MIAMI UNIVERSITY The Graduate School
Certificate for Approving the Dissertation
We hereby approve the Dissertation of
Craig S. McClure
Candidate for the Degree:
Doctor of Philosophy
______Director Dr. Philip A. Russo, Jr.
______Reader Dr. Melvin Cohen
______Reader Dr. John P. Forren
______Graduate School Representative Dr. Peter M. Schuller
ABSTRACT
SEEKING JUSTICE: EXAMINING ADULT OFFENDER REENTRY COURT PARTNERSHIPS FROM A POLICY IMPLEMENTATION PERSPECTIVE
by Craig S. McClure
This dissertation reveals a unique and atypical role for community level judges as adult offender reentry coordinators. Reentry court partnerships (RCPs) place the judge at the center of post-release supervision and treatment. RCPs are new and innovative community-based programs that are designed to help offenders leave the state prison system and successfully return to society. This study asks the fundamental question, “How are reentry court partnerships being implemented?” In answering the question, reentry court actors and their decisions are the focus of data collection using a values- based survey instrument. This dissertation contributes to clarifying a disparate body of policy implementation research generally, as well as provides data that will aid current and future reentry court development nationwide. The key findings of this dissertation are that an actors’ sense of accountability most strongly influences decision making in the policy implementation process, and that elected judges can emerge as powerful agents for social change in the community.
SEEKING JUSTICE: EXAMINING ADULT OFFENDER REENTRY COURT PARTNERSHIPS FROM A POLICY IMPLEMENTATION PERSPECTIVE
A DISSERTATION
Submitted to the Faculty of Miami University in partial fulfillment of the requirements for the degree of Doctor of Philosophy Political Science Department
by
Craig S. McClure Miami University Oxford, Ohio 2005
Dissertation Advisor: Dr. Philip A. Russo, Jr.
CONTENTS
I. List of Tables vi II. Preface vii A. Research Question viii B. Acknowledgements ix C. Dedication x
PART 1
CHAPTER 1
TWO SUBFIELDS OF POLITICAL SCIENCE: PUBLIC POLICY AND ADMINISTRATION PERSPECTIVES AND APPROACHES
I. Introduction 1 II. Background and History 1 III. Public Policy and Its Definition 4 A. First Area 4 B. Second Area 5 C. Policy Types 6 D. Policy Areas 7 IV. The Development of Public Policy Implementation Research 7 A. First Generation 7 B. Second Generation 8 1. Part 1, “Top-down” 8 2. Part 2, “Bottom-up” 11 3. Part 3, “Synthesis” 13 C. Third Generation 17 V. Public Administration and its Definition 18 A. Wrongly Separating Politics from Administration 18 1. Characteristics of Bureaucracy 20 2. Principles of Scientific Management 21 B. Rediscovering Democratic Values in Public Administration 22 VI. Conclusion 25
CHAPTER 2
VALUES-BASED PUBLIC POLICY AND ADMINISTRATION: IMPLEMENTATION CONTEXT, VARIABLE DEFINITION, AND RESEARCH MODEL
I. Implementation as Decision Making in Context 26 A. The Implementation Context in Terms of Ambiguity and Conflict 27 1. Administrative implementation 28 2. Political implementation 28
ii 3. Symbolic implementation 29 4. Experimental implementation 30 B. The Experimental Context of Reentry Court Partnerships 30 II. A Taxonomy: Separating Variables by Classification, Type, Category and Variety 32 A. Variables by Classification and Type 33 B. Variable Types Explained in Terms of Responsibility 34 1. Personal responsibility 34 2. Procedural responsibility 34 3. Professional responsibility 35 4. Political responsibility 36 C. From Variable Classification to Categories 36 D. Defining Discretion: Responsibility & Accountability 38 1. Responsibility (Internal/Informal) 39 2. Accountability (External/Formal) 40 E. Defining Resources: Expertise & Material 42 1. Expertise (Internal/Formal) 43 2. Material (External/Informal) 43 F. Variable Varieties 43 G. Applying Context and Variables to the RCP Environment 46 III. Variable Types Explained in terms of Decisions 47 IV. Conclusion 48
PART 2
CHAPTER 3
THE RISING COST OF OFFENDER SUPERVISION: REENTRY COURT PARTNERSHIPS AS AN INNOVATIVE SOLUTION
I. The Context for Reentry Court Development: Prison and Parole Policy 50 A. State Financial and Social Costs 51 B. The Social and Administrative Impact of Incarceration 53 C. The Failure of Post-Release Supervision and the New Prisoner Reentry Philosophy 55 D. Revitalize or Replace Parole Supervision? 56 E. Administrative Realities and Advocacy Initiatives 57 II. Reentry Court Partnerships Defined 59 A. The Role of Judges 60 B. The Role of the Courts 62 C. The Role of the Community 63 D. Public Policy Implementation Research & RCPs 64
iii III. The Richland County, Ohio Reentry Court Partnership 66 A. Ohio Reentry Court Concept Model 67 1. Assessment and Planning 67 2. Merging Parole and Probation Supervision 69 3. Developing Shared Standards 70 4. Institutionalizing a Shared Sense of Ownership 72 B. Ohio Reentry Court Program Elements 73 1. Objectives 73 2. Community Partners and Treatment 75 IV. The Allen County, Indiana Reentry Court Partnership 76 A. Indiana Reentry Court Concept Model 76 1. Community Corrections 77 2. Joint Monitoring and Supervision 79 B. Indiana Reentry Court Program Elements 79 1. Risk Assessment and Reintegration Plan 80 2. Job Academy 81 3. Community Partners 82 V. Conclusion 83
CHAPTER 4
REENTRY COURT PARTNERSHIPS EXAMINED: VALUES-BASED DECISION MAKING AS THE KEY TO UNDERSTANDING POLICY IMPLEMENATION
I. Introduction: “How are Reentry Courts Being Implemented?” 84 II. Key Actors: The Judges 86 A. Key Findings: The Data 87 B. Ohio Judges by Decision Type 90 C. Indiana Judges by Decision Type 92 D. Decisions Measured by Category and Division 96 E. Ohio and Indiana Judges Decisions by Category and Division 96 1. Discretion: Responsibility and Accountability 96 2. Resources: Expertise and Material 98 F. The Judges’ Implementation Decisions 99 III. Key Actors: The Administrators 100 A. Ohio Administrators by Decision Type 101 B. Indiana Administrators by Decision Type 104 C. Ohio and Indiana Administrators Decisions by Category and Division 106 1. Discretion: Responsibility and Accountability 106 2. Resources: Expertise and Material 108 D. The Administrators’ Implementation Decisions 109 IV. Key Actors: The Community Partners 110 A. Ohio Community Partners by Decision Type 110 B. Indiana Community Partners by Decision Type 112
iv C. Ohio and Indiana Community Partner Decisions by Category and Division 113 1. Discretion: Responsibility and Accountability 113 2. Resources: Expertise and Material 115 D. The Community Partners’ Implementation Decisions 115 V. Aggregated Findings 117 A. Decision Making as the Key to Understanding Policy Implementation 117 1. Ohio RCP Actor Decisions Informed by Type 119 2. Indiana RCP Actor Decisions Informed by Type 120 3. Ohio RCP Actor Decisions Influenced by Category 121 4. Indiana RCP Actor Decisions Influenced by Category 122 B. Findings and Recommendations 123 C. Conclusion 127
APPENDICES
Appendix A: Case Selection Value Key and Table 129 Appendix B: Democratic Implementation Research System Model 131 Appendix C: Reentry Court Participant Survey 132 Appendix D: Richland County, Ohio Reentry Court Process Flowchart 138 Appendix E: Allen County, Indiana Reentry Court Process Flowchart 139
REFERENCES 140
v TABLES
Table Page
2.1. Ambiguity – Conflict Matrix: Policy Implementation Process 28
2.2. Variable Classification and Type 33
2.3. Categories of Variables 38
2.4. Combined Table of Variables and Definitions 45
2.5. Specific and General Variables by Classification, Category and Type 46
3.1. Prison Costs for Fiscal Year 2001 (States in This Study) 51
4.1 Ohio Reentry Court Judges’ Mean Survey Scores by Decision Type 89
4.2 Indiana Reentry Court Judge’s Mean Survey Scores by Decision Type 93
4.3 All Reentry Court Judges’ Mean Scores by Jurisdiction, Division & Category 97
4.4 Ohio Reentry Court Administrators’ Mean Scores by Decision Type 102
4.5 Indiana Reentry Court Administrators’ Mean Scores by Decision Type 105
4.6 All Reentry Court Administrators’ Decisions by Jurisdiction, Division & Category 107
4.7 Ohio Reentry Court Community Partners’ Mean Scores by Decision Type 111
4.8 Indiana Reentry Court Community Partners’ Mean Scores by Decision Type 114
4.9 Reentry Court Community Partners’ Decisions by Division & Category 116
4.10 All Actors’ Mean Scores Compared by Decision Type and Category 118
vi PREFACE
Reentry court partnerships (RCPs) are innovative community programs designed to place judges at the center of the offender reentry process. This unconventional placement and definition of a judge’s role has public and private dimensions and implications. The public role of judges in the RCP model transforms them from being a neutral arbiter interpreting the law in an adversarial setting, to that of an active partner in setting and enforcing reentry program standards. Behind the scenes, the judge takes on the role of lead reentry administrator and case manager in order to regulate the process and the progress of reentering offenders. The reentry process, simply defined, is the series of events and interventions that occur in the time an offender is released from prison and successfully returns to society as a reformed citizen, or is returned to prison as a recidivist. This process, specifically as it applies to RCPs and the new role of judges, has yet to draw the attention of political scientists, and little social science work has been done on comparing the implementation of these courts in various states.1 Traditional reentry programs that assist offenders in their transition from state prison to local community are not a new idea, but involving judges in the decision making process of reentry supervision and treatment is a recent development.2 RCPs are still considered experimental in nature because of their limited number and the administrative, legal, and philosophical obstacles still existent in each jurisdiction. These programs are a result of the ideas and efforts of community-based coalitions of partners that have come together to address the connected issues of offender recidivism and public safety. Their ultimate success or failure will be determined based on their impact on recidivism rates. In the meantime, RCPs offer an interesting case study example of a bottom-up (community- based) policy formulation and program implementation process that fundamentally alters the role of judges.
1 As of August 2005, there is only 1 unpublished comparative evaluation known for adult offender reentry courts (RTI.org), and 2 unpublished single court evaluations (OH, KY) in a current universe of 8 single jurisdiction courts nationwide (CO, DE, IA, IN, OH, NY, TX, WV). 2 Reentry courts were formally proposed in 1998 by the Director of the National Institute of Justice (NIJ) Jeremy Travis, program planning began in 1999 (USDOJ 1999), and initial court operations began in 2000. Nine state jurisdictions answered a National Institute of Justice call for reentry court concept papers in 1999 and became part of an informal pilot project intended to test the viability of the concept.
vii An examination of the policy implementation process of selected RCPs will provide an initial look at this developing area of public policy, and deliver an in-progress process evaluation to RCP administrators and policy implementation scholars. The in- progress nature of this study is important because public policy implementation scholarship has largely focused on retrospective post facto policy analysis of implementation outcomes (policy evaluation). Therefore, the focus of research attention for this study is the values-based decisions of the actors involved in the RCP implementation process rather than in defining the “success” of the program. This study also relies on the assumption that policy implementation is an iterative and cross-cutting process worthy of social science research and analysis in itself, especially within the discipline of political science. Implementation as an iterative process assumes no clear political distinction between decision making in the formation or the implementation phases of public policy. In other words, no gap between the two phases is assumed when the policy process is taken as a whole. The basic reason for this assumption as applied to RCPs is that the policy creators and the policy implementers are the very same actors. RCPs in two states3 will be used to analyze the implementation decisions of key policy actors. Their decisions will be the dependent variables measured using values-based independent variables drawn from existing public policy and public administration scholarship. The use of a formal model and empirical testing in a small-n comparative case study in this instance is interested in understanding the relationship between actor values-based decision making and the public policy implementation process by answering the main research question: “How are reentry court partnerships being implemented?” This study is organized in two parts, with each part consisting of two chapters. Part one addresses the perspective, approach, and research design of the study. The unique program design and working relationships of the actors in the RCP model demands a perspective that crosses traditional boundaries of academic literature, and a research model that brings together and focuses the applicable components into a single approach. The introductory chapter for this study of RCPs builds a research framework
3 See Appendix A. Originally, by the case selection criteria, four courts were selected and contacted as objects of study. Subsequently, two courts have been eliminated from participation because operations were permanently discontinued in one (Florida), and indefinitely suspended in another (Delaware).
viii using a meta-analysis (literature review) of public policy and public administration literature. Next, the best defined and transferable elements of research are combined to provide a single perspective to orient the discussion and analysis of the dynamic and complex process of public policy implementation. This base perspective is further refined through a values-based decision making approach drawn from variables discerned from the meta-analysis. Chapter 2 describes and operationalizes a research model built upon this approach. The resultant research model is a new and unique way to consistently and uniformly study the implementation process of current and future RCPs. Part two of this study is concerned with applying the research model to the RCPs of interest. Chapter 3 first discusses why and how RCP programs developed as a response to failed probation and parole supervision models. Each of the RCP programs of interest is then described in detail before using the preliminary results of this study (chapter 4) to answer the fundamental research question and to offer prescriptive advice for the operational practice of current and potential RCPs. I would like to thank a number of people that provided me with assistance and advice during the course of this study. The judges, administrators, and community partners involved with the RCPs in Richland County, Ohio and Allen County, Indiana have been wonderful in their openness and assistance by sitting for interviews, helping in the dissemination of the survey instrument, and allowing me to observe their staffing meetings and courtroom hearings. I would especially like to thank Mr. Dave Leitenberger, Ms. Toya Bowman, Officer Brett Snavely, James (JJ) Bittinger, Pete Semenyna, Joseph Baker, Dr. Jeffrey Spelman, and Judges James DeWeese and James Henson from the Richland County, Ohio RCP; and Sheila Hudson, Stan Pflueger, Amy Krieger, Tony Hudson and Judge John Surbeck from the Allen County, Indiana RCP. I also thank my dissertation committee members; Dr. Philip A. Russo, Jr., Dr. Melvin Cohen, Dr. John Forren, and Dr. Peter Schuller for their valuable feedback and advice. Thanks to my wife Agnieszka and daughter Sylvia for their patience and understanding during my absence for field research and isolation during writing and rewriting. Thanks also to my mother and father, Gary and Karen McClure, for housing me during field research visits to Richland County, Ohio, and helping to prepare and label envelopes containing my survey instrument. Above all, thank God for His mercy and grace.
ix
To my family
x CHAPTER 1
TWO SUBFIELDS OF POLITICAL SCIENCE: PUBLIC POLICY AND ADMINISTRATION PERSPECTIVES AND APPROACHES
Introduction This chapter will focus exclusively on building the research perspective and approach of this study. To do this effectively, the discussion will encompass the “big picture” of the foundational literature. In order to accomplish this task, a detailed meta- analysis is offered to orient those unfamiliar with previous public policy and administration scholarship. This exercise is necessary for two reasons. First is that public policy and administration literature pursues multiple and disparate paths of inquiry. This is a result of the numerous types of public policies and techniques of administration that are the objects of academic study. The result of this multiplicity is that there is no standard philosophy or approach in conducting policy and administration research and analysis. In order to establish a clear trajectory for current and future research of RCPs, a detailed review of past literature is necessary to illustrate accomplishments in other areas and discern transferable variables. This will help to refine both the macro (systematization) and micro (values) components of a research philosophy concerned with describing RCP practice, as well as prescribing future program decisions and development. The second reason for this exercise is that RCPs, given their community- based partnership design and operation, cross the boundary lines of traditional subdisciplinary literature. There currently is no established research perspective and approach that can adequately explain or analyze the decisions and operations of RCPs. The best example of this vacuum in scholarship is in the atypical role that judges play in the decision making process and routine operations of RCP programs. There currently is no literature that addresses the judicial self-selection, behavior, or decision making in the case of RCPs. Therefore, in order to successfully analyze RCPs, a new research perspective and approach is offered here that builds on the transferable accomplishments of previous public policy and administration literature. Background and History Political science’s subfields of public policy and public administration do not share a unified theoretical or methodological framework. There are three basic reasons
1 for this divide. The first reason is that these subfields encompass the multiple and dynamic areas of human activity and processes found in the institutions, organizations, and professions that directly or indirectly affect every citizen of the United States. In other words, the subfields of public policy and public administration are not yet able to join together in theory or research method a practical endeavor that is simultaneously an operational art, an analytical science, and an administrative craft. A second reason is the utility of the various proven methodological means and research agendas that successfully frame and measure certain aspects of governmental institutions and political processes.1 Third is that the development of these two subfields is separated in time by eighty years. The study of American public administration began in the 1880s when Woodrow Wilson, James Bryce, Richard Ely and Albert Shaw assembled a curriculum at Johns Hopkins University for the study of public service based in politics, law, history, economics and ethics (Hoffman, Curtis M. 2002, p. 12).2 In contrast, the formal study of public policy didn’t develop until the 1960s (Rosenbloom, David H 2002, p. 504).3 Any theory used as a basis of analysis of subjects within these subfields is also colored by the perspective from which one views the activity. Public administration is simultaneously a professional practice that seeks to satisfy the “public good,” a field of academic research aimed at discovering new knowledge, and the administrative arm (bureaucracy) that is an
1 Careful and systematic research in the social sciences can be defined by several positivist/quantitative criteria (purpose, validity, testability, causality, topical importance, cutting edge significance), as well as by other-than-positivist/qualitative modes of social research (explanatory, interpretive, critical) (White, Jay D., (1994). Abraham Kaplan helps to frame a conceptual understanding of methodology used in the conscious effort to advance knowledge as: Techniques, the specific procedures used in a given science; Honorifics, a ritual invocation attesting to concern itself with meeting standards of scientific acceptability, and; Epistemology, involving the most basic philosophical questions about the pursuit of truth (see Kaplan, (1964), in Perry & Kraemer (1994), pp. 93-94). 2 Woodrow Wilson acknowledged the ancient Greek origins of political science, but wrote that the science of administration, “…is a birth of our own century, almost of our own generation [as] developed by French and German professors. If we would employ it, we must Americanize it, and that not formally, in language merely, but radically, in thought, principle, and aim as well. It must learn our constitutions by heart, must get the bureaucratic fever out of its veins; must inhale much free American air” (Wilson, Woodrow 1887/1997, p. 14, 16). Public administration became a subject of study in the new departments of political science just as the Progressive movement gained a foothold in American political discourse. The matching of the two was useful for both, as Progressivist ideology gave efficiency in government second place only to democracy itself (Mahoney, Dennis J. 2004, p. 133). 3 As early as 1922, however, University of Chicago political scientist Charles Merriam sought to connect the “theory and practice of politics to understanding the actual activities of government, that is, public policy” (Birkland, Thomas A. 2001, p. 4).
2 access point for citizens to interact with and influence their government. Within each of these perspectives as well are found various approaches that shape and orient research by emphasizing various human values found along a continuum between the purely rational (self-interested) and the purely altruistic (selfless).4 Multiplicity in conceptual frameworks that includes theory, perspective, and approach is mirrored in the struggle that political science and its subfields endure in finding agreeable research designs and empirical models. As Dennis Mahoney put it, “The history of American political science…has been, to a large extent, the history of a discipline looking for a methodology” (Mahoney, Dennis J. 2004, p. 119). This academic struggle is best reflected today in the “Perestroika” movement that promotes methodological diversity and seeks a synthesis between, or resolution of, the conflict between the relative value of qualitative and quantitative research designs and models.5 Getting less attention has been the lack of an agreed upon general theory that adequately frames the various research designs and models of concern. This disparity of opinion is not a recent development. From its beginnings in 18806 as an academic discipline in its own right, political science has developed and relied on three general social science theories with constituents enough to propel the discipline to its present methodological debates. Pluralism (systems of republican government are non-hierarchical, overlapping, and egalitarian), Policy Sciences (using scientific principles to explain and predict policy
4 A pioneer in the attempt to unify policy research perspectives is Harold Dwight Lasswell (1951). Lasswell wanted to create an applied social science that would act as a mediator between academics, government decision-makers, and ordinary citizens by providing objective solutions to problems that would minimize or eliminate “unproductive” political debate. His perspective was threefold: a multidisciplinary approach, a problem oriented focus that was contextual in nature, and an explicitly normative orientation (see Torgerson 1985, in Fischer 2003, p. 3). Normatively, Lasswell recognized the need to anchor such an approach in human values. It was to be a “policy science of democracy” (Fischer 2003, p.3). This study will define a values-based (democratic) approach to the decision making behavior of actors in the implementation of adult prisoner reentry court partnership programs. 5 At its heart, this is a philosophical debate over the merit of a political science based in the traditional pursuit of the understanding of immutable principles, or self-evident truths, about the nature of man and of political things, versus the denial of such principles and the idea that politics is guided by evolutionary progress (Mahoney, Dennis J. 2004). 6 A characteristic of an academic discipline is that it is an organized body of scholars. The Academy of Political Science (A.P.S.) was founded in 1880 by the Columbia School of Political Science, and published America’s first political science journal, the Political Science Quarterly, in 1886. The A.P.S. was not independent or comprehensive enough to serve as the basis for organizing the entire discipline, however, and in 1903 the American Political Science Association (A.P.S.A) was created with Frank J. Goodnow elected its first president. The founding of the A.P.S.A. represented the achievement of the new political science of the status of a profession (Ibid).
3 and administration), and Public Choice (self-interested rational behavior in the aggregate) have each had significant impact on the evolution of the discipline. These theoretical frameworks still divide political scientists today regarding their applicability, validity, and long term value to the discipline.7 Public Policy and Its Definition Public policy is whatever governments choose to do or not to do (Dye, Thomas R. 2001, p. 2) in its authoritative allocation of societal values and resources (see Easton, David 1965). Public policies deliver “… goods and services as well as regulations, income, status, and other positively or negatively valued attributes” (Schneider, Anne Larason and Ingram, Helen 1997, p. 2), and have as their normative8 objectives in a democratic society to solve societal problems, support democratic values and institutions, and serve justice (Schneider & Ingram, 1997, p. 202). “Stated most simply, public policy is the sum of government activities, whether acting directly or through agents, as it has an influence on the life of citizens” (see Peters, Guy 1999, in Birkland p. 21). Regardless of the particular definition for public policy, the study of public policy within the academic field of political science is divided into the two areas of policy design and evaluation (analysis), and policy making and implementation research. In other words, there is a theoretical science of policy making and a practical science for policy making (Lane, Jan- Erik 2000, pp. 319, 321). First Area The first of the two areas of study is primarily concerned with systematically designing policy that addresses a problem of society (design),9 and the client oriented advice relevant to public decisions that is informed by social values (analysis) (Weimer, David L. and Vining, Aidan R. 1999, p. 27). Evaluating both the intended and unintended
7 Other theories with a smaller following among those concerned with American politics and policy include Elite Theory which posits that social elites largely influence the policies of government (see Robert A. Dahl, “Who Governs,” 1960; and Thomas R. Dye, “Who’s Running America? The Bush Restoration” 2002). Functionally, Elite Theory can be considered a subcategory of Public Choice Theory. 8 The concept of normative behavior and policy objectives in the context of this study will always refer to implied values-based standards or principles used as a guide for right decision making and action. 9 Five basic elements of policy design are: The goals of the policy (to eliminate, alleviate, or keep the problem from getting worse); the causal model (if X is done will Y result?); the tools of the policy (will the instruments used include incentives, persuasion, or information?); the targets of the policy (whose behavior is to change either directly or indirectly?); and the implementation of the policy (how, who and why?) (see Table 7.1 in Birkland, 2001, p. 153). For a more detailed discussion of policy goals, problems, and solutions see Deborah Stone (2002).
4 outcomes of particular types of public policy are necessary for the analyst to explain what governments’ do, why they do it, and what difference it makes (Dye, Thomas R. 2002). In doing public policy evaluation, the objective for both policy practitioners and political science scholars is to use theory to describe the actions of government, determine the causes for the actions, and explain the consequences of the actions. This activity is directed toward a goal of offering technical understanding, professional advice, and policy recommendations to policy makers. Policy makers desire knowledge about which policy choices will produce desired outcomes, and when it is wise to take action (Granato, Jim and Scioli, Frank 2004, p. 316). To this end, policy evaluation has been formalized and codified into various models of public policy analysis, even though policy analysis is routinely considered more an imaginative art, or a problem-solving craft, than a science (Wildavsky, Aaron 1979; Bardach, Eugene 2000). Policy evaluation is practiced by various types10 of policy analysts both within government (Meltsner, Arnold J. 1976, p. 16), and outside government from various perspectives and political agendas (Heineman, Robert A., Bluhm, William T. et al. 2002). No matter what kind of analyst, agenda, or policy type, policy analysts - in order to be effective in achieving their goal - must practice their creative art within the same political environment that public policy is created, adopted, and implemented in order for them to have any positive impact in the decision making process (Stone, Deborah 2002, p. xi). Second Area The second area, public policy making and implementation research, is more interested in investigating questions of how government is doing what it has decided to do. This perspective can best be thought of as studying government as it reconciles the processes of democratic decision making with the practical administration (Berkley, George and Rouse, John 2004) that is necessary for public policy implementation. It searches for the optimum synthesis needed to “…bridge the distance between theory and practice, knowledge and power, contemplation and action, …[and] philosophy and
10 Types of policy analysts are defined by levels (High or Low) of political skill and analytical skill. Analysts exhibit various motivations, standards of success, time horizon (short or long term focus), and attitudes that are summarized as: Entrepreneur (High-High); Technician (Low-High); Politician (High- Low); Pretender (Low-Low). Overall, Meltsner determines that policy analysts are largely what their clients want them to be as they work together to justify public policy decision making (Meltsner, Arnold J. 1976, p. 80).
5 politics” (Statham, E. Robert, Jr. 1995, p. 4, 5). In order to better understand and explain this process oriented activity through policy research, much of the same type of theory based investigation is conducted as in policy evaluation. The locus of analysis instead becomes the implementation actors and their behavior rather than the policy itself, and the focus becomes the decision making outputs of actors in the process rather than the outcomes of the policy in question. This process focus on human action assumes that there is no single rule of behavior, and that it is highly iterative in nature. “…[T]he process leading to decisions and action is one of framing (defining the situation), searching for ideas, crafting possibilities, simulated testing of the ideas, reframing, and so forth” (Schneider & Ingram, 1997, p. 69). This type of investigation can be largely subjective and rely on interpretive analysis rather than quantitative analysis, but the two tools are not mutually exclusive (Brady, Henry E. 2004). Just as formalized public policy evaluation has developed rational models for empirical analysis, policy implementation research can also formulate models that parsimoniously combine rational and interpretive criteria.11 Policy Types Various policy types have been proposed by scholars conducting research in public policy. Policy types are loosely defined within broad categories that seek to describe the target of policy attention.12 The idea behind developing these general policy types is that a political relationship is determined by the type of policy at stake, so that for every type of policy there is likely to be a distinctive type of political relationship (Lowi, Theodore J. 1964). Additional implications in this kind of categorization is that certain types of policies are harder to implement than others due to the kinds, numbers, and nature of relationships of the actors involved, and that public policy can be a cause of
11 One of the objectives of this study will be to accomplish the construction and exercise of a simple research design and model that combines variables drawn from past policy implementation research based both in rational theory and interpretive case dependent approaches. This combination will be focused on the actors in the implementation process, with the dependent variable established as the political and administrative decisions (outputs) made by actors in the process of implementing public policy. 12 Various examples of policy typologies have been proposed and argued, but most refer to the typology based in pluralist theory proposed by Theodore J. Lowi (1964) as a starting point. Later, Randall Ripley & Grace Franklin (1982), then Raymond Tatalovich & Byron Daynes (1998) refined Lowi’s policy types into four general categories: Regulative – both protective and competitive regulatory policy (policy toward conduct); Distributive (policy toward facilities); Redistributive (policy toward status); and Constituent (policy toward structures).
6 politics as well as a consequence of it. It must be recognized as well that these typologies are not authoritative, and in most cases a single policy can have aspects of more than one policy type.13 Policy Areas A more descriptive and exclusive way of categorizing public policy within these general descriptions of policy types is to identify specific policy areas. Whether a public policy is examined within the area of defense, health and welfare, education, the environment, civil rights, criminal justice, or any other policy area of interest, the challenge for the researcher is to choose a theoretical framework from which to conduct research and interpret research findings. Once a framework and policy is selected, the research design and model can only be constructed after selecting a unit of analysis (policy focused or process focused), and sifting through numerous and competing independent and dependent variables drawn from earlier social science studies. This selection process is largely accomplished by allowing theory to inform the interpretive selection of a few explanatory variables that likely will shed new light on the dependent variable from within the chosen framework. If a simple and valid research design and model can be constructed using commonly agreed upon independent and dependent variables, public policy research can be accomplished for any policy process simply by accounting for new historical and environmental contextual conditions. The Development of Public Policy Implementation Research First Generation Within the subfield of public policy, policy implementation studies developed in the early 1970s in two distinct and simultaneous generations (DeLeon, Peter and DeLeon, Linda 2002). The first generation consisted simply in case studies that focused on the gap between the definition of policy and its practical execution. The prime example of this form of implementation research is the seminal work by Jeffrey Pressman and Aaron Wildavsky in their study of the Economic Development Administration and the city of
13 Competing typologies for public policy focus instead on the differing patterns of democratic participation among policy makers and citizens based on the benefits bestowed by the policy. James Q. Wilson (1979; Wilson & DiIulio, 2004, p. 442) propose a way of classifying and explaining the politics of different policy issues as majoritarian politics - perceived benefits widely distributed and perceived costs widely distributed (national defense policy); interest group politics - benefits concentrated and costs concentrated (regulatory policy); entrepreneurial politics - benefits distributed and costs concentrated (education policy); and client politics - benefits concentrated and costs concentrated (pork-barrel projects).
