of direct statutory initiative procedures (Y/N; Williams, 2003)
Legislative professionalism	State legislative salary (Makse & Volden, 2011)*[−]
	Standardized legislative salaries (Stemen, 2007)*[+]
	Squire’s (1992) Index (Williams, 2003)
Government ideology	W. D. Berry, Ringquist, Fording, and Hanson (1998) Government Ideology Score (Dharmapala et al., 2010; Grossback, Nicholson-Crotty, & Peterson, 2004; Makse & Volden, 2011; Stemen, 2007)
State-level policy preferences	Factor loading score of multiple measures of punitiveness (Nicholson-Crotty, 2004b)*[+]
	History of felony disenfranchisement (Grossback et al., 2004)
	Police per 100,000 (Dharmapala et al., 2010)
Citizen ideology	W. D. Berry et al. 1998 (Allen et al., 2004; Dharmapala et al., 2010; Nicholson-Crotty, 2004a *[+])
	Percent of republican voters over the national percent (Link & Shover, 1986)
	Percent adherents to fundamentalist religion (Stemen, 2007)
	Elazar’s (1999) Moralistic Political Culture Scale (Williams, 2003)
	Liberalism as determined by exit polls (Williams, 2003)
Interest groups	# of Amnesty Intl Chapters per 1,000 Citizen (Allen et al., 2004)
	% of public employees unionized (Nicholson-Crotty, 2004a)

[ ]Indicated by author as a statistically significant predictor within the specified model.

Further research suggests that the electoral security of officials will affect their willingness to adopt new policies (F. S. Berry & Berry, 2007). Variously, authors predict that political rivalry variables such as party competition, divided government, election timing of judges, and governors, or the presence of direct statutory initiative procedures will result in either an unwillingness to adopt controversial reforms or special readiness to appear “tough on crime.” Accordingly, Allen et al. (2004) and Williams (2003) found that two separate measures of party competition were a positive predictor of the adoption of truth-in-sentencing laws. In addition, Dharmapala et al. (2010) found that the likelihood of truth-in-sentencing and sentencing guideline enactments increased along with the number of years spent with a divided government.

Three studies tested the hypothesis that legislative professionalism would increase stability and the likelihood of policy adoptions. Operationalizing legislative professionalism using legislative salaries, Stemen (2007) found that legislative professionalism increased the likelihood of determinate sentencing reforms, while Makse and Volden (2011) unexpectedly found that the same variable decreased the likelihood of adoption of 27 various criminal justice policies. Williams (2003), using Squire’s (1992) index of legislative professionalism, found no significant effect on truth-in-sentencing or three strikes law adoptions. Taken alone, these results suggest that legislative professionalism may have distinctly different effects on different types of policies and that operationalization makes a difference in outcomes.

Two of the most widely explored and consistently operationalized political variables are scores of government and citizen ideology, yet only one study in this sample found either significantly predictive of sentencing or corrections policies as operationalized (see Nicholson-Crotty, 2004a). Nicholson-Crotty (2004a), like most others, used W. D. Berry, Ringquist, Fording, and Hanson’s (1998) measures to operationalize ideology. Some explored alternate operationalizations including the percent of Republican voters, the percent of adherents to a fundamentalist religion, the rate of liberalism captured by exit polls, and the presence of a moralistic political culture as measured by Elazar’s (1999) formulation; however, none proved useful in predicting targeted policy adoptions. Three studies also tested indicators of prior state policy preferences, with only Nicholson-Crotty’s (2004b) finding a significant association between the adoption of prior punitive policies and current policy adoptions.

In sum, the most consistently predictive political variables influencing sentencing and corrections policy adoptions have been features of the legislature itself including party affiliation, party competition, and legislative professionalism. General indicators of government and citizen policy preferences have had less influence on sentencing policies of the past few decades. Other important areas remain underexplored. While interest groups have been noted in prior studies as key informants in the spread of information about policy issues (Karch, 2007), the two studies testing interest group influence through rough proxy measures found no significant relationship. Also notably absent from the literature on sentencing and corrections policy formation is an exploration of media influence. Various measures of media attention have been found to have some effect on other criminal justice policy adoptions (Bergin, 2011), and theoretical literature prominently conjectures about the role of media sensationalism in crime policy formation (Beale, 2006). Suggesting a promising connection between media and sentencing policy, Nicholson-Crotty (2009) provided a brief case study anecdotally exploring the role of media in increasing the salience of three strikes legislation in California. Despite measurement challenges, this is an important area for future research in the sentencing and corrections public policy arena.

