Politics and Policy Discretion

8/8/2019 Politics and Policy Discretion

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Politics and Policy Discretion: How Local Contextual Characteristics Influence theImplementation of Statewide Ballot Initiatives*Garrick L. PercivalDepartment of Political ScienceUniversity of California, Riverside

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*Prepared for delivery at the annual meeting of the American Political Science Association,Chicago, IL September 2-5, 2004

AbstractMuch of the scholarship on initiatives emphasizes the link between voting behavior and

initiative election outcomes or the strategies employed during the policy enactment phase. Littleresearch has considered implementation or whether initiatives ultimately achieve their intendedgoals. Although the initiative process provides a direct link between the people and policy, itcannot be assumed that upon voter approval, an initiative will simply be implemented in a

meaningful and uniform manner within the scope of the initiatives original intent. Using a casestudy of Californias Substance Abuse and Crime Prevention Act (SACPA/Proposition 36) I askhow local politics and other local contextual factors influence the implementation of a statewidevoter initiative. Using aggregate data drawn from each of Californias 58 counties, resultsindicate that politics at the county-level, measured via counties general ideological dispositionsand more specific policy preferences toward drug abuse and drug offenders affect how theyimplement the initiative. Contrary to popular conceptions, results here confirm that initiatives arenot uniformly implemented, but in fact, will be manifested in quite different ways due to localcontextual differences.Introduction

The initiative process is an institutional tool that citizens and policy entrepreneurs can useto promote policy change that is too risky or otherwise unacceptable to elected politicians(Gerber, 1999; Mintrom, 2000). Increasingly over the past two decades voters residing in stateswith the initiative have mandated policy changes in areas as diverse as environmental protection,insurance reform, criminal sentencing laws, and affirmation programs among others. Givenvoters propensity to impose drastic policy change via the ballot initiative , it is not surprisingthat a considerable degree of scholarly attention has been paid to better understanding the process. However, much of the scholarship on initiatives emphasizes the link between votingbehavior and initiative election outcomes or the strategies employed during the policy enactmentphase (Bowler and Donovan, 1998). Little research has considered implementation or whetherinitiatives ultimately achieve their intended goals. Unlike the traditional legislative process,where voters influence on public policy is indirect, direct democracy offers voters opportunitiesto bypass the traditional legislative process to directly affect public policy. Because of this, itmight be assumed that upon voter approval, an initiative will simply be implemented in ameaningful and uniform manner within the scope of the initiatives original intent.

In contrast to much of the previous work on the initiative process, this paper provides arelatively unique examination of the fate of an initiative after its enactment through an analysisof the implementation of Californias Substance Abuse and Crime Prevention Act(SACPA/Proposition 36). The initiative delegates large implementation responsibilities to localcounty governments operating in widely different contextual environments. Because of this, I


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argue that the implementation of the initiative should not be expected to be uniform but vary as afunction of local political preferences and other local contextual characteristics. Resultsdemonstrate, in fact, that a statewide ballot measure can be manifested in quite different waysdue to local contextual differences.

Voter Imposed Authority Migrations and the Added Importance of Local PoliticsOne unmistakable characteristic of direct democracy is that it continues to transform theinstitutional contexts of states governments. A useful distinction can be made between thoseinitiatives that transfer policy making authority from local to state government to those thattransfer authority from state to local governments. Perhaps this distinction is best exemplified inthe state of California. The landmark anti tax initiative, Proposition 13, is a good example of aninitiative that transfers significant policymaking authority away from local governments andinstills power in the hands of state agencies and officials. More recently however, voters havetransferred significant programmatic responsibilities (and discretion) to local governmentsoperating in diverse contextual environments through the enactment of initiatives likePropositions 36.1 Whether policy making authority is transferred from local to state officials or

vice versa is likely to impact the extent to which local political forces impact the implementationof a voter initiative. Importantly for my purpose here, the impact of local politics is most likelyto be felt when initiatives transfer implementation responsibilities to local governments operatingin diverse political environments.

The transfer of policymaking authority to local governments via the initiative process hasimportant implications to the study of direct democracy. For initiatives that place largeimplementation responsibilities upon local governments, to what extent do policy outputs varyby locality, and to what degree do local politics and other local contextual characteristics explainsuch variation? On a similar note, is compliance less likely when implementing responsibilitiesare largely transferred to local governments, where local political forces could potentially shapeand reshape policy outputs and outcomes? Or put another way, to what degree do political forcesoperating at the local level impact whether local governments comply with an initiativesoriginal intent?

I present below a discussion as to why a case study of a California initiative is best suitedto answering these important questions. This is followed by a brief background of Proposition36, a review of the literature highlighting the influence of contextual characteristics on policyimplementation, a presentation of the measures and methods used, formal hypotheses, andempirical findings. I conclude with a discussion concerning the implications of this research tothe study of direct democracy.

Why a Case Study?Nicholson-Crotty and Meier (2002) argue that case studies, such as that employed here,

are most advantageous when unique characteristics of a state make it an ideal venue in which totest a theory. Because of Californias wide use of the initiative process, its diverse citizenry, andwidely divergent local political orientations, the state provides a unique laboratory to examinein detail the expectation that local politics encourage or discourage the implementation of acitizens initiative. Single-state analyses also allow researchers to incorporate more contextualdetail or nuance into a study (Nicholson-Crotty and Meier, 2002). As will be detailed below,contextual factors like local political dispositions are influential in determining policy outputsand outcomes, but are often vaguely measured in multi-state studies. A research design focused


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on one state and one initiative, allows for more explicit measures of important theoreticalconcepts. For example, focusing solely on the state of California lends me the use of theCalifornia Field Poll, a multi-year survey enterprise that provides an excellent methodologicaltool to create more reliable and valid measures of local political dispositions that are a centralfocus of this research. Then, for both theoretical and measurement reasons, California offers a

unique perspective of the implementation of a voter initiative not available in multi-stateanalyses.

Californias Proposition 36: A Dramatic Shift in the States Drug PolicyProposition 36 is an example of a statewide initiative that places specific programmatic

responsibilities on county governments operating in widely different contextual environments.Approved by 61% of California voters, Proposition 36 was enacted in November 2000.Supported by the Drug Policy Alliance and other public health related agencies, but opposed bythe California Republican Party and the California District Attorneys Association, Proposition36 imposes a dramatic shift in Californias fight against illegal drug use and drug-related crimefrom a more punitive approach to a more rehabilitative one, as the initiative mandates that non-

violent drug offenders be placed into drug treatment programs rather than sentenced toincarceration (Riley et al., 2001).Since the early 1980s, Californias approach to fighting drug-related crime has followed a

deterrence and incapacitation theory, which promotes increased arrests, stricter probation and parole monitoring, mandatory sentences, and higher rates of incarceration to dissuade streetcrime by removing offenders from the larger community (Macallier et al., 2000; Maxwell, 1999;Tonry, 1999). These policies have proven to be popular politically as they allow state and localpoliticians to portray themselves as tough on crime and drugs (Beckett, 1999, Tonry, 1999).Given the political and electoral benefits of the get tough approach, California has experienceda 25-fold increase in the number of drug offenders sentenced to state prison during the past twodecades. By the year 2000, Californias rate of incarceration for drug offenders led the nation,with the state incarcerating 130 per 100,000 population (Males, Macallair, and Jamison, 2002)

To break this punitive trend the initiative appropriates to county governments using astandardized formula that takes into account county size and number of drug arrests, $60 millionin fiscal year 2000/2001 for initial start-up costs, and $120 million for each of five subsequentfiscal years concluding with fiscal year 2005/2006 (Ford and Smith, 2001). These funds are to be primarily used for drug treatment but can also be used to defer probation and court costsaccrued as a result of SACPA clients.