7 Oakland (Pressman, Jeffrey L. and Wildavsky, Aaron 1973). They showed that if policy goals and practical considerations of implementation are not considered in planning, or realized as changing over time and unique in some regards by location, that policy is doomed to implementation failure or significant deflection in practice. As a practical consideration, they understood that the implementation process is an integral ingredient that shapes the success or failure of the policy itself. In the case of the Oakland Project, the problem had nothing to do with goals or resources, but found to be in the lack of political unity and cohesion among administrators at all levels. The inability of the various actors to coordinate made the abundant fiscal resources for the program ineffectual because too much time passed before program implementation was completed. Another factor found to reduce program effectiveness was an overly broad and optimistic policy goal. In this case, program implementation could not bridge the gap between the stated policy goal and the practical and political conditions that existed in the contextual environment of Oakland. If the policy implementation process is to be successful, the theory that the policy it is based upon in the first place must be politically agreeable. In the case of the Oakland Project, Pressman and Wildavsky make the argument that the policy itself was mis-specified, and that there was a failure to recognize that the policy implementation process is a political and not merely a technical problem. Second Generation This first generation of implementation studies served to put public policy implementation on the academic map, but did little in terms of establishing a useful theory, framework, or model of implementation for use by scholars or practitioners. The second generation of implementation studies consisted of three concurrent parts, the first of which sought to harness empirical analysis and to develop more sophisticated and deliberate theoretical frameworks. Part 1, “Top-down” The first part of this second generation was institutional in nature, command and control oriented, and came to be known as a “top-down” perspective (DeLeon, Peter and DeLeon, Linda 2002). This top-down focus on policy implementation studies tended to neglect parsimony due to the complexity of the empirical framework, although precision still relied on many subjective variables and measurements. The top-down perspective
8 invariably began policy implementation analysis with the guidance traditionally emanating from legislatures, while simultaneously ignoring unique environmental factors and nongovernmental actors (Hill, Heather C. 2003). The unit of analysis in the top-down study of policy implementation was the program itself. Little or no consideration was given to goal displacement, the inclusion of formal theories of social and individual choice of the implementers, or the context of the implementing organization. Donald Van Meter & Carl Van Horn (1975), Eugene Bardach (1977), George C. Edwards III & Ira Sharkansky (1978), George C. Edwards III (1980), Robert Nakamura and Frank Smallwood (1980), and Daniel A. Mazmanian & Paul Sabatier (1981; 1983; 1989), however, aimed at uncovering the gap between policy formulation and program implementation. Their focus was the information revealed in the conduct of implementers in relation to policy formulators and real policy outcomes. To try to uncover and explain this relationship, Bardach (1977; 2000), and Lynn (Lynn, Laurence E. Jr. 1993), developed a hierarchy of interaction based on game theory. They hypothesized that non- cooperation based on self-serving rather than collective goals leads to prisoner’s dilemmas that short-circuit the intended goals of the policy embodied in programs. In addition to adopting rational choice models for implementers, the top-down scholars highlighted the importance of the specificity of enabling legislation for policy implementation success in the short-term, and positive economic conditions and constituency support in the long-term. Top-down scholars developed variables to examine the decision making process as it applied to policy formulation rather than policy implementation. Their framework focused on separating the policy makers from the implementers of the policy, and their approach was an after-the-fact (post facto) analysis of policy outcomes. Their attention to the personal and psychological complexities that influence policy making decisions is important for this study as well, even though the policy makers and implementers for RCPs are one-in-the same. Top-down scholars understood the importance of policy goals being clearly and consistently stated, and then clearly assigned to an agency sympathetic to implementing the policy’s goals. Independent variables introduced by the top-down scholars that help to explain the linkage between policy formulation and policy performance in practice include resources, interorganizational communication and
9 enforcement, economic, social and political conditions, and disposition of the implementers (Van Meter, Donald S. and Van Horn, Carl E. 1975). Other variables include the notion of leadership that connects policy formulation, implementation, and program evaluation in a circular and systematic process (Nakamura, Robert T. and Smallwood, Frank 1980), the presence of a sovereign (Mazmanian, Daniel A. and Sabatier, Paul A 1981), or “fixer” (Bardach, Eugene 1977) in the process who may be an important legislator or executive official controlling resources and a desire and ability to intervene favorably on behalf of the implementing agency. Additional independent variables of note for this study drawn from the top-down perspective include those developed by Edwards & Sharkansky that focus on the limits of rational decision making by policy makers who instead use decision rules, or routines, to simplify the complex political and economic environments of policy formulation and implementation (Edwards, George C. and Sharkansky, Ira 1978). Van Meter and Van Horn believed their framework superior because they better consider the complexity of interorganizational coordination problems, and do not neglect the presence and capacity of veto points during the process. George C. Edwards is very similar to Van Meter and Van Horn with his four areas of interest in the implementation process (Edwards, George C. 1980): • Communication – Implementers need to know what it is they are supposed to do. Directions must flow to the correct personnel in clear, consistent, and accurate fashion. Implementers’ using their own discretion is seen as problematic in this conceptualization, but they still must be able to exercise their expertise and creativity in order to implement the policy. • Resources – Seen as material or financial in nature. Without sufficient material and financial resources, implementation will fail. • Disposition of the Implementers – A measure of desire that the implementer has in carrying out the objectives of the policy. In order for policy implementation to be successful, implementers must take responsibility for it. • Disposition of Outside Actors – public attitudes and opinion are influential in determining the success or failure of policy implementation. • Bureaucratic Structure – The development and use of effective standard operating procedures (SOPs), and avoiding organizational fragmentation that leads to overly decentralized power and authority structures that waste resources and cause agencies to work at cross-purposes rather than in cooperation.
10 Daniel Mazmanian and Paul Sabatier (1981) suggest that the degree of effectiveness of implementation can be explained by a limited number of variables organized in a parsimonious framework, as long as it considers the underlying causal theory directing the manner in which policy objectives are attained. Of primary importance in their framework is the tractability of the problem defined in terms of the technical accuracy, the diversity of target group behavior, target group as a percentage of the population - the smaller and more definable the target group, the more likely political support can be mobilized in favor of the program and the more likely that objectives will be achieved - and the extent of behavioral change required in the target population. The overall structure of their model takes a system approach starting with problem tractability, then considers the policy environmental conditions as well as the implementation structure available, evaluation of policy outputs, compliance with the outputs, policy impacts (real and perceived), and finally measures policy deflection, the degree of goal achievement, and the degree of policy failure. The model for this study too will rely on a simple systems approach using independent variables refined and combined from earlier studies to help explain decision making outputs (dependent variable) during the implementation process. This focus on decision making highlights a principle obstacle to successful implementation, namely the difficulty of coordinating action within any given organization and among numerous, semi-autonomous agencies and actors involved in the implementation process. A key to overcoming this obstacle is in having implementers that are committed to the attainment of the policy objectives (outputs), especially as they are directed at changing the behaviors of the targeted group and achieving the policy goal (outcomes). Implementers in this model cannot be neutral, but must be persistent in their implementation behavior, and normatively committed to the agreed upon, codified, and operationalized policy objectives and ultimate goal. Without this normative and common orientation of purpose based in the underlying, if unstated goal of the policy, implementation is chaotic and will ultimately be unsuccessful. Part 2, “Bottom-up” In conjunction with the top-down approach, a second part to the second generation of scholarship developed from a perspective seeking to incorporate the relationship between political agenda setting and policy implementation. This perspective
11 became known as “bottom-up”, and focused on the importance of the street-level bureaucrat who practically makes policy while implementing it, and simultaneously determines what public policy means in coordination with, or in contrast to, the policy authors. Michael Lipsky (1980) believed that the aggregated total of all the discretionary decisions made by street-level bureaucrats equaled public policy in practice. Street-level bureaucrats, including teachers, police officers, judges, other court officials, and other public employees deliver public benefits and sanctions as a daily part of their discretionary behavior. In this sense, street-level bureaucrats mediate the constitutional relationship of citizens to the state, and hold the key to a crucial dimension of democratic citizenship (Lipsky, Michael 1980). This perspective, however, still assumes that policy is formulated by central actors in a strictly hierarchical sense. Richard F. Elmore’s (1980) “backward mapping” begins at the last stage of the implementation process where the targeted social behavior exists that inspired the policy. His bottom-up approach considers the limitations of the actors in the implementation process, their motivations, reward systems, and bargaining relationships in the exercise of their discretionary behavior. His measure of success for policy implementation hinges on the ability of actors at one level (implementers) to influence the private behavior of the target audience at which the policy is aimed. Elmore’s is a normative framework, and he specifically discounts market-like incentives as a substitute for established organizational relationships and behaviors among actors implementing policy. Bottom-up scholars believe that in a diffused federal system like that of the United States, their framework is better able to capture the full range of environmental factors and variables that affect policy implementation in practice. Their focus also included looking beyond central actors and strictly hierarchical lines of authority and communication by conceptualizing policy formulation as a complex web of interaction between various levels of government in the formulation and implementation process. This concept allows scholars to look at actors in various locations in the process and analyze their goals, activities, problems, and informal communication contacts. By doing this, one can map a network to identify key implementation structures among actors and levels of government, as well as the effects of outside influences on policy implementation (Hjern, Benny and Hull, Chris 1983). This network conceptualization is
12 still seen as a way to revitalize the study of policy implementation (O'Toole, Laurence 2000). Attempts to refine the model for the benefit of both academicians who study the implementation process from the “outside,” as well as practitioners who implement policy from the “inside” are underway (Schroeder, Aaron D. 2001). The importance of the bottom-up perspective for the purpose of this study is in its concentration not on the program being implemented, but on the actors simultaneously formulating and implementing the program, as well as the acknowledgement that both state and nonstate actors influence public policy implementation. In contrast, even though top-down approaches posit useful explanatory variables for implementation actors, their exclusive reliance on a central dominant actor in a democratic environment that has facilitated a before-the-fact (a priori) consensus among all stakeholders in the implementation process is problematic in practice. “Policy processes today are being viewed not as the ex ante implementation of formulated goals, but as an interaction in which actors exchange information about problems, preferences and means, and make trade-offs between goals and resources” (Schroeder, Aaron D. 2001 p. 9). In the case of RCPs, the judge does serve in a role much like the dominant actor in a top-down model, but is much better understood from the bottom-up perspective as a “facilitator” between unconventional coalitions of actors, and as one who can create incentives and alleviate blockages from a central exercise of discretionary behavior based in democratic accountability and personal responsibility. There is in fact always a “top” somewhere in the policy implementation process, but it can frequently be found at the bottom. Part 3, “Synthesis” Synthesis models are the third part of the second generation of implementation scholarship, and seek to bring together the top-down and bottom-up perspectives. In their effort to combine both top-down and bottom-up perspectives, synthesizers like Malcolm Goggin (Goggin, Malcolm L., Bowman, Ann et al. 1990) sought to incorporate the variation of policy implementation success over time, place and policy. Earlier, Richard F. Elmore (1978) specifically took cues from the policy and decision making scholarship of Graham T. Allison (1971) whose study of the Cuban missile crisis used different theoretical models to triangulate accounts and explain what happened (Hill, Michael and Hupe, Peter L 2002, p. 58). Elmore focused on the actions of individual actors as a
13 starting point and used four different models in juxtaposition to help better understand how implementation research should be conducted and policy developed in practice (Hill & Hupe, 2002, p. 58): • Implementation as systems management • Implementation as bureaucratic process • Implementation as organization development • Implementation as conflict & bargaining.
Elmore used the individual actor within the implementing organization as the focal point, and worked outwards through the rules, procedures and structures closest to them (backward mapping). This type of actor-focused process model is the foundation for the research model that will be constructed and used for this study (see Chapter 2). Later, Elmore would work to bring together his forward and backward mapping approach and suggest along the line of Michael Lipsky (1980) that the best place for precise policy formulation was at the bottom, or street level (Elmore, Richard F. 1983). Proponents of the synthesis approach were making an effort to be more “scientific” and systematic in explaining why behavior varies over time, policies, and units of government. Malcolm Goggin, Ann Bowman and James Lester tried to capture this idea in a macro-level communications model of intergovernmental policy implementation that brought together top-down and bottom-up approaches. They focused on the acceptance or rejection of messages between layers of government in an attempt to further the scientific development of policy implementation research (Goggin, Malcolm L., Bowman, Ann et al. 1990). Their attempt at synthesis is broad in scope and therefore makes it difficult to specify variables, but it does highlight the importance of the individual actors at various levels as they become the source and focus of communications during the implementation process. Richard Matland followed the work of Malcolm Goggin (1986) by attempting to give structure to the numerous key variables in public policy implementation literature while taking into account contextual variables and contingency theories that direct implementation strategies (Matland, Richard E. 1995). He believed that scholars needed to define the conditions under which their variables are important and the reasons why they are expected to be so. In regards to dependent variables, he implies that for top-down studies of implementation they necessarily be focused on policy outcomes, while for bottom-up studies they be focused
14 somewhere other than outcomes. His outline for implementation studies is largely based on identifying how discretion should be assigned to the implementation actors, and in determining the extent to which various actor’s values are given primacy in a democratic (values-based) theory framework. The vaguer the policy goal, the more important societal norms and values become during implementation (Matland, Richard E. 1995, p. 155). Matland’s focus on democratic theory and proposals to standardize implementation studies will be more fully developed later. Jan-Erik Lane (1987; 2000) highlights the contrast between the normative considerations necessary in policy implementation process research, and the rational concerns of methodological frameworks designed for policy analysis. He ultimately argues for dual approaches in implementation studies. He describes this approach as the contrast between the value of trust in the discretionary behavior of implementation actors, and the value of responsibility and ultimate policy outcomes (accountability). Paul A. Sabatier (1986) urged an “advocacy coalition approach” that took a more holistic view of the policy process by promoting a bottom-up unit of analysis (actors at all levels), with a top-down use of environmental (contextual) variables. The intent of his advocacy coalition approach was to highlight the points of conflict in the policy implementation process in order to better narrow and focus the study of public policy implementation. Other scholars pursued the natural connection between the top-down and bottom-up approaches found in studying policy networks. The goal of this synthesizing activity is to link the numerous and conflicting “proverbs” of the various subfields of social science that have an interest in explaining public policy implementation (O'Toole, Laurence 1986). Network analysis approaches the study of policy implementation from the perspective that it is unlikely that any significant public policy can result from the decisions of any single actor or group. Rather than being institutionally focused, network analysis develops a framework based on the pluralistic nature of public policy and its implementation as well as the following propositions (Hill, Michael and Hupe, Peter L 2002, pp. 77-78): • Public policy is made in complex interactions (games) with a large number of actors within networks of interdependent actors • Policy networks are stable patterns of these relations shaped around specific public policy problems
15 • Over time, these form a context in which actors act strategically • Different actors have different perceptions • There is a tension between the interdependency & the diversity of goals & interests • Success or failure is measured in the extent of cooperation achieved • To achieve cooperation, steering is needed • Governments are unique actors in a policy network representing the “common good” • Governments can choose to act alone, not to act, or cooperate with private, semi-public, or other actors
The intent of network analysis is to blur the lines between policy formulation and implementation, and explain how the resulting policy comes from the interactions of a plurality of separate actors, interests, goals, and strategies (Scharpf, Fritz W. 1978, p. 347 in Hill & Hupe). Policy implementation in policy networks is both a purposive activity, and an empirical process of interactions to be explained in terms of its causes (Hill, Michael and Hupe, Peter L 2002, p. 60). This is an important distinction in terms of outputs and outcomes respectively, and helps to illustrate that the policy making and implementation process can have a horizontal as well as a vertical orientation for actors in the pursuit of a purposive solution to a policy problems. Further, it is assumes that the problem solving goals of policy would matter to the actors in the decision making and implementation process. Accordingly, implementation research should focus on the process of coordination and collaboration of actors as they pursue their common problem solving goals (Scharpf in Hill, Michael and Hupe, Peter L 2002, p. 60). Randall B. Ripley and Grace A. Franklin (1982) highlighted five features of the implementation process that serve as an outline for a basic actor-focused process model: • There are many important actors • Who have diffuse & competing goals • Who work within a large complex mix of programs • That requires input from numerous layers/units of government • And are affected by powerful factors beyond their control
Ripley and Franklin were concerned with the contextual influence bureaucracy and federalism had on the above five features in policy implementation. They also emphasized the environmental influence of democratic politics on the implementation process. They believe that the political nature manifest in the operational systems of
16 government is largely non-hierarchical, overlapping, and open at many access points in accordance with their pluralism based framework. They highlight the probability that although actors in a policy implementation process share a common goal, individual objectives along the way often come into conflict. Identifying these points of conflict among actors in the implementation process is a common theme among synthesizers. Bo Rothstein sought synthesis in highlighting the normative role of the state in public policy implementation by trying to distinguish between what it should do and what it can do effectively (Rothstein, Bo 1998, in Hill & Hupe pg. 79). In the process of his review of implementation literature, Rothstein determines that in doing research, the scholar must keep in mind that the state is often compelled to act even when it doesn't know what will work, and that there are three identifiable problems repeated in implementation research (Rothstein, Bo 1998, in Hill & Hupe p. 80): • A tendency to focus on failed programs • A tendency to focus on complex programs with high ambitions • An excessively mechanistic & rationalistic view of the policy implementation process
Other synthesizers who add their perspectives and models to informing the top-down, bottom-up debate are Michael T. Hayes (1991; 1992; 2001), James Lester with Malcolm Goggin (1998), and David Weimer & Aidan Vining (1999), who take an incremental, intergovernmental, and strategic perspective to synthesized analysis of policy implementation respectively. Third Generation Others have tried to go beyond the simple idea of synthesis to a third generation of policy implementation study. Their efforts are aimed at redirecting the locus of implementation research by reworking concepts like “network management” and combining scholarship on public management, governance, and institutional analysis (O'Toole, Laurence 2000). This redirection effort is based on the idea that the top- down/bottom-up dichotomy is nothing more than looking at the same phenomenon in a different way and, most importantly, that each perspective is based on fundamentally different notions of democracy. Top-down policy implementation proponents justify the conventional overhead-democratic tenets focused on a central, hierarchical structure,
17 while bottom-up scholars focus on the interactive processes, client involvement, and target population co-production of outcomes (O'Toole, Laurence 2000). In order to account for this difference in democratic values, a new generation of policy implementation research based on a democratic approach has been suggested (DeLeon, Peter and DeLeon, Linda 2002). This approach would essentially align policy implementation research with a broader trend in policy sciences that seeks to emphasize the democratic ethos and citizen participation. This emphasis on democratic values would also release policy implementation studies from a strict identification with the public policy subfield, and shift it toward identifying more closely with the subfield of public administration. Public policy implementation research and literature might serve to highlight the historical tension, although not actual dichotomy, between democratic politics and public administration. In order to complete this connection, and firmly plant a values-based democratic approach to policy implementation studies within the development of American public administration literature generally, a brief review of the foundational scholarship is in order. Public Administration and Its Definition American public administration research and literature since the inception of the field and Woodrow Wilson’s “The Study of Administration” (1887/1997), has struggled within itself to define a unifying theoretical foundation. The body of public administration research and literature that marks the beginnings and development of a democratic values-based explanatory approach includes Chester I. Barnard (1938), Carl J. Friedrich (1940), A. H. Maslow (1943), Paul Appleby (1945), Robert Dahl (1947), Dwight Waldo (1948/1997), Charles Gilbert (1959), Frederick C. Mosher (1968/1982), Emmette Redford (1969), Vincent Ostrom (1973), Aaron Wildavsky (1979), David Rosenbloom (1983/1997), and H. George Frederickson (2001). In contrast to the proponents of the democratic values approach have been influential rationalists like Max Weber (1913/1946), Frank Goodnow (1900), Frederick W. Taylor (1912), and Herbert Simon (1947/1997). Wrongly Separating Politics from Administration Woodrow Wilson was largely misunderstood in his assertion that “the field of administration is a field of business. It is removed from the hurry and strife of politics”
18 (1887/1997, p. 20). Rather than separating the selection of administrators from the party- machine bound partisan politics of the day as was Wilson’s intent, the politics- administration dichotomy that developed instead held that each was a separate and distinct sphere of activity. In Wilson’s intended schema, centralization begets efficiency and becomes the fundamental reference point for hierarchical organizational design. A hierarchical and centralized organization in turn begets bureaucratization. Wilson believed in Americanizing the practices of the Prussian and British civil service in order to achieve the effect of centralization and enhance democratic accountability. Wilson believed that administration in the United States could separate the facts of the European model from the values of the Europeans and apply the altered model directly to the American system. This adjustment would serve to enhance the democratic accountability of administration in the exercise of democratic state power. “Politics has to do with policies or expressions of the state will. Administration has to do with the execution of these policies” (Goodnow, Frank J. 1900 p. 27). Even though others would later argue that politics and administration are separate and compartmentalized processes, this conclusion is “a perversion of Goodnow’s doctrine” (Lynn, Laurence E. Jr. 2001, p. 148). Rational empiricists transformed Wilson’s warning and Goodnow’s theorem into two separate and dichotomous components of the same field of study. In fact, Herbert Simon would criticize Goodnow for not being careful enough in drawing a line between the two (Simon, Herbert A. 1947/1997, p. 63).14 The words of early Chicago School behavioralist and political psychologist Harold Dwight Lasswell contained democratic values in defining politics as deciding “who gets what, when, how” (1936). Even his mentor, Charles Merriam, professed a great parsimonious equation ripe with democratic values: p } d } r = P (private emotions displaced upon public objects and rationalized in terms of public interest equals Politics (Almond, Gabriel A. 2004, p. 92). Administration for the rational empiricists, on the other hand, is only a process of routinely (value-free) translating the institutional product of politics
14 This perspective can be best understood by framing it in democratic theory. Goodnow’s intent is to distinguish between politics as the means to create policy within formalized institutions of government, and administration as the rational application of the policy product. His concept stands in opposition to the popular sovereignty doctrine of democratic theory that allows for the influence of state and local government institutions and citizens in the political and administrative process. It is in the politics of federalism that the policy making and implementation processes become means for society to direct its institutions and bureaucracies toward realizing its (normative) goals, hopes, and aspirations.
19 (policy) into programmatic activity. It is left for the public administrator, who theoretically has no influence in who gets what, when, and how, to dispassionately implement and execute the product of the policy making process. Goodnow believed that it was the party system that secures the harmony between this dual natured interpretation of politics and administration in the American system of government. The ideal situation for him is administrators who are politically neutral, impartial and objective in making the decisions necessary to implement policy. This way it is possible to believe that public administration can be defined purely in terms of scientific principles (facts), while eliminating any notion that there is a democratic values-based discretionary craft to the workings of public administration. Characteristics of Bureaucracy The rationalist hope was to empirically establish a systematic and objective way to assess whether the practice of public administration was efficient. The ultimate administrative goal in this perspective is to combine efficiency and effectiveness and define them in purely economic terms. This combination is necessary to establish a common and universally accepted standard unit of analysis that codifies a scientific theory of administration. Only objective means can measure the efficiency of administration if the desired separation from politics is to be achieved. Foundational in attempt at achieving this combination is the writing of Max Weber, a German sociologist at his peak of influence at the time of Wilson and Goodnow. Weber was the first to use the term “bureaucracy” and his ideal type was based on empirical observations combined with pure conceptual thought.15 Empiricists believe that there are discoverable fact-based rules of public administration that have universal application and replicability from one government agency to the next. This belief is largely based on Weber’s Wertfreiheit, or
15 Weber’s bureaucracy is an ideal type and therefore is not a goal to be achieved, but a tool to measure reality. Weber’s characteristics of bureaucracy are defined by three key elements (Weber, Max 1946/1997): Rules and regulations - these rules and regulations are codified and documented and are objectively applied universally and equally across cases in order to deliver predictability and calculability. Hierarchical ordering of superior and subordinate relationships - these relationships are centralized and exhibit a division of labor and specialization in function. Decision making is based on a calculable and rational behavior. Authority system - Weber's authority system is the glue that holds his ideal type together and is based on the third of the three characteristic types of an authority system: traditional, charismatic, legal/rational. Legal/rational authority is based in a position, and not a person. The qualifications and credentials used to measure those eligible for the job are objective, predictable, calculable, efficient, effective, and rational.
20 “value-freedom” thesis that considers only objective criteria and discounts the ability of social science to judge the desirability or undesirability (normative basis) of social phenomena (Ciaffa, Jay A. 1998, p. 13). The desire to base public administration practice on scientific fact alone also expects that the science of administration will be stable over time and is a skill that can be learned as well as taught. Therefore, once the science of administration is fully developed, it can not only be used as a prescriptive tool, but also used to objectively evaluate the daily practice of public administration. Principles of Scientific Management This idea was firmly established in Frederick Taylor’s search for the “one best way” to create an organizational product based in his four principles and duties of scientific management (Taylor, Frederick W. 1912): 1. Managers gather traditional knowledge to replace “rules of thumb” 2. The scientific selection and progressive development of workmen 3. Bring science and the scientifically selected and trained workmen together 4. Equal division of work between workmen and management
Taylor's critical analysis was focused on inadequate management skills. The practical application of his technique, however, was eventually seen as anti-worker because his idea that “a fair day's wage for a fair day's work” is based on factual science and not on collective bargaining. His factual science was in turn based on time-motion studies and the benefit of a piece rate wage system. Taylor’s metaphor for the organization was that of a machine, with workers and management being relegated to cogs. Scientific management eventually came to be derogatorily called “shop management” or “micro management.” Herbert A. Simon’s (1947/1997) arguments to further separate facts from values in the study of administrative decision making behavior was a catalyst for the behavioralist (rational choice) movement in the social sciences in the mid 20th century. “Broadly speaking, the behavioral revolution meant that in political science and economics the presumption of rational self-interest made historical generalization and historical knowledge superfluous… erasing time and situation as elements of human understanding” (Ashford, Douglas E. 1992, p. 27, 29). Rational behavior theory sought to combine a value-free social science with the tenets of logical positivism developed by
21 philosophers in the early part of the century.16 Simon designated logical positivism as his foundation stone for administrative decision making (1947/1997, p. 55), and deemed any establishment of democratic values-based research (synthetic a priori) in the administration of organizations as mere “proverbs” (1946). These proverbs, Simon says, must be discarded for the advancement of scientific research based in logical positivism alone. His persuasive adoption and promotion of the fact-value dichotomy served to perpetuate the false conclusions of a politics-administration dichotomy drawn from Wilson and Goodnow, and subsequently strengthened by Weber, Taylor, and Simon himself. Rediscovering Democratic Values in Public Administration Democratic values-based scholarship stood in opposition to the value-free perspective in believing that a theory of administration – and by association policy implementation – is by necessity political theory as well. Political theory, in turn, is inextricably linked to democratic values, and any attempt to separate democratic values from administrative practice was in effect an attempt to separate individual persons from value-based discretionary behavior and decisions, and a rejection of democratic values themselves. It then becomes impossible, if democratic values are separated from a theory of public administration and implementation, to explain how various actors function in a democratic system. This challenge is centered on the individual actor and their relationship to the organization and the influence that this dynamic process has on behavior and decision making by government managers. Robert A. Dahl (1947) saw that there were three main problems with the scientific principles of management; they were hindered by the obstruction of different values contending for prominence, there are clear differences in human personality, and each system has its own social framework. Paul Appleby (1945) viewed the politics- administration dichotomy as a myth because government is politics and therefore it is different from every other activity in society because of its scope, impact, and accountability to the public. In order to live up to expectations and fulfill this obligation
16 Logical positivism holds that logical reasoning (analytic a priori) and empirical experience (synthetic a posteriori) are the only two sources of knowledge, and a theory is meaningful only if it can be proved by experience (verifiability principle). This empirical framework effectively eliminates the possibility of a value dependent social science, as well as the traditional moral philosophical basis (synthetic a priori knowledge) for explaining the human condition.
22 to the community, those who provide government services must be active, and have a public interest attitude. Dwight Waldo (1948/1997) asked whether it would be useful not only to provide a technical education for public administrators, but imbue them with a political philosophy. Acknowledging a foundational political philosophy and organizational purpose seeks to forestall a situation in which a formal value-free scientific analysis of organizations and actors becomes “a tedious elaboration of the insignificant” (1948/1997 p. 144). A.H. Maslow’s “A Theory of Human Motivation” (1943) introduced a hierarchy of human needs and motivations that are intrinsic to the individual and strongly influence social behavior. These needs progress from psychological (bodily homeostasis and appetite), to safety, to love, to esteem, to self- actualization. Chester I. Barnard (1938) built upon the idea of psychology in public administration with his idea of informal organizations within formal organizations that are based on interpersonal and cooperative exchange systems between the informal and formal. The work of the manager in this schema is to maintain the equilibrium of the dynamic system, and implicitly requires a balance of both rational and values-based decision criteria. With a focus on the executive manager as key decision maker, Anthony Downs (1967) and Hugh Heclo (1979) began to develop ideas to explain why and how these actors made decisions in relation to the life cycle of bureaus and within “issue networks” respectively. 17 Vincent Ostrom’s “Intellectual Crisis in American Public Administration” (1973) focused on the tension between democratic administration (decentralized) and bureaucratic administration (centralized). Ostrom bemoaned the expanding gap between public administration theory and practice and research agendas that sought to develop theory from proposing and testing hypotheses that ultimately ended in more bureaucratic centralization. His idea was that the search for a solution must take place outside of the
17 Downs distinguishes between advocates, or zealots, who are not primarily motivated by self-interest and are present at the start of a bureaucracy. They have a specific idea they want to put into practice on a large scale. Climbers are innovators who are attracted to growing bureaucracies by opportunities for increased power, promotion, income and prestige. Conservers will not be drawn to fast-growing bureaucracies, and may be repelled by them, because rapid growth means uncertainty, constant restructuring, and hard work. They will actively resist shrinkage to the size and importance of existing bureaucracies. Heclo built upon his study of the relationship between career civil servants and political appointees he describes as “executive politics” by arguing that the permanent career civil service, or bureaucracy, has become more and more politicized while the political leadership appointed over them has become more and more bureaucratized (Heclo 1977).