Social determinants

Social determinants such as population, urbanization, and citizen wealth were some of the first variables emphasized in models explaining state policy diffusion (Gray, 1973; Walker, 1969). In addition, factors such as race, education, and poverty have been offered up as key indicators within the context of theories of racial and economic threat, which suggest that public policies are “mechanisms for managing the underclass” (Garland, 1990, p. 134). Widespread racial disparities in the criminal justice system suggest a pattern likely to extend into policy formation (Tonry, 1995). There is evidence that governing forces respond to high minority populations, racial tensions, and public portrayals of minority crime with more punitive crime control policies (Jacobs & Carmichael, 2001; Jacobs & Helms, 1999; Liska, Lawrence, & Sanchirico, 1982). Studies employing models of economic threat have explored connections between poverty rates, unemployment, and welfare spending as predictors of incarceration rates and punitive correctional policies, finding promising albeit inconclusive support for the theory (Beckett & Western, 2001; Greenberg & West, 2001; Jacobs & Carmichael, 2001; Link & Shover, 1986; Stemen, 2007).

Seven of the studies identified in this review explore at least one social determinant as a part of their specified model of sentencing and corrections policy formation, and six of these seven include a variable designed to capture racial threat (see Table 5). Three studies find a statistical relationship between the size of the African American population (Allen et al., 2004), the non-White population (Makse & Volden, 2011), or the population of Black and Hispanic males aged 15 to 34 (Link & Shover, 1986) and the passage of general criminal justice reforms.

Table 5.

Social Determinants of State Sentencing and Corrections Policy Making.

Social determinants	Operationalization (source)
Race	Percent African American (Allen, Pettus, & Haider-Markel, 2004 *[+]; Brown, 2013; Nicholson-Crotty, 2004b; Stemen, 2007)
	Percent African American or Hispanic males aged 15 to 34 (Link & Shover, 1986)~[+]
	Percent White (Makse & Volden, 2011)*[−]
Income	Per capita income (Makse & Volden, 2011; Nicholson-Crotty, 2004b; Stemen, 2007)
Unemployment rate	10 year average annual rate of change in unemployment (Link & Shover, 1986)*[+]
	Unemployment rate per 100,000 (Stemen, 2007)
Poverty	Percent population below poverty level (Stemen, 2007)
	Public welfare expenditures per 100,000 (Stemen, 2007)
Education	Percent of population with 4+ years in college (Link & Shover, 1986)
	Proportion high school educated (Makse & Volden, 2011)*[+]
Population density/region	Population (Makse & Volden, 2011)*[+]
	Percent population in urban areas (Stemen, 2007)
Region	Southern states as defined by census (Stemen, 2007)

[ ]Indicated by author as a statistically significant predictor within the specified model.

~[ ]Indicated by author as partially supported within the specified model.

Results of Link and Shover’s (1986) materialist model provide support for a combined theory of racial and economic threat, indicating that large “problem populations” accompanied by rising unemployment rates and declining state economies were predictive of sentencing reform efforts. In general, however, less support is apparent in the sentencing and corrections literature for economic threat hypotheses than racial threat ones. Though three studies set out to test the effect of per capita income, and two the unemployment rate, only Link and Shover (1986) found either influential in policy adoptions. Likewise, Stemen (2007) found no support for his hypothesis that poverty levels and public welfare expenditures will influence adoption of sentencing and corrections policies.