Implementation requires cooperation between county and state institutions including theCalifornia Department of Alcohol and Drug Programs (DADP), county public health andcriminal justice agencies, and community treatment providers. A significant degree of discretionis given to counties to determine their respective treatment regimens and number of treatmentfacilities that provide services to Proposition 36 clients (Ford and Smith, 2001). Once determinedeligible for SACPA treatment services by counties criminal justice officials, drug offenders areto be placed into outpatient or residential treatment programs.

Implementing Citizen Initiatives and Other Public Policies

The study of policy implementation is far from reaching a consensus on what variablesserve as good predictors of policy outputs and policy compliance (deLeon and deLeon, 2002).Scholars have more recently treated contextual variables as pivotal factors that help explain theimplementation process. A central goal of contextual studies is to advance our understanding of


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the extent to which contextual variablesor aggregate measures of characteristics found withinspecific political locales (such as a state, county, or city) influence policy choices made byindividuals operating in those environments (Books and Pysby, 1991). The nexus betweencontext and public policy implementation is most commonly illustrated in research of federalpolicy implementation in the decentralized American federalism structure. Research shows that

in a decentralized institutional structure, policy is not implemented according to hierarchicalWeberian principles, where policy enacted by national politicians is simply implemented bystate and local officials in ways that mirror the original intent of national policy makers. Instead,states contexts matters, and policy outputs reflect political forces found at the sub-national level(Pressman and Wildavsky, 1973; Scheberle, 1997).

Although Californias counties are the specific contextual unit of interest here, priorresearch brings attention to several contextual variables relevant to policy implementation and policy outputs at the local level (Goggin et al. 1990; Mazmanian and Sabatier, 1983). Thesevariables can be separated into four primary dimensions: political factors, program budgetallocations, policy needs, and socioeconomic characteristics. These variables and their effects onpolicy outputs are explained in greater detail below.

Political Factors

Prior research, most commonly found in the study of comparative state politics has foundclear associations between state policy decisions and general political orientations like politicalideology and more specific public demands (Erikson, Wright, and McIver, 1993; Hill andHinton-Andersson, 1995; Hill and Leighley, 1996). Political ideology influences individualsviews about the proper scope of government in public affairs and works to constrain policy preferences and policy-making decisions. Erikson, Wright and McIver (1993), constructaggregate measures of state-level political ideology and find convincing evidence that states withmore liberal publics produce more liberal policy outputs. Rather than focusing on a particularstates ideological make-up my focus here is on the impact that ideological variation within aparticular state (measured at the county level) has on the implementation of a statewide ballotinitiative. Counties ideological dispositions may affect implementation in a couple of ways.First, the institutional structure of Californias county governments is likely to strengthen theconnection between counties ideological dispositions and policy outputs. County boards ofsupervisors, district attorneys, and superior court judgesall key implementing actors--areelected officials operating in diverse political environments. Because they are elected rather thanappointed, it is likely these officials are likely to curtail the implementation of the initiative toreflect the ideological preferences of their constituents which then works to increase their ownchances of reelection. Second, street-level bureaucrats in more conservative/liberal counties may be more likely to be ideological conservatives/liberals, and therefore work to implement theinitiative in ways that closely reflect their ideological preferences (see Lipsky, 1980 for adiscussion of the significance of street-level bureaucrats on policy implementation).

In addition the influence of general ideological orientations, researchers haveincreasingly found that more specific policy attitudes regarding abortion rights, environmental protection, and the death penalty (among others) influence policy outputs across the states(Arceneaux, 2002; Brace, Sims-Butler, Arceneaux, and Johnson, 2002; Norrander, 2001). Inshort, policy outputs tend to be reflective of a given localitys general ideological dispositionsand more specific policy preferences.


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Program Budget AllocationsThe degree to which public programs are funded can have a large impact on public

programs ultimate success or failure (Goggin et al., 1990). Including measures of publicprograms budget allocations as a contextual variable to be considered in the local policy makingprocess can serve two purposes. Budget allocations can function as measures of policy outputs,

or as Otoole (1986) has shown, predictors of other outputs associated with a specific program Atthe local level of government program budgets may influence implementing agencies capacityto carry out implementation tasks thereby altering the amount of benefits and services the publicreceives. The target of spending also matters. Research on the Resource Conservation andRecovery Act found that states with better environmental protection records were not necessarilythe wealthiest, but those that targeted a larger proportion of their budgets toward the specificpurpose of clean up (Goggin et al, 1990). Overall, the extent to which programs are funded, andthe target of that spending is expected constrain the policy choices of implementing officials.

Community NeedsIn its simplest form, the needs based approach to explaining policy outputs suggests that

local governments will adopt or implement policies in response to an objective need for a policy.Where a problem is more severe, it might be expected that the need to fix the problem is moreurgent (Thompson and Scicchitano, 1985). Because local government is associated with closecontact between the people and policy makers, it is often believed that local government can bestmatch the response of government to the needs of the community. Indeed, a small body ofresearch shows clear links between need and adoption of economic development incentives,groundwater protection programs, and drug treatment programs (Rubin and Rubin, 1987; Lesterand Kepter, 1984; Meier, 1994).

Socioeconomic Characteristics

Socioeconomic characteristics refer to the constraints stemming from the resources andcapacities within a given locale. Localities with higher socioeconomic status tend to have highertax revenues and therefore have a greater capacity to increase valued public services orregulatory oversight (Treadway, 1985). At the state level for example, fiscal capacity is a strongpredictor of policy outputs (Dye, 1966; 1979).

Taken together, it is expected that these contextual variables structured around four primary dimensions: political characteristics (e.g. general ideological dispositions and specific policy preferences), program budget allocations, community needs, and socioeconomicconditions constrain the choices (and thus help direct) the policy decisions of countyimplementing officials. Constraint placed on the decisional choices made in the implementationprocess should affect policy outputs that ensue.