23 traditional orthodoxy based on Wilson misunderstood, and Simon’s value-free decision making. A new orientation emerged that was partly because of Ostrom’s “crisis,” partly because of practitioner and business school cooptation, and partly as a result of the continuing distinction between the administrative actor and a political organization. Now, instead of politics and administration being considered dichotomous within a single field of study, politics and administration became two separate fields of study (Moe, Terry M. 1991). The politics-administration dichotomy became the theory-practice dichotomy (Frost-Kumpf, Lee and Wechsler, Barton 1993). With the advent of Barry Bozeman’s focus on public management (Bozeman, Barry 1979), and Lawrence E. Lynn Jr.’s thesis on public management (1993;, a new focus in the study of public administration was to more clearly define the fuzzy line between practitioners and scholars, and to take a more holistic approach to public administration by including management’s input in theory construction. Action theory, that holds one can be an actor in the process while simultaneously formulating theory, became prominent in the methodological use of case analysis in the study of public managers. For public management scholars case analysis is more than storytelling and more than theory, it becomes a useful combination of the two. According to those who study public management, there's no higher function in public management theory than the other-than-positivist modes of “criticism and synthesis” (Bozeman, Barry 1993). The strong emphasis on inductive reasoning using both field research based on practitioner behavior and secondary sources of information drawn from scholarly synthesis is seen as a continuation in the line established by such disparate manager/philosophers as Taylor and Barnard (Behn, Robert D. 1993). A common thread in the discussion of public management is its relationship with private business practice. Graham T. Allison and Ronald C. Moe attempt to establish a common ground from which to work, but from two different perspectives. Allison chose a more comparative approach in an attempt to establish a common terminological and theoretical foundation for the study and comparison of public organization management contrasted with successful private organization practices (1980). Allison attempted to get to the bottom of what he calls “terminological tangles” that have seriously hampered the development of public management as a field of knowledge. He identifies the barrier that
24 is created to the clear discussion and conceptual ordering of observed phenomena when there is no overarching framework because of this terminological thicket. Moe (1987), on the other hand, tried to review public administration’s public law tradition and took exception to authors (Bozeman) who believe that public and private administration is similar in its essentials. Moe believes that the economic theory driving much of the push to privatize government functions severely weakens the democratic accountability of government. It is then important for the practice of democratic values by the actors in a public organization in order to define the underlying purpose of the organization. Conclusion This first chapter has outlined the theory, perspective and approach that will be the operational foundation for the rest of this study. The methodological process just completed in the form of a literature review, otherwise known as a meta-analysis, is intended to cumulate relevant knowledge across studies to better inform this one. This process will be continued in the next chapter with the intent of more specifically refining and operationalizing the component variables, while framing the research design and constructing a formal model.
25 CHAPTER 2
VALUES-BASED PUBLIC POLICY AND ADMINISTRATION: IMPLEMENTATION CONTEXT, VARIABLE DEFINITION, AND RESEARCH MODEL
Implementation as Decision Making in Context A good way to look at the policy process is to consider policy making as strategic decision making behavior, and implementation decisions as tactical behavior. From this perspective it is easy to understand that each is distinct and necessary, but that they frequently must happen concurrently for successful implementation.18 The strategic and tactical nature of decisions is not the only operational or contextual factor influencing actor behavior in the policy implementation process.19 Governments, institutions, organizations, and partnerships, like the individuals that compose them, are aggregations of norms, values, rules and practices that shape or constrain decision making behavior (Peters, Guy B. and Pierre, Jon 1998, p. 565).20 With these various influences in mind, and a meta-analysis of policy implementation and public administration literature
18 For the seminal discussion of this in regards to implementation literature, see Pressman and Wildavsky (1973). For an alternative view, see Rein and Rabinovitz (1977). Rein and Rabinovitz viewed the process in two distinct stages: 1. Guideline Development - normally this stage is the response of administrators to legislative guidelines. This stage for them includes initial resource distribution. 2. Program Oversight – concerns the internal monitoring and evolution of administrative rules and standard operating procedures during the implementation process. 19 Any model of the policy process is an oversimplification, but necessary to order thinking about the real world. What is important is to identify and explain the assumptions used to create and operationalize the model from a particular perspective and approach. An example of this simplification from an elite perspective is the “Oligarchical Model” of the policy process that incorporates the influences of: Resources – corporations, personal wealth, endowments and directorates; Research – foundations, universities, grants and contracts; Decision Making – policy planning groups, research personnel and reports; Opinion Making – government commissions, councils, recommendations, and news media and media reports; and Law Making – executive, legislative, and judicial action with public attention (Dye, Thomas R. 2002, pp. 171- 175). 20 Institutional contexts and theories include: Normative Institutionalism - the values and norms of actors will influence and change the institution in the political decision process (strategic) of policy making. Simultaneously, institutions influence policy implementation (tactical) decision making. Understanding this dual impact is a matter of understanding the largely incremental and iterative nature of the processes by which actors exchange values and influence each other’s behavior (see Gormley, William T. Jr. 1987; Peters, Guy B. and Pierre, Jon 1998, p. 574). Institutional Analysis and Development (IAD) - a rule-based perspective founded on rational choice theory. It seeks to understand the emergence and impact on policy of institutional forms. IAD does help to inform implementation research in its analytical approach and conceptual detail, although it sacrifices parsimony in its complexity O'Toole, Laurence (2000). Actor- Centered Institutionalism - “…combines insights from game theory, welfare economics, and institutional analysis to suggest an approach to modeling policy-relevant settings of many types…that may be able to elucidate a number of implementation circumstances” (see Scharpf, Fritz W. 1997; O'Toole, Laurence 2000, p. 275).
26 completed (chapter 1), the next step is to build a values-based framework and model to guide implementation research and answer the research question.21 The Implementation Context in Terms of Ambiguity and Conflict The general context of the policy implementation process has consequences as actors communicate, exchange values, and influence others’ behavior. Discovering the dynamic and democratic relationships behind this process in RCPs directly relates to developing contingency approaches to how policy implementation works. Incorporating elements of rational as well as normative behavior derived from observing contexts and processes, various matrices offer explanations for institutional and organizational change,22 administrative responsibility,23 different implementation strategies,24 as well as defining policy implementation success. A major concern of all these matrices is to discern and define both deductively and inductively the key factors (contextual variables) that influence the success or failure of the policy implementation process. One commonly reproduced and adapted matrix for defining implementation success is presented below in a further adapted form for the purposes of this study (Matland, Richard E. 1995;25 see
21 The remainder of this chapter will mine the common ground between the bounds of purely rational decision making in policy implementation and public administration on the one hand, and purely altruistic and normative actor behavior on the other. 22 Peters and Pierre (1998, pp. 573; 577) construct a process matrix of institutional change linked to changes in the values and objectives that guide political action. This institutional change is driven by the need for harmonious relationships within its environment, and is based in the nature of the process (Continuous or Discrete), and the drivers of change (Internal or External). Therefore, institutional change can be Contingent (Continuous & External), Disruptive (Discrete & External), Organic (Continuous & Internal), or Enacting (Discrete & Internal). Jeffrey Pfeffer (1981/2005) models organizational change as decision making power based in various dimensions including goals and preferences, rules and norms, relationships, decisions, and ideology. 23 Herbert Simon’s Administrative Behavior (1947/1997) is most often cited. Another early example is from Charles Gilbert (1959, p. 382) who examined the practice of administrative responsibility by actors in four possible environments: Internal Formal - those approaches that stressed direction and control by the executive via such methods as budgeting, personnel management, standards, rules and procedures, and structuring and restructuring of formal organizations; Internal Informal - emphasizes the moral, representative, and professional aspects of public service; External Formal - primary focus is on direction and control generally recognized by congressional-administrative relations, and control by the courts through the judicialization of the administrative process, and; External Informal - considers interest group representation, citizen participation, and grassroots democracy. Later, Rosembloom & Kravchuk (2002) framed their perspectives on public administration that included characteristic values, organizational structure, view of the individual, cognitive approach and decision making. 24 Matrices (2x2) based in contingency theories, and attempting to adapt to and synthesize the complexity of implementation practice and research by indicating different implementation strategies. Most often cited is Richard Matland (1995), but others include Helen Ingram (1990), and Denise Scheberle (2004). 25 William T. Gormley Jr. proposed a similar matrix entitled, “Coercive Controls of Bureaucracy: A Normative Model” (1989, pg. 22). His is an integrative approach encompassing issue characteristics (complexity, conflict) similar to Matland (1995), but also includes bureaucratic characteristics (skill,
27 also Chackerian, Richard and Mavima, Paul 2000, p. 357; DeLeon, Peter and DeLeon, Linda 2002, p. 485; Hill, Michael and Hupe, Peter L 2002, p. 76): Table 2.1: Ambiguity – Conflict Matrix: Policy Implementation Process Ambiguity Conflict Low High Administrative Implementation Political Implementation (top-down) (top-down) Decision-making type: Decision-making type: Low communal authoritarian Required resources: Required resources: administrative power Experimental Implementation Symbolic Implementation (bottom-up) (bottom-up) Decision-making type: Decision-making type: High democratic anarchic Required resources: Required resources Local actor resources Local coalitions
Administrative implementation Administrative implementation is simply the everyday business of government that is carried out without innovation or violation of traditional norms in public administration practice. An example of administrative implementation would be an office memorandum that makes an incremental adjustment to established standard operating procedures (SOPs). This type of implementation is defined as having both low levels of conflict and complexity, as well as low levels of ambiguity. This type of implementation is top-down in perspective, and because conflict and ambiguity is low, no intervention above the level of implementation is required in its routine execution. In relation to democratic theory, decision making at this location on the matrix is best described as communal in nature. The most important resource in this context is the routinized operational performance, and practiced implementation process shared among members of an established work group, coalition, or network. Political implementation Political implementation enters into the high end of the conflict scale while remaining low in ambiguity. It assumes top-down characteristics because of the likely intervention of policy authors above the level of policy implementers in a hierarchical organizational structure. This type of intervention is highly reliant on authority to resolve
support). Matland’s intent is to define implementation success, while Gormley is concerned with recommending coercive (nondemocratic; “muscles”) or noncoercive (democratic; “prayers”) public responses to the exercise of bureaucratic discretion.
28 conflicts in decision making made complex by the highly iterative nature of the implementation process found even in hierarchical organizations. Authority is used in this case to harmonize the strategic and tactical decisions that are necessary to translate policy into program. Implementers in this scenario are frequently not the same actors responsible for the formulation of the policy in question, and the policy itself is often a product of legislation. Incentives and controls for implementation are driven from the top-down, and imply a very traditional notion of positive (a priori) control and accountability for program implementation. Another way to describe this type of implementation in theory is that policy elites force the bureaucracy to carry out elite ideas whether or not the individual bureaucrat “buys in” to the policy concept. This implementation type is also called by other names, such as the “policy planning model,” or the “textbook policy process” that prescribes goals be clearly stated up front along with detailed plans, tight controls, and implementer indoctrination (Golden, Olivia 1997, pg. 150-151). Symbolic implementation Symbolic implementation comprises the most intractable cases of policy implementation and likely combines questions of constitutionality with a great deal of emotional and ideological tension. Types of policy decisions described by this cell are questions concerning church and state issues, affirmative action policies, or same sex marriage. This cell is best understood from a bottom-up perspective because the high conflict, ambiguity, and political tension present can best be resolved by building local coalitions. It is likely that any power applied to resolve these implementation processes in a traditional top-down sense would illicit a negative response from implementers and citizens alike (a case in point is the Massachusetts State Court decision in 2003 to allow same-sex marriage). This context can create a temporarily anarchic (non-hierarchical) environment (DeLeon, Peter and DeLeon, Linda 2002) that draws into question the democratic accountability of policy authors and implementers alike. At the same time, a window of opportunity is provided for “organized” anarchies to form long enough to solve problems.26
26 The garbage can model of “organized” anarchic administrative decisions is characterized by inconsistent and ill-defined preferences, unclear technology, and fluid participation in “organized
29 Experimental implementation Experimental implementation focuses attention on the actors that are most directly involved in the policy implementation process and acknowledges that contextual conditions dominate (DeLeon, Peter and DeLeon, Linda 2002). Participants in the process agree among themselves on the value of the policy, and accept that continuous adjustments will be necessary to refine their decisions and the policy during the implementation process. Understanding that the policy in question is experimental in nature also allows for innovations (discretionary decision making) in implementation, and facilitates learning among implementers and policy authors (most often the same individuals or working groups). Rather than beginning with a well defined policy, actors in this type of implementation instead start with a strong sense of mission or direction even though they may not initially know how to achieve their objectives or goal. Scholars have described this real-world administrative dilemma variously as “adaptive administration” (Maynard-Moody, Steven, Musheno, Michael et al. 1990, p. 845), “implementation as exploration,” “mutual adaptation,” or as “management by groping along,” even though brief initial and subsequent planning periods are often present (see Browne, Angela and Wildavsky, Aaron 1984; in Behn, Robert D. 1988; Golden, Olivia 1997, p. 152). This implies a learning process during implementation that compels changes in actions, and possibly the underlying ideas, objectives and goal of the policy or program. “Rather than seeking to make tractable eternally intractable social problems…a learning organization must…analyze its policies for their informational yield. It should evaluate the implementation of these policies not against prospectively stated objectives alone, but in light of discoveries made during implementation” (see Browne, Angela and Wildavsky, Aaron 1984, p. 255; in Golden, Olivia 1997, p. 153). The Experimental Context of Reentry Court Partnerships One context from within the four cells of Table 2.1 is necessary to orient research in the implementation process of RCPs. Since RCPs are best described as experimental in nature given the aforementioned definition in Table 2.1, a “…democratic
anarchies.” Success or failure of policies depends on the random intersections of policy problems, solutions, and requisite decision-makers (see Cohen, Michael D., March, James G. et al. 1972; Kingdon, J. W. 1984; DeLeon, Linda 1998).
30 approach…would be the most appropriate strategy for policies that fall into this cell” (DeLeon, Peter and DeLeon, Linda 2002). Experimental implementation and the democratic approach also connect well with the values-based point of synthesis of public policy and public administration discussed in the meta-analysis of chapter one. Additionally, the democratic approach shares common ground with scholars focused on aspects of citizen participation (Weimer, David L. and Vining, Aidan R. 1999), new public administration (Frederickson, H. George 1971/1997), political and legal perspectives of public administration (Rosenbloom, David H 1983/1997), implementation understood as problem solving behavior with both administrative and political content (Goggin, Malcolm. 1986), and the importance of the values of the implementation actors themselves in the process (Lin, Ann Chih 2000; O'Toole, Laurence 2000). With experimental implementation being the context selected for the democratic approach to studying RCPs, variables used to examine RCPs will be refined through this cell for three basic reasons: • RCPs are a new approach to a substantive new policy area that is being implemented from the bottom-up for the very first time in disparate jurisdictional contexts. • There is no top-down authority providing guidance or financial resources to the implementation process in the RCP jurisdictions. Partners agree on the positive value of the policy to their community, and the necessity of democratic decision making (strategic) along with administrative discretion (tactical) during implementation. • Nongovernmental actors, and the citizen ex-offenders themselves, are crucial in the successful implementation process of RCPs.
The use of an experimental policy implementation context is also generally consistent with foundational literature that highlights the significant role in the implementation process of existing bureaucracy, management staff levels and expertise, and policy decision makers’ values, discretion, and levels of cooperation (Edwards, George C. and Sharkansky, Ira 1978; Edwards, George C. 1980)
31 A Taxonomy: Separating Variables by Classification, Type, Category and Variety In the development of implementation theory, hundreds of variables (dependent and independent) have been proposed and analyzed.27 Depending on the perspective and approach of the particular study, all variables can be treated as either dependent or independent variables in the implementation process in realizing that, “implementation needs to be studied both as a dependent variable and as an independent variable” (DeLeon, Peter and DeLeon, Linda 2002). In realizing this dilemma, and by further refining the general classification of variables in relation to the democratic approach, this study uses variables applicable not only to research on RCPs, but useful for a uniform and replicable small n quantitative model within a largely qualitative framework transferable to any experimental (democratic approach) implementation process.28 Obtaining reliable definitions and measures of selected variables is also extraordinarily difficult in practice. This difficulty is merely, “reflecting the complexity of social and human processes and the limitation of one’s ability to fully observe and quantify them” (Lynn, Laurence E. Jr., Heinrich, Carolyn J. et al. 2001). The difficulty in selecting variables in context and then measuring them, even when constructing as clear a framework and model as possible for policy implementation research, is in the great complexity of environmental (sub-contextual) variables and conditions at the local, state and national level.29 The discussion to this point has been focused on a review of the general (macro) division and classification attempts of democratic variables by various
27 Heather C. Hill (2003, p. 267) proposes four general classes of variables from past implementation study: Policy and policy process: Includes policy design, resources, validity of a policy’s causal theory, the presence of “fixers” or other sovereigns, and policy outcomes. Organizations and their milieu: Includes the production of outputs, and problems of cross-organizational cooperation. Agents (actors): Includes a focus on their leadership abilities and preferences in shaping outputs or outcomes. Implementation environment: Includes groups’ behavior affected by policy, economic conditions, and public opinion. This area has been the main focus of work by the synthesizers. 28 Decisions of actors in the implementation process will be fixed as the object of research in relation to the values-based characteristics of democratic action. A democratic approach best acknowledges cases of change in local policy and practice that precede changes in state or federal policy. Implementation research using a democratic approach also does not confuse itself with implementation analysis outlined in classical bottom-up/top-down models. The intent of process research is to discover new knowledge about policy implementation as a continuous process of decision making, rather than on providing policy analyst’s with hard and fast rules for making policy design choices.
29 For a discussion of this issue regarding the influence of local contextual (environmental) characteristics on policy implementation, see Percival, Garrick L. (2004); for the contextual implications on initial formulation and subsequent adjustment of policy decisions, see DeLeon, Peter (1989); and for the influence of sociohistorical and motivational contexts on public service see Perry, James L. (2000).
32 scholars.30 The task now is to set forth a clear understanding of the variables used in this study from the broadest and most inclusive classification down to the narrowest variety.31 Variables by Classification & Type
Table 2.2: Variable Classification & Type
Classification Internal/Normative External/Rational
Informal/Individual Personal Professional
Formal/Regime Procedural Political
The classification terms for the variables in Table 2.2, or the largest grouping of variables under the general division of dependent or independent, is a continuation of research previously discussed summarized into the following classes: A. Internal/Normative B. Informal/Individual C. External/Rational D. Formal/Regime Arranging these classes into a 2x2 matrix allows for the types of variables to be deductively discerned from the more general classes. This deductive process is also based in previous scholarship, and produces the following variable types that can be interpreted democratically as types of responsibility and decisions: 1. Personal = Internal/Normative + Informal/Individual 2. Procedural = Internal/Normative + Formal/Regime 3. Professional = External/Rational + Informal/Individual 4. Political = External/Rational + Formal/Regime
30 Primarily in view here is the macro division of all variables into dependent or independent, and then the further classification of contextual variables as internal and external, formal and informal, individual and regime, and normative and rational. This taxonomy now must continue down to type, category, and variety. 31 This exercise is necessary to improve the internal validity of the overall research design, as well as connect the design to the case being studied. The assembled taxonomy is not all inclusive, nor can any social science taxonomy or model hope to be. What it is, however, is a succinct statement of the assumptions and proposals contained in the framework of research from an implementation perspective and democratic approach. It consists of a representative selection of terms and values drawn from past scholarship and exploratory research intended to show the relationships between the research perspective and approach, and the organizations, actors, and their decisions that are the objects of research. This reasoning, detailed as a taxonomy and later assembled into model format, can be transferred as a complete framework to all other experimental implementation studies conducted with a democratic approach.
33 Variable Types Explained in Terms of Responsibility Type 1: Personal - Internal/Normative + Informal/Individual This first sense of responsibility in decision making relies heavily on moral values and responses to leadership and clients within the organization or program, as well as being much more an individual “character responsibility” (Lacey, Nicola 2001, p. 262), or personal “functional responsibility” rather than a “political” one (Gilbert, Charles E. 1959, p. 389). Gilbert refers to J. Donald Kingsley’s idea of personal responsibility that posits internal informal administrative arrangements as critical means of democratic control. “[This] essence of responsibility is psychological rather than mechanical. It is to be sought in an identity of aim and point of view…which leads the agent to act as if he were the principal. In the first instance, it is a matter of sentiment and understanding, rather than of institutional forms [of control]” (Kingsley, J. Donald 1944, p.282; Gilbert, Charles E. 1959, p. 391). For the democratic approach to implementation, the internal informal, or personal type of decision is defined and measured as a normative and individual control on the RCP actor. Type 2: Procedural - Internal/Normative + Formal/Regime This aspect of responsibility is familiar to anyone who has worked in an organization, large or small, and has come to know the standard operating procedures (SOPs) of their particular agency, bureau, or office. In most cases, even though many unwritten rules are practiced and developed by experience, procedural responsibilities such as codes, rules, and policies are codified and can carry the weight of law. SOPs serve not only as an internal formal mechanism to establish official expectations and acceptable conduct of routine business in the organization, but also serve as a common foundation and source for office orientation and communication. Set office procedure also serves to remind individuals of their commitments to the group, as well as the established standards and actions required by law. Standards for performance rewards and punishments are common to all under the SOP, and knowledge of procedural responsibility is expected and required of all actors under its authority. Procedural responsibility is intended to foster both efficiency and effectiveness within the group, and help lead to better decisions that serve as an additional check on government. SOPs in this sense serve as a middle ground between actors in an organization restrained and
34 directed only by personal (character) responsibility, and those who act only on the basis of external rules and laws, with no personal style or commitment (Dobel, J. Patrick 1990, p. 359). Procedural responsibility is not intended to snuff out personal initiative, but to establish and codify the moral, ethical, administrative, and legal boundaries of the group. For a values-based democratic approach to implementation, the internal formal decision is defined and measured as a normative and regime control on the RCP actor. Type 3: Professional - External/Rational + Informal/Individual There are various sources of external and informal controls on the individual actor in a democratic society, including family, friends, neighbors, church and synagogue. The external formal control of central importance in the democratic approach to policy implementation, however, is centered on professional associations and their various codes of conduct and peer networks. Professional responsibility by definition requires that actors have a clear and sound concept of their professional duties, and “…act in accordance with due deliberation, sound reasoning, and consideration of relevant facts and circumstances…[that ensures] a course of action derived from some set of ideals” (Burke, John P. 1986, p. 9; Dunn, Delmer D. and Legge Jr., Jerome S 2000, p. 75). For example, public administration professionals form voluntary professional organizations like the National Council for Public-Private Partnerships (NCPPP), and the International City/County Management Association (ICMA). These professional associations publish their own magazines, case studies, white papers, codes of ethics, training and academic literature, and credentialing programs, as well as promote member consultants, hold association meetings, symposiums, and conferences in order to share and disseminate new ideas, technical advances, and best practices in the profession. The belief that is promoted by these professional organizations is that administrators are essential in democratic government and therefore are encouraged to act in good conscience to influence results for the better, often with innovative alternatives to the status quo, and possibly in defiance of self interest or formal organizational pressures (O'Toole, Laurence J. Jr. 1997, pp. 449-450, 454, 457).32
32 Judges, lawyers, probation and parole officers, social service case managers, court administrators, police officers, and nonprofit organizations all have similar associations that serve as external and informal controls on the individual decisions and actions of members in the respective professions. These associations promote their ideals and maintain influence in the profession by various means including
35 Type 4: Political (Accountability) – External/Rational + Formal/Regime Later, the external and formal, or “political responsibility,” will become the definition of accountability discussed under the categories of variables in the next section. This is consistent with public administration and implementation literature, and better helps to clarify and distinguish between responsibility and accountability as the two-part definition of administrative discretion. From Variable Classification to Categories A democratic approach toward the study of policy implementation views discretionary actions by the implementers of policy as legitimate and necessary behavior. Democratic theory in general, and a federal/republican form of government specifically, is based on the notion that the governed give consent to the discretionary decisions of the implementers of policy acting on behalf of the democratic regime. This implicit understanding acknowledges that administrators of public programs and services know what works best in practice because of their professional experience and developed working relationships with program clients. This perception recognizes that administrators are not only professionally motivated, but that they have a personal stake in the decision making process of policy implementation based in individual normative expectations (Maynard-Moody, Steven, Musheno, Michael et al. 1990, p. 845).33 This values-based decision making behavior, when observed in practice in the implementation decisions of RCP actors, combines direct regime representatives and administrative
regional or state branch organization oversight and the application of sanctioning rules and regulations for both individual accomplishment and malfeasance. For a values-based democratic approach to policy implementation, the external and informal decision is defined and measured as a rational and individual control on the RCP actor.
33 This interaction between the representatives of government and citizens has been formed into a four-part typology and juxtaposed over a three-part measure of political culture to help explain what each side brings to these interactions by the levels (High or Low) of citizen cooperation and government discretion. In cases where both citizen cooperation and government discretion is low (Low, Low), the interaction is Confrontational; high citizen cooperation and low government discretion (High, Low) results in Rule Compliance by both sides; when citizen cooperation is low and government discretion high (Low, High) the interaction is Arbitrary; and when both citizen cooperation and government discretion is high (High, High) both sides are Responsive. Confrontational interaction is most typical in a political culture that is Individualistic (as needed, politics/government is for promoting personal interests) and Traditionalistic (politics/government is for promoting elite personalities in control & the status quo); Rule Compliance by both sides is most typical in a Traditionalistic and Moralistic (a positive role for politics/government in promoting public interests and citizen participation) culture; Arbitrary interaction is Individualistic and Moralistic in nature, and Responsive interaction is wholly Moralistic. See Dresang, Dennis L. and James J. Gosling (1996).
36 actors, as well as indirect regime representatives working in partnership in pursuit of democratic purposes. The democratic implementation process suggests something much more normative and value-laden than can be measured or analyzed from purely rational perspectives.34 Therefore, decisions for democratic implementation are posited as a combination of rational and normative components. The rational component is associated with regime representatives working officially on behalf of the governed, and the normative component is associated with individual actors in the decision making process.35 In the case of community partnerships generally, and RCPs specifically, this association considers decisions measured along a spectrum of values from the purely rational (self-interested) to the purely altruistic (selfless) by both state and nonstate administrative actors.36 Defining Discretion: Responsibility & Accountability The two primary measures of the variable discretion will be drawn from the categories of responsibility and accountability. These two measures together will serve as the definition of decision making discretion because they best explain how public policy
34 In contrast, social scientists like Herbert Simon believe that administrative discretionary behavior is best defined in purely rational, self-serving terms. He uses this assumption to argue that since all administrative decision making is limited by imperfect information, that self-serving shortcuts are created as models for a bounded rationality, or “satisficing” rational compromise (Simon, Herbert A. 1947/1997). It seems an unlikely assumption that both state and nonstate actors in RCP implementation – a democratic, bottom-up, normative, and value-laden policy and program – have come to a simultaneous value-free (rational) application of administrative behavior in unique and disparate jurisdictions. This study suggests that something more than an independent and dispassionate analysis of facts in separate jurisdictions led to RCP development, and continues to guide democratic implementation. 35 In a liberal democracy, where the delegation of powers results in a great deal of administrative discretion, there are several conditions that must be met by regime actors (state & nonstate) as both administrators for the governed, and as individuals, in order to legitimize this situation: Administrators must act in accordance with basic principles that sustain the authority of constitutional government; individuals must subordinate their personal judgments to the outcomes of legitimate processes by constitutional and legal directives; individuals must remain accountable for their actions to the relevant authorities and the broader public; administrators must try to be honest and accurate in accounting for their actions; administrators must try to act competently and effectively to achieve their purposes, and; administrators agree to use public funds with care and efficiency for authorized public purposes only and not for their own gain or the private gain of others Dobel, J. Patrick (1999). 36 Public administration is most fully legitimized in its process of social direction when it conforms as fully as possible to the tenets of democratic morality (normative standard). This democracy in its practiced form is defined as the most democracy that is achievable under the conditions that have produced the administrative state (workable democracy), and is a functional part of the American political regime Redford, Emmette S. (1969). “Given these realities, researchers need to explore more fully the decision- values or operating norms employed by street-level workers as they distribute the benefits and burdens of human services through their continuous interaction with interested citizens, clients, and fellow workers.” (see Musheno, Michael 1986, and Maynard-Moody, Steven, & Musheno, et al. 1990).
37 and administration ultimately are translated democratically by state and nonstate actors and oriented toward public preferences. Responsibility and accountability are often used interchangeably, but are separate and distinct concepts within discretion and democratic implementation. The key question for the component parts of discretion is, “how should responsibility be defined and accountability exercised in a democracy” (Dunn, Delmer D. and Legge Jr., Jerome S 2000, p. 75)? Simply stated, from the implementation perspective and the democratic approach, responsibility is both an internal and external principle of control placed upon individuals and organizations, while accountability is purely an external and formal principle of democratic political control placed primarily upon programs and organizations. Responsibility and accountability serve together to guide and inform discretionary decision making by both elected and non-elected state and nonstate actors in the democratic implementation process.37 Maintaining the classification definitions as the standard and further reducing the variable types to categories is accomplished by substituting in the matrix the component parts of two particular variables (decision discretion and resources) selected from Table 2.1. These categories are drawn from past scholarship and exploratory research for the study of implementation using a democratic approach. The format of the 2x2 matrix requires that the variables be separated into their component parts for definition and fit: Table 2.3: Categories of Variables
Classification Internal/Normative External/Rational
Informal/Individual Responsibility Material
Formal/Regime Expertise Accountability
37 The distinction between these two category components of discretion first came to light in public administration literature as the “Friedrich-Finer Debate” of the early 1940s. Herman Finer championed the idea that elected officials are the natural focus of accountability in the regime, and that responsibility in a democratic society limits the discretion of administrators. Carl Friedrich, on the other hand, advanced the idea that non-elected professionals can have a broader realm of administrative discretion and also be the focus of accountability as well as responsibility in a democratic society (Friedrich, Carl J. 1940). The importance of this debate is still relevant to public administration generally, and this study particularly, because the perspectives they argued for the definition and approach to these categories continues to play an important role for contemporary scholarship in democratic politics and administration.