Hypotheses which suggest that larger or more educated populations will be more innovative yield mixed findings. While Makse and Volden (2011) found that more populated states and states with a higher percentage of high school–educated residents are more innovative in justice policy, neither Link and Shover (1986) nor Stemen (2007) do so. Support within the sentencing and corrections policy literature for the predictive value of social variables is divided, yet is also less thoroughly explored than other areas. Theories of racial threat appear to account for some sizable portion of policy making, while the utility of economic threat theories is less clear. Adding to the complexity of understanding social contexts, the potential for correlation between social indicators is high. Yet social variables have important implications for social justice and deserve special consideration by justice-oriented policy makers and practitioners.

External determinants

In addition to internal decision making within states, external forces of diffusion contribute to the spread of policies from one state to another. Public policy theorists suggest that states are likely to adopt policies from other jurisdictions on impulses of imitation, emulation, or even competition (Karch, 2007). The more states that adopt a policy, the more likely others are to follow suit. Walker (1969) was among the first to study the role of diffusion in spreading policies throughout the American states, specifically focusing on the role of geographic proximity to previous adopters in the spread of 88 policy innovations. Geographically determined diffusion patterns have since been widely studied in the public policy literature, including a number of studies exploring policies in the criminal justice arena; however, there is limited empirical support for the hypothesis (Bergin, 2011; Karch, 2007; Mooney, 2001). Half of the studies identified for this review explored some measure of geographic diffusion (see Table 6). Four of the five operationalized the variable through “neighbor adoptions” and one through shared U.S. Census region. Only Makse and Volden (2011) found any statistical support for the geographic diffusion hypothesis in their study of 27 various criminal justice policies.

Table 6.

External Determinants of State Sentencing and Corrections Policy Making.

Diffusion variables	Operationalization (source)
Federal influence	Passage of Violent Crime Control & Law Enforcement Act of 1994 (Allen, Pettus, & Haider-Markel, 2004)*[+]
	Availability of federal funds as percent of total corrections spending (Brown, 2013)*[−]
	Implementation of Federal Sentencing Guidelines (Grossback, Nicholson-Crotty, & Peterson, 2004)*[+]
	Passage of Sentencing Reform Act of 1987 (Nicholson-Crotty, 2004b)*[+]
Geographic proximity	No. of Prior Adopters in U.S. Census Region (Allen et al., 2004)
	No. of Neighbor Adoptions (Grossback et al., 2004)
	Proportion of Neighbors Having Adopted (Makse & Volden, 2011)*[+]
	Y/N if Neighbors Have Adopted (Nicholson-Crotty, 2004b)
	No. of Neighbor Adoptions in Prior Year (Stemen, 2007)
Ideological distance	Absolute Value ([(MostRecentAdopterIdeo.+ AllOtherAdopterIdeo.) / 2]—PotentialAdopter))
	(Grossback et al., 2004)*[−]
	Grossback et al.’s (2004) Formula of Ideological Distance (Nicholson-Crotty, 2004a)*[−]
	Grossback et al.’s (2004) Formula of Ideological Distance (Nicholson-Crotty, 2004b)*[−]
	Number of ideologically similar states adopting in previous year (Stemen, 2007)
Previous adopters	No. of prior adopters (Makse & Volden, 2011)*[+]

[ ]Indicated by author as a statistically significant predictor within the specified model.

Grossback, Nicholson-Crotty, and Peterson (2004) advanced a theory of social learning to better explain diffusion patterns among states. A social learning framework suggests that measures of ideological distance between reference states and adopting states act on the likelihood of adoption more predictably than geographic proximity. In addition, the ideological distance between adopting states and the federal government moderates the effect of federal influence on adoption. Four of the identified studies tested a measure of ideological diffusion in their model of sentencing and corrections policy development, three operationalizing the measure with a formula first published in Grossback et al. (2004), and all four studies used W. D. Berry et al.’s (1998) government ideology indicator as a starting point for formulas determining ideological distance. Grossback et al. (2004), Nicholson-Crotty (2004a), and Nicholson-Crotty (2004b) found strong statistical support for the ideological distance hypothesis: When faced with a greater ideological distance from previously adopters, states were less likely to adopt the same policy. Controlling for a variety of political, legal, and economic variables, Nicholson-Crotty (2004a) found statistical support only for his ideological diffusion hypothesis.