Implementing Citizen InitiativesThe political science profession is just beginning to tackle the question of what happens

to initiatives after their enactment. With the recent budget crisis in California, journalisticaccounts have frequently highlighted that once enacted, initiatives produce many unintendednegative consequences and are largely to blame for the decline in valued public services as voterimposed mandates severely constrain the policy choices that legislators have to work with(Schrag, 1998). Gerber et al., (2001) and Bali (2003) are two of the few systematic studies thatfocus on the fate of initiatives after their enactment. Using case studies of several California


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initiatives, Gerber et al., (2001) explain why the implementation of initiatives often fails. Usinga principle-agent model, they argue that initiatives do not enforce themselves, but ratherimplementation often requires the help of multiple government officials and agencies operatingat both the state and sub-state levels. Because of this, opportunities become available formembers of state legislatures, localized bureaucrats, or specialized interest groups to implement

policies in ways that meet their own preferences rather than the general public. Studying theimplementation of Californias Proposition 227, Bali (2003) finds political, institutional, andsocio-demographic characteristics within school districts affects compliance with that initiative.

The work of Gerber et al. (2001) and Bali (2003) provides enlightening analysis of howthe decentralized structure of the implementation process influences policy outcomes of severalimportant California initiatives. This paper, however, measures the extent to which a set of moreexplicit county contextual variables affects policy outputs of an initiative that places majorprogrammatic responsibilities on a critical component of the state's governing apparatus--localgovernment.

Understanding SACPA Implementation in County Context

Motivated by the literature highlighting the importance of contextual characteristics onpolicy implementation and policy outputs, I test the influence of counties political orientations,in addition to other local contextual characteristics on four important policy outputs associatedwith Proposition 36the proportion of SACPA expenditures targeted toward drug treatment,quality of treatment services that SACPA clients receive, the percentage of clients whosuccessfully complete their treatment regimens, and the number of persons in each countyincarcerated for low-level drug offenses during the first two years of implementation (2001-2002).

Recall that counties have significant discretion when determining how to target SACPAallocationsfunds may be targeted toward drug treatment purposes or criminal justice activitiessuch as probation monitoring and court costs. Providing a measure of the amount ofexpenditures counties target toward drug treatment is important insofar as it serves as anindicator of policy variation between counties, but more importantly, may serve as a predictor ofcounties capacity to provide high quality drug treatment and overall treatment success.Moreover, measuring treatment quality and the proportion of clients within each county thatsuccessfully complete treatment is important insofar as they help gauge counties abilities toachieve the initiative's ultimate goal of statewide reduction in drug addiction and drug-relatedincarceration and crime. Because the initiative provides county governments with considerablediscretion in determining their respective treatment regimens, it is expected that the quality oftreatment services, and the proportion of clients who successfully complete treatment will varyas well, as differing county contextual characteristics are expected to influence countiesresponse to the initiative and their abilities to meet the treatment needs of SACPA clients.

Recording the number of persons incarcerated for low-level drug possession tests theinfluence that local contextual factors such as counties more specific political preferencestoward drug offenders has on counties compliance with the initiatives original intent. Becauseit is difficult to measure counties compliance when outputs are expected to vary in areas liketreatment quality, a better and more interesting test is found by analyzing specific provisions ofthe initiative where counties appear to have little or no discretion in its implementation andwhere little variation in outputs might be expected. One such provision is that which determineseligibility standards for SACPA clients. Recall that as a result of Proposition 36, non-violent


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drug offenders charged with simple drug possession are to be made eligible for treatment ratherthan be incarcerated. Similar to the intent of Californias 1994 3-strikes initiative, Proposition 36is structured to standardize the behavior of the states criminal justice system as a whole.However, this may be difficult given California does not have one criminal justice system but58one in each county (Riley at al., 2001)

It is well documented in the political science literature that institutional rules affect policyoutcomes by limiting the nature and scope of political actions and choices (Bickers andWilliams, 2001, pp 41). Initiatives, and the rules connected to them are no exception andshould be expected to influence the choices implementing officials make. Relative to theconsiderable discretion given to counties in determining their treatment regimens, Proposition 36appears to provide little or no discretion to county judges and prosecutors when determiningeligibility requirements for SACPA services. Yet, a closer look at the text of the initiative showsthat criminal justice officials do have a sliver of discretion when sentencing potential clients.This discretion provides a window of opportunity for criminal justice agents operating inpolitical environments opposed to the initiative to circumvent the initiatives original intent bycharging potential SACPA clients with offenses that make them ineligible for the program and

allow offenders to be incarcerated under preexisting law (Riley et al., 2001).

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HypothesesThe literature presented above suggests that localized politics and general policy attitudes

like political ideology affects policy implementation and outputs (Erikson, Wright, and McIver,1993). Given this, it is expected that county ideology dispositions will have both a direct andindirect impact on the implementation of the initiative. The first hypothesis tests the expectationthat more liberal counties will target a greater percentage of SACPA funds toward treatmentduring implementation than conservative counties. This follows that traditionally ideologicalliberals are more likely to believe that solving drug abuse and drug-related crime is best done viathe treatment process, whereas ideological conservatives have tended to support tougher punitivemeasures (Beckett, 1999). Following this H1 posits:Ideologically liberal counties are more likely to target a greater proportion of SACPA fundstoward drug treatment than are conservative counties.

In turn, the target of SACPA funding is also expected to impact counties capacity toprovide higher quality treatment services in addition to influencing the rate of treatment successrates across counties. It is expected that counties that expend a greater proportion of SACPAfunds toward treatment will be more likely to provide more high quality treatment services andbe more likely to have a greater proportion of clients that successfully complete their treatmentregimens. This flows from the assumption that counties that spend more SACPA funds ontreatment will also have a greater capacity to provide higher quality treatment services to a largernumber of clients. In addition, greater spending on drug treatment likely increases countiesabilities to curtail treatment regimens to meet individual needs of clients which improve thelikelihood of successful treatment outcomes (Gerstein et al., 1994).

The quality of treatment services, measured here, makes a distinction between the typesof services SACPA clients receive. Higher quality services are considered those treatmentprograms that are residential in nature, where clients receive more intensive treatment, are longerin duration, and programs that require clients to remain in residence during the full course oftreatment. Research on the effectiveness of different modalities of drug treatment findsresidential treatment and length of treatment both strong predictors of decreased drug usage


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(Gerstein et al., 1994). Drug treatment success includes clients who are reported by their drugtreatment providers to have successfully met all the obligations of their treatment program asoutlined by a court mandate. Formally hypothesis H

2posits:

Those counties that target a greater proportion of SACPA funds toward treatment are more

likely to provide more high quality treatment services by sending a higher proportion of SACPAclients to residential programs during SACPA implementation.

H 3 posits:

Those counties that target a greater proportion of SACPA funds toward treatment are morelikely have higher a proportion of clients who successfully complete treatment during SACPAimplementation.

Given the nature of the expected relationships posited in hypotheses 1-3, it is expectedthat counties ideological dispositions will have an indirect impact on treatment quality and

treatment success during implementation. Formally, hypothesis H

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posits:

More liberal counties are more likely to provide more high quality treatment services and havehigher rates of treatment success as a result of targeting a greater proportion of SACPAexpenditures toward drug treatment.

Finally, the fifth hypothesis aims to test the extent to which counties more specificpolitical preferences toward drug offenders influences counties compliance with the initiativesmandate that individuals charged with simple drug possession or drug use be diverted away fromincarceration and instead placed into treatment. Given this, H 5 posits:

Counties that have traditionally taken a more punitive approach to drug users and drug abusebefore the enactment of Proposition 36 are more likely to incarcerate individuals for low-leveldrug possession during the implementation of Proposition 36.