38 These categories appear frequently in political science research, and fit well into the general classification parameters. Adding together the component parts illustrate inductively the sum definition of the two of the main variables of concern in this study: a. Discretion = Responsibility + Accountability b. Resources = Expertise + Material Responsibility - Internal/Normative + Informal/Individual In a liberal democracy, no one working on behalf of the government - whether an elected, appointed, or administrative agent – can claim that, “they made me do it,” or “I was just following orders.” All public actors possess a degree of personal responsibility because their actions create precedents or procedures, real power devolves in practice to those with experience, skills, and expertise, and principled decisions serve as an additional check on governmental abuse (Dobel, J. Patrick 1990, pp. 358-59). The complexity of this intermingling of individual responsibility in the exercise of government power creates something of a creative competition among the various actors, and is an additional “…assurance of the existence of checks and balances more pervasive than those formally defined by the Constitution…” (Appleby, Paul 1949). Responsibility in this sense refers to the formally or informally delegated powers that are entrusted to individual government agents by the governed to accomplish the purposes of the organization or program they administer or implement. Another way of looking at it is that elected and non-elected agents act responsibly when they show “policy and administrative initiative and leadership in the areas for which they are responsible” (Dunn, Delmer D. and Legge Jr., Jerome S 2000 p.74). This responsibility is often subjective in nature because of its indirect linkage mechanisms to the principal (citizens), and is largely enforced in the “psychological responsibility” the individual actor feels toward those at whom the program is targeted (Mosher, Frederick C 1982 p. 8). Accountability - External/Rational + Formal/Regime Considering accountability as a regime value, positive techniques of civil service oversight are in place to monitor, direct and control public administrators in the course of their daily job performance. These positive control techniques and mechanisms, however, tend to become a value in themselves over time, and gradually obscure the purposes they were designed to serve in the first place. This displacement of true purpose creates an
39 “imprisonment” by administrative technique in the organization rather than facilitating problem solving through the “working out” of new innovations (Sayre, Wallace 1948). In the traditional community justice system for example, accountability has been framed in an adversarial context pitting the state (executive) against the citizen (accused), and refereed by the “least dangerous” branch of government to the political rights of citizens, the judiciary (Hamilton 1788, Federalist 78). RCPs alter this traditional practice of democratic accountability in the community for post-release offenders. They remove the adversarial context and placing the judicial official in a dual decision making position of responsibility as reentry manager (administrative), and the accountable regime official who has direct control over the political rights of the offender.38 This innovative arrangement further serves to highlight the traditional tension between politics (accountability) and administration (responsibility), while showing in practice that they are not dichotomous in their operation or theoretical foundation. Judges are openly working in this dual capacity while still within the democratic theory framework. The question of accountability in this dual function includes not only “who is accountable,” but also “how are they accountable.” Nonstate actors are involved as well (community partners) and their means of accountability must also be considered.39 Democratic accountability and control is also accomplished to a certain extent by an implicitly shared set of democratic values. This implicit understanding informally holds both elected officials and public administrators to task with an expectation of
38 Whereas responsibility is a principle of concern to the individual, accountability is a fundamental principle in democratic theory that explains the origination of authority and the connection of the regime official to the governed. Accountability in relation to law enforcement policy and community programs is traditionally though of as passing mainly through the executive branch of government, but in the case of RCPs, the democratic official of first account is in the judicial branch. The idea that policy implementation in RCPs is a democratic endeavor also alerts one to questions of accountability of the other administrative actors in the process as they exercise their discretionary behavior in the implementation process. 39 RCPs in this light are an innovation in American government. They are a new idea and approach that has been put into practice from the bottom-up. Any new way of doing business in the public sector that creates a permanent new organization, whether it is a formal reorganization of an existing body, or a new coalition assembled for accomplishing an old or a new mission, is going to face questions of regime accountability. In RCPs, the democratic conflict is in the “working out” of a problem solving innovation that requires administrative discretion be focused in a consolidated judicial authority within a decentralized partnership organization. This innovation requires all actors to take risks, redefine autonomy, and incorporate unprogrammed learning from action directed at solving a problem. This activity causes perturbations in the traditional notions of regime accountability that require standardization, predictability, replicability, and stability (Lynn, Laurence E. Jr. 1997, p. 99). Regime accountability in RCPs is an anathema to the traditional strategy of democratic accountability and bureaucratic reform; “more rules more tightly enforced” (Altshuler, Alan A. 1997, p. 44).
40 responsiveness and effectiveness to citizens. Formal accountability, however, becomes more problematic when new roles are assumed by elected officials and administrators alike, and the clear line between administrators as agents for elected officials becomes as blurred as the new roles. In the new arrangement, formal lines of accountability become less important while newly developed informal lines based in democratic values become more important. This is the kind of accountability that promotes individual actor responsibility, yet permits them the leeway needed to get positive results (see Jordan, Fred 1990; in Lynn, Laurence E. Jr. 1997, p. 95). Normatively, this accountability type seems preferable to the traditional red-tape accountability, and may even improve traditional accountability measures based in purely rational ideas of performance and responsiveness. Accordingly in this concept, the locus of regime decision making is decentralized and diffused in order to empower actors and their innovative ideas (see Osborne, David E. and Gaebler, Ted 1992, p. 275; in Lynn, Laurence E. Jr. 1997, p. 96). This act of innovation is based on the individual creativity of administrators, and their willingness to respond to and exploit new ideas as key actors in positions of influence or authority. The image of implementation in this model of accountability is no longer that of routinely and rationally applying long-established policies and procedures. Instead, actors are encouraged to engage in a continuous process of innovation, adaptation, and problem solving behavior that is informally but powerfully controlled through democratic values and after-the-fact accountability (Moore, Mark H., Sparrow, Malcolm et al. 1997, p. 294). On an operational basis, after-the-fact accountability is more heavily weighted on individual responsibility than on regime accountability, with both being heavily influenced and controlled by democratic values. Democratic values combine into underlying principles that cross formal administrative boundaries variously described by scholars as either “traditional” (professional practice standards), or “contemporary” (based in competition, outcomes, and partnerships). Contemporary principles of administration, such as deregulation and risk taking, and traditional principles such as laws, regulations, and professional latitude, are still difficult to define and measure despite the best efforts of categorization by scholars (Frederickson, H. George and Smith, Kevin B. 2003, p. 113). Regardless of principles, using underlying democratic values to
41 orient research is rich enough to transcend time-based and evolutionary ideas of administrative discretion, and allow a transferable and replicable explanation of decision making behavior. Defining Resources: Expertise & Material The two primary measures of the variable resources are drawn from the categories of expertise and material. These two measures together serve as the best definition of resources in decision making because they explain, in conjunction with the discretion categories of responsibility and accountability, how public policy is translated democratically and oriented toward public preferences. From the implementation perspective and the democratic approach, expertise is an internal and formal category of resources that is attributable to individuals and organizations, while material is an external and informal category of resources that influences programs and organizations. Expertise and material serve together to inform decisions by elected and non-elected state and nonstate actors in the democratic implementation process. The tactical decisions needed for democratic implementation success (bottom-up) are opportunistically achieved using the available resources at hand. Resources in this sense is more about ideas and opportunity than of balance sheets and physical assets on hand.40 Expertise - Internal/Normative + Formal/Regime A non-materiel resource like expertise is critical for achieving both the long term goals of public policy, as well as the short term objectives necessary for programmatic implementation. The interesting thing about expertise as a resource in democratic implementation is its relationship with the experimental nature of democratic
40 Defining and measuring resources in this way is a key assumption of this study. To operationalize the categories of resources in this sense requires a focus on the actors in an organization. This is necessary, first, as a positive control on the study of RCPs in disparate jurisdictions that rely on various levels of assistance from their respective city, county, state, and the federal government. Second, the non-materiel aspects of resources serve as a better standardized way to analyze the connections between public policy as it is conceived strategically, and policy implementation decisions made tactically within a bottom-up democratic approach (Hill, Heather C. 2003, p. 270). Third, resources as they are defined in this study are based in common democratic values rather than physical equipment as an additional way to standardize and transfer the research framework from one study of democratic (experimental) policy implementation to the next. Fourth, using this definition keeps the focus of analysis on the behavior (decisions) of the actors in the implementation process, thereby building on the values, organizational culture, and experience of people rather than on the physical plant of the organization or program (Petter, John, Byrnes, Patricia et al. 2002, pp. 381-382). All these reasons serve to enhance replicability of the research design, fix the object of study as the decisions of actors in the democratic implementation process, and answer the fundamental research question, “How are reentry court partnerships being implemented?”
42 implementation. Experts often times apply this non-materiel and values-based resource immediately in the form of a discretionary decision when an unanticipated opportunity arises in the process (Slade, Stephen 1994, p. 71). This democratic application of expertise can be for a fundamental innovation, or simply for an incremental improvement on the continuing implementation process. Additionally, using the composite variety definitions of cooperation, consistency, judgement, and persuasion as the foundation for the definition of expertise increases the transferability and replicability of the research model (see Table 2.4 in next section). Material - External/Rational + Informal/Individual The term material is chosen here instead of materiel because the latter is concerned only with the physical equipment, apparatus, and supplies of an organization. Material, on the other hand, is focused on the substance or substances out of which a thing is constructed, including both physical substances (money, facilities, etc.), and non- material things such as ideas, information, experience, and authority. Material resources in relation to this study of RCPs will focus exclusively on the non-materiel aspects of this variable category. Communication, consensus, competence and bargaining, along with their composite values, will be the measure of material in experimental implementation. Variable Varieties In order to operationalize and measure the class and category of variables, the various values that constitute them must first be enumerated before being used in a survey instrument. Discussions about what values are (normative and rational), their definitions, and how they function at a personal and social level have been a staple of the social sciences for many years. These discussions come from all social science fields including psychology, sociology, anthropology, economics, education, religion, philosophy, as well as political science (Feather, Norman T. 1999, p. 52). Many scholars interested in administrative responsibility in particular have been interested in a definition drawn from discernable and replicable sets of values. Political science has, however, been almost exclusively focused on defining and measuring rational values in theory and research concerning political and administrative behavior. Both rational and normative values play an important role in actor decision making, and are defined simply as those things that “I need to have or do” (external and rational), or “I ought to have or do”
43 (internal and normative). In order to operationalize the normative and rational aspects of the variable categories in this study, the values by variable variety contained in Table 2.4 are drawn and refined from past scholarship to construct and list the normative and rational values to be measured.
44 Table 2.4: Combined Table of Variables and Definitions Division/Class. Category Type, Variety, and Definitions (Values) Type Personal Procedural Professional Political Variety Compassion Fairness Effectiveness Responsiveness Responsibility Values Sympathy Impartial Designs Concern Unbiased Solutions To clientele
(Norm./Ind.)
Discretion Internal/Informal Variety Conscience Openness Efficiency Responsiveness
Accountability Honesty Honesty Creative Respect Candor Innovation To citizens Values (Rat./Regime) (Rat./Regime) External/Formal Variety Cooperation Consistency Judgment Persuasion
Expertise Knowledge Uniformity Insight Influential Understanding Routines Perception Convincing Values
Internal/Formal Resources (Norm./Regime) Variety Communication Consensus Competence Bargaining
Material Information Agreement Qualified Compromise Skills Unity Capable Negotiate Values (Rat./Ind.) (Rat./Ind.) External/Informal
Compiled, adapted and refined from:(Gilbert, Charles E. 1959, pp. 375-378; Williams, Walter 1980, Chapter 5 & 6; Waste, Robert J. 1989, p. 10; Dobel, J. Patrick 1990, p. 363; Frederickson, H. George 1994, pp. 460-461; O'Toole, Laurence J. Jr. 1997, p. 452; Chackerian, Richard and Mavima, Paul 2000, pp. 359- 361; Dunn, Delmer D. and Legge Jr., Jerome S 2000, p. 76; Perry, James L. 2000, p. 481; Petter, John, Byrnes, Patricia et al. 2002, pp. 382-385; Hill, Heather C. 2003, pp. 269-273; Kernaghan, Kenneth 2003, p. 712). Applying Context and Variables to the RCP Environment
Table 2.5: Specific & General Variables by Classification, Category & Type
Class State Actors Nonstate Actors
Categories Judges Administrators L/P/C* Community Ex- Managers partners offenders (Environment) (Environment) Specific Variables
Personal Dependent Type Procedural Variable (Decision) Professional Political
Responsibility & Accountability Categories Expertise & Material
(Context) Class Discretion & Resources General Variables General Variables
Form adapted and refined from (Rosenbloom, David H and Kravchuk, Robert S. 2002 p. 39)and. (Goldkamp, John S, Weiland, Doris et al. 2001 p. 30) * Law enforcement/Probation/Parole/Case Managers
The dependent variable derived from this table is the decisions of the actors within the decision making process, and are reported by the type of decision. These decisions become the outputs of the schematized system model displayed in Appendix B. Decisions are measured by the degree of rational or normative behavior contained therein based on the variable classification, category and variety of Table 2.4. The decisions of actors in policy implementation is not to be confused with the decision making process which is the conversion mechanism for the two independent variables of discretion and resources – each with two component parts measured by degree. Table 2.4 and Appendix B combines and simplifies for the first time democratic implementation research from the general variable categories proposed by public administration and policy implementation
46 scholars, with the specific case variables of experimental implementation found in the organization of RCPs. The dependent variable as a decision measured in degrees of rational or normative behavior and reported by type is considered to be the product (output) of the actors in the decision making (conversion mechanism) process within the organization of the RCP. The general variable class and categories become the independent variables in this approach. The independent variables are also measured in degrees; degree of responsibility and accountability (discretion), and expertise and material (resources) respectively. Combined, Table 2.4 drawing democratic variables from theory, and Appendix B providing a useable framework, incorporate the policy purposes, processes, and the implementation environment in question into a readily understandable and practical research model for RCPs. Variable Types Explained in Terms of Decisions By focusing on a question and doing research concerning the decisions of the actors in the implementation process, and by further refining cases in the study, the contextual field is narrowed and a reasonably parsimonious environmental model can be developed. This serves to minimize system variance, and increases both internal and external validity of the overall research design. Therefore, for RCPs and democratic implementation research in general, the question, theory framework, variables, and model is tuned specifically to the task and object of study at hand. This is a bottom up process modeled in itself. The importance of a tuned model particularly in studying partnership organizations is further found in the grassroots democratic tradition; RCPs combine nonstate actors (community partners along with offenders), with state actors from both judicial and executive branches and functions into one operational organization. In other words, the cases of interest for applying a democratic implementation model for research on RCPs are those that have either democratically elected or executive appointed judicial branch judges (no administrative law judges), and include state and nonstate actors that traditionally cater to “back end” adult offenders - defined as parolees and prison early release. The courts in Ohio and Indiana meet this criterion. Other courts in CO, IA, and NY are quasi-judicial in their exclusive use of administrative law judges, and WV and
47 TX are oriented only to juveniles, and established only as a diversionary program respectively In the search for good fit and parsimony in a research model, it is first prudent to eliminate models that do not fit the situation and are unnecessarily cumbersome as well as positively identify those that can best do the job. It is clear upon initial exploratory investigation into RCPs that a top-down authoritarian implementation model would not benefit a study in this particular area of policy implementation research. Top-down models start with an assumption that implementation is triggered by an authoritative decision emanating from a statute, court decision, executive order, or administrative ruling. In this top-down schema, the states have traditionally been the middle man in negotiations between federal and local agencies, as well as between local community and national interest groups in policy implementation processes. RCPs provide, in addition to a comparison of the democratic implementation processes in four jurisdictions, the interesting aspect of certain actors in the implementation process (judges) taking on the role of middlemen while simultaneously assuming the role of policy managers in the implementation process. While being a small n study particularly in regards to the judges (3 total in 2 jurisdictions), the wider emphasis on state and nonstate actors in the implementation process will provide multiple means to understanding the democratic implementation process of RCPs. Further, by defining and providing a typology for the decisions of the actors in the implementation process as the dependent variable in the implementation process, it will be possible to use actor understanding of the policy objectives, goals and resources as a contextual control in relation to individual beliefs, values, and principles in order to best explain RCP democratic policy implementation. By further using the process of decision making as the conversion mechanism from where the dependent variable (decision) is produced, observation and data collection will have a central focus that also serves to highlight the democratic nature of RCP organization and implementation. Conclusion The meta-analysis of chapter one laid the foundation for research from a policy implementation perspective. This chapter has built the framework and defined the
48 variables and model for research from a democratic approach. The case of interest for application of the research model is the RCPs, and in chapter 3 the administrative history and community justice concerns that encouraged their formation will be explained.
49 CHAPTER 3
THE RISING COSTS OF OFFENDER SUPERVISION: REENTRY COURT PARTNERSHIPS AS AN INNOVATIVE SOLUTION
The Context for Reentry Court Development: Prison and Parole Policy The purpose of any offender reentry program should be to solve the persistent problem of recidivism. The difficulty in measuring the success or failure of these programs is largely found in the lengthy periods of time needed to establish baseline data followed by controlled longitudinal study. Lost in this long term perspective is the preliminary account of the dynamic processes and decisions pursued by the innovators and implementers of the programs. Innovative models created in such cases to solve real problems often cut across traditional separation of power boundaries and administratively establish new partnerships and programs. These cross-cutting solutions also frequently confront legal obstacles. By focusing on the decision making processes of the key actors in RCP implementation, this study’s observations and results will lay the groundwork for a prescriptive discussion of RCP development. The details of how RCPs refigure the traditional and legal separation among branches of government in an attempt to solve the problem of offender recidivism are also detailed in this chapter. Managing the incarceration and reentry programs of offenders can be contentious when administrative advocacy on the one hand is weighed against societal resources and expectations on the other. This conflict is magnified because law enforcement and sentencing powers are split between the executive and judicial branches by statutory law drafted to satisfy the separation of powers. The administrative inefficiency of this split constitutional system has come under the professional scrutiny of public administration practitioners and elected judicial officials. This scrutiny is focused in practice by management innovations designed to improve the efficiency and effectiveness of public programs intended to deliver a superior service to the citizen client. Basic inefficiencies built into the separated powers system are the natural objects of attention of public administration professionals as the republican desire to control power comes into conflict with the entrepreneurial desire to eliminate redundancy and promote cost (time and material resource) savings. Cost savings are ultimately counted in dollars, but may be initially measured in other forms of currency that directly relate to the public process or
50 program in question. For prisoner reentry court programs, the measure of savings will initially be found in reduced court appearances by offenders for probation or parole violations and new crimes,41 lower offender recidivism rates,42 fewer post-release supervisees per case officer, and increased levels of public safety. These are by no means the only ways that benefits can be measured. In the short term, as these new programs are being implemented, measurement of the discretionary decision making processes of the key actors is a good way to understand how and why these early programs succeed or fail. State Financial and Social Costs The fifty state departments responsible for managing prisons and caring for nearly 2 million inmates annually account for a significant percentage of state budgetary outlays. States spent a total of $29.5 billion for prisons in 2001, nearly a $5.5 billion increase over 1996 after adjusting for inflation, and nearly three times the amount spent in 2001 constant dollars over the $11.7 billion spent in 1986 (Stephan, James J. 2004, p. 1). State budgeting amounts per inmate vary from a low of $8,128 per year in Alabama, to a high of $44,379 per year in the state of Maine (Stephan, James J. 2004, p. 3). Table 3.1: Prison Costs for Fiscal Year 2001 (States in this Study) Expenditures (1,000s of dollars) Annual Operating Costs State Prisoners State Total Operating Capital Per Per State (U.S.) As of Inmate Resident 6/30/01 Ohio 1,277,622 1,201,269 76,354 26,295 106 45,684 Indiana 477,628 449,406 28,222 21,841 73 20,576 (Stephan, James J. 2004, Table 2, p. 3).
41 One way to estimate these costs is to use national statistical averages to build a predictive model of costs to society for crimes committed by offenders on post-release supervision. The model then becomes the standard against which the “control group” of RCP participants can be measured. An internal study conducted by the Allen County, Indiana RCP using a model that estimates the number and types of crimes offenders returning to Fort Wayne, Indiana are expected to commit found that RCP participants offend at a lower rate than the national average. The model predicted that the total number of returning offenders participating in the RCP would likely be charged with twenty property crimes (burglary or theft) in the first year of release. The predicted cost to society of these charges using national averages was $61,146. RCP participants in the first year were charged with only six property crimes with an associated cost of $15,689 – a savings of $45,457 (Warner, 2003). 42 A similar model using national statistics on recidivism rates was used by the Richland County, Ohio RCP to predict, and then compare, expected rates of re-arrest for new crimes in the first year of release from prison (rather than new charges as in the Indiana model) for RCP participating offenders. The national average expectation of arrest of offenders for new crimes while under post-release supervision in the first year is 44.1%. The “control group” of RCP offenders were re-arrested at a rate of 6%, or a reduction of 86% from the predicted rate (Spelman, Jeffrey B., 2003).
51 In Ohio from 1985 to 2000, state spending on corrections rose by 211% compared to an increase of 38% in spending for higher education. In Indiana, like spending increases were 214% and 39% respectively (Zeidenberg, Jason and Schiraldi, Vincent 2002, p. 7). While total dollars spent by states on higher education is still greater than on prisons, the percentage of increase in corrections spending is bringing these totals closer together. In Ohio for example, state spending on higher education outpaced spending on corrections in 1985 by 3.625 to 1 ($1,762,000,000 to $486,000,000), but shrank to 1.608 to 1 in 2000 ($2,432,000,000 to $1,512,000,000). Nationally, total annual state spending on corrections has risen by 266% from 1985 to 2000 ($12,012,000,000 to $32,002,000,000). The negative implications that this rapid increase in spending has for other line items in state budgets is obvious. Increasing costs were fueled by incarceration rates in the United States rising to nearly five times what they were in 1970 (Stern, Vivien 1998; Caplow, Theodore and Simon, Jonathan 1999), and a 487% increase in drug offenders committed to state prisons between 1985 and 1996 (Peters, Roger H. 2000 p. 28). As prison populations grew and state budgetary outlays increased, political pressure to make state prison systems operate more efficiently brought administrative attention to the need for professional development and training of the respective executive agencies (Riveland, Chase 1999). Connected to the efforts to improve administration were concerns about the availability, training and quality of state corrections officers (Belluck, Pam April 21, 2001), and the difficulties of leveraging the efficiencies of volunteers into a system already facing budgetary and legal constraints (Coffey, Alan 1975; Connelly, Michael 1996). Concurrent with rising costs for corrections operations in the states has been the increased levels of administrative centralization. This administrative trend, coupled with the physical growth of corrections operations, is exacerbated by the operational intervention of the courts due to poor prisoner treatment (DiIulio, John J 1990; Marquart, James W. and Crouch, Ben M. 1998), and a heightened concern for accountability to the public. Court intervention, despite its specific focus on improving prison conditions, has resulted in much of the autonomy and decision making discretion that local wardens once
52 possessed concerning prisoner supervision to be eroded (Goodstein, Lynne 1989 p. 3).43 This development has evolved over several decades as public sentiment shifted from rehabilitating criminals with the intent of returning a reformed citizen to society (Rotman, Edgardo 1990), to an emphasis on punishing and warehousing criminals (Platt, Anthony M. 2001; Richards, Stephen C. and Ross, Jeffrey Ian 2001). This shift has resulted in an exponential growth in incarceration rates in the United States that have become the highest per 100,000 population in the western world (Blumstein, Alfred and Beck, Allen J. 1999). High incarceration rates in the United States also contribute to a growing class of citizens that are placed at a social disadvantage, particularly in the area of employment, after successfully completing their designated prison sentences (Petersilia, Joan 1999; Williams, Juan 2000). The social stigma of incarceration can be informal (shunning by family, friends, neighbors, and employers) as well as formal through various state laws and local ordinances that legally prohibit freedom of employment and certain forms of civic activity such as voting.44 The Social and Administrative Impact of Incarceration The effects on civil society are significant when the criminal justice system is releasing ex-offenders into the community with little or no prospects of resuming what would be considered a normal life (Strang, Heather and Braithwaite, John 2001). This truth is best realized by focusing on drug crime related incarceration rates. The drug offender prisoner population in state prisons in the United States accounted for nearly
43 Ironically, as the courts have reduced the executive administrative discretion of wardens, judicial discretion in sentencing has been reduced by legislatures. Control over sentencing has shifted away from judges to the control of state legislatures who used their election mandates to implement determinate sentencing laws beginning in the 1970’s (Mulcrone, Richard T. 1987), soon followed by presumptive sentencing guidelines in the 1980’s (Knapp, Kay A. 1989). This politicization of crime stressing positive law and order (Jacobs, David and John T. Carmichael 2001) became the center of policy debate among elected office seekers at the state level. Electioneers use societal concerns about crime rates to create ready- made campaign issues and to identify their candidates as carrying the “tough on crime” banner (Goodstein, Lynne, Ed. 1989, p. 16). This drove higher the costs of prison administration by increasing the number of legislative mandates and their resultant administrative regulations. State corrections agencies were forced to comply with increased levels of statutory and administrative law (McGee, Richard A. 1981, p. 76), and public support for more prisons and tougher sentencing laws were being magnified in each subsequent election cycle (Davey, Joseph Dillon 1998). 44 This exacerbates the stigmas already attached to ex-offenders for employers reluctant to hire under the best of circumstances. Adding to this stigma are numerous state policies that prohibit released prisoners from holding many public and private sector occupations. Examples of occupations on the prohibition list includes law, real estate, medicine, nursing, physical therapy and teaching in California, and dentists, engineers, and pharmacists in Colorado (Petersilia, Joan 2000). Several other states permanently prohibit any position of public employment to ex-offenders (AL, DE, IA, MS, RI, and SC) (Petersilia, Joan 1999).
53 one-third of the total population in 1996 (29% of all inmates), while only a fraction (13%) receive any form of drug rehabilitation services while incarcerated (Blumstein, Alfred and Beck, Allen J. 1999 p. 25). Sociologically while in prison, inmates are forced of practical necessity to cope with the prison environment by developing attitudes, behaviors and norms needed for prison survival that are then transmitted back into the community upon their release (Petersilia, Joan 2000). Many other social and psychological problems are manifested and must be dealt with when offenders are incarcerated and then released to the community.45 Given these concerns in total, and the lack of a political solution, administrators of corrections programs were transformed into advocates on behalf of the incarcerated population. These administrators realized that a new perspective was needed to make a fundamental change in a now self-perpetuating cycle of criminal behavior and incarceration. The point of action for many administrators intent on breaking the cycle was prisoner reentry programs. Organized efforts at the local level began to actively plan for and prepare the offender to successfully return to society. Intangible as well as tangible reasons are given by administrators and public actors turned advocates focused on preparing offenders for a return to the community.46 Tangibly, material and social benefit is to be gained by the returning offender and the community if gainful
45 The financial, legal, and moral debate associated with prisoner incarceration and reentry leads to inquiries about the social effects of incarceration (Covington, Jeanette 1997; Blumstein, Alfred 2000; Platt, Anthony M. 2001), prison overpopulation (Welsh, Wayne N. 1991), and experiments in proprietary prisons (Goodstein, Lynne 1989 p. 45; McDonald, Douglas C. 1998). Others are concerned about adverse psychological effects on prisoners (Zamble, Edward and Quinsey, Vernon L. 1997), high recidivism rates (Beck, Allen J. 1997), and the humane treatment of prisoners (Haas, Kenneth C. and Alpert, Geoffrey P. 1989; Sturm, Susan 1998). Also of concern are problems directly related to overcrowding in state prison systems including adequate sanitary and health conditions (Brien, Peter M. and Beck, Allen J. 1998; McDonald, Douglas C. 1999), combating gang related activity (Bottoms, Anthony E. 1999), and the unique variables involved in the incarceration of women (Rafter, Nicole Hahn 1989; Robinson, Robin A. 1992; Lord, Elaine M. 1998). By the end of the 1990’s, it was also obvious that the war on crime had taken a disproportionate toll on minority populations in the United States, particularly among black males (Tonry, Michael 1998; Zeidenberg, Jason and Schiraldi, Vincent 2002). Incarceration rates stated as a ratio of black/white ranged from 5.21:1 in Georgia to a high of 35.31:1 in the District of Columbia, with a national average of 7.66:1 (Stern, Vivien 1998 p. 119). 46 For example, the three judges interviewed for this study unanimously expressed the sentiment that they were tired of seeing the same offenders, from the same families, one generation to the next, appearing before them on criminal charges. The intangible aspect of this desire to break the cycle of recidivism and the learned behavior of offenders, and the judge’s subsequent voluntary participation and personal commitment to RCP hearings and rehabilitation, is an example of the altruistic rather than rational nature of many decisions. As politically elected officials, the political risks of offenders becoming violent under RCP supervision and re-offending are seemingly greater and more negative than any potential positive tangible rewards.
54 employment can be secured and maintained after release rather than becoming the material for recurring arrest and imprisonment. This advocacy focus resulted in the call for improved pre-release (Scott, Mike 2001), as well as post-release reentry programs (Ryan, T.A. 1998; Petersilia, Joan 1999). The Failure of Post-Release Supervision and the New Prisoner Reentry Philosophy The philosophy behind tradition prison programs (prior to the war on crime) was to rehabilitate and successfully return the criminal offender to society (Cullen, Francis T. and Gendreau, Paul 1989; Losel, Freidrich 1998; Lin, Ann Chih 2000). Traditional philosophy gained new professional supporters in the mid 1990s, and in-prison programs that emphasized restorative justice over retributional justice also gained new popularity (Strang, Heather 2000; Strang, Heather and Braithwaite, John 2001).47 An important guiding supposition for reform was the possibility of broad social benefits from combining community with prison based programs. This perspective uses a philosophy that considers crime to be a social problem that affects the life of a community. In order to be successful, reentry programs require that prevention be an essential element of criminal justice work by uniting prisoner rehabilitation and victim compensation (Watts, Elizabeth L. 1990; Fulton, Betsy A 1996; Read, Edward M 1996; Dooley, Michael J. 1998; Karp, David R. 1998; Petersilia, Joan 1998; Kurki, Leena 2000; Karp, David R and Clear, Todd R 2002). Another way to look at this development is as a non-adversarial court process (mediation). This way of dispute resolution involving the offender, victim, community partners and the court is a continuation of alternative dispute resolution (ADR) methods that have long been encouraged by the judicial branch of government.48
47 The intent of restorative programs is to link the confinement of the criminal, rehabilitation efforts, and the compensation of the victim of the crime through various service, community and religious based activities (Braswell, Michael 2001; Niebuhr, Gustav April 12, 2001). Additionally, the adverse effects recorded on the development and adjustment of the children of both male and female prisoners is recognized and addressed (Bennett, William J., John J DiIulio, et al. 1996; Chapple, Karen V. 1998; Wayne, Larry 1998; Hagan, John and Ronit Dinovitzer 1999). 48 Ohio has been a leader in the alternative dispute resolution (ADR) movement. Through the efforts of the Ohio Supreme Court and the Commission on Dispute Resolution and Conflict Management the number of court and community mediation programs had grown from 11 in 1991 to 121 programs in 44 counties in 1999. These efforts allow people, with the assistance of a neutral party, to solve their own problems in ways that best satisfy their personal needs. The Ohio Supreme Court’s Office of Dispute Resolution currently makes grant funding available to courts in all areas of the state, with the goal of having ADR programs in all of Ohio’s common pleas courts by 2006 (OCFC 2000, p. 62).