In addition to diffusion from state to state, policy making may be prompted by federal adoption or implementation of policy. The strength of this hypothesis was tested by four of the studies identified in this review, with all four finding a statistically significant effect of federal influence variables on state policy adoption. Allen et al. (2004) found that the passage of the Violent Crime Control and Law Enforcement Act of 1994, which included federal incentives for state implementation of crime control mandates, was a significant predictor of state passage of truth-in-sentencing laws. Similarly, Grossback, et al. (2004) and Nicholson-Crotty (2004b) found that the implementation of federal sentencing guidelines and the passage of the Sentencing Reform Act of 1987, respectively, were positively correlated with state adoption of sentencing guideline legislation. Brown (2013) operationalized federal influence as the availability of federal funds for corrections as a percentage of a state’s total corrections spending, finding that less federal funding for corrections was a significant predictor of the passage of policies reducing the state’s reliance on incarceration—a more costly corrections strategy than its alternatives.

This review indicates that external forces acting on state policy environments—both state to state and federal to state—are among the most consistently strong predictors of state sentencing and corrections policies. While there is limited support for geographic proximity as a predictor of state policy innovation, statistical support for the utility of ideological proximity in understanding state policy decisions lends support to learning theories of policy diffusion.

Policy attributes

While several authors have suggested that the attributes of policies themselves may be a crucial predictor of state policy adoption (Gray, 1973; Makse & Volden, 2011; Stemen, 2007), this is the least explored determinant of criminal justice policy making in the existing literature. While some attempts have been made to separately model the predictors of different criminal justice policies within a single study (Dharmapala, Garoupa, & Shepherd, 2010; Williams, 2003), far fewer have attempted to identify characteristics of policies which may explain differentiation in causes of policy adoption. Gordon’s (1989) factor analysis suggests that even sentencing and corrections policies termed as “get tough” vary in their underlying purposes and are therefore likely to be predicted by different state characteristics and diffusion patterns.

Two of the studies identified in this review explore policy attributes as a predictor of state policy adoption. Stemen (2007) found partial support for his hypothesis that unique causal factors existed for policies coded as either developmental, expressive, or responsive. For instance, crime rates were likely to predict the adoption of determinate sentencing policies and administrative policies but not the adoption of policies termed expressive or designed to “communicate moral outrage” (Stemen, 2007, p. v). Overall, Stemen indicated the need for a better fitting typology of attributes.

Makse and Volden (2011) relied on the perceptions of policy makers to determine relevant attributes, asking criminal justice key informants to rate 27 different criminal justice policies on five scales. Policies rated higher in terms of relative advantage, compatibility, observability, and trialability were significantly more likely to be adopted quicker; whereas, complexity reduced its likelihood of adoption. In addition, Makse and Volden coded the “policy ideology” of the examined policies as conservative, neutral, or liberal and found statistically significant support for their hypothesis that congruence between policy ideology and government ideology would increase the likelihood of adoption. While more study is needed in this area, the research to date indicates that policy attributes may certainly be a meaningful determinant of how and when criminal justice public policies are diffused and adopted.

Discussion

By means of an exhaustive review of the empirical literature, this article provides a detailed look at a number of social, economic, and political variables which help explain the state adoption of sentencing and corrections policies including sentencing guidelines, truth-in-sentencing laws, three strikes laws, and policies governing the privatization of corrections as well as decarceration approaches. Four interrelated but distinct theoretical perspectives on criminal justice policy formation are used to frame contributions from the literature which support internal motivations for policy decision making; these include functional, economic, political, and social motivations occurring within the adopting state. Little support is found for functionalist perspectives which assume that policy development is primarily a product of features of the problem environment. Explanations focusing on the economic capacity of states are more promising, particularly suggesting that state revenue and corrections spending per capita are promising predictors of both sentencing and corrections policies. While there is little support for traditionally advanced hypotheses about the connection between government or citizen ideology as predictors of policy making, other political determinants focusing on party affiliation, political competition, and legislative stability show utility. Social explanations have been more rarely and less conclusively explored; however, considerable support for the potential of racial threat theories to explain sentencing and corrections policies suggests that this is fertile ground for future research.