A priori, where there is little policy discretion given to county governments in areas suchas determining SACPA treatment eligibility, it might be expected that the influence of local political factors on implementation would be attenuated. If however, results support thishypothesis, and counties are finding ways to implement SACPA in ways that closely matchestheir own political preferences, this would further exemplify the importance of local politics onthe implementation of the initiative. Empirical evidence showing some counties incarceratingmore individuals for low-level drug offenses than others, a behavior that subsequently works todisqualify more people for SACPA services, would provide evidence that local political forcescan move policy outputs away from the initiatives original intent of treatment, even underconditions where it is least expected.


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Modeling Proposition 36 Policy Outputs

Dependent VariablesThe first dependent variable labeled SACPA drug treatment expenditures measures the

percentage of SACPA funds targeted toward treatment during implementation. The expenditure

data used here is gathered from Ford and Smith (2001, 2002) and measures the total amount ofSACPA funds targeted toward treatment between 2001-2002. Calculations are based on 100%of useable funds. Larger numbers represent greater spending toward drug treatment. As will beillustrated in the causal diagram below, the drug treatment expenditures variable also serves asan independent predictor of service quality and treatment success.

The second dependent variable, labeled treatment quality measures within each countythe percentage of SACPA clients referred to residential treatment programs duringimplementation. This variable serves as a measure of service quality where residential servicesare considered higher quality services than less intensive outpatient programs. Data is collectedfrom the California Department of Alcohol and Drug Treatment Programs.

An additional variable labeled drug treatment success is also included and measures the

percentage of SACPA clients who satisfactorily completed their mandated treatmentrequirements as reported by clients treatment providers. Data are gathered from the CaliforniaDepartment of Alcohol and Drug Programs.

Finally, a fourth dependent variable, labeled drug incarcerations measures the totalnumber of persons incarcerated (per 1,000 persons) in each county for low-level drug possessionduring the first two years of SACPA implementation. Data are gathered from CaliforniaDepartment of Corrections Data Analysis Unit. The low-level drug possession measure is theprincipal controlling offense and refers to individuals charged with possession of small quantitiesof drugs for personal use. Incarcerations for low-level drug offenses is of most interest here because the initiative mandates that low-level, non-violent drug users are to be placed intotreatment, while high-level drug offenses are not eligible for SACPA services.

Independent VariablesSeveral contextual variables are included as predictors of the dependent variables.

Among political contextual factors is a measure of county-level ideology created from poolingCalifornia Field Poll surveys between 1990-1999. (See the Appendix for measures of reliabilityand stability and further discussion of the methodology used). The ideology variable provides ageneral measure of counties political orientations and policy preferences and is used to predictSACPA drug treatment expenditures, treatment quality and success, and incarcerations of low-level drug offenders. This latter expectation is motivated by the assumption that moreconservative counties will incarcerate a greater number of low-level drug offenders duringSACPA implementation considering that traditionally, ideological conservatives tend to betougher on drugs (Beckett, 1999).

Three additional political variables are included as predictors and serve as more specificmeasures of counties drug policy preferences. The first measure, what I call tough on drugs isincluded as a predictor of incarceration rates for low-level drug offenses during SACPAimplementation. This measure is calculated by averaging the total number of incarcerations dueto all drug offenses in each county between 1996 and 1999. Drug offenses in this measureinclude those incarcerations for drug sales, manufacturing, possession in quantities large enoughto presume intent to sell, and low-level drug possession. 3 The second is an averaged measure of


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counties drug treatment expenditures between 1995-1999. This serves as a predictor of SACPAdrug treatment expenditures where it is expected those counties that expended greater fundstoward treatment before the enactment of the initiative will seek to maintain this policy trend bytargeting a greater proportion of SACPA funds toward treatment during implementation. Thethird is an averaged measure of counties probation expenditures between 1996-1999. 4 It is

expected counties appropriating greater funds toward probation prior to the initiatives enactmentwill continue this policy trend by targeting less SACPA money toward treatment and moretoward criminal justice related activities.

Counties drug problem severity is included as a measure of counties policy needs and isused to predict drug treatment expenditures, treatment quality, in addition to serving as a controlvariable predicting drug incarcerations. The degree of drug problem severity is measured usingthe average number of deaths caused by drug overdose in each county between 1999-2001. Dataare collected from the Center for Health Statistics, California Department of Health Services. Itsuse as a control for predicting drug incarcerations follows an alternative expectation that somecounties where the drug problem is more severe may take a more punitive approach todecreasing drug use and drug-related crime by incarcerating more individuals for low-level

possession.Although the political contextual variables are central to testing the hypotheses, severaladditional variables are included as controls to complete the regression models presented below.The total number of residential treatment facilities in 2002 is added to predict treatment qualityacross the counties. This serves as a proxy measure of residential treatment capacity within eachcounty. This is an important measure insofar as the residential treatment capacity within eachcounty likely constrains the choices that implementing officials make when determining thequality of treatment SACPA clients receive. For example, counties that have fewer/greaternumbers of residential facilities capable of providing those services might be expected to refer alower/higher percentage of SACPA clients to residential programs.

Counties socioeconomic status is included as a factor score combining measures ofmedian income and educational attainment. 5 Counties with higher socioeconomic characteristicsare expected to be less likely to incarcerate low-level drug offenders. A race variable, measuringthe number of racial minorities (Blacks and Hispanics) per 1,000 persons in each county isincluded as a predictor of drug incarcerations. Counties where a greater number of racialminorities reside might be expected to incarcerate more low-level drug offenders as priorresearch has shown racial minorities are more likely to be incarcerated for drug offenses than arewhites (Meier, 1990). Finally, two individual level measures including SACPA clients drugaddiction severity and levels of educational attainment are included to predict treatment successrates. The severity of SACPA clients drug addiction is measured by the percentage of SACPAclients in each county who self-reported daily drug use before entering treatment. It is expectedthat counties where clients have less severe addiction problems will have higher overalltreatment success rates. Clients educational attainment is measured by calculating the percentageof SACPA clients in each county who have at least some college education or have completeda college degree. It is expected that those counties where SACPA clients have highereducational levels will have greater rates of treatment success.

Results

Table 1 shows results of regressing the percentage of SACPA funds targeted toward drugtreatment on counties general ideological preferences and more specific drug policy preferences.


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As expected in the first hypothesis, counties general ideological orientations influence the extentto which counties target SACPA funds for drug treatment services rather than criminal justicerelated activities. During the first year of implementation, counties ideological dispositions didnot significantly impact expenditure choices, however during the second year of implementationthere are substantial differences between more liberal and conservative counties and how they

choose to target SACPA funds. Ceteris paribus, more ideological liberal counties expend agreater proportion of funds toward treatment than do conservative counties. This followstraditional ideological beliefs among liberals that fighting drug abuse and drug related crime is best done via the treatment process. As will be shown in greater detail below, greaterexpenditures toward drug treatment-related services among liberal counties provides animportant foundation for higher treatment service quality and treatment success.