55 Revitalize or Replace Parole Supervision? The war on crime caused the functions of parole to be overwhelmed by the rapid growth in parole officer caseloads. Individual parole officer caseload ratios rose as high as 69:1 (Petersilia, Joan 1999 p. 505). An additional symptom related to an over- burdened parole system is that post-release offenders become particularly likely to return to prison in states with mandatory sentencing laws because of the lack of alternative recourses other than imprisonment for parole violations or minor new crimes (Greenwood, Peter W. 1994). An example of mandatory sentencing is seen in the “three strikes” laws that require three time offenders to be sentenced to lengthy prison terms even for minor infractions. This kind of mandatory sentencing came under scrutiny in the late 1990s. In 2001, the state of California’s mandatory sentencing law was ruled to be in violation of 8th Amendment protections against cruel and unusual punishment. Prior to this ruling, however, legal challenges had been unsuccessful in overturning mandatory sentencing laws even when citing the same protections against cruel and unusual punishment contained in the United States Constitution (Cooper, Phillip J. 1998). Judges and corrections professionals are particularly critical of mandatory sentencing laws because judicial and administrative discretion is taken from the bench and the corrections environment and concentrated in the state legislature. Opposition to mandatory sentencing is an important justification used by judges and corrections officials in offering alternatives to politically driven incarceration policies based only in public opinion trends and perceived dangers to society (Zimring, Franklin E. and Hawkins, Gordon 2001). It is candidate focused electioneering that helps shape public sentiment in support of incarceration over other forms of punishment or rehabilitation (Shichor, David and Sechrest, Dale K. 1996). Various alternatives to the incarceration of many categories of criminals have been proposed (Anderson, David C. 1998). Specifically, the development of technologies for in-home electronic monitoring systems (Renzema, Marc 1992), community “volunteer” work (Thoroman, Bill 1998), short term shock incarceration (Clark, Cheryl 1998), boot camp style training in lieu of imprisonment (Bourque, Blair B. 1996; Rochelle, Tom 1998), or partnerships with various private not-for-profit service providing organizations such as Habitat for Humanity (Keilin, Sharon B. 1998). Other
56 ideas are counted under the heading of “smart sentencing” that impose intermediate sanctions short of incarceration as a means of adjusting criminal behavior. These ideas include monetary sanctions (Cole, George F. 1992; Hillsman, Sally T. 1992), home confinement (Byrne, James M., Lurigio, Arthur J. et al. 1992), day reporting centers or “halfway houses” that are either publicly or privately administered, treatment and drug testing outside of the formal prison environment (Fox, Vernon 1977; McDevitt, Jack and Milano, Robyn 1992; Williams, D. J. 2001), and intensive probation and parole supervision (Fogg, Vern 1988; Petersilia, Joan and Turner, Susan 1993; Rhine, Edward E. 1993; Raynor, Peter and Vanstone, Maurice 2002). The preponderance of research efforts concerning intermediate sanctions and adjusting criminal offender behavior and improving accountability has been focused, however, on reevaluating and redefining probation and parole operations (Rhine, Edward E. 1991; 1993; Petersilia, Joan 1997; Rhine, Edward E. 1998). Administrative Realities and Advocacy Initiatives Various policy and program initiatives attempt to treat the numerous problems produced by an incarceration focused criminal justice system. Management models and administrative tools have been developed that specifically deal with the rapid rise in incarceration rates and requirements for new facilities and personnel to operate them (Carlson, Peter M. 1999; Phillips, Richard L. and Roberts, John W. 2000). Various viewpoints have been taken to better frame the problems and formulate the programmatic solutions needed to efficiently and effectively administer state prison systems (Freeman, Robert M. 1999). A common frame of reference is seeing prisons as a microcosm of constitutional government generally (DiIulio, John J. Jr. 1987), and capable of the same type of reforms and innovations used in the changing operations and management of other government agencies. Reforms based in seeking operational and financial efficiencies fall into the entire range of the ideological spectrum. This begins at privatizing administration outright (Logan, Charles H. 1989; Weiss, Robert P. 1989; Shichor, David 1995), and progresses through partnering with private providers for the various ancillary programs and services required in prison administration (Sellers, Martin P. 1993). Intergovernmental initiatives include cross-leveling prisoners among local jails, state and federal prisons on a per diem contract basis (Szostak, Edward W. 1998),
57 creating regional multijurisdictional corrections facilities (Bounds, Bruce 1992), maintaining the status quo in state government administration (DiIulio, John J 1989), or in partially or completely federalizing and centralizing prison administration at the national level (Lawson, Robert H. 1984; DiIulio, John J. Jr. 1991). In all of these scenarios, legal and fiscal considerations play an important role when entering into any type of partnership activity (Zimmerman, Joseph F. 1983) or contract agreement (May, Peter J. and Williams, Walter 1986). As far as privatization is concerned, of the 1.8 million prisoners in the United States in 1998, only 77,500 were confined in privately operated facilities as the states maintain virtual monopoly rights on the warehousing of convicts (Welch, Michael 1999 p. 280). Once a course of administration action is decided upon, whether it is privatization, partnering, or increased centralization, a definite organizational strategy, policy goals, program objectives, and institutional structure and design for operations must be adopted (Freeman, Robert M. 1999; Wilkinson, Reginald A. 2001). None of this administrative activity occurs in a vacuum. It is achieved in the political context of the state and not without first taking into account the political consequences of institutional and programmatic reorganization (Marcelli, Ralph J. 1977). Without politically vetted and articulated policy parameters and purposes from which to orient administration, the policy and program evaluations of existing and proposed initiatives is difficult at best (Gilsinan, James F. 1997). The underlying purposes as defined by the administrative authority for these programs must remain at the center of evaluation, and it is in the variation that is observed from one state prison system to another that provides the opportunity for comparative studies of programs and impacts (Currie, Elliott 1997). Difficulty in analysis is also present in identifying and measuring external threats to program validity inherent in shifting implementation among fairly unique state political and fiscal environments (Merlo, Alida V. and Benekos, Peter J. 1997). Once the local contexts and disparities in politics and fiscal realities are identified, these divergent variables can better be controlled in evaluating the possibility of transferring the application of a policy solution from one state to another. Partially equalizing this disparate federal environment is national government project financing and grant programs aimed at standardizing state sentencing practices and providing uniform and
58 sufficient prisoner care while held in state facilities (Freeman, Robert M. 1999). As will be seen with prisoner reentry courts in this study, however, a uniform financial source among the jurisdictions is not present. Reentry Court Partnerships Defined Reentry court partnerships themselves are a community based approach to prisoner reentry programs that aid offenders in leaving the adult state prison system and return to society (Lehman, Joseph, Beatty, Trudy Gregory et al. 2002; Travis, Jeremy, La Vigne, Nancy G. et al. 2003). Using the vehicle of problem solving courts (Berman, Greg and Feinblatt, John 2001; Casey, Pamela and Hewitt, William E 2001) that apply the concept of therapeutic jurisprudence (Wexler, David B. 2001; Maruna, Shadd and LeBel, Thomas P. 2003), adult offender reentry court partnerships can be studied from different academic perspectives. Until recently, however, the preponderance of study concerning offender reentry and long term recidivism rates has largely focused on reevaluating and redefining probation and parole operations (Petersilia, Joan 1999; 2001; Travis, Jeremy and Petersilia, Joan 2001). Even though this study is interested in the short term implications of policy implementation, the long term survival of RCPs will depend on establishing causal relationships to reduced recidivism rates,49 budgetary cost savings,50 and resolving administrative, legal, and political problems involved in intergovernmental and state-nonstate (nongovernmental) partnerships. RCPs are founded operationally on the established model and practice of specialized docket courts, also known as problem solving courts. Drug courts, DUI courts, mental health courts, domestic violence courts, and now reentry courts seek to combine elements of restorative justice and therapeutic jurisprudence (Maruna, Shadd and LeBel, Thomas P. 2003). This court model - which has its proponents (Wexler, David B. 2001), and its opponents (Hoffman, Morris B. 2002; Thompson, Anthony C.
49 Initial 1-year recidivism figures (August 2002) provided by the Richland County, OH RCP show a significant short term reduction in recidivism rates for offenders in the 12 month program when recidivism is defined as arrests for new crimes. The Richland County RCP recidivism rate is reported at 6% compared to a national average of 44.1% for those on parole (n=160). 50 Initial figures (2003) provided by the Allen County, IN RCP measures cost savings in terms of re-arrest costs by criminal charge. Re-arrest charges and costs for offenders are compared between 2001-2002 (pre and in-progress RCP) at 3 and 12 months. Re-arrest charges at 3 months dropped from an expected number of 39 to 21 for a savings of $127,940, and a 12 month reduction of re-arrests from 66 to 54 resulted in a reported cost savings of $414,785.
59 2004) - attempts to reduce the fundamentally adversarial basis of the judicial process by bringing “treatment into the court and the courts into treatment” (Terry, W. Clinton III 1999). If in the long term problem solving courts of all kinds are seen as reducing offender recidivism while conserving fiscal resources, then they are likely to evolve from their current locally specialized and process oriented form to their logical and operational end as a system of justice linking all communities in the state (Tauber, Jeffrey S and Huddleston, C. West 1999). Issues of power sharing between the judiciary and executive branches regarding the supervision of probationers and parolees, and the legal operation and administration of these partnership organizations are yet to be resolved. Some legal and criminal justice scholars are working with state corrections and judicial practitioners to establish a plausible narrative for the long term explanation of reentry courts through a “jurisprudential lens” (Travis, Jeremy and Petersilia, Joan 2001), while not yet investigating the short term processes involved in program implementation. The jurisprudential lens, in contrast to the short term process focus, will primarily be concerned with analyzing the long term administrative, political, and legal implications of judges as “reentry managers” (Travis, Jeremy 2000). The short term focus of this study will instead focus on the actors in the implementation process to better explain how the political and administrative decisions of judges and other principals and agents are directing the implementation process. The Role of Judges The in-progress study of the RCP implementation process also highlights the fundamental shift in the type of role the trial judge plays in this particular judicial partnership. Typologies of judicial roles based on levels of political autonomy and judicial creativity have been proposed (Guarnieri, Carlo and Pederzoli, Patrizia 2002, pg. 70) that are similar in heuristic nature to the typologies for policy analysts (Meltsner, Arnold J. 1976) and policy types (Lowi, Theodore J. 1964) previously mentioned.51 These judicial types are defined as a set of expectations, values and attitudes about the way judges make decisions as influenced by their judicial role (Murphy, Walter and
51 A typology of judicial roles based on levels (High or Low) of political autonomy from political institutions, especially the legislature, and judicial creativity defined as the extent to which decisions are taken or not taken based on pre-existent substantive law: Executor (Low-Low); Guardian (High-Low); Delegate (Low-High); Political (High-High). RCP judges exemplify the Political role.
60 Tanenhaus, J. 1972, pp. 140-44), and by the disharmony (activism), or harmony (restraint) between the policy of the court and other decision makers (Schubert, Glendon 1965, pg. 154). The existence of a more involved and active role for judges is presupposed by the recruitment process where political considerations are openly present in direct popular election (Huber, Gregory A. and Gordon, Sanford C. 2004), or appointment by the political branches (Guarnieri, Carlo and Pederzoli, Patrizia 2002, pg. 76). By extension, from the judicial types of individual judges, courts at all levels take on a political nature in that they are generally responsive, politically aware, and politically sensitive to the public and elite support necessary to keep their policy making power (Peretti, Terri Jennings 1999, pg. 183). The role of judicial policy making in a democratic system of separated powers is the focus of much attention (especially the Supreme Court) by both political scientists (DiIulio, John J 1990; Segal, Jeffrey A. and Spaeth, Harold J. 1993; Freeley, Malcolm M. and Rubin, Edward L. 1998; Pickerill, J. Mitchell and Clayton, Cornell W. 2004) and legal scholars (Epstein, Lee 1985; Schultz, David A. 1998; Murphy, Walter, Pritchett, Herman C. et al. 2002), but will not serve as a framework for this study. Instead, the judges in RCPs will be treated as a key policymaker and implementation manager apart from their judicial role, but connections will be made between their policy and judicial roles as they are developed in the context of the study. Judges traditionally have had little role beyond the trial and sentencing phase of the criminal justice system, with the only exceptions being probation or parole violation hearings. Reentry courts, on the other hand, place the judge at the center of the reintegration process by giving him/her the authority to immediately apply either graduated sanctions to noncompliant offenders, or positive reinforcement to those who successfully move toward the program’s goal. The judge’s vital location and authority is also conducive to directing the application of community (state and nonstate) resources to better facilitate an offender’s reentry into society, while promoting the development of positive behavior in the offender (USDOJ 1999). In this general therapeutic sense, reentry courts trace their lineage to the successful implementation of drug courts that focus exclusively on bringing court supervised treatment programs to drug addicted offenders
61 (Terry, W. Clinton III 1999). The key difference with RCPs is, however, that a general offender population is being supervised and not just specific types of offenders. The Role of the Courts Until the advent of problem solving courts, offender reentry and supervision had been the role of state executive parole board authorities. As offenders near the end of their terms of confinement, they are screened to determine readiness for transition. While still in prison, they are linked by a parole officer to family members, potential employers, and social workers on the outside in order to facilitate transition. In this system, offenders who do not live up to the terms of their parole are sent back to prison, many for technical violations of the terms of parole, including failure to meet with a parole officer at scheduled times. This system, although still effective when given adequate resources (Burke, Peggy B 1995), has suffered from overload of parole eligible cases. Conversely, there is a growing number of released offenders who lack any supervision whatsoever when released. Determinate sentencing initiatives, where offenders “max out” there sentences while in prison and are released with no parole requirement, account for 22% of released offenders (USDOJ 1999). Given the high failure rate for parole supervision during the 1990s that saw parole violators constitute 35% of all state prison admissions by the end of the decade (USDOJ 1999; Travis, Jeremy 2000; Petersilia, Joan 2001), a search for a new philosophy in problem solving based on state and nonstate partnerships for prisoner reentry began to take practical form. As they developed, the various problem solving court venues shared some common characteristics (Berman, Greg and Feinblatt, John 2001): • Seek tangible outcomes for victims, offenders and society (restorative justice), • Seek to re-engineer how government systems respond to social problems, • Rely on the active use of judicial authority to change offender behavior and solve problems, • Utilize a collaborative approach using government (state) and nonprofit (nonstate) partners to achieve program goals, • Alter the traditional dynamic of adversarial proceedings in order to foster cooperation and tailor individual offender reentry objectives.
Fundamentally, problem solving courts are an attempt to be more systematic in the handling of offenders’ reentry into society while reducing recidivism rates, parole and probation violation caseloads, and general court caseloads in the long term. The
62 individual offender is the focus of attention in this schema, and the eventual measure of success is based on completion of an individually prepared and judge supervised reentry plan that incorporates therapeutic treatment by the executive, judicial, and community partners. The Role of the Community Translating the circumstances of the parole system in context locally, communities have determined that parolees constitute a substantial risk to public safety, and accept that many are likely to be sent back to prison for violating parole terms. The local community is where the idea of reentry court partnerships has gained its foothold, and has looked to judges at the local level to become more active stakeholders in the offender reentry process. Offenders almost always return to the communities from which they first entered the criminal justice system. Whether this return is on a divergence program instead of confinement, or post release from prison, the offender must still live and function in the community among family members, treatment providers, employers and law enforcement agencies. In large measure, the extent to which the offender will be successful in reentering society will rest in the treatment assistance available for family support services, job placement assistance, and other nonprofit community resources (Seiter, Richard P. 2001). In 1980, there were fewer than 170,000 prisoners released back into society annually, but today nearly 600,000 offenders are released from prison each year (Travis, Jeremy 2000) into communities that are experiencing tightening budgets and specialized employment markets. Add to this the social stigma and legal limitations placed on convicted offenders in both private and public employment (Petersilia, Joan 2000), and the need of nearly three quarters of reentering offenders for drug and alcohol treatment (Beck, Allen J. 2000), the ethical argument for direct advocacy on behalf of this relatively powerless group has taken root in many jurisdictions (Jansson, Bruce S. 2003). The long-term negative economic effects to ex-offenders’ income and employment possibilities, the restricted exercise of civic liberties associated with voting and holding public office, limitations on receiving certain types of public assistance, and the damaging effects to family life are largely absent from public scrutiny (Tonry, Michael and Petersilia, Joan 1999). This effect is counter to the ideal situation in a civil society where all citizens should be put in “a position to manage their own affairs and to
63 take part in social cooperation on a footing of mutual respect under appropriately equal conditions” (Rawls, John 1999 p. xv). Tied to the advocacy concept for the offender is that reentry services should also take into account advocacy for crime victims (restorative justice), while enforcing the offender’s sense of responsibility to his or her community at large (Lehman, Joseph, Beatty, Trudy Gregory et al. 2002). If the criminal justice system is to improve public safety through the delivery of justice to the community, it becomes a matter of economy in effort and resources to ensure as few offenders as possible re-offend and reenter the criminal justice system. Local government and nonstate actors in RCPs are democratically working to improve levels of public safety (prevent a negative market externality) by searching for social equity through a new bureaucratic (specialized) organization (Frederickson, H. George 1971/1997). Job placement and housing assistance are prescriptive program objectives being used to head off some of the socially generated problems from prisoners reentering society. This is a simple pragmatic approach that does not yet consider the theoretical foundations of therapeutic jurisprudence or restorative justice, but begins to address the underlying social problems of offenders. Public Policy Implementation Research & RCPs Whether or not legal experts believe in the efficacy, or approve of the theoretical foundations of restorative or therapeutic jurisprudence as applied in RCPs, the partnerships have become in practice an area of interest within the field of criminal justice, and now political science. RCPs are especially interesting for public administration and policy implementation research because they are a democratic local initiative that has gained the support of national government (Travis, Jeremy 1995; USDOJ 1999; 2000; 2001; 2002) as they seek a better way to deliver justice. In so doing, they have crossed traditional separation of powers and federalism boundaries in government operation and organization, and are planned, organized and implemented by the very practitioners that administer them daily. The challenge now for these practitioners at the local government level is to win support for them at the state level.52
52 Indiana has enacted legislation that encourages the formation of RCPs through community corrections; Indiana Code (IC) 11-12-2, “State Grants to Counties for Community Corrections and Charges to Participating Counties for Confined Offenders;” IC 11-12-10, “Community Transition Programs;” IC 35- 38-2.5, Home Detention;” and IC 35-38-2.6, “Direct Placement in Community Corrections Programs.” The
64 In order to build a foundation of resources for continued operation under a unified state authority, the reentry courts must convince state legislatures that their various component pieces and core judicial elements can most efficiently and effectively be managed through administrative consolidation. The importance to policy implementation studies in examining RCPs is found in analyzing the implementation processes of this new approach to reentry policy. With a foundation that provides a clear measure of how the actors and their decision making outputs have formed and developed program guidelines, objectives, and operations, long term study can subsequently better analyze and compare initial outputs to the final program outcomes. Focusing on decision outputs will be a needed contrast to much of the developed body of policy implementation literature that has largely been concerned with post facto analysis of policy implementation outcomes. In fact, implementation research has largely favored descriptive, static, and anecdotal accounts of administrative outcomes with little in the way of theoretical foundations (Lynn, Laurence E. Jr. 1993). A survey of implementation literature reveals a common assumption that all public policies are intrinsically equal in nature and are assumed to have a shared a priori meaning among policy authors, implementers, and their managers (Hill, Heather C. 2003). While much can be learned in retrospect about implementation outcomes in these post facto analyses, greater attention is needed for the early research of new approaches in substantive policy implementation. Framed within the developed literature of policy implementation, this study seeks to measure and analyze decision making by actors in the process of policy implementation. This will be accomplished largely through observing, interviewing and surveying the implementers themselves while focusing on discretion and utilization of resources in decision making. This examination has an additional practical value to the implementation of future court partnerships. With early process comparison and analysis, future policy implementation failures may be reduced, chances for successful policy implementation improved, policy deflection minimized, and likely candidates to set policy agendas and advocate in other jurisdictions predicted.
OH RCP is working informally through the Ohio State Supreme Court to encourage similar enabling legislation in Ohio.
65 The Richland County, Ohio Reentry Court Partnership The idea of helping prisoners reenter society through various programs is not new. The concept for using courts as a vehicle for reentry, however, was first proposed in 1999 as an initiative of the Department of Justice’s Office for Justice Programs. The proposal was to involve the courts not only in the front end of the criminal justice process (criminal trial and sentencing), but utilize the case experience and expertise of the judge and court administrators to promote public safety and rehabilitation on the back end of the process as well (shock probation and post-release supervision). Whereas under the traditional operation of the judicial system the judge only sees a post-release offender in an adversarial setting for probation or parole violations, the reentry court concept seeks to redirect this paradigm to correct for a failing post-release supervision system. The key ingredient in redirecting this paradigm is involving the court as a therapeutic partner in the rehabilitation of the offender rather than adversary. This operational paradigm shift and therapeutic partnership brings to bear the significant political leverage of the court in the community to arrange for offender services and treatment. The court in this concept becomes the focus of positive efforts for prisoner reentry and rehabilitation by keeping the judges and administrators involved in monitoring and influencing offenders through the completion of post-release supervision. This is a fundamental change from a traditional process that divides supervision between judicial and executive authority and loses the continuity and expertise of the court in individual cases. This continued contact and involvement of the court from criminal trial and sentencing to the offenders return to the community is an administrative initiative for continuity and synergy of efforts designed to bring court and reentry services together under one authority. The goal of this unified effort is to rehabilitate the offender, realize administrative and societal resource savings through lower recidivism rates, and ultimately to increase public safety.
66 Ohio Reentry Court Concept Model53 In 2000, the Richland County, Ohio Common Pleas Court partnered with the Ohio Department of Rehabilitation and Corrections (ODRC), Office of Best Practices, to put together a reentry court concept paper for submission to the Department of Justice, Office of Justice Programs. Their concept paper outlined plans for an operational authority and power sharing model for supervision of offenders returning from the state prison system to Richland County. The model considered the utility of leveraging the case expertise and leadership of officials already established in the court, combined with the state parole authority knowledge of the offender developed during the confinement period. This collaborative planning effort resulted in a concept model intended to integrate components from both the judicial and executive branches of government in Ohio for a reentry court that satisfied the legal separation between the two authorities. This is necessary because when looking at the process as a whole, it is apparent that the key actors in the model are the two people who share a unique relationship at both the front- end and back-end; the judge and the offender. Assessment and Planning Implementing an operational model was the next step needed to bring the reentry court to reality. The joint planning body identified the key legal and operational obstacles inhibiting offender reentry, and the working operational model developed in the summer of 2000 addressed the need for a shared and comprehensive assessment of offenders starting at sentencing. This assessment was combined with a strong commitment to reentry planning well before an offender is released and begins reentry. This is an acknowledgement that assessment is an important first step for the overall continuity of the RCP process, and that a thorough initial profile assessment of the offender is needed at sentencing. This assessment must also anticipate a treated offender returning to the community under supervision after release. Administratively, it is necessary for the judge to refer the offender to the court coordinator for assessment based on either the term of sentence mandated by law (such as for gun crimes), or on his discretionary sentencing
53 Information for this and the next section developed from on-site observation, interviews, and notes taken at a presentation by the Richland County, Ohio Reentry Court at the Annual Training Institute of the American Probation and Parole Association; Cleveland, Ohio, August 26, 2003.
67 authority (providing for judicial early release or shock probation) based on the crime and knowledge of the offender’s prior record. The RCP court coordinator then works with ODRC representatives in the first thirty days of confinement to evaluate the offender using a standardized psychological assessment tool.54 A standardized offender risk assessment tool is also used prior to release to inform and help direct their reentry accountability plan (RAP).55 This assessment gives the RCP coordinator a standard indication of the expected risk level (low, medium, or high)56 in working with the offender and their treatment and supervision needs. This coordinated effort between the court and ODRC is an efficiency of efforts and resources that eliminates duplicate assessments by both the judicial and executive authorities in the process. This combined assessment tool is the best initial source of information about the offender, and is an administrative improvement by the court over relying completely on the police investigation report, or the offender’s criminal defense attorney to provide detailed information about the offender to the court or ODRC. Once the offender is in the custody of ODRC, the RCP coordinator is in routine contact with ODRC case managers, prison wardens of participating institutions, and prison unit (cellblock) supervisors to track the offender and ensure participation in treatment and rehabilitation (such as completing drug treatment or working toward a General Education Diploma; GED). This inter-organizational coordination is necessary to ensure the offender is being prepared sufficiently for early release. Without the possibility of early release, there is no possibility for the offender to participate in the RCP because they lack the “tail” necessary for time under supervision that is central to
54 As it applies to reentry cases, an assessment of seven dynamic needs areas (domains) is conducted on offenders and is designed to determine appropriate programs or interventions to effect change in the offender’s behavior. These dynamic needs areas (domains) include employment, marital and family, associates and social interaction, substance abuse, community functioning, personal and emotional orientation, and attitude (ODRC 2003, p. 2). 55 This assessment is conducted on all offenders to measure their risk of re-offending. The assessment is based on six static risk factors which include: prior convictions, prior commitments, recent commitment free period, prior probation/parole revocation, older offender status, and probation, parole, confinement, or escape status (DRC Form #3153). Additionally, special conditions may be imposed by the court, by the parole board or by the parole supervision section of the APA pursuant to policy. A consultation among actors involved in RCP offender post-release supervision to document and exchange information is also accomplished with the intent of making decisions, and following a course of action that will help facilitate the supervision of an offender and protect the community (Ibid, p. 2). 56 According to the Richland County Reentry Court Coordinator, most RCP offenders are assessed as high risk.
68 the RCP program.57 Offenders are still expected to “earn their way out” of confinement through good behavior, and all Richland County inmates are informed of this expectation up front by the RCP court coordinator and ODRC counselors. Merging Parole and Probation Supervision Planners set out to alter their reliance on a divided prisoner reentry process that is split among probation and parole authorities in the first year after release. This division of resources causes a short term focus on addressing only the immediate (violation) problems of the offender, usually in the form of a probation or parole violation hearing before the judge. In the first year of post-release supervision, many offenders fail reentry because they don’t get the intensive short term focused services they need to address the immediate problems of housing, education, and employment. If the offender cannot make it through the first year of post release, then the long term focused treatments and assistance programs do not pay dividends to the offender or the community.58 The RCP idea is to put all these resources (judicial and executive) at the discretion of the judge in the first year after release in order to transform probation and parole services from a short term law enforcement focused program to a holistic rehabilitation program.59 This
57 A “tail” is defined as a period of legal post-release supervision by the state or the county. In order to ensure that an offender has a “tail” and is therefore eligible for participation in the RCP, it is important that offenders are classified at the time of sentencing, or early during the period of incarceration. RCP participants may enter the program from either the county, through a split sentence or judicial release by the sentencing judge, or from the state Adult Parole Authority (APA), through post-release control or parole (only those sentenced prior to a 1996 truth-in-sentencing law; Senate Bill 2). Offenders entering the program from the county are identified on the “front end” (prior to sentencing) and receive treatment and monitoring in prison throughout their incarceration. Offenders entering the program from the state are identified on the “back end” (during incarceration) and are identified by an institutional parole officer and assessed by the RCP program coordinator prior to release. Currently, RCP participation by all offenders returning to Richland County is mandatory for all except sex offenders refusing treatment, or those with severe mental illness (Lindquist, Christine, Jennifer Hardison, et al. 2003, p. 30). 58 Because program participants may be under the authority of either the executive branch (state parole) or the judicial branch (county probation), the RCP program utilizes both probation and parole officers to supervise participants. The judge and an APA board member jointly preside over hearings. During the year- long program, participants appear in court an average of once per month, unless they are excused from appearing because of good behavior. Services available to program participants include mental health treatment, health care, substance abuse treatment (including residential treatment), domestic violence counseling, sex offender treatment, employment assistance/vocational training, education assistance, housing assistance, and faith-based community sponsorship (Ibid, p. 30). 59 The Ohio APA issued an official policy memorandum in July, 2003 dealing with reentry supervision and identifying procedures to be used by APA staff when supervising offenders designated as reentry cases. The memorandum established Community Reentry Management teams in each APA region. The mandatory representatives on the team are the supervising parole officer, offender services network staff, and volunteer services providers. Recommended team members include community linkage partners, family members of offenders, community based offender support groups, institutional staff, victim
69 transformation is intended to pay dividends in the long term with lower offender recidivism rates, increased public safety, and resource savings. Developing Shared Standards Developing a shared set of offender classification and supervision standards for RCP cases for use by the ODRC, the State Parole Board Authority, and the Richland County Court Services Adult Probation Department was an important consideration. This set of shared offender assessment and supervision standards for RCP cases necessarily departs from the traditional approaches to offender classification and supervision standards for the three authorities involved. These standards are the guidelines by which each authority determines the risk level and treatment programs for offenders.60 The legal as well as practical necessity of a new approach to standardizing supervision expectations is exacerbated by Ohio’s bifurcation of criminal sentencing and supervision. Ohio operates under two sentencing codes because of the passage in July 1996 of Senate Bill 2.61 This Bill, also known as a “truth in sentencing” approach to criminal incarceration,
advocates, and representatives from the faith community (ODRC 2003, p. 3). These teams have the primary responsibility for developing and/or monitoring the offender’s Reentry Accountability Plan (RAP). RAP is an individualized plan designed to identify and target the offender’s risk and needs areas through appropriate programming. The development and monitoring of the RAP begins at reception and continues throughout the term of incarceration, including any period of community supervision that follows. If the offender is under more than one type of supervision, the RAP may be utilized in both cases (ODRC 2003, p. 6). 60 Five probation and four parole officers maintain partial RCP caseloads. The probation-based Intense Supervision Program (ISP) is used as the model for all RCP cases. ISP has three phases that are flexible in length (depending on progress), and distinguished primarily by reporting frequency. Phase 1 (up to 4 months) requires 8 contacts a month; Phase 2 (up to 3 months in length) involves 6 contacts a month; Phase 3 (remainder of program) is 3 contacts a month. Contacts with officers include office, home, and work visits and are not limited to the stated number. Depending on the case, contacts could occur as many as 15 to 20 times a month. All parole and probation officers have personal electronic devices (Palm Pilots) with information on all RCP participants and can share information and contacts. All offenders are on electronic monitoring, have curfews, and are expected to abide by ISP conditions (limited and monitored contacts, no bars, no alcohol, no communication devices—cell phones, pagers, scanners, etc.—no cohabitation or marriage without permission). Drug testing is conducted on a regular basis with frequency dependent on the individual case (Lindquist, Christine, Jennifer Hardison, et al. 2003, p. 32). 61 Effective July 1, 1996, Ohio’s senate Bill 2, or “truth in sentencing” legislation changed the way post- release supervision is conducted. Offenders convicted prior to July 1, 1996 will continue to be reviewed on all indeterminate sentences for the propriety of release to the community. Most offenders who commit crimes after July 1, 1996, will be released at the end of their determinate sentences (APA 1996). The most common exception to Senate Bill 2 is “judicial release” which allows a judge to send someone to prison as punishment and then after a period of time order the prisoner's release under community controls imposed and monitored by the local court. “Community control” is a more accurate description than "probation" since it encompasses traditional probation as well as other residential, nonresidential, and financial penalties. Judicial release requires a public hearing with input from victims and others directly involved in the case. Otherwise, Senate Bill 2 virtually eliminates prison officials' ability to release offenders early. The
70 replaces discretionary parole board authority for early release possible under the old indeterminate sentencing scheme with new mandatory terms and parole guidelines based on a determinate sentencing approach.62 The sentencing scheme under Senate Bill 2 provides that offenders are incarcerated for a fixed period of time and then released to the community, usually with little or no parole supervision because the intent is for offenders to “max-out” their full sentences in confinement. In order to ensure that offenders “have a tail” and can be supervised as an RCP case, judges must allow for the possibility of early release, or shock probation, during sentencing. The approval and cooperation of state prison wardens has been critical in the successful coordination and implementation of a shared assessment and supervision standard in RCP cases. When starting the program in November of 2000, there were waiting lists for ODRC institutional treatment programs. The immediate access to treatment given to RCP participants by the wardens was crucial in allowing the program to get off the ground. ODRC cooperation allows the RCP coordinator to personally work with institution case managers and to receive bi-monthly reports on RCP offender progress. This has helped on both sides to synchronize program assessment, supervision and treatment programs, and ensure that no offender comes out of the institution on early release without the maximum amount of information available in the possession of the RCP coordinator. For the benefit of the offender and for the safety of the community, no offender is released early unless they have received the treatment deemed necessary at their initial, as well as in their in-progress assessments. The RCP coordinator also uses
bill abolished parole releases for most crimes and eliminated the practice of giving "good time" reductions for time served. In theory, truthful sentencing required a shift in control from unelected (parole) administrators, who make decisions in private at the prisons, back to elected judges who impose the true sentence (or modify it) in open hearings (OSBA 2005). 62 The Ohio “Parole Guidelines Chart” sets forth the applicable guideline range (in total months to be served before release, including jail time) based on the seriousness of the offender’s current offense and the offender’s criminal history/risk score. The applicable guideline range presumes good institutional conduct, fulfillment of any special conditions imposed by the APA, and the development of a suitable release plan. The Parole Board may depart from the guidelines (either upward or downward) for good cause (not the same as “good time”) upon the provision of specific written reasons. Offense categories range from a low of 1 to a high of 13. Aggravated murder carries an offense category of 13 while vehicular homicide falls under category 7. The risk score is determined by adding points for prior convictions, recent convictions (within three years of the current offense), whether the offender was on parole, probation or escape status at the time of the offense, any history of parole revocation (for violating parole), and age at the time of offense. The applicable guideline range does not supersede any minimum or maximum sentence applicable to the offender (ODRC 2000).