The literature also successfully looks beyond internal state characteristics to understand the diffusion of sentencing and corrections policies across the United States. On the whole, the contents of this review suggest that federal influences and prior state adoptions are the most consistently predictive determinants of state sentencing and corrections innovations. In addition, policy transfer is facilitated by ideological similarities between prior and potential adopters far more predictably than geographic proximity. Last, a few studies make important attempts to determine the role of policy attributes on adoption rates with limited success. The relative complexity and salience of policy issues appear to influence criminal justice policy making and provide an important starting point for further research.

While this article identifies major contributions to the understanding of sentencing and corrections policy formation, it also reveals that much remains unknown about the predictive ability and relative importance of an extremely diverse array of theorized determinants. Ismaili (2006) emphasized the complexity of the policy-making process and the need for a deeply contextual understanding of criminal justice policies in particular. Understanding is also limited by the relatively small number of published studies representing any one policy area, such as that of sentencing and corrections. Single explorations of some determinants, occurring through the lens of a single operationalization, provide limited evidence of potential utility. Only as patterns are developed across studies employing multiple models and measures can a contextual, holistic understanding of sentencing and corrections policy making begin to emerge.

Implications for Research and Practice

One of the goals of this synthesis is to identify unexplored and underexplored areas of the literature. As observed above, some traditionally supported political determinants of criminal justice public policy formation remain mostly untouched in the empirical literature on sentencing and corrections policy. These particularly include the highly speculated-upon influence of both interest groups and media coverage on increasing the salience of policy issues and rallying public and elected official concern. Only two studies in this review explore the role of interest groups and both use narrow proxy measures of operationalization. It may be that operationalizing interest group influence is a significant challenge which criminal justice policy researchers still need to overcome. The role of media is surprisingly not addressed in the sampled studies at all, though it has been identified as a promising predictor of other criminal justice policy adoptions within the broader literature base on this topic (Bergin, 2011). As sentencing and corrections reforms are frequently a highly publicized and politicized issue, this oversight is considerable and deserves further attention in the empirical literature (Beale, 2006).

Also notably absent from the literature is an exploration of recidivism rates as a feature of the problem environment. While crime rates have been widely tested for their effect on criminal justice policy adoptions, recidivism rates are potentially a more relevant indicator of the problem environment that sentencing and corrections policies seek to address. If the goal of sentencing reforms is to deter crime by locking up more offenders for longer periods of time, then crime rates may provide a proxy measure of general deterrence but do little to measure specific deterrence of the actual offenders targeted by sentencing reforms.

Finally, significantly more exploration is needed to understand the social influences of criminal justice policy making. In particular, theories of racial and economic threat have high relevance for understanding the social justice of crime policies. Moderate support for racial threat variables in the literature suggests the need for expansion of this area of knowledge through the testing of additional measures and operationalizations with the potential to capture a fuller social context of sentencing and corrections policies.

Ultimately, the social context of criminal justice policy making has important implications for policy practitioners in the fields of criminal justice and social work. Criminal justice scholars and practitioners are looking for effective solutions to the crime epidemic in the United States. Social workers are actively engaged in the administration of social justice and have an ethical obligation to address societal factors contributing to the marginalization of populations who lack the political, economic, and social capital necessary to drive policy decisions such as the ones discussed here. Social work is called to respond to ongoing disparities in the incarceration of minority and low income populations as well as appeals for the criminal justice system to be more accountable to the needs of victims and communities vulnerable to the effects of crime. The intersection of political, economic, and social forces with public policy formation represents potential points of intervention for both criminal justice and social work scholars and practitioners engaged in policy work. A deeper understanding of criminal justice policy decisions is necessary to meaningfully inform the development of ethical and effective solutions to the administration of criminal and social justice.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biography

Shannon M. Sliva is a lecturer in the School of Social Work at the University of Texas at Arlington. She researches and publishes on the overlap between criminal justice, social work, and public policy, with a special focus on the implications of justice policy and practice for social, economic, and racial justice.

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