[Place Table 1 About Here]

Results in Table 1 also show that counties specific policy preferences toward drug abuse,in this case measured via counties prior drug treatment expenditure levels, explains policy

choices during the implementation of SACPA above and beyond that of counties generalideological dispositions. Those counties that chose to appropriate a greater amount of publicfunds toward drug treatment and rehabilitation before the enactment of Proposition 36 are morelikely to continue that policy trend during the implementation of the initiative by targeting agreater proportion of SACPA funds toward treatment.

Finding variation between counties in terms of how they choose to target SACPA fundsis intriguing but perhaps not that surprising. Because counties have considerable discretion inchoosing how they target SACPA funds, significant variation should be expected given that localelected officials and other implementing agents operating in diverse political contexts are likelyto curtail spending outputs in ways that match local political preferences. Given this, it is perhapsmore interesting to test the extent to which variation in SACPA spending impacts moresubstantive outputs associated with Proposition 36 such as treatment service quality and drugtreatment success rates.

Table 2 provides results of testing the extent to which the target of SACPA fundingimpacts the quality of treatment services. It is important to note that the SACPA drug treatmentexpenditures variable that was used as a dependent variable in Table 1 is now used a predictoroftreatment quality during the second year of implementation. The positive and statisticallysignificant association between the SACPA drug treatment expenditures variable and thetreatment quality measures shows support for the second hypothesis. After controlling for otherconfounding factors such as counties policy needs and residential treatment capacity, resultsindicate that those counties that target a greater amount of SACPA funds toward treatment havea greater capacity to fund higher quality treatment programs and thus are able to send a greaterproportion of SACPA clients to higher quality residential treatment programs.


One major criticism of the implementation of Proposition 36 has been the relatively high proportion of clients who do not successfully complete their treatment regimens. Indeed,averaging drug treatment success rates across all 58 counties during the first year ofimplementation shows that only 26% of clients successfully completed their treatment programs.


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This improved slightly during the second year, as 32% of clients successfully completedtreatment. Although it is out of the scope of this particular paper to understand all the factorsbehind the relatively low overall treatment success rates, it is important nonetheless to attempt toexplain some of the variation in success rates across the counties.

Results presented in Table 3 shows even after controlling for clients educational

attainment and drug addiction severity, SACPA drug treatment expenditures have a significantinfluence on counties treatment success rates, indicating support for the third hypothesis.Counties appropriating greater funds toward treatment, on average, have a greater proportion ofSACPA clients who successfully complete their treatment programs. Reviewing the aggregatedata used here, it is difficult to determine exactly how increased expenditures improve treatmentsuccess rates. However, initial evidence from a statewide survey of implementing officials (thesurvey is currently in the field) suggests that higher levels of treatment funding allows countiesto make better assessments of clients treatment needs, provides drug treatment professionalsmore opportunities to curtail treatment programs to the specific needs of clients, and in somecases, provides for transportation services to and from treatment facilities.


The importance of counties ideological dispositions on the quality of SACPA treatmentservices and overall treatment success is perhaps best understood by viewing the causal model inFigure 1 which shows the indirect effects of county ideology on treatment quality and treatmentsuccess during the second year of implementation. As shown, county ideology influences thetarget of SACPA allocations, which in turn directly affects the treatment quality and thetreatment success rates of SACPA clients. Translating abstract standardized coefficients intomore meaningful units, this model suggests a one standard deviation (in this example moving astandard deviation in the liberal direction) in a countys ideology score produces a 2% increasein SACPA funds used for drug treatment related services. Ceteris paribus, liberal San FranciscoCounty (ideology score=-25.21) which is over 3 standard deviations below the ideology mean(that is, moving in the liberal direction), would increase the proportion of SACPA funds used fortreatment by approximately 8% more than Kern County (ideology score=36.62) which is overone standard deviation above the mean.

A one standard deviation increase (S.D.=10%) in SACPA funds targeted toward drugtreatment produces a 2.6% increase in the number of clients who receive higher quality treatmentservices. As predicted in hypothesis four, counties ideological dispositions have an indirectimpact on both the quality of services SACPA clients receive and treatment success rates whereliberal counties are more likely, on average, to provide higher quality services and have greatertreatment success than more conservative counties.

[Place Figure 1 About Here]

Recall the fifth hypothesis posits that counties that were tough on drugs before theenactment of Proposition 36 will be more likely to incarcerate individuals for low-level drug possession during the implementation of the initiative, effectively making those incarceratedineligible for SACPA services.


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Indeed, the total number of individuals incarcerated for low-level drug possession inCalifornia has dramatically decreased since the implementation of Proposition 36. Datacollected from California Department of Corrections Data Analysis Unit indicates that in 2000,the last year prior to the implementation of the initiative, 12,156 individuals were incarceratedfor low-level drug possession. By the end of the second year of SACPA implementation, this

number had nearly been cut in half with 6,439 individuals incarcerated. Although these numbersare intriguing, they do not provide an answer to an important questionare county governmentsuniformly complying with the initiatives original intent that low-level drug offenders receivetreatment and avoid incarceration? To help answer this question, and to test the fifth hypothesis,I turn attention again to analysis of county-level data.

I begin testing hypothesis H 5 by placing counties into 1 of 3 categories--low, moderate,or highwith their placement dependent upon their respective average number of incarcerationsdue to drug related offenses between 1996 and 1999. Those with a high number ofincarcerations due to drug related offenses are considered tough on drugs (and placed into thehigh category), with those incarcerating the fewest, considered the least tough (and placed inthe low category). 6 Counties that are considered the toughest toward drug offenders before the

enactment of Proposition 36 incarcerate greater numbers of individuals for low-level drugpossession during the 2001 and 2002 SACPA implementation period than do counties that areconsidered least tough on drug offenders. On average, counties considered traditionally tougheston drugs are 4.1 times more likely to incarcerate individuals for low-level drug possession thanare counties that have been traditionally most lenient on drugs during the second year of SACPAimplementation. This represents only a slight decrease from 2000, when counties consideredtoughest on drugs were 4.5 times (incarcerating 45 per 100,000 persons) more likely toincarcerate for low-level drug possession than the most lenient counties (incarcerating 10 per100,000). Although the absolute number of individuals incarcerated for low-level drugpossession has decreased across all counties during SACPA implementation, between the yearsof 2000 and 2002 there has been only a slight change in the rate of incarceration among countiesthat are considered toughest on drugs relative to those in considered most lenient. Overall, theresults suggest that even with a specific initiative mandate where, a priori, little variation mightbe expected between the counties, politics at the local level, in this case measured via countiesspecific policy preferences toward drug offenders has a significant impact on the implementationof the initiative. At least in some counties, these political forces pull policy outputs away fromthe original intent of policy formulators and in doing show signs that some are working tocircumvent the original intent of the initiative.