71 this detailed information on the offender to secure approval from the prosecutor and various victim services providers prior to requesting an early release to the RCP program.63 This type of cooperation and intervention by the RCP coordinator and ODRC case officers is an example of how the RCP model transcends the traditional approach to divided offender supervision and rehabilitation. Institutionalizing a Shared Sense of Ownership Planners desired a shared sense of ownership among RCP partners for the offenders sentenced from, and then returning to the community. The RCP, by design, deals particularly with the offenders leaving from and returning to the community (county).64 In order for coordination between the county court and the state prisons to be established and stabilized, ODRC had to accommodate acceptance of offenders from Richland County into a cluster of five selected prisons.65 This accommodation was accomplished through the classification and reception offices at the participating institutions. The selection and clustering of particular prisons provides a geographic as well as an administrative coordination efficiency that allows for ownership of supervision and treatment beginning immediately at sentencing and maintained throughout offender incarceration by both the institution and the RCP liaison (court coordinator). By the time an offender is released from the state institution, a sense of joint ownership between the court and the executive authority is already established. A
63 Senate Bill 2 (1996) also helped to transform the criminal justice system into the “victim's justice system.” Senate Bill 2 mandates that victims have input from the time of an arrest through trial and sentencing, incarceration, and for any type of early release. Senate Bill 2 also formally created the Office of Victim Services within ODRC (ODRC 2003). This Bill also helped to redirect monies from the state budget to community run programs in order to prevent low risk offenders from going to prison, and encourage treatment by the community and supervision by community corrections (APPA 2003). 64 The Richland County RCP decided in its operation plan not to “cherry pick” only low risk offenders for the program, but accepts most everyone sentenced from and returning to the county. Whether offenders are released by the APA as a discretionary parole release, regular parole case, or come out automatically as a post release control supervision case, they will be coming through the RCP. Offenders cannot avoid the RCP by “maxing out” their sentences. They all will have supervised time of some sort in order to participate in the RCP program in accordance with the agreement between Richland County and the APA. The explicit as well as implicit incentive to the offender is that their rewards and release from the program is performance based. The better they progress in their treatment while in ODRC custody and then outside in the RCP program, the quicker they will be released from parole or probation supervision altogether. This gives the offender a certain amount of control over their destiny (APPA 2003). 65 The Richland County RCP has an agreement with ODRC to incarcerate its offenders as close to “home” as possible considering their security classification at intake. The five institutions are; Mansfield Correctional Institution, and the Richland Correctional Institution (both located in Richland County), the North Central Correctional Institution and Marion Correctional Institution (both located in Marion, Ohio), and the Ohio Reformatory for Women located in Marysville, Ohio (Spelman, Jeffrey B. 2003, p. 52).
72 continuation of the joint ownership concept is manifested in the courtroom after the offender is released to post-release supervision. At the RCP courtroom hearings, both judicial and executive branch representative sit behind the bench to share the responsibility for the offender’s progress, and the authority to sanction recalcitrance as necessary.66 This cooperation and decision making agreement is largely accomplished in RCP court pre-meetings where the details of the individual offenders’ case is discussed at length.67 This physical representation in the courtroom, and the face-to-face cooperation of the two authorities in the decision making process is a unique aspect of using the court as a reentry mechanism.68 Ohio Reentry Court Program Elements Objectives The cooperative legal authorities and their respective representatives convene monthly as the RCP in order to encourage the basic objectives of the reentry court: Monitor offender progress Reinforce and praise offender good behavior
66 Overall, there is judicial hesitancy in other states and counties in Ohio to participate in a RCP program because of the lack of clear and explicit statutory criminal code that positively provides for judges to take this role. Richland county judges are taking political, personal and legal risks as innovators in this area. For some judges, “…if the statute doesn’t say they can’t, they will, but all other judges [in Ohio] so far say unless the statute says we can, we won’t” (APPA 2003). In order to try to rectify this situation and encourage other jurisdictions in Ohio to establish RCP programs, the Criminal Sentencing Commission is discussing the framework of a statute that will positively say that Ohio judges can participate if they choose. The proposed statute will authorize RCP Programs where courts agree to enter into an agreement with the ODRC and work out through the provision of the law shared understandings that will reflect in time the principles that drive the Richland County RCP program (APPA 2003). Additional judicial hurdles in establishing new RCP programs is that they do create extra work for judges, and the sense of judicial conservatism and reluctance to depart from established practices must also be overcome. 67 Participants in the RCP pre-meetings include the presiding judge, a representative from the state parole board, the court coordinator, a community law enforcement officer, and all the probation and parole officers that supervise RCP participants appearing in court that day. Each offender on the docket for the day is discussed regarding progress or problems. Each supervising probation and parole officer is asked to give an account of their contacts with the offender since the last RCP hearing, and recommend reward or sanction. The court coordinator reports on treatment progress, and any information provided by community partners working with offender. The judge and the state parole board member mutually agree to a course of action in each offender’s case, but the authoritative decision is left to the legal controlling authority - determined by whether the offender is under executive or judicial control. 68 All Richland County, Ohio RCP cases are split between two county Common Pleas Court judges. Program participants appear before the same judge throughout the duration of the program, usually their sentencing judge. Both the judge and an APA board member jointly preside over the monthly status hearings (since the judge does not have jurisdiction over parole cases). Also in attendance are the parole and probation officers, the reentry court coordinator, and a local law enforcement official. During the open courtroom hearing, the judge and APA board member talk with each participant, ask questions, provide verbal praise, and if necessary, impose/uphold sanctions (Lindquist, Christine, Jennifer Hardison, et al. 2003, p.32).
73 Apply sanctions to offender supervision violations Incentivise and encourage the offender’s progress and completion of the program
The standard philosophy from both the judicial and executive representatives of the RCP is that rewards and incentives work better than sanctions to influence behavior and encourage success. 69 RCP partners desire to institutionalize incentives for positive behavior and believe that judges should be the focus in the joint ownership of offender reentry as the coordinator of these incentives to the offender (employment services, housing assistance, and treatment programs). With an emphasis on rewards over sanctions, the RCP itself becomes a microcosm and example for the modeling of pro-social behavior from the bench by both the state executive and county judicial representatives. The court setting is of critical importance to the RCP model because it serves as the focal point for the continuity of offender supervision from sentencing, through incarceration and post-release supervision, to completion and release from the program.70 The court, the community, and the judge – along with the offender – are held constant in order to create a stable foundation upon which a reentry framework is built.71 The courtroom in essence becomes the meeting
69 Sanctions used in the program are graduated and include increased levels of drug testing, supervision contacts, court appearances and treatment sessions. Other sanctions include fines, community service, short-term incarceration in jail, bond revocation, house arrest, written or verbal reprimand, placement in out-patient treatment programs, or commitment to community residential facility (Spelman, Jeffrey B. 2003, p. 44). Incentives and rewards include reducing the frequency of court appearances and probation contacts, extending curfew, less frequent drug testing, special passes for out-of-county or state travel, restored driving privileges, dismissal of charges, verbal praise, and when appropriate, phasing the offender out of treatment (Lindquist, Christine, Jennifer Hardison, et al., 2003, p. 32; Spelman, Jeffrey B. 2003, p.45). 70 Partners in the RCP believe that a model for prisoner reentry must use the court and the judge as a focal point to encourage the effectiveness and success of the program. Partners believe this based on every offender sentenced to prison knowing the judge that sentenced them, and knowing that when they are released that they will have to face that same judge every month at RCP courtroom hearings. They also know that the judge (or the state parole board member) has the power to send them back to prison. Using the court format, the RCP judge will hear about their behavior for that month and is expected to be more likely to pay attention to what their probation/parole officer asks them to do knowing that the probation/parole officer does not have the direct authority and influence to sanction as does the judge (APPA 2003). 71 The judge uniquely represents the community as the only elected official in the midst of the reentry program. As an elected official, the judge has the political influence to gain access to more treatment programs designed to help offenders reenter society, and can get offenders into programs that are backlogged. Judges also provide the sort of accountability and authority figure within the special docket (RCP) court context that is needed to incentivise the positive decision making behavior desired of the supervised offender by holding them personally accountable and responsible for their actions (Ibid).
74 place for surrogate parents to deal with offenders who are either under probation or parole supervision.72 At the hearings, offenders are praised or scolded from the bench in an effort to instill self-ownership for successful reentry. The RCP hearings are also used as formal settings to recognize offenders graduating from the program (usually 12 months of satisfactory progress) and symbolically beginning a new life as a rehabilitated citizen of the community. Community Partners and Treatment A final component in the operational model for the Ohio RCP is the role in treatment provided by community partners.73 These partners play a vital role in reentry because they directly address and help correct the shared adverse characteristics of most every returning offender: Unskilled Unemployed Untreated, or not complete in their treatment, for drug/alcohol/mental health, or anger issues No housing Not used to self government Easily manipulated Return to their old associates and quickly return to crime.
Regardless of the type of old or new crime that offenders’ commit, it is a local crime and a community problem. It therefore makes sense for communities to commit resources to help this cohort of citizens for their own, as well as the community’s benefit.74 Committing these resources of time, effort and money only makes sense if they are applied according to a logical model, and with the intent to produce measurable results.
72 This concept is particularly important because it sets expectations for success and enforces them, while providing the help needed to achieve success. In essence, the RCP hearings take the place of the two parent family – “the greatest crime fighting institution ever created” - that most offenders lack (Ibid). Judges become in effect, symbolically, the surrogate parents of the reentry offenders. Following this logic to its conclusion, the resultant prediction is that reentry courts are potentially the most successful reentry programs because they most closely resemble the best crime fighting model – the two parent family. 73 There are currently (2005) eight community treatment providers working with the Richland County, Ohio RCP. Four out-patient treatment providers are located locally in Mansfield, Ohio (County seat), and four other resident treatment providers are located in Tiffin, Newark, Akron, and Dayton, Ohio respectively. 74 For this and other reasons, the designed length of the RCP program is 12 months in order to help get the offender through the first year of post-release. The first year of post-release is the time of greatest risk of re-offending and re-arrest, so it is a conscious decision at an economy of efforts in this period to make the best use of available resources.
75 Judges, administrators, and community partners will only willingly commit the resources necessary to operate RCPs if they first believe, and then realize, positive results such as: Lower substance abuse rates Higher employment rates, and most importantly, Lower recidivism and repeat crime rates.
Offender treatment should be local if possible to familiarize the offender with the resources that are in the local community (halfway houses, etc.). An added benefit of local treatment is in getting the family involved as much as possible in order to get the thought process and decision making actions of the offender and his family synchronized. Local treatment also encourages family members to gain contact with offenders before release, and then accompany them to treatment and the RCP hearings. This process is beneficial in establishing, or reestablishing, positive family involvement and relations in treatment and reentry. Local churches are also actively involved in sponsoring and mentoring offenders in the program. The judges involved in the Ohio RCP “know” that offenders are much more likely to have a change of heart if there is a religious component involved. “I have seen it over and over again in people I thought were beyond hope” (2003). The RCP operational model also has the benefit of encouraging offenders to associate with “winners” as much as possible because the greatest predictor of whether or not an offender will make it on the outside is the people that they associate with. “The best sources of winners are those associated with the church because they are always encouraging and offering to help the offender” (2003). The Allen County, Indiana Reentry Court Partnership75 Indiana Reentry Court Concept Model The Allen County, Indiana RCP developed concurrently but independently from the Department of Justice, Office of Justice Programs’ 1999 initiative. In the same year, the Indiana state legislature passed statutory law enabling counties in Indiana to develop
75 Information developed from on-site observation, interviews, the unpublished “Reentry Court Project Summary” prepared by Reentry Court Director, Stan Pflueger (2001), and the Allen County RCP “Standards and Operations Manual” (2005).
76 local Community Transitions Programs.76 The legislation defined which prisoners in the state corrections system are eligible for early release to community supervision.77 Offenders released before completing their full sentences come under the control of their respective Community Corrections (CC) authority.78 This authority allows for an offender to be released up to 180 days prior to completing the term of confinement, and creates the window of parole supervision authority necessary for the RCP and other transition programs to legally be administered. Allen County Community Corrections (ACCC) is still the only county in the state with CC authority that has instituted a RCP program model.79 Community Corrections Using the CC authority established in 1999, Allen County began to directly address high recidivism rates among offenders returning to Fort Wayne, Indiana (Allen
76 The Allen County, Indiana Reentry Court Project is not defined by one specific statute. Authority for the Court’s operation is drawn from interrelated Indiana sentencing laws. The foundation for the RCP centers on alternative sentencing guidelines defined by the community corrections statute, Indiana Code (IC) 11- 12-1 (Surbeck, Hon. John F. Jr. and Sheila Hudson 2005, p.1). Additional sources of legal authorization come from Indiana Code (IC) 11-10-11.5, “Community Transition Statute,” (ACCC 2005) which addresses eligibility rules for the early release of offenders sentenced to a minimum two year prison term; IC 11-12-2, “State Grants to Counties for Community Corrections and Charges to Participating Counties for Confined Offenders;” IC 11-12-10, “Community Transition Programs;” IC 35-38-2.5, Home Detention;” and IC 35- 38-2.6, “Direct Placement in Community Corrections Programs” which is used as an alternative to prison for one year or less if a sentence cannot be suspended. The Richland County, Ohio RCP is working informally with the Ohio State Supreme Court to encourage similar enabling legislation in Ohio. 77 This initial legislation excluded certain serious offenses from consideration from early release, such as murder and attempted murder. A change to the statute in 2004 made individuals incarcerated for murder eligible for early release. All inmates returning from the Indiana Department of Correction with a minimum of sixty-one days early release from prison are now assigned to the Allen County RCP. All others that do not have at least 61 days of early release from prison return under Community Corrections Control. At any given time, Allen County has approximately 500 offenders under supervision with about one-third (150) in various stages of the RCP program. 78 Sixty-seven of Indiana’s ninety-two counties have established community corrections authority. These counties have created the Indiana Association of Community Corrections Act Counties (IACCAC). The association, in collaboration with the Indiana Department of Correction, encourages development of a system of offender treatment and reintegration that serves local communities. System programs treat and supervise mentally ill offenders, provide reconciliation between victims and offenders, monitor offenders using electronic devices, provide accountability to the courts, and reduce the funding needed to run the state’s prisons (IACCAC 2005). Each CC authority also establishes a Community Corrections Advisory Board. The Allen County Advisory Board consists of the county commissioners, prosecutor, sheriff, a superior and circuit court judge, the Fort Wayne mayor and chief of police, a victim advocate, local business owner, pastor, and a defense attorney. 79 Marion County, Indiana (Indianapolis) is currently (2005) in the research and planning phase of establishing a RCP program using the Allen County model.
77 County seat).80 The reentry court model first developed was intended to operate within the 180 day early release maximum allowed under Indiana state law, and admit only offenders returning to the southeastern quadrant of Fort Wayne. Additionally, the RCP concept would rely heavily on existing resources available at the state and county level, along with nominal user fees charged to participating offenders.81 The model utilized in the start-up and fiscal administration of the RCP program is, and remains, a blend of public and private sector business philosophy. The executive director of ACCC has developed diverse funding sources and innovative operations to balance RCP program requirements with the administrative and operational mandates for CC under local, state and federal regulations. The funding mix for the average annual ACCC budget of nearly $4 million (of which the RCP is a component piece) is stable at 50% from offender user fees, 25% from state funds, and 25% from various federal grants.82 With fiscal as well as administrative obstacles fully in view, the decision to initiate the Allen County RCP program in June 2001 as a two-year pilot project was made pragmatically with the intent of later expanding to the entire city of Fort Wayne, and all of Allen County, if successful.83
80 The impetus for the beginning of the program was a joint meeting in early 2000 to discuss the high average recidivism rates (66% in the first year) of offenders returning to the southeastern quadrant of the city of Fort Wayne, Indiana. The meeting was attended by the city mayor, the executive director of Allen County Community Corrections (ACCC), an Allen County Superior Court judge, and a Fort Wayne native working for the Department of Justice. The original motivations for the meeting were a professional refusal to accept the high recidivism rates and the associated costs to society, an admission that the existing programs were not coordinated and were failing, and a desire to solve the problem before it became a political liability. An idea for a solution that involved coordinating the efforts of the state corrections and parole authority, county court and probation supervision, as well as city law enforcement and community corrections monitoring became the initial concept model for the Allen County Reentry Court. 81 The program helps to support itself through a $35 per day per diem paid by the Indiana Department of Corrections (IDC) for the first thirty days of early release, then $15 per day for the remainder of the early release time. This payment is a savings to the IDC of approximately $40 per day per early released offender averaged over the period of RCP supervision (IDC cost to supervise and house an offender daily is $59). The RCP also charges each early release offender under the program a $7 per day fee (initiated after the offender has been in the program for 60 days) to assist in paying for the cost of electronic monitoring during the supervision period. Unemployed offenders can work off a portion of their fees by performing community service. Fees are waived for indigent or disabled offenders. 82 Allen County Community Corrections maintains a full-time financial manager that is trained to write for state and federal grant monies. Even though ACCC is located in Fort Wayne and has political ties to the city, it gets no municipal funding. Most outside grant funding is generated because of the ability of ACCC to cluster programs like electronic monitoring and home detention together with the RCP program rather than requesting RCP specific funds. 83 Phase I of the project ran from July 1, 2001 to June 30, 2003. Preliminary initial success of the project during the first two years was sufficient to justify expansion of the project, and beginning July 1, 2003 parolees from all quadrants of the county were accepted to the project. This second phase of the project ran
78 Joint Monitoring and Supervision Administratively, the offenders released early to ACCC and the RCP remain under a similar bifurcated system of monitoring and supervision as in Ohio. During the period of early release, the offenders technically are under the dual supervision of the state parole authority and the ACCC authority. Allen County has instituted a verbal agreement with the Division of Parole Services and the Indiana Parole Board so that ACCC case managers supervise RCP offenders in lieu of a parole officer.84 The parole district supervisor does, however, attend reentry court sessions to answer any technical or legal questions concerning offender behavior, sanctions, or early release from supervision. The Allen County RCP currently (2005) uses three case managers who supervise an average of 150 RCP offenders under this dual supervision agreement. Once an offender has reached the earliest possible release date (EPRD) under their original prison sentence, they revert to the post-release supervision of a state parole officer if they have not served the maximum time of their sentence, or a county probation officer if they are under a split sentence that requires probation supervision after their served prison time. This system, even though legislation has given it legal sanction, is technically confusing and requires detailed coordination among the parole authority, case managers, and probation officers facilitated by the ACCC Transitions Coordinator and RCP Director.85 Indiana Reentry Court Program Elements The coordination process between ACCC and the Indiana Department of Correction (IDC) begins sixty days prior to an offender’s eligibility for early release.
for one year until June 30, 2004. The third (current) phase began July 1, 2004 and included split sentence cases (those cases that had probation supervision ordered after their prison time). Phase III also included selected cases referred by the Circuit Court. These cases are primarily comprised of felony drunk driving cases and other felony traffic offenses (Surbeck, Hon. John F. Jr. and Sheila Hudson 2005, p. 3). 84 In return for this agreement, ACCC provides several functions for the Division of Parole Services including conducting appointments with parolees, approving employment and residence changes, completing travel permits that are then signed by the Parole Supervisor, and providing release and violation summaries for the Division of Parole Services and Parole Board when participants successfully complete or are terminated from the RCP (Ibid, p. 13). 85 An information intensive staff coordination takes place weekly at the RCP pre-meeting attended by the 3 RCP case managers, 2 county probation officers, the state parole district supervisor, and either the RCP Director, or the ACCC Transitions Coordinator. In this meeting, each RCP offender file is “scrubbed” in order to track progress, to coordinate and agree on the recommendations to the judge in each case, and issue internal staff directives and administrative actions. Staff recommendations for each case are thoroughly discussed and documented for transmittal to the judge prior to the weekly RCP court session.
79 Unlike the Richland County, Ohio RCP program that requires participation by all returning offenders based on an agreement between the state Adult Parole Authority and the Richland County Probation Authority, Allen County offenders must positively accept enrollment into the ACCC and RCP as a separate but associated project under the Community Transitions Program. Offenders that deny enrollment into the RCP can either accept ACCC early release control and the supervision of state parole or county probation officers as required, or they can deny early release altogether and serve their entire term in prison.86 In order to incentivise the RCP program and encourage participation by returning offenders, those agreeing to RCP supervision enjoy fewer restrictions during the twelve month program, greater access to job training and placement services, and priority scheduling for program counseling and services as long as they fulfill RCP monitoring and progress expectations.87 Additionally, the presiding RCP judge can legally adjust (reduce) under CC authority the period of probation or parole supervision for offenders successfully completing the program. Risk Assessment and Reintegration Plan When RCP offenders arrive at ACCC, they meet with and are assigned a case manager who processes them into the program and explains in detail the expectations of the RCP.88 At the inprocessing, the participants are scheduled for forensic assessment to determine their treatment needs and risk level of re-offending. The forensic assessment
86 ACCC contacts early-release eligible offenders by mail, supplies written information about the CC and RCP program, and requires the offenders to either send a letter denying the program or complete an Information Release and Residence Information Form as notice that they are accepting program conditions (Surbeck, Hon. John F. Jr. and Sheila Hudson 2005, p. 5). If the offender denies early release to both ACCC and the RCP, they will serve their complete prison sentence and then be released directly to state parole supervision. The letter sent by ACCC notifying offenders of their eligibility for early release clearly states that everyone released to ACCC or RCP control will be subject to electronic monitoring for at least the period of early release (60-180 days). An additional requirement for all early release offenders is that they return to a residence with a working telephone due to the technical operation of the electronic monitoring devices placed on their wrist or ankle. 87 Programs and services available to RCP participants include faith-based mentoring, the Family Re- Connect Program, job placement and training, substance abuse counseling, sex offender counseling, victim- offender conferencing, GED classes, the Life After Incarceration program, emotions management, Choices Classes, and community service work. It is during inprocessing that offenders are evaluated to determine which of the programs and services are recommended. 88 Multiple items are covered at the offender’s inprocessing session. Topics discussed at orientation, along with accompanying forms for the offender to complete, include: job search policy and instructions, employer agreement and release of information document; determination of offender paid fees based on a worksheet of current wages earned and budget; dress code; weekly schedule form for work, community service, or job search plan; electronic monitoring regulations and pass policy; and offender pay procedures for fees, turning in work time cards, or employer check stubs.
80 includes an educational/intelligence assessment (Kaufman Brief Intelligence Test), a personality assessment, a clinical interview with a mental health therapist, an assessment for other risks including spousal abuse, substance abuse, sex offender and violence when warranted based on the current charge or past behavior (Surbeck, Hon. John F. Jr. and Hudson, Sheila 2005, p.5). Based on the needs identified during inprocessing, an individual Reintegration Plan (RP) is created for each participant.89 They then appear before the RCP judge within two weeks of inprocessing for their first hearing. Offenders normally are required to return to court monthly during the year-long program to face public accountability for their progress measured against their RP. Satisfactory progress is the most important condition of the participants’ continuation in the RCP program. Progress that is not considered satisfactory by the court meets with a graduated set of sanctions legally administered by the RCP judge. Job Academy A major obstacle that all returning offenders must overcome is gaining employment. From a personal success as well as compliance perspective in the RCP program, offenders must have a source of income in order to progress satisfactorily through and complete the program. ACCC sought to reduce this obstacle early in its program by establishing a thirty-hour training and job academy.90 The job academy was intended to be one component part of offender reentry in preparing offenders for transitional jobs, but an additional self sustaining and ACCC administered business
89 The RP is a simple one-page document that provides an overall recommendation for reintegration based on factors of: Supervision; details the type and frequency of offender monitoring, risk level as determined by the Level of Service Inventory (LSI-R) quantitative survey assessment, and required frequency of drug testing. Treatment; intensity and level of counseling administered by Allen County Community Corrections (ACCC), and community partner services. Education; the offender’s current level of education and plan to enroll or complete GED, or continuation of education with enrollment in community college classes. Other Programs/Services; areas such as job search assistance, assistance with obtaining a driver’s license, and community service obligations. 90 ACCC acknowledges that vocational and occupational training does not in itself reduce recidivism rates. The idea is to develop a “one stop delivery system” within its Community Transitions program. This concept was initially inspired by Welfare to Work programs beginning in 1998. With no external sources of funding, the ACCC job academy partnered with as many local and state nonprofit agencies as possible through written contracts of agreement. The focus of the job academy is to teach the “soft skills” needed for gaining and retaining employment rather than vocational or occupational training. The curriculum is centered on helping the offender build a positive self attitude, self esteem and motivational skills. The job academy also partners with a local community college (Ivy Tech) whose human resources personnel volunteer to conduct mock interviews with the reentering offenders. ACCC employment specialists work with offenders to first establish, and then facilitate a reentry job readiness plan.
81 venture to supplement the transitional workforce was in the concept phase early in the program. Realizing that government funding through state budgets and grants was an unreliable source for operating costs, the idea of the job academy was expanded to include the development and establishment of a social enterprise that is legally and administratively separated from ACCC. This example of social entrepreneurship created by ACCC is named Blue Jacket, Inc. (2005) and is intended to be a self contained nonprofit organization. The designer and first executive director of Blue Jacket resigned his position as the Employment and Training Director of ACCC in order to complete the legally separate but vitally connected partnership. Blue Jacket does contract business with local industry to provide the finishing and packaging services in demand in the local Fort Wayne economy. Blue Jacket is intended to provide transitional employment for the average of 20% of returning offenders that do not find employment on the local economy within three weeks of release.91 Community Partners Faith-based organizations have also been actively involved in the Allen County RCP since its inception. This involvement is focused in the areas of reconnecting families and providing positive role models as mentors and counselors. Several area pastors attend each RCP hearing and are willing as necessary to stand before the judge and be an advocate on behalf of an offender. Pastors may also be voluntarily assigned to offenders as the counselor of choice established in the offender’s RP. Combining the mentor and counselor role with the need to reestablish family units that have been broken by incarceration, the local faith-based community has designed a four-part program specifically designed for offenders participating in the Allen County RCP program.92 The
91 Similar to Blue Jacket, Inc., the desired result of the ACCC job academy is an offender placed in a transitional job with a local employer. A transitional job is defined as time-limited, publicly subsidized job that combines real work, skill development, and support services to help offenders overcome substantial barriers to employment. The public subsidy can be in the form of financial payment, or frequently in the form of supervisory assistance as practiced in CC and RCP programming. This supervisory aspect is an important incentive for local employers willing to offer a transitional job to a reentering offender. Subsequent permanent placement for the offender is aided by a network of local employers, ACCC and Blue Jacket support service specialists, and community partners (faith-based and treatment providers). 92 The Unity of Love Family Re-Connect Program provides compassionate assistance to offenders and their families. The program is designed to ease reentry and encourage the acceptance and support of the offender by his/her family. This program coordinates directly with the Allen County RCP to maximize the opportunity for a successful reentry by providing family counseling, parenting classes, family coaching to encourage harmony and goodwill, and family dinner workshops intended to build family values.
82 Faith-based community has also been instrumental in assisting RCP participants with housing. The Fort Wayne Rescue Mission provides long-term housing for individuals accepted into their residential substance abuse treatment program immediately after the offender completes the electronic monitoring portion of the RCP program. Four halfway houses in Fort Wayne that are faith-affiliated also provide housing and treatment programming for offenders returning to Fort Wayne and the RCP program (Surbeck, Hon. John F. Jr. and Hudson, Sheila 2005, p. 7). Conclusion This chapter has discussed the political, social and policy environment that gave rise to the idea of prisoner reentry programs hosted by the courts. In the context of rising costs, both in terms of dollars and failing parole supervision, the need for innovative policy and program designs laid the foundation for a shifting paradigm in helping prisoners reenter society. The question about whether to revitalize or replace parole supervision was transformed in certain jurisdictions into a partnership between branches of government and community partners. The political and administrative actors in the two cases discussed in this chapter came together at the grass roots level in order to effectively solve a problem that adversely impacted their communities. Institutional cultures, traditional practices, and legal obstacles were overcome in order to create and implement conceptual models designed to solve the problem at hand, not cater to established practices. New boundaries for intergovernmental and public-private partnerships were established using the guiding purposes and objectives of the derived prisoner reentry court model. In the next chapter, the values-based decision making approach that was foundational in creating the reentry court concept will be tested based on survey responses of actors directly involved in implementing the programs.
83 CHAPTER 4
REENTRY COURT PARTNERSHIPS EXAMINED: VALUES-BASED DECISION MAKING AS THE KEY TO UNDERSTANDING POLICY IMPLEMENATION
Introduction: “How are Reentry Courts Being Implemented?” The answer to the fundamental research question is discussed in this chapter. The answer is illustrated in the types of decisions each actor makes while implementing RCPs. The decisions made by actors in RCP implementation are simultaneously strategic and tactical, rational and normative, formal and informal, and influenced by internal and external considerations. In order to measure the decision outputs of the actors in the implementation process, the values-based research design and survey instrument developed in chapter 2 is used to capture RCP participants’ observations of this iterative process. The measure of these values-based variables are organized, presented, and compared in this chapter to illustrate the implementation decisions being made by key actors in each RCP. The key actors will be discussed in turn, and the qualitative foundation of field observation and interviews discussed in the previous chapter is used to inform the interpretation of the quantitative data collected in participant survey responses. The fundamental research question, “How are reentry court partnerships being implemented?” will be the point of orientation, and the types and categories of decisions will be the tool of explanation. The presentation of observation and survey data in this chapter aims to answer the research question by accomplishing two main objectives. First is to present the data in a way that is clear and systematic. To accomplish this first objective, the organization of the chapter focuses on each actor in turn by RCP jurisdiction. The actors in context are the focus of interest in this implementation process study, so the survey data is presented in this way to keep the jurisdictions distinct and avoid confusion. This manner of presentation helps to standardize survey response data by allowing the mean scores for each variable variety, type, category and division to be displayed first within the context of the respective RCP before being compared across jurisdictions.93 The second objective
93 Certain data set biases (positive skewness measures) are apparent in the survey responses for both RCP jurisdictions. The best comparison for the purpose of this study, and for reporting results to the respective RCPs themselves, is accomplished by separately presenting the data by jurisdiction before comparing it
84 is to validate the research design by showing that the survey data is robust internally, and that the results can be replicated. All data tables presented in this chapter are labeled with the SPSS variable nomenclature that corresponds to the survey instrument variables of interest. The data set is organized in such a way that others can easily replicate the reported results, refigure the data into new variables if desired, or add additional cases in the future from similar survey instruments for additional RCPs. It is also a consideration and intent of the research design that it be valid for transference to other examples of the bottom-up implementation process. This is desired because the premise of the design is that values-based decisions are fundamental and continuous in the iterative process of policy implementation. It is apparent in the remainder of this chapter that the answer to the research question varies by the type of actor under consideration. It will be shown in data presented that even though all actors rely most heavily on elements of discretion rather than resources when making implementation decisions, the types of decisions that they make varies according to actor and jurisdiction.94 Accountability to the community most influences judges’ decision making, but only as it is informed by personal and professional considerations. Administrators, on the other hand, tend to make decisions influenced by professional and procedural considerations. Community partners in the process are similar to judges in their types of decisions, but survey respondents’ rate judges significantly higher in agreement scores on most measured values. Decision making values are also presented in a way to compare judge’s decisions to that of the decisions of survey respondent’s own family members. Surprisingly, in many measures of decision making values, judges score equally as well or better than do family members.95 In order to highlight these examples and others, the survey response data for all actors is presented in table form. This allows for easy comparisons across categories, and enables the reader to follow the aggregation of data from the fundamental values, to varieties, to type, category and division.
across jurisdictions. This also helps to frame the data in a way that can better determine its internal robustness before converting to other standardized measures such as z scores in the future. 94 Numerous statistically significant differences across actor category by variable variety and RCP jurisdiction are discovered and presented 95 In measures such as conscientiousness, communication, fairness, openness, judgement, and responsiveness, judges scored equally as well, or significantly (statistically) higher in agreement than did the respondent’s rating of their own family members.
85 Key Actors: The Judges The single most important actor to the implementation of the RCP model is the judge. The judge is crucial in a psychological as well as an operational sense. Psychologically, every offender who goes to prison knows and remembers their sentencing judge. When this familiarity is utilized for the purpose of promoting successful offender reentry after prison, the idea is that the judge applies his unique position and knowledge to encourage consistent and positive behavior in the offender. This central focus on the judge also helps to encourage consistent and intensive supervision and treatment of the offender by administrators as well. The offender knows that when they are released from prison and come home to the community, they will be frequently facing a judge that is familiar with them personally as well as with their criminal case. For the first twelve months after an offender returns to the community, it is the judge that sets and enforces the expectations of the reentry program.96 In this unique position of authority and administrative influence, the judge sets expectations for offender reentry, and then publicly enforces them in the RCP hearing. With the judge directly involved and frequently briefed of the offender’s behavior and progress during the RCP program, the expectation is that the offender will positively respond to direction received in an open court hearing as well as privately from their case officer or treatment provider. The immediacy and frequency of this process, focused on the relationship between the judge and the offender, is intended to overcome the sense of disjointedness and detachment the offender otherwise experiences in leaving prison and reentering the community under a separated powers system. The judge is able to direct an offenders’ case completely from its beginning to its conclusion, and becomes a repository of institutional knowledge on the offender. In this regard, the judge is able to make decisions holistically by considering all aspects of the offender’s case history and current progress. This consistent involvement by the judge throughout the entire process also eliminates the possibility of an offender “playing” one branch of the criminal justice
96 At the first appearance in court after release, Ohio judges step out from behind the bench and shake the hand of the offender and welcome them home to the community. It is also the judge who acknowledges and congratulates offenders before the court when presenting graduation certificates to those who successfully complete the program. Hugs are not uncommon. On the other hand, offenders know that at any time the judge (as well as the state parole board member in the case of the Ohio RCP) has the power to immediately invoke lesser sanctions or send them back to prison.
86 system against another, or falling through the cracks of multiple and loosely coordinated supervision and treatment programs. Operationally, the RCP model can ultimately provide a feeling of job satisfaction for the judge, and a sense of accomplishment for the offender if reentry is successful. If unsuccessful, the RCP model provides a stable platform for continuation of the rehabilitative process at a later date. The RCP model also highlights the judge’s unique representation of the community as the only elected official directly involved in the reentry process. In this exceptional position, the judge has direct access to all treatment providers and programs designed to help offenders successfully reenter society. Working in the capacity of a reentry advisor, the judge can directly petition program providers from the executive or judicial branch, as well as the private sector, to accommodate reentering offenders into supervision and treatment programs that might not otherwise be available. Judges, in effect, provide the direct political accountability that is needed to incentivise cooperation among government, private, and nonprofit partners in the community. This advisory role helps to focus expertise and material assets on the prime objective of the RCP: promoting the positive behavior (decision making) of offenders. The judge alone has the authority to hold offenders personally and directly accountable to the community for their actions. The RCP model then, in one sense, is a pseudo family unit within the community established for offenders that oftentimes lack the real thing. Even if this philosophical example of the family unit is applicable to RCPs, judges realize that they only see the offender for one or two hours a month in court. Judges perceive that their most important job in the RCP model is to orchestrate all available help for reentry and to use their unique position to facilitate a change of heart, mind and attitude in the offender if possible. Harnessing this desire and giving it operational form helps the RCP model be potentially the most effective form of all reentry programs because, in the words of one RCP judge, “It most closely resembles the greatest crime fighting institution ever created; the two-parent family.” Key Findings: The Data In order to determine how judges are making decisions while implementing RCPs, decisions measured by fifteen values-based variable varieties are derived from
87 Table 2.4 (chapter 2) and included in the survey instrument contained in Appendix C.97 These values are rated by respondents on a scale of 1 (Strongly Agree) to 5 (Strongly Disagree), and the mean (average) scores and their standard deviations from the mean are shown in the following tables (Table 4.1 through 4.9). A lower score (closest to a value of 1) indicates a higher level of agreement. These mean scores are then compared and tested statistically to determine significant differences across actor categories.98 A statistical test for variable reliability (Alpha) is also included.99 The tables are similar in format to Table 2.4, and the values of concern are presented by decision making type and category.100 By examining respondent mean scores of agreement and comparing them to other respondents and actors, a basic picture can be formed that illustrates how reentry courts are being implemented by the types of decisions judges and other actors regularly make in RCP implementation and operation. Using the data from all respondent categories helps to illustrate a mix of decisions made in the courtroom that are obvious to the offender, with “behind the scenes” decisions obvious only to administrators and community partners. This data provides clues only to judge’s decision making generally, and certainly does not preclude individual decisions falling into any of the four decision making types or categories.101
97 Distribution and response rates of surveys are summarized in the table below: Actors Ohio Indiana Distributed Returned % Response Distributed Returned % Response Offender 92 41 .4456 136 71 .5221 Administrators* 17 11 .6471 11 11 1.000 Community Services 13 5 .3846 10 7 .7000 Total 122 57 .4672 157 89 .5669 * Administrators include Judges, Case/Parole/Probation Officers, Police Officers, and Court Staff 98 Statistical significance, or probability (p value), identifies the likelihood that a particular outcome occurred by chance. Social scientists generally agree that a p value less than .05 is statistically significant. This implies that if the mean scores of one group, or set of responses, differs from that of another at the p < .05 level of significance, that there is a 5 in 100 (1 in 20) probability that the difference happened by chance, and a 95 in 100 (19 in 20) probability that the discrepancy in scores is a reliable finding. A t test (2- tailed in this case to determine direction) is the procedure used for comparing sample means to determine if there is a significant difference. 99 The alpha score is based on the formula: Alpha = rk/[1 + (k-1)r], where k is the number of variables considered (15 in this case of variable variety) and r is the mean of the inter-item correlations. In most cases, an alpha score of > .7 is acceptable, and > .9 is excellent. 100 The four types of decisions are Personal, Procedural, Professional, and Political. Categories of decisions are Responsibility, Accountability, Expertise, and Material. See Table 2.4 and Appendix B for detailed explanation. 101 Missing values in survey responses for independent variables were replaced with the mean score of all other subjects for that variable. A new variable is created in this way for the purpose of analysis by using the SPSS default option: “Transform; Replace Missing Values; Series mean (default).”
88 Table 4.1: Ohio Reentry Court Judges’ Mean Survey Scores by Decision Type (Lower Scores = Higher Agreement) SPSS Judges: Judges: Judges: Family: Decision T Variable All Offender AD+CO Offender Offender Type: R y Variety (1A) (1O) (1M) (1O): (1M) (6O) (1O) : (6O) SPSS a p Names Mean/ Mean/ Mean/ t test/ Mean/ t test/ Variable n e (4x) Std Dev Std Dev Std Dev Signif. Std Dev Signif. Mean/ k N=57 N=41 N=16 (2-tail) N=41 (2-tail) Std Dev COMP1_ 1.6226 1.6579 1.5333 .884 1.4194 1.693 A, O, M, 6_O .8286 .9021 .6182 .382 .7648 .098 Personj CONSC1_ 1.4902 1.5278 1.4000 1.188 1.4516 .708 1 A, O, M, 6_O .6373 .6887 .4899 .242 .7362 .483 1.7198 COOP1_ 1.7451 1.8056 1.6000 1.435 1.4545 *2.451 .6878 A, O, M, 6_O Personal .8418 .9170 .6110 .159 .7775 .019 COMMO1_ 2.0213 1.8235 2.5385 **-5.205 1.7778 .333 A, O, M, 6_O 1.0087 .8795 1.1897 .000 .6455 .741 FAIR1_ 1.9167 1.9412 1.8571 .553 1.6923 1.638 A, O, M, 6_O .8626 .9732 .4976 .583 .7990 .109 Procedj OPEN1_ 1.6600 1.6389 1.7143 -.574 1.6071 .242 3 A, O, M, 6_O .8369 .8412 .8508 .569 .6833 .810 1.8580 CONSI1_ 1.8980 1.9143 1.8571 .363 1.6552 1.644 .6868 A, O, M, 6_O .9111 1.0092 .6172 .719 .7834 .108 Procedural CONSE1_ 1.9574 1.9091 2.0714 -1.149 1.7500 1.126 A, O, M, 6_O .8855 .9045 .8536 .257 .6937 .267 EFFEC1_ 2.0000 1.9412 2.1429 -1.364 1.5926 *2.357 A, O, M, 6_O .8660 .9471 .6172 .180 .6426 .023 Professj EFFIC1_ 1.9592 1.9143 2.0714 -1.148 1.8333 .592 2 A, O, M, 6_O .8443 .8767 .7715 .258 .9768 .558 1.8019 JUDGE1_ 1.8200 1.9444 1.5000 *2.452 1.7667 .981 .7270 A, O, M, 6_O 1.0297 1.1607 .4830 .019 .7963 .333 Professional COMPE1_ 1.4286 1.5143 1.2143 *2.667 1.7037 -1.684 A, O, M, 6_O .6547 .7201 .3964 .011 .7354 .100 RESPO1_ 1.7083 1.7353 1.6429 .754 1.6207 .935 A, O, M, 6_O .7309 .7845 .5896 .455 .6861 .355 Politicj PERSU1_ 1.8571 1.9143 1.7143 1.511 1.7778 1.031 4 A, O, M, 6_O .7792 .8477 .5690 .139 .6831 .309 1.9708
Political Political BARGA1_ 2.3469 2.2286 2.6429 *-2.716 2.0741 1.013 .6679 A, O, M, 6_O .9920 .9769 1.0071 .010 .8921 .317 - Variety Variables Reliability Coefficients (15 items) alpha = .9418, Standardized item alpha = .9454. - Decision Type Variables Reliability (4 items) alpha = .9334, Standardized item alpha = .9336. - Variety variable names correspond to actor variety variables from Table 2.4. For example: COMP1_A is the Compassion scores for all respondents concerning judges. COMP1_O is for responding offenders only, COMP1_M is a combined variable for administrators and community partner responses, and COMP6_O is for offenders only scoring their families. This pattern is duplicated by actor for the other fourteen varieties surveyed. - AD + CO is the combined variable (M) of administrators (AD) and community partners (CO). - Highest agreement scores for each type in bold, lowest in italics (lower score = higher agreement). - Degrees of Freedom (df) for ((1O) : (1M)) = N-1. “One-Sample t Test” function used in SPSS for t scores and significance (2-tailed). Two tailed test level of significance (.05) at 40 degrees of freedom is 2.021. * significant at the .05 level of probability (p < .05). ** significant at the .01 level of probability (p < .01).
89 There is a positive skew on all of the values-based variables measured for all respondents (1A) concerning judges in Table 4.1.102 This skewness lessens for later table presentations of data for administrators and community partners. In general, the positive skew toward higher agreement scores for judges is not problematic since all data is standardized and tested by mean scores by RCP.103 This positive skew is also an indication of the central and positive role that the judge plays in the RCP model. All respondents scores (1A; N=57)) are presented first, in the next column to the right is offender only scores (1O; N=41), and then administrator scores (1M; N=16). In the next column, the responses by offenders only in their rating of judges is then compared to the responses of administrators only and their rating of judges ((1O):(1M)). The t test values and significance levels of this comparison are then displayed, with the statistically significant differences indicated by either a single (p < .05), or double (p < .01) asterisk. Finally, offender only scoring for the decisions of their own family members is presented and compared statistically to offender only responses for judges. Ohio Judges by Decision Type Looking at the mean scores and standard deviations by type of decision for Ohio judges in Table 4.1, it is apparent that broad agreement on certain values in each decision type is commonly shared among survey respondents. The lowest mean score (highest agreement) and associated standard deviation in the Personal decision type is for conscientiousness (CONSC1_). The survey question asks the respondent their level of agreement with the statement, “My judge is honest and treats me with respect.” There is no significant difference in how either offenders or administrators rate the judges here. The least agreed upon variable in the Personal type of decision is the communication
102 The Skewness Statistic ranges from a low of .220 for the bargaining variable, to a high of 1.866 for the competence variable. All have a skewness standard error of .316. Skewness measures the extent that a distribution of values deviates from symmetry around the mean. A positive skew indicates a greater number of smaller values (higher agreement in this case). A skewness value between + 1.0 is considered excellent, but a value between + 2.0 is also considered acceptable in most cases. 103 The conversion of the original variables in this study from mean scores to z scores would better enable future comparisons across additional RCP jurisdictions. Z scores are values that are that have been mathematically transposed to create a distribution with a mean of 0 and a standard deviation of 1. This is not done here to provide a more intuitive reading of the data and provide the RCPs in the study with an easy to understand external evaluation. As an example, the mean score for Ohio judges compassion (COMP1_A) is 1.6226, and the z score is -3.5838; the mean score for the next variable in the column, conscientiousness (CONSC1_A), is 1.4902, and the z score is 2.9605. The variable skewness measure is identical for z scores as for their corresponding mean scores.
90 variable (COMMO1_). Surprisingly, offenders agree at a statistically significant higher rate than administrators that “My judge informs me about the details of my case” (**- 5.205 @ .000)104 Another surprising finding is that there is no statistically significant difference in the way in which offenders rate their judge and their families on the variables of compassion, conscientiousness, and communication. Offenders do agree at a significantly higher rate, however, that “My family knows and understands the details of my situation” (COOP1_O : COOP1_6 = *2.451 @ .019). For Procedural decisions, there are no significant differences noted either between offenders and administrators, or offenders and family members. The highest level of agreement is shared by both offenders and administrators in the level of openness displayed by the judges in their decision making. Surprisingly again, however, there is no significant difference in how offenders rate their judge compared to their own family members on the variables of fairness, openness, consistency, and consensus ((1O) : (6_O)). In matters of Professional decisions, there are statistical differences between how offenders and administrators rate judges on judgement (administrators in higher agreement by *2.452 @ .019), and competence (administrators in higher agreement by *2.667 @ .011). Competence, however, is the variable that presents the highest overall agreement scores for any variable in any decision type for both offenders and administrators. Offenders are statistically higher in agreement on rating the effectiveness of their family over their judge based on the statement; “My (family/judge) designs clear solutions to resolve my problems” (*2.357 @ .023). An interesting, but not quite significant, difference is recorded in the variable of competence. Here, offenders agree in higher measure over their family members (-1.684 @ .100) that, “My judge is qualified and capable to work on my case.” There are three interesting results in the Political type decisions of the Ohio judges. The first is the shared perceptions and rank orderings of all three variables in this decision type by both offenders and administrators (responsiveness showing the highest agreement, and bargaining the lowest). The second is that offenders
104 The t test value signifies the number of standard deviations of difference between the two compared variables. For example; there is a negative relationship when comparing the offender respondent scores for judges communication (COMMO1_O) to the administrator respondent scores for the same variable (COMMO1_M) of -5.205 that is significant at the .000 level (p < .001). In other words, there is a negative difference of 5.205 standard deviations in these scores (meaning that offenders are in higher agreement because a lower score = higher agreement in this study) that is significant at greater than 99 in 100 occurrences (p < .001).
91 agree more than do administrators in the bargaining decision behavior of the judge (statistically significant). Offenders agree more that, “My judge negotiates and compromises with others in deciding my case” than do administrators (*-2.716 @ .010). The third is that again, there is no statistical difference in how offenders rate their judge compared to their family in areas of responsiveness, persuasion, and bargaining. Overall (1A), the two Ohio judges are rated with the lowest mean score (highest overall agreement) in the Personal type of decision making (compassion + conscientiousness + cooperation + communication = 1.7198). Next in ranking of agreement is Professional decision making (effectiveness + efficiency + judgment + competence = 1.8019). Third is Procedural decision making (fairness + openness + consistency + consensus = 1.8580), and last is Political decision making (responsiveness + persuasiveness + bargaining = 1.9708). Ohio judges make decisions at higher frequency in the operation and implementation of their RCP by relying on their personal skills and interaction with offenders and administrators than they do with the political opportunities they have to resolve conflict (*-2.755 @ .008; not displayed in Table 4.1). Similarly, the second highest ranked decision types for judges, Professional, is nearly statistically significant when compared to political decisions (-1.754 @ .085; not displayed in Table 4.1). These rankings and differences indicate that the Ohio judges are perceived as implementing their RCP program most often by making decisions that utilize their personal skills followed by their professional judgement, more so than they do based on their procedural knowledge or political position. This is an interesting finding given the unique position the judges occupy in the community, and the advisory role the judges have created for themselves in RCP implementation. Indiana Judges by Decision Type The first difference that should be emphasized in transitioning from a discussion of the Ohio judges’ decision types to the Indiana judge decision types in Table 4.2 is the fact that in Ohio there are two judges being evaluated, and in Indiana there is just one. This difference is noted only for informational purposes, and does not in any way affect the validity of the data presented for either RCP.
92 Table 4.2: Indiana Reentry Court Judge’s Mean Survey Scores by Decision Type (Lower Scores = Higher Agreement) SPSS Judge: Judge: Judge: Family: Decision T Variable All Offender AD+CO Offender Offender Type: R y Variety (JA) (JO) (1) (JO) : (1) (6I_6) (JO) : (I6) SPSS a p Names Mean/ Mean/ Mean/ t test/ Mean/ t test/ Variable n e (4x) Std Dev Std Dev Std Dev Signif. Std Dev Signif. Mean/ k N=89 N=71 N=17 (2-tail) N=71 (2-tail) Std Dev INJ_1 1.6914 1.7302 1.5882 1.469 1.2540 **4.927 JA, JO, 1, I6 .8068 .8143 .7952 .146 .6097 .000 PersoIj INJ_2 1.4691 1.5397 1.2353 **4.081 1.4121 1.710 2 JA, JO, 1, I6 .6232 .6285 .5623 .000 .6684 .092 1.6592 INJ_3 1.7564 1.7667 1.7059 .569 1.4355 *3.100 .6079 JA, JO, 1, I6 Personal .8553 .9003 .6860 .571 .7095 .003 INJ_4 1.7200 1.5965 2.0588 **-6.427 1.7407 *-2.005 JA, JO, 1, I6 .7317 .6062 1.0290 .000 .8483 .049 INJ_5 1.6667 1.8000 1.2353 **5.438 1.8182 -.175 JA, JO, 1, I6 .8483 .8751 .5623 .000 .9272 .861 ProceIj INJ_6 1.6923 1.7000 1.6471 .616 1.6207 .924 3 JA, JO, 1, I6 .7120 .7231 .7019 .540 .7714 .359 1.7451 INJ_7 1.8421 1.9655 1.4118 **4.736 1.8182 1.260 .6703 JA, JO, 1, I6 .9421 .9851 .6183 .000 .8959 .212 Procedural INJ_8 1.7792 1.8305 1.5882 *2.277 1.7679 .588 JA, JO, 1, I6 .8611 .8969 .7123 .026 .8943 .558 INJ_9 1.6329 1.6230 1.6471 -.275 1.5862 .418 JA, JO, 1, I6 .7099 .7400 .6063 .784 .7752 .677 ProfesIj INJ_10 1.7500 1.7931 1.6471 1.727 1.6140 *2.119 1 JA, JO, 1, I6 .7091 .7123 .7019 .089 .6493 .038 1.6120 INJ_11 1.5714 1.6271 1.3529 *3.144 1.8571 *-2.637 .6129 JA, JO, 1, I6 .7140 .7348 .6063 .002 .9773 .010 Professional INJ_12 1.4935 1.9434 1.1765 **6.932 1.8000 1.296 JA, JO, 1, I6 .6147 .9322 .5286 .000 .8000 .199 INJ_13 1.5641 1.6000 1.4118 *2.199 1.7069 -1.249 JA, JO, 1, I6 .7005 .7211 .6183 .031 .8620 .216 PolitiIj INJ_14 1.8400 1.8772 1.7647 1.058 2.0357 -1.491 4 JA, JO, 1, I6 .9796 .8955 .8314 .293 .9556 .140 1.8014
Political Political INJ_15 2.0000 1.9636 2.1765 *-2168 2.0741 -1.125 .6554 JA, JO, 1, I6 .9045 .8275 1.1851 .034 .8921 .264 - Variety Variables Reliability Coefficients (15 items) alpha = .9342, Standardized item alpha = .9393. - Decision Type Variables Reliability (4 items) alpha = .9037, Standardized item alpha = .9056. - Independent variable names correspond to actor variety variables from Table 2.4. For example: INJALL_1 is the Compassion scores for all respondents concerning judges (with missing values replaced by series mean). INJO_1 is for responding offenders only, and COMP1 is for administrators and community partner responses, and COM6I_6 is for offenders ranking their families. This is duplicated by actor for the other fourteen varieties. - AD + CO is the scores only for administrator (AD) and community partners (CO) (no values replaced). - Highest agreement scores for each type in bold, lowest in italics (lower score = higher agreement). - Degrees of Freedom (df) for ((JO) : (1)) = N-1. “One-Sample t Test” function used in SPSS for t scores and significance (2-tailed). Two tailed test level of significance (.05) at 70 degrees of freedom is 2.000. * significant at the .05 level of probability (p < .05). ** significant at the .01 level of probability (p < .01).
93 For the Personal type of decision making, the Indiana judge shares the highest agreement among offenders and administrators in his display of conscientiousness (INJ_2),105 even though there is a statistically significant difference in the relative degree of agreement of administrators over offenders (**4.081 @ .000). The communication (INJ_4) variable shows that offenders agree in a significantly higher way than do administrators that, “My judge informs me about the details of my case” (**-6.427 @ .000). This is an interesting difference that should be addressed by the judge and administrators alike. Not surprisingly, offenders agree in a significant way that their families are both more compassionate (INJ_1; **4.927 @ .000) and more cooperative (INJ_3; *3.100 @ .003) than the judge in their particular case, but agree in a significantly higher way that the judge communicates with them better than their own families (INJ_4; *-2.005 @ .049). The Procedural type decision making of the Indiana judge shows statistically significant higher levels of agreement by administrators over offenders in three of the four variables measured. Fairness, consistency, and consensus are all rated significantly higher in agreement by administrators than offenders (**5.438 @ .000; **4.736 @ .000; and *2.277 @ .026 respectively). Interestingly, offenders rate the judge identically with their own families in all four variables in this decision type. Professionally, Administrators rate judges significantly higher in agreement for judgment and competence than do offenders (*3.144 @ .002; and **6.932 @ .000). When comparing
105 Due to an initial error made in data entry, the variable names for the Indiana judge data were changed in order to correct the problem. The variable names correspond in order to the variable varieties contained in Table 4.1 as drawn from Table 2.4: 1. INJALL_1 SMEAN(COMP1) 2. INJALL_2 SMEAN(CONSC1) 3. INJALL_3 SMEAN(COOP1) 4. INJALL_4 SMEAN(COMMO1) 5. INJALL_5 SMEAN(FAIR1) 6. INJALL_6 SMEAN(OPEN1) 7. INJALL_7 SMEAN(CONSIST1) 8. INJALL_8 SMEAN(CONSENS1) 9. INJALL_9 SMEAN(EFFECT1) 10. INJALL10 SMEAN(EFFIC1) 11. INJALL11 SMEAN(JUDGE1) 12. INJALL12 SMEAN(COMPET1) 13. INJALL13 SMEAN(RESPONS1) 14. INJALL14 SMEAN(PERSUAS1) 15. INJALL15 SMEAN(BARGAIN1)
94 offender ratings of the judge to their family members in efficiency and judgment, they alternately agree in a significantly higher way that, “My family is creative and innovative in helping resolve my case” (*2.119 @ .038), but agree at a significantly higher level that, “My judge has the insight and perception to decide my case” than does their family (*-2.637 @ .010). In the area of Political decision making, offenders and administrators are in agreement as to the ordering of the variables by level of agreement (responsiveness, persuasiveness, and bargaining in order from highest to lowest agreement), but disagree in the strength of their rankings. Administrators believe that the judge is more responsive and, “always considers and answers my questions and concerns at a significantly higher rate than do offenders (*2.199 @ .031), but offenders believe the judge is more willing to bargain, or “negotiate and compromise with others in deciding my case” than are administrators (*-2.168 @ .034). Interestingly, offenders rate the judge at higher levels of agreement in all three of the Political variables than their own family members, but none of the values rise to the level of statistical significance. Overall, The Indiana RCP judge ranks highest in agreement among all survey respondents in the Professional decision making type (effectiveness + efficiency + judgment + competence = 1.6120). This type of decision making indicates a high level of individual confidence in making decisions that are informed by job related experience, professional education, and administrative staff input. Offenders and administrators alike recognize, and agree at relatively as well as statistically higher levels compared to other decision types, that the judge for the Indiana RCP applies professional values above all in making operational and implementation decisions. Comparing the mean score for Professional decisions to that of Political decisions (-2.916 @ .004; not shown in Table 4.2), it is obvious that the Indiana RCP judge values to a much higher degree his ability to apply his professional experience and standing in making decisions than his political position in the community. Likewise, when Professional decision making is compared to Procedural decision making, all respondents rate the judge at a statistically higher level of agreement (-2.049 @ .043; not shown in Table 4.2) in the former over the latter. The only non-statistically significant difference in decision type compared to the professional decision is the Personal type decision (-.727 @ .469). This helps to illustrate, by using mathematical comparison, how the Indiana RCP judge primarily uses his personal skills
95 (compassion + conscientiousness + cooperation + communication) to complement his professional knowledge when making operational and implementation decisions. Decisions Measured by Category and Division Table 2.4 in chapter 2 not only specifies a model for determining decision making behavior by type (column values), but also specifies decision making behavior at the category and division level (row values). The key to unlocking the interpretation of both the column and row values of Table 2.4 is by focusing on the fifteen variable varieties. It is in the various combinations of these building blocks that operational and implementation decision making behavior is measured. While decision types (columns) cut across divisions and categories and help us to understand the relative emphasis of individual values in the decision making process, categories and divisions help to isolate and explain the relative importance of specific and aggregated kinds of influences. In other words, each type of decision contains all elements of normative and rational, internal and external, formal and informal, and individual and regime influences. Categories of decisions, however, focus on specific aspects of these influences. For example, the variable varieties contained within the category of Responsibility reflect only the internal and informal influences related to normative and individual behavior. Accountability, on the other hand, is concerned with the external and formal influences on rational regime related decisions. By isolating the influences in this way, their relative degree of importance can be determined in comparing category mean values. For the purposes of this study and its intent to answer the basic research question, the exercise of analyzing both the row and column values adds an internal elasticity to the overall research design, and helps to better explain operational and implementation decision making behavior. Ohio and Indiana Judges Decisions by Category and Division Discretion: Responsibility and Accountability Table 4.3 reemphasizes that all decision making contains two basic elements; discretion and resources (Division). By displaying survey mean scores first of the variable varieties, then aggregating them into category and division, one can compare and analyze the relative influences of each. First, in the category of Responsibility, Ohio
96 Table 4.3: All Reentry Court Judges’ Mean Scores by Jurisdiction, Division & Category (Lower Scores = Higher Agreement) C SPSS Ohio Ohio R Indiana Indiana R OH/IN Division A Variable Judges: Judges: A Judge: Judges: A Discretion T Variety Variety Category N Variety Category N Resources (2x) Mean/ Mean/Std K Mean/ Mean/Std K Division Y. Std Dev Dev Std Dev Dev Mean/Std Dev COMP1_ 1.6226 1.6914 A, INJA_1 .8286 Responsj .8068 ResponIj DiscreOj FAIR1_ 1.9167 1.6667 A. INJA_5 .8626 1.8119 2 .8483 1.6388 2 1.7575 EFFECT1_ 2.0000 .6777 1.6329 .6117 .6625 A, INJA_9 .8660 .7099 (Normative/Ind.) Internal/Informal Responsibility RESPON_ 1.7083 1.5641 A, INJA_13 .7309 .7005 DiscreIj CONSC1_ 1.4902 1.4691 Discretion A, INJA_2 .6373 Accountj .6232 AccounIj 1.6380 .5735 OPEN1_ 1.6600 1.6923 A, INJA_6 .8369 1.7031 1 .7120 1.6371 1 .6800 ..5752 EFFIC1_ 1.9592 1.7500
External/Formal A, INJA_10 (Rational/Regime) Accountability .8443 .7091 COOP1_ 1.7451 1.7564 A, INJA_3 .8418 Expertj .8553 ExpertIj ResourOj CONSIS_ 1.8980 1.8421 A, INJA_7 .9111 1.8301 3 .9421 1.7525 4 1.8843 JUDGE1_ 1.8200 .6979 1.5714 .6572 .6449 A, INJA_11
Expertise 1.0297 .7140 Internal/Formal PERSUA_ 1.8571 1.8400 (Normative/Regime) (Normative/Regime) A, INJA_14 .7792 .8796 ResourIj COMMO1_ 2.0213 1.7200 A, INJA_4 1.0087 Materiaj .7317 MateriIj 1.7503 Resources CONSEN_ 1.9574 1.7792 .5833 A, INJA_8 .8855 1.9386 4 .8611 1.7482 3 COMPET_ 1.4286 .6718 1.4935 .5683 A, INJA_12 Material .6547 .6147 (Rational/Ind.)