A multivariate analysis shows similar results. Table 4 provides results of regressing thenumber of individuals incarcerated for low-level drug possession during the first two years ofSACPA implementation on the tough on drugs measure, county ideology, drug problem severity,socioeconomic status, and the racial minority variables included as controls. 7 The standardizedbeta coefficients in Table 4 indicate that the tough on drugs measure is the strongest predictor ofincarcerations in both 2001 and 2002 with the full models explaining 65% and 66% of thevariance in the dependent variable in each respective year. Controlling for other confoundingvariables the results remain substantively the same--those counties toughest on drugs incarceratemore individuals for low-level drug possession during the implementation of Proposition 36.



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In sum, it appears that as intended, Proposition 36 is working to reduce the number ofindividuals incarcerated for low-level drug offensesthe number of those statewide incarceratedfor these offenses has been nearly cut in half during the first two years of SACPAimplementation. These results only tell part of the story however. How counties implementProposition 36, and more specifically how counties deal with low-level drug users is not

uniform. This variation in policy outputs is a function of local political forces as countiesimplement Proposition 36 in ways that closely matches their policy preferences before theinitiative was even enacted.

Discussion

This research has provided a unique look at a statewide voter initiative that has imposedspecific programmatic responsibilities to local governments. The results confirm that contrary to popular expectations, voter initiatives are not uniformly implemented but rather outputs are afunction of local political preferences and other local contextual characteristics.

The empirical results presented here provide explicit measures of several contextualfactors that influence the implementation of Proposition 36. Using the California Field Poll to

create a measure of county ideology, I find that both counties general ideological dispositionsand more specific policy preferences matter in shaping the implementation of initiatives that areexogenously introduced. Counties ideological dispositions are found to have an indirectinfluence on the quality of treatment services SACPA clients receive in addition to clientstreatment success rates. Ceteris paribus, more liberal counties expend a greater proportion ofSACPA funds toward drug treatment which provides SACPA implementing officials operatingin those environments a greater opportunity to refer more SACPA clients to higher qualityresidential treatment services in addition to improving clients overall treatment success rates.Counties specific policy preferences toward drug offenders also matters, where countiesconsidered tough/less tough on drug offenders implement the initiative in ways that closelymatch these preferences during the first two years of SACPA implementation--countiesconsidered tough on drugs are more likely to incarcerate low-level drug offenders than those thatare more lenient. Thus, even in the relatively early stages of Proposition 36 implementation,local political forces are in some counties moving outputs away from the initial intent of policyformulators.

How does this study of Proposition 36 help our understanding of the fate of statewideinitiatives after enactment? The results indicate that when large implementation responsibilitiesare transferred to local governments via the initiative process, policy outputs should be expectedto vary given the opportunities provided to local governments operating in widely differentpolitical environments to shape policy.

On one hand, it can be argued that variation in outputs like treatment expenditures andquality of treatment is not surprising, and is in fact beneficiallocal governments are merelyproducing outputs that are more closely responsive to the states diverse citizenry. On the otherhand, when considering policy outputs (e.g. incarcerations) that provide a better measure ofcompliance, and where policy formulators appeared to expect more uniformity across counties,these findings are in some respects, rather troubling. During the initiatives campaign,proponents repeatedly sold the initiative as a vehicle to transform the states approach to druguse and drug related crime and not a policy that would force some counties to comply with theinitiative intent but not others. With respect to determining sentencing and eligibility for drugtreatment, Proposition 36 attempts to standardize across the state those who qualify for


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treatment, and in doing so, tries to take discretion away from counties in how they deal with non-violent offenders after they are arrested. Whereas prior to the enactment of the initiative,counties could choose among alternatives of incarceration or treatment, Proposition 36 tries toeliminate this latter choice by mandating treatment for nonviolent offenders. Although theresults here show fewer offenders are being incarcerated for lowlevel drug possession, the fact

that some counties appear to be finding small, but significant areas of discretion where they areable to curtail policy outputs to match their policy preferences is likely disconcerting to some.Importantly, the findings here suggest that when the implementation of initiatives is placed in thehands of local officials operating in differing political environments, uniformity in compliancemay be difficult to achieve.

Future research on this initiative should consider more closely, measures of policyoutcomes or policy change. Studying this initiative over a longer period of time would provideresearchers a great opportunity to analyze its substantive impact on drug addiction rates acrosscounties, growth in treatment capacities, and the impact of treatment on drug-related crime. This particular research will hopefully encourage others interested in direct democracy and policystudies to pay closer attention to the policy outputs and outcomes of voter initiatives. Because the

impact of policy ultimately reflects the implementation of policy, not merely its enactment,measuring the actual implementation of initiatives is just as important as understanding whyvoters choose to support or oppose initiatives.Appendix

Erikson, Wright, and McIver (1993) significantly advanced the understanding of state-level public opinion by creating political ideology and partisanship measures by pooling 1976-1988 nationally sampled CBS/New York Times polls and disaggregating them to the state level.These measures were shown to be reliable, stable, and valid.

Here, I use similar methodology to create measures of county-level ideology bydisaggregating to the county-level statewide Field Poll surveys conducted between 1990-1999.The Field Poll uses samples of the California telephone household population drawn fromrandom digit dial (RDD) samples of Survey Sampling Incorporated. In each survey, the primarysampling unit is California counties where samples are systematically stratified to all counties inproportion to each countys share of telephone households in the survey area. Further samplinginformation can be referenced from the California Field Poll Code Books 1990-1999.

A total of 51,930 individual respondents were gathered from a total of 48 Field Pollsurveys. Respondents were asked to place themselves along a 3-point political ideologycontinuum. Specifically, respondents were asked, do you consider yourself to be politicallyconservative, liberal, middle-of-the road, or dont you think of yourself in this way.Conservatives were coded 100, middle-of-the-road 0, and liberals 100. Fortunately, the FieldPoll asks each respondent his or her county of residence allowing me to link each response to agiven county. Individual responses were then reaggregated to create ideological scores for 52 ofCalifornias 58 counties. The number of cases in each county ranged from 13,873 in Los Angelescounty to 17 in Alpine county (mean=659.01). Six small rural counties including, Alpine(n=17), Colusa (n=36), Mono (n=33), Modoc (n=33), Sierra (n=18), and Trinity (n=30) are notused in the analysis because of low sample size. Ideology scores ranged from the mostconservative Madera county (41.26) to the most liberal San Francisco county (-25.35) with amean=21.88.

Auditing the County-Level Measure ofIdeology


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Individual responses are treated here as aggregate data, and therefore it is not appropriateto use standard measures of individual-level reliability like Cronbachs alpha (Brace et al., 2002).Because of this, Jones and Norrander (1996) recommend testing reliability analysis on the basisof aggregate units, and not individuals. To first test the reliability of the ideology measure I usethe OBrien coefficient (see OBrien, 1990). Presented by Jones and Norrander (1996), the

OBrien reliability test seeks to compare the within-unit variance to the across-unit variancewhile taking into account sample size (Norrander, 2001: 113). 8 An OBrien reliabilitycoefficient that exceeds .70 is considered to be highly reliable, and values between .60 and .70are considered to be moderately reliable. The OBrien coefficient for the county-ideologymeasure is .96.

An additional test of reliability is the split-half approach used by Erikson, Wright, andMcIver (1993). The split-half approach involves splitting the Field Poll sample into two subsetsby assigning odd-year surveys to one subset and even years to the other. Mean scores for countyideology were calculated for each subset and correlated using Pearsons r coefficients. TheSpearman-Brown prophesy formula was then used to assess the reliability of each measure.Reliability scores of .70 and above are considered reliable and those between .60 and .70 are

considered moderately reliable, and those below .60 are considered unreliable (Jones andNorrander, 1996). The Spearman-Brown formula:

Where r 12 = the Pearsons r correlation between the split-halves. The Spearman-Browncoefficient for the ideology measure equals .60.

To test the stability, the Field Poll sample was divided into early and late subsets.The early subset included survey years between 1990-1995 and the late subset between 1996-1999. Mean scores for county ideology were calculated and correlated. The Spearman-Browncoefficient for the ideology measures equals .62.

In sum, the assessment of the reliability of the ideology and partisanship measures ismixed. The OBrien measure is highly reliable although the Spearman-Brown coefficients usingthe split-half approach are at the low end of scores considered to be moderately reliable. Ihave chosen to use the ideology measure here, but at the same time make note of its possibledeficiencies.

ValidityTo test the validity of the Field Poll sample a series of demographic characteristics were

derived from the Field Poll and correlated with county demographic characteristics collected bythe U.S. Census (see Brace et al., 2002). Results presented in Table 5 show that county samplesobtained from the Field Poll are remarkably representative. Specifically, I find a strongcorrelation between the educational attainment of the sample and educational attainment reportedby the U.S. Census in 1990 and 2000. A similarly strong relationship is found among betweenthe income of Field Poll respondents and U.S. Census statistics. Racial characteristics ofrespondents, although showing a slightly weaker correlation to U.S. Census figures than do theeducation and income figures, are moderately strong nonetheless. The strong correlations foreducation and income, and the moderately strong correlations for the race variables suggest thatthe Field Poll samples reflect county populations.


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Tackle and Old Question. Political Research Quarterly 54:143-160.Bali, Valentina A. 2003. Implementing Popular Initiatives: What Matters for Compliance?

The Journal ofPolitics 65: 1130-1146.

Beckett, Katherine. 1997. Making CrimeP

ay: Law and Order in Contemporary AmericanPolitics.New York, NY: Oxford University Press.

Books, John W., and Charles L. Pysby. 1991. Political Behavior and the Local Context. NewYork, NY: Praeger.

Bowler, Shaun, and Todd Donovan. 1998. Demanding Choices. Ann Arbor, MI: University ofMichigan Press.

Brace, Paul, Kellie Sims-Butler, Kevin Arceneaux, and Martin Johnson. 2002. Public Opinionin the American States: New Perspectives Using National Survey Data. AmericanJournal ofPolitical Science 46: 173-186.

deLeon, Peter, and Linda deLeon. 2002. What Ever Happened to Policy Implementation? AnAlternative Approach. Journal ofPublic Administration Research and Theory 4: 467-

492.Dye, Thomas R. 1966. Politics , Economics, andPublic Policy: Outcomes in the AmericanStates. Chicago, IL: Rand McNally.

Dye, Thomas R. 1979. "Politics and Economics: The Development of the Literature on PolicyDetermination. Policy Studies Journal(June)652-662.

Erikson, Robert S., Gerald C. Wright, and John P. McIver. 1993. Statehouse Democracy. NewYork, NY: Cambridge University Press.

Feiock, Richard C., and Jonathan West. 1993. Testing Competing Explanations for LocalPolicy Adoption: Municipal Solid Waste Recycling Programs. Political ResearchQuarterly 46, 2: 399-419.

Ford, A., and Micky J.W. Smith. 2001. "Substance Abuse and Crime Prevention Act of 2000:Analysis of Plans from the 58 Counties." Report prepared by Health Systems ResearchInc. for the Center for Substance Abuse and Mental Health Services Administration

Gerber, Elisabeth R. 1999. The PopulistParadox: Interest Group Influence and the Promise ofDirect Democracy. Princeton, NJ: Princeton University Press.

Gerber, Elisabeth R., Arthur Lupia, Matthew McCubbins, and D. Roderick Kiewiet. 2001.Stealing the Initiative: How State Government Responds to Direct Democracy. SaddleRiver, NJ: Prentice-Hall.

Gerstein, D.R., R.A. Johnson, H.J. Harwood, D. Fountain, N. Suter, and K. Malloy. 1994.Evaluating Recovery Services: The California Drug and Alcohol Treatment Assessment.

Chicago, IL: National Opinion Research Center; and Fairfax, VA: Lewin.Goggin, Malcolm, Ann OM. Bowman, James P. Lester, and Laurence J. OToole Jr. 1990.

Implementation Theory andPractice: Toward a Third Generation. Glenview, IL: Scott,Foresman/Little Brown.

Hill, Kim Quaile, and Angela Hinton-Andersson. 1995. Pathways of Representation: A CausalAnalysis of Public Opinion-Policy Linkages. American Journal ofPolitical Science39:924-35.

Hill, Kim Quaile, and Jan E. Leighley. 1996. Political Parties and Class Mobilization inContemporary United States Elections. American Journal ofPolitical Science 40:787-804.


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Jones, Bradford S., and Barbara Norrander. 1996. The Reliability of Aggregated Public OpinionMeasures.American Journal ofPolitical Science 40: 295-309.

Lester, James P., and Patrick Keptner. 1984. State Budgetary Commitments to EnvironmentalQuality Under Austerity. In Western Public Lands, eds. John G. Francis and RichardGanzel. Totawa, NJ: Rowman and Allanheld.

Lester, James P., and Ann OM. Bowman. 1989. Implementing Environmental Policy in aFederal System: A Test of the Sabatier-Mazmanian Model. Polity 21, 4: 732-753.Lipsky, Michael. 1980. Street-level Bureaucracy: Dilemmas of the Individual in Public Services.

New York: Russell Sage Foundation.Macallier, Daniel, Michael Males, Cheryl Rios, and Deborah Vargas. 2000. Drug Use and

Justice: An Examination of California Drug Enforcement Policy. Report prepared forCenter on Juvenile and Criminal Justice.

Males, Mike, Daniel Macallier, and Ross Jamison. 2002. Drug Use and Justice 2002: AnExamination of California Drug Policy Enforcement. Report prepared for Center ofJuvenile and Criminal Justice.

Mazmanian, Daniel, and Paul Sabatier. 1983. Implementation andPublic Policy. Chicago, IL:

Scott Foresman and Company.Maxwell, Sheila R. 1999. "Conservative Sanctioning and Correctional Innovations in the UnitedStates: An Examination of Recent Trends." International Journal of the Sociologyof Law 27: 401-412.

Meier, Kenneth J. 1994. ThePolitics of Sin: Drugs, Alcohol andPublic Policy. Armonk, NY:M.E. Sharpe, Inc.

Mintrom, Michael. 2000. Policy Entrepreneurs and School Choice. Washington D.C.:Georgetown University Press

OBrien, Robert M. 1990. Estimating the Reliability of Aggregate-Level Variables Based onIndividual-Level Characteristics. Sociological Methods and Research 18: 473-504.

Nicholson-Crotty, Sean, and Kenneth J. Meier. 2002. In Defense of Single-State Studies.State Politics andPolicy Quarterly 2, 4: 411-422.

Norrander, Barbara. 2001. Measuring Public Opinion with the Senate National Election Study.State Politics andPolicy Quarterly 1: 111-125.

Pressman, Jeffrey L., and Aaron Wildavsky. 1973. Implementation. Berkeley, CA: University ofCalifornia Press.

Riley, Jack. K., Pat Ebener, James Chiesa, Susan Turner, and Jeanne Ringel. 2001. DrugOffenders and the Criminal Justice System: Will Proposition 36 Treat or CreateProblems? RAND Corp.

Rubin, Irene, and Harold Rubin. 1987. Economic Development Incentives: The Poor (Cities)Pay More. Urban Affairs Quarterly 23:39-57.

Scheberle, Denise. 1997. Federalism and Environmental policy. Washington D.C.: GeorgetownUniversity Press.

Sharpe, Elaine. 1999. The Sometime Connection: Public Opinion and Social Policy. Albany,NY: State University of New York Press.

Thompson, Frank, and Michael J. Scicchitano. 1985. State Implementation and FederalEnforcement Priorities.Administration and Society 19: 95-124.

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Treadway, Jack M. (1985). PublicPolicymaking in the American States.New York: Praeger


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TABLE 1. SACPA Drug Treatment Expenditures Regressed on Selected Predictors

Predictors % SACPA Funds

Used Toward Drug

Treatment (2001)

% SACPA Used

Toward Drug

Treatment (2002)

% SACPA Used

Toward Drug

Treatment Avg 01-

02

b Beta b Beta b Beta

Ideology -.101 -.152(.089)

-.127 -.205**(.079)

-1.37 -.221**

Drug TreatmentExp. 1995-1999

.00009 .432***(.000)

.00009 .432***(.000)

.00009 .470***(.000)

Probation Exp.

1996-1999

-.076 -.145

(.068)

.0016 .982

(.000)

-.003 -.064

(.062)

Drug ProblemSeverity

-18.60 -.085(30.32)

-30.72 .138(30.05)

-29.40 -.144(27.66)

(Constant) 90.26 (4.52) 88.78**(4.37)

90.35(4.12)

R2 = .23 F =3.68** R2 = .22 F =3.52** R2 = .26 F = 4.46**

Note: Reported above are unstandardized and standardized OLS regression coefficients withstandard errors in parentheses **p


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SACPA Drug TreatmentExpenditures

.002 .182*(.002)

(Constant) -.138

(.138)R2 = .38 F=8.10***

Note: Reported above are unstandardized and standardized OLS regression coefficients withstandard errors in parentheses *p


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

Ideology .099 (.002) .13*(.011)

.11(.001)

Socioeconomic Status -.089(.022)

.001(.017)

.051(.017)

(Constant) (.070)* (.056)(.056)*

R2 =.65, F=17.72*** R2 =.66, F=17.95*** R2 =.71, F=22.34***

Note: Reported above are OLS standardized beta coefficients with standard errors in

parentheses. *p


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FIGURE 1. The Indirect Impact of Local Political Variables on the Quality of SACPA

Treatment Services and Treatment Success Rates

Reported above are standardized OLS regression coefficients drawn from results in Tables 1-3.

Notes

1 Californias Children and Families First Initiative (Proposition 10) enacted in 1998, is anotherrecent example of an initiative placing specific programmatic responsibilities on countygovernments. The initiative mandates newly established county-level commissions to fundcommunity education, childcare, healthcare and other social services for children five years ofage and under.2 During the 2000 campaign proponents of the initiative claimed criminal justice agencies mighttry to charge potential and/or existing clients with offenses that make them ineligible forservices. There are several ways criminal justice agents can disqualify individuals for treatmentand sentence him or her to incarceration. For example, if a probationer participating in SACPAtreatment is arrested for simple drug possession, a judge can revoke probation and treatment ifthe state has proven by a preponderance of the evidence that the defendant poses a danger to the

safety of others. [Sec. 1210.1(e)(3)] Likewise, if an individual violates probation duringtreatment and is unamenable to drug treatment provided and all other forms of drug treatment--incarceration is also permitted [Sec. 1210.1(c)(2).]. Both of these provisions permit judges andprosecutors operating in environments with more punitive views toward drugs to circumvent theoverall intent of the act through broad interpretations (Riley et al., 2001).

In addition, there are opportunities for county prosecutors to divert potential SACPAclients to incarceration before they even begin the treatment process. Under the initiative, it is

County Idiology Succes Drug Treatment Rate

% SACPA FundsSpent on Treatment(2002) .182*

Drug Policy Preferences(Drug Treatment Expenditures 1996-

1999)

Treatment Quality

-.205* .629***

.432***


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possible to divert to incarceration a defendant who is charged with simple-drug possession andwho is otherwise eligible for probation and treatment by charging him with co-occuring offensesother than the one related to drugs [Sec. 1210.1(b)(2)]3 Ideally, it would be better to add a length of sentence component to the tough on drugsmeasure. Unfortunately, 1993 was the last year the Administrative Office of the Courts collected

statewide data for drug offenders sentenced to prison. Because data have not been collected forover 11 years at the time of this writing, I have chosen not include this data in the measure.4 Drug treatment and probation expenditures are gathered from the California Association ofCounty Governments.5 Because of multicollinearity concerns between the education (percentage of county residentswho have earned a bachelors degree or higher) and county median income variables, thesemeasures are collapsed to form a socioeconomic factor variable which explains 90.2% of thecommon variance.6 Counties are ranked based on the average number of incarcerations per 1,000 persons between1996 and 1999. Numbers are calculated based on incarcerations for high-level drug offenses(drug sales, manufacturing, or possession of quantities large enough to presume intent to sell,

and simple drug possessions). Counties in the bottom one-third of rankings are placed in thelow category, middle-third medium category, and top-third, high category.7 As noted above, several scholars have found that aggregate measures of specific policyattitudes like the death penalty and abortion explain specific policy outputs above and beyond theimpact of general ideological orientations (Brace et al., 2002; Norrander, 2001). Moreover, in thecontext of initiative implementation, Gerber et al., (2001) argue that the political sanctions fornot complying with the intent of an initiative becomes more costly where public support ishigher. Under conditions where public opinion is more supportive of a specific initiative, theirresearch suggests policy outputs should be more responsive to public preferences. Based on thisresearch I included in other models not shown here the percentage of voters in each county whovoted yes on Proposition 36 as an additional measure of specific attitudes toward the initiative.The expectation is that those counties with greater support for the initiative will provide higherquality services and be less likely to incarcerate individuals for low-level drug possession. In allmodels the measure failed to reach statistical significance. I believe this is partly due tomulticollinearity between the ideology and the percentage voting yes on the initiative wherePearsons r correlation equals .71 (p

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