External/Informal BARGAI_ 2.3469 2.0000 A, INJA_15 .9920 .9045 - Data for Ohio Judges: N=57. Variety Variables Reliability Coefficients (15 items) alpha = .9418, Standardized item alpha = .9454. Category Variables Reliability (4 items) alpha = .9486, Standardized item alpha = .9487. Division Variables Reliability (2 items) alpha = .9391, Standardized item alpha = .9393. - Data for Indiana Judge: N=89. Variety Variables Reliability Coefficients (15 items) alpha = .9342, Standardized item alpha = .9393. Category Variables Reliability Coefficients (4 items) alpha = .9470, Standardized item alpha = .9482. Division Variables reliability (2 items) alpha = .9377, Standardized item alpha = .9378.
97 respondents agree most strongly that compassion is the strongest trait displayed in their judge’s decision making behavior (1.6226), while Indiana respondents agree most strongly that responsiveness characterizes the decision making of their judge (1.5641). There is a statistically significant difference in Ohio respondents’ ratings within the category of responsibility between their agreement on compassion and effectiveness (**-3.438 @ .001; not shown in Table 4.3), and compassion and fairness (*-2.679 @ .010; not shown in Table 4.3). There is no statistical difference between the highest and lowest agreement values of Indiana respondents for their judge’s responsibility scores. For both Ohio and Indiana judges, Responsibility rates as the second most important category in explaining overall decision making behavior. The other category within the division of discretion is Accountability. Both Ohio and Indiana respondents are in highest agreement that conscientiousness anchors the accountability category in the decision making of their judge (1.4902 and 1.4691 respectively). There is a significant difference between the highest and lowest scores of agreement in this category between the variety of conscientiousness and efficiency for both Ohio and Indiana judges (**-5.556 @ .000, and **-4.252 @ .000 respectively; not shown in Table 4.3). Likewise, the category of accountability is ranked number one in agreement among all respondents in both jurisdictions as the most influential category in overall decision making behavior. Resources: Expertise and Material In the category of Expertise, Ohio and Indiana respondents are split in their agreement about the variable variety that best describes the judge’s decision making. For Ohio respondents, cooperation elicits the highest agreement (1.7451), but in Indiana judgement receives the highest agreement (1.5714). There is significant difference between the highest and lowest agreement scores in Indiana (**-3.577 @ .001), but not in Ohio (-1.371 @ .176). There is also a difference in the overall category ranking of expertise between the two jurisdictions. Ohio has the expertise category rated third overall in agreement, and the highest ranked of the two categories in the Resources division, but Indiana respondents rate expertise least important among the four categories. The Material category shows a consensus between the jurisdictions that competence best marks the decision making behavior of judges. There is a mutually shared significant difference between the scores for competence in Ohio and Indiana
98 when compared with every other variety in this category (bargaining; **-10.591 @ .000, and **-7.774 @ .000 respectively; communication; **-6.836 @ .000, and **-3.476 @ .001 respectively; and consensus; **-6.099 @ .000, and **-4.385 @ .000 respectively; not shown in Table 4.3). This is evidence not only that the judges in both jurisdictions are believed to be highly competent, but also that the other influences in the material category are much weaker in comparison. The Judges’ Implementation Decisions In comparing the mean scores of the two categories that represent external and rational influences (accountability and material), there is a significant difference in how respondents rate Ohio judges on decisions based in discretion versus resources (**-2.614 @ .011; not shown in Table 4.3), but not between the two categories of internal and normative influences (responsibility and expertise) of discretion and resources (.196 @ .845; not shown in Table 4.3). This indicates a significantly high level of agreement in the Ohio jurisdiction that judges make decisions based first in their use of discretion (particularly relying on their sense of accountability to the community), and informed most directly by the dual normative influences of individual responsibility first, and their professional (regime) expertise second. The material resources category that contains the variable varieties of communication, consensus, competence and bargaining is the least important influence on Ohio judges’ decision making. Comparatively, there is a near significant difference (-1.892 @ .062) between the Indiana judge’s decision category of highest agreement (accountability), and the category of least agreement (expertise). This indicates that like the Ohio judges, the Indiana judge primarily makes discretionary decisions informed most by a sense of accountability to the community, but differs from Ohio judges in that he next considers the material (external/informal and rational/individual) influences rather than considerations of professional expertise. This conclusion is only tentative, however, because there is no significant difference in mean scores between categories of expertise and material for either the Indiana judge or the Ohio judges. In comparing the mean scores of each variable division (last column of Table 4.3), and considering the previous paragraph, it is clear that discretion is perceived to play the most important role in judges’ decisions in both jurisdictions. Again, this
99 conclusion is tentative because the difference between the division mean scores for discretion and resources do not reach the level of statistical significance in either jurisdiction (Indiana comes the closest with -1.848 @ .068). Even so, general conclusions can be drawn from the results as presented in Table 4.3 and earlier in Tables 4.1 and 4.2. For instance, it can be inferred that Ohio judges are implementing RCPs by regularly making decisions that rely more on their use of discretion than on considerations of resources, and that these discretionary decisions are informed primarily by their personal and professional type values and skills (top two ranked types from Table 4.1). Likewise, the Indiana RCP judge is making what are primarily discretionary decisions informed first by his professional and then his personal type values and skills (top two ranked types from Table 4.2). This finding in both jurisdictions serves to illustrate the advisory and community advocate role that the judges have created for themselves in the implementation of the RCP model. Even though their unique position demands that accountability to the community is the most important influence on their discretionary decisions, the strength of personal and professional influences over those of resources, procedures, and politics is an important and interesting finding that helps to explain the judge’s decisions in RCP implementation. Key Actors: The Administrators For the purposes of this study, the definition of administrators includes probation, parole, and case officers, as well as other RCP staff that have direct contact with offenders such as court coordinators and counselors. RCP administrators have a twofold mission in the operation and implementation process. First they must be the subject matter experts on the offenders that they personally supervise. This supervision is centered on personal interaction with the offender in face-to-face meetings in the office and on the street. This contact also extends into the prisons prior to release and is often a continuation of a previous failed supervisory relationship that resulted in the offender’s return to prison. Administrators must monitor the progress, or lack thereof, of the offender and be able to expertly brief the RCP judge on the status of their supervisees. Supervision extends to regular contact with the family, associates, employers, and treatment providers of those they supervise. All of this immediate and personal information is necessary to develop a firsthand account of the offender’s reentry attitude
100 and commitment to changing their behavior in a positive way. Second, all of this vital information that is collected and documented must be transferred accurately and efficiently to the RCP judge at court pre-briefings and staffing meetings. The extent of the professional and personal knowledge of the staff administrators determines to a great degree the types of decisions the judge ultimately makes in the case of the offender. Judges want the court administrators to be able, at the best of their ability, to tell them “where they (offenders) are in their head” and how committed they are to treatment and successful reentry. Before the judges (and parole board hearing officer in the case of the Ohio RCP) sit behind the bench and make any decision concerning the life of the offender, they will have been extensively and frequently briefed on the status of the case by RCP administrators. Ohio Administrators by Decision Type First looking at Ohio administrators (Table 4.4) concerning their Personal type decisions, the variable variety of conscientiousness garners the highest level of agreement among all (AO) respondents (2.1419), while cooperation exhibits the least level of agreement (2.2901). The variable variety of conscientiousness is also the one that was at the highest level of agreement for all respondents (1A) concerning Ohio judges. When the two column mean scores are compared and tested statistically, it is revealed that respondents are much more confident in their agreement scores for judges than for administrators (**6.026 @ .000). In fact, the same significant difference is seen in three of four variable varieties for the personal type of decision. The only variety that does not show significant difference for personal type decisions is communication (1.585 @ .119). In further comparison with like mean scores of all family members (A6O), significant differences are observed for all varieties except compassion. Here, even though the difference is not significant, it is surprising in that administrators and family members are rated evenly in compassion.
101 Table 4.4: Ohio Reentry Court Administrators’ Mean Scores by Decision Type (Lower Scores = Higher Agreement) SPSS Admin: Judges: Family: Decision T Variable All All (AO): (1A) All (AO):(A6O) Type: R y Variety (AO) (1A) t test/ (A6O) t test/ SPSS a p Names Mean/ Mean/ Signif. Mean/ Signif. Variable n e (3x) Std Dev Std Dev (2-tail) Std Dev (2-tail) Mean/ Std k N=57 N=57 N=57 Dev COMPAO_ 2.2794 1.6226 **7.018 2.4107 -1.403 1A, 6_O .7065 .8286 .000 1.9065 .166 PersoOa CONSAO_ 2.1419 1.4902 **6.026 1.6444 **4.600 4 1A, 6_O .8165 .6373 .000 .7828 .000 2.2255 COOPAO_ 2.2901 1.7451 **4.647 1.6596 **5.376 .6922 1A, 6_O Personal .8854 .8418 .000 .8297 .000 COMMAO_ 2.1907 2.0213 1.585 1.9750 *2.018 1A, 6_O .8068 1.0087 .119 .6940 .048 FAIRAO_ 2.4909 1.9167 **5.094 2.1053 **3.421 1A, 6_O .8511 .8626 .000 .9597 .001 ProceOa OPENAO_ 1.9589 1.6600 *3.177 1.9512 .082 2 1A, 6_O .7102 .8369 .002 .8007 .935 2.2033 CONAO_ 2.1716 1.8980 *2.623 2.0244 1.411 .6442 1A, 6_O .7876 .9111 .011 .8962 .164 Procedural CONSAO_ 2.1917 1.9574 *2.474 2.0732 1.251 1A, 6_O .7149 .8855 .016 .7881 .216 EFFEAO_ 2.2748 2.0000 *2.627 1.9231 **3.362 1A, 6_O .7898 .8660 .011 .7412 .001 ProfesOa EFFICAO_ 2.2200 1.9592 *2.801 2.1163 1.114 1 1A, 6_O .7031 .8443 .007 ..9858 .270 2.1458 JUDGAO_ 2.2179 1.8200 *3.170 2.0476 1.357 .7326 1A, 6_O .9478 1.0297 .002 .8441 .180 Professional COMPTAO_ 1.8705 1.4286 **4.034 2.0750 -1.866 1A, 6_O .8272 .6547 .000 .8942 .067 RESPOAO_ 2.1767 1.7083 **3.912 1.9524 1.873 1A, 6_O .9038 .7309 .000 .7781 .066 PolitiOa PERSUAO_ 2.1083 1.8571 *2.887 2.1250 -.192 3 1A, 6_O .6569 .7792 .006 .8278 .849 2.2226
Political Political BARGAO_ 2.3829 2.3469 .338 2.2368 1.378 .6399 1A, 6_O .7992 .9920 .737 .8114 .174 - Variety Variables Reliability Coefficients (15 items) alpha = .9574, Standardized item alpha = .9581. - Decision Type Variables Reliability (4 items) alpha = .9455, Standardized item alpha = .9468. - Variety variable names correspond to actor variety variables from Table 2.4. For example, COMPAO_O is the Compassion scores for all respondents concerning combined variable for Administrators. COMP1A_O is all respondents for judges only, and COMPA6_O is all for Family. - Administrator variable created in SPSS by combining number 2 variables (Case Officer/P.O.) and number 4 variables (Court staff). Missing values were replaced prior to combination. - Highest agreement scores for each type in bold, lowest in italics (lower score = higher agreement). - Degrees of Freedom (df) for ((AO) : (1A)) = N-1. “One-Sample t Test” function used in SPSS for t scores and significance (2-tailed). Two tailed test level of significance (.05) at 56 degrees of freedom is 2.021. * significant at the .05 level of probability (p < .05). ** significant at the .01 level of probability (p < .01).
102 For Procedural type decisions, administrators are seen as being most open (1.9589), and least fair (2.4909). There is a significant difference between these two scores themselves (**-5.656 @ .000; not shown in Table 4.4). Significant differences are seen in all four varieties contained within procedural decision types compared between administrators and judges, with judges uniformly receiving the higher agreement scores. Interestingly, the only significant difference in this type between administrators and family members is for fairness (**3.421). Openness, consistency, and consensus are rated similarly for administrators and family members alike. Procedural type decisions are also rated in a significantly different way when compared across actors, with judges uniformly gaining the highest agreement scores. All varieties except effectiveness (**3.362 @ .001) are rated similarly when comparing administrators and family members. Political type decisions show significant differences for two of the three varieties compared with judges. Bargaining is the only variety that shows no significant difference (.338 @ .737). Again, surprisingly, there is no significant difference in how administrators and family members are rated for political type decisions. Overall, Ohio administrator’s decision types are ranked in agreement as first Professional (effectiveness + efficiency + judgment + competence), second Procedural (fairness + openness + consistency + consensus), third Political (responsiveness + persuasion + bargaining), and last Personal (compassion + conscientiousness + cooperation + communication). The order of these decision types is tentative, however, because there is no significant statistical difference separating the first from the last ranked in agreement ratings. It is interesting, however, that the personal type decision is rated least in agreement for administrators, and highest in agreement for judges. Further, there is a significant difference between the two (**5.515 @ .000; not shown in tables). Not surprisingly then, given the significant differences between the variable varieties compared between administrators and judges, there is also a significant difference between the remaining three decision types compared between administrators and judges (Procedural: **4.046 @ .000; Professional: **3.544 @ .001; and Political: *2.970 @ .004; not shown in tables). This finding helps to solidify the robustness of the survey data by eliminating concerns of response set bias, and indicates an interesting and uniform difference of opinion among all survey respondents concerning administrators and
103 judges. This distinction helps to highlight the differences of influence in the decision making of actors in the implementation process. It is clear at this point that judges in Ohio are strongly informed in their decision making behavior by personal and professional skills and experiences, while Ohio administrators are likely most informed in their decision making behavior by professional skills and procedural considerations. Indiana Administrators by Decision Type Looking at the Personal type of decision and the variable variety ratings of agreement for Indiana Administrators, conscientiousness displays the highest level (1.7268), and compassion the lowest agreement (1.9428). There is a significant difference between the mean scores of these two variables within the administrator (INA) column (*-3.274 @ .002; not shown in Table 4.5), as well as between conscientiousness and communication (*-2.829 @ .006), and conscientiousness and cooperation (*-2.634 @ .010). This intra-column difference among respondent scores is strong indicator of the uniformly high degree of agreement on this variable variety. In fact, the only variable variety that achieves higher agreement scores for Indiana administrators is competence in the professional type decision. When comparing administrator personal decision mean scores with that of the judge, significant differences are seen in three of the four variable varieties. Even though both administrators and judges are ranked highest in agreement on conscientiousness, the strength of agreement in the scores is significantly different (**3.907 @ .000). The only variety not showing significant difference between administrators and judges is cooperation (1.663 @ .100). Family members rate significantly higher in agreement in three of four personal decision varieties as well. The exception is a negative difference where all respondents rate administrators higher in agreement than their own family members in the area of communication, even though this difference is not significant (-1.372 @ .174). Procedural decisions of Indiana administrators (Table 4.5) all vary significantly in strength of agreement when compared to the judge, but none vary significantly when compared to family members. Another interesting negative relationship is seen in the variable variety of fairness. Here, all respondents rate administrators higher in agreement than family members, and the difference just misses being significant at the p < .05 level (-1.884 @ .063). The Professional decision type of Indiana administrators is marked by
104 Table 4.5: Indiana Reentry Court Administrators’ Mean Scores by Decision Type (Lower Scores = Higher Agreement) SPSS Admin: Judge: Family: Decision T Variable All All (INA):(JA) All (INA):(6I) Type: R y Variety (INA) (JA) t test/ (6I_A) t test/ SPSS a p Names Mean/ Mean/ Signif. Mean/ Signif. Variable n e (3x) Std Dev Std Dev (2-tail) Std Dev (2-tail) Mean/ k N=89 N=89 N=89 Std Dev COMPINA, 1.9428 1.6914 *3.147 1.4875 **5.700 INJA1, 6I_A .7535 .8068 .002 .7833 .000 PersoIa CONSCINA, 1.7268 1.4691 **3.907 1.5875 *2.112 2 INJA2, 6I_A .6223 .6232 .000 .7491 .038 1.8709 COOPINA, 1.9006 1.7564 1.663 1.5949 **3.526 .6437 INJA3, 6I_A Personal .8178 .8553 .100 .7616 .001 COMMOINA 1.9134 1.7200 *2.639 2.0139 -1.372 INJA4, 6I_A .6912 .7317 .010 .9593 .174 FAIRINA, 1.9631 1.6667 **3.813 2.1096 -1.884 INJA5, 6I_A .7333 .8483 .000 1.0825 .063 ProceIa OPENINA, 1.8835 1.6923 *2.532 1.8533 .399 3 INJA6, 6I_A .7122 .7120 .013 .8751 .691 2.0124 CONSIINA, 2.1288 1.8421 *3.119 2.0959 .358 .6423 INJA7, 6I_A .8671 .9421 .002 1.0131 .721 Procedural CONSEINA, 2.0744 1.7792 **3.434 2.0548 .228 INJA8, 6I_A .8110 .8611 .001 .9988 .820 EFFECINA, 1.8402 1.6329 *2.860 1.8667 -.365 INJA9, 6I_A .6839 .7099 .005 .9211 .716 ProfesIa EFFICINA, 1.9742 1.7500 *3.095 1.9189 .763 1 INJA10, 6I_A .6833 .7091 .003 .8224 .447 1.8556 JUDGEINA, 1.9149 1.5714 **4.627 2.1096 *-2.622 .5913 INJA11, 6I_A .7004 .7140 .000 1.0064 .010 Professional COMPEINA, 1.6933 1.4935 *2.948 2.0833 **-5.756 INJA12, 6I_A .6393 .6147 .004 .9741 .000 RESPOINA, 1.8856 1.5641 **4.373 1.9600 -1.012 INJA13, 6I_A .6936 .7005 .000 .9468 .315 PolitiIa PERSUINA, 2.0277 1.8400 *2.733 2.2603 **-3.387 4 INJA14, 6I_A .6479 .8796 .008 .9656 .001 2.0422
Political Political BARGAINA, 2.2133 2.0000 *2.639 2.2958 -1.020 .6045 INJA15, 6I_A .7627 .9045 .010 .9582 .310 - Variety Variables Reliability Coefficients (15 items) alpha = .9569, Standardized item alpha = .9587. - Decision Type Variables Reliability (4 items) alpha = .9366, Standardized item alpha = .9371. - Variety variable names correspond to actor variety variables from Table 2.4. For example, COMPINA is the Compassion scores for all respondents concerning combined variable for Administrators (COMP2 and COMP4). INJA is all respondents for judges only, and COMP6I_A is all for Family. - Administrator variable created in SPSS by combining number 2 variables (Case Officer/P.O.) and number 4 variables (Court staff). Missing values were replaced prior to combination. - Highest agreeability scores for each type in bold, lowest in italics (lower score = higher agreement). - Degrees of Freedom (df) for ((INA) : (JA)) = N-1. “One-Sample t Test” function used in SPSS for t scores and significance (2-tailed). Two tailed test level of significance (.05) at 88 degrees of freedom is 2.000. * significant at the .05 level of probability (p < .05). ** significant at the .01 level of probability (p < .01).
105 significantly strong agreement in their competence when compared to other variable varieties within the column (Effectiveness: *-2.168 @ .033; Efficiency: **-4.146 @ .000; and Judgment: *-3.271 @ .002; not shown in Table 4.5). Again as well, when all four variable varieties are compared to the judge’s scores, the judge displays significantly higher agreement scores across the board. Even more interestingly when administrators are compared to family members in this decision type, there are two statistically significant negative relationships. Indiana administrators are ranked significantly higher in agreement over family members in judgement (*-2.622 @ .010), and competence (**- 5.756 @ .000). Administrator Political decision type behavior displays similar significant results in comparisons with the judge and family members. All three variable variety scores are significantly stronger in agreement for the judge, and negative in favor of the administrators over family members. Indiana administrators are rated in higher agreement over family members in responsiveness, persuasiveness, and bargaining behavior. Of the three, however, only persuasiveness shows a statistically significant difference (**-3.387 @ .001). Ohio and Indiana Administrators Decisions by Category and Division Discretion: Responsibility and Accountability First looking at Ohio administrators’ variable variety mean scores (Table 4.6) in the internal/informal and normative/individual influenced category of Responsibility, responsiveness stands out with the highest level of agreement (2.1767), and fairness the lowest (2.4909). The difference between these two scores is significant (*-2.625 @ .011; not shown in Table 4.6). For Indiana administrators on the other hand, effectiveness is the variable variety receiving the highest level of agreement (1.8402), while fairness remains the variable with the lowest level of agreement (1.9631). There is, however, no significant difference between the high and low scores for Indiana administrators in this category. The ranking scores of the responsibility category for Ohio and Indiana administrators’ is last and second respectively. In the external/formal and rational/regime influenced category of Accountability, Ohio administrator see the most agreement in the
106 Table 4.6: All Reentry Court Administrators’ Decisions by Jurisdiction, Division & Category (Lower Scores = Higher Agreement) C SPSS Ohio Ohio R Indiana Indiana R OH/IN Division A Variable Admin: Admin. A Admin. Admin. A Discretion Variety Variety Category N Variety Category N Resources T K K Y. (2x) Mean/ Mean/Std Mean/ Mean/Std Division Std Dev Dev Std Dev Dev Mean/Std Dev COMPAO, 2.2794 1.9428 INA .7065 ResponOa .7535 ResponIa Discreoa FAIRAO, 2.4909 1.9631 INA .8511 2.3055 4 .7333 1.9079 2 2.2062 EFFECAO, 2.2748 .7059 1.8402 .6107 .6677 INA .7898 .6839 (Normative/Ind.) Internal/Informal Responsibility RESPONAO, 2.1767 1.8856 INA .9038 .6936 DiscreIa CONSAO, 2.1419 1.7268 Discretion INA .8165 AccounOa .6223 AccounIa 1.8847 .5894 OPENAO, 1.9589 1.8835 INA .7102 2.1069 1 .7122 1.8615 1 .6677 .6000 EFFICAO, 2.2200 1.9742
External/Formal INA (Rational/Regime) Accountability .7031 .6833 COOPAO, 2.2901 1.9006 INA .8854 ExpertOa .8178 ExpertIa Resouroa CONAO, 2.1716 2.1288 INA .7876 2.1970 3 .8671 1.9930 4 2.1779 JUDGAO, 2.2179 .6620 1.9149 .6102 .6299 INA
Expertise .9478 .7004 Internal/Formal PERSUAO, 2.1083 2.0277 (Normative/Regime) (Normative/Regime) INA .6569 .6479 ResourIa COMMAO, 2.1907 1.9134 INA 8068 MateriOa .6912 MateriIa 1.9833 Resources CONSEAO, 2.1917 2.0744 .5752 INA .7149 2.1518 2 .8110 1.9736 3 COMPETAO, 1.8705 .6467 1.6933 .5742 INA Material .8272 .6393 (Rational/Ind.)
External/Informal BARGAO, 2.3827 2.2133 INA .7992 .7627 - Data for Ohio Administrators: N=57. Variety Variables Reliability Coefficients (15 items) alpha = .9574, Standardized item alpha = .9581. Category Variables Reliability Coefficients (4 items) alpha = .9564, Standardized item alpha = .9567. Division Variables Reliability (2 items) alpha = .9417, standardized item alpha = .9425. - Data for Indiana Administrators: N=89. Variety Variables Reliability Coefficients (15 items) alpha = .9569, Standardized item alpha = .9587. Category Variables Reliability Coefficients (4 items) alpha = .9675, Standardized item alpha = .9677. Division Variables reliability (2 items) alpha = .9624, standardized item alpha = .9626.
107 variable of openness (1.9589), and the lowest in efficiency (2.2200). There is a significant difference between these two scores (*-2.776 @ .007; not shown in Table 4.6). Indiana administrators are rated the highest in agreement on conscientiousness (1.7268), and lowest on efficiency (1.9742) like their Ohio counterparts. There is also a significant difference between these two scores (**-3.750 @ .000), as well as between conscientiousness and the score for openness (*-2.375 @ .020; not shown in Table 4.6). Resources: Expertise and Material In the internal/formal and normative/regime category of Expertise, Ohio respondents agree most strongly that their administrators exhibit a high degree of persuasion (2.1083) in relation to the other variable varieties in the category. Within the category there is a significant difference between the highest and lowest agreement scores (*-2.089 @ .041), with cooperation being the least agreed upon. Just the opposite is seen in Indiana where cooperation is the variety of highest agreement (1.9006), and consistency the lowest. Here as well there is a significant difference between the highest and lowest agreement scores in the category (*-2.633 @ .010). Expertise ranks third and fourth overall in importance for influencing administrator decisions, and least important respectively among the two categories in the division of resources. For administrators in both jurisdictions, material resources have a higher influence on decisions than does expertise. This conclusion is tentative, however, as there is no statistically significant difference in either jurisdiction between agreement scores on expertise and material. The Material category is in agreement across jurisdictions that competence is the most important variable variety in evaluating the resource influenced decision making of administrators. There is a significant difference between the competence scores in each jurisdiction and all other variable varieties in the material category and the expertise category. Competence is the single variable variety that is the key to understanding all administrators’ resource influenced decision making. In the case of Ohio, the external/informal and rational individual influenced Material category exerts the most influence within the variable division of Resources, and is ranked second overall in agreement (2.1518). In Indiana, it is ranked third overall (1.9736).
108 The Administrators’ Implementation Decisions It is apparent from the agreement scores for both Ohio and Indiana administrators in the external/formal and rational/regime influenced category of accountability that it is the primary influence on discretionary decision making specifically, and the most influential category in decision making overall. When comparing the agreement scores in accountability for Indiana administrators to the other three categories, a significant difference is not present within the division of Discretion (accountability and responsibility), but is present between accountability and the Resources division category of expertise (*-2.068 @ .042; not shown in Table 4.6), and nearly significant when compared to the material (-1.763 @ .081). For Ohio administrators, there is a significant difference within the division of discretion between accountability and responsibility (*- 2.245 @ .029; not shown in Table 4.6), but not between either category in the division of resources. It seems to be clear that just as for the judges in both jurisdictions, accountability is the strongest influence in the decision making behavior of administrators. When it is understood that accountability is owed “up” by an actor (external/formal and rational/regime), then it becomes clear that in the judges’ case accountability is directed specifically to the community, and for the administrators it is directed specifically to the head of their particular branch of government. That branch as a representative of the people, in turn, answers to the community. Overall, the finding that the influence of Resources (2.1779) is greater than that of Discretion (2.2062) for Ohio administrators is tentative because the difference between the two is not significantly different. The finding that Indiana administrators make discretionary decisions (1.8847) over resource influenced decisions (1.9833) is also tentative as the difference between the two scores is also not significant. What can be inferred, however, is that when Ohio administrators make operational and implementation decisions they are most likely to first consider the external and rational influence of accountability (category) as informed by their sense of professional knowledge and procedural considerations (one and two ranked decision types in Table 4.4). Indiana administrators are also most likely to make decisions based on the external and rational influence of accountability, but instead are informed most by their professional knowledge and personal skills. In both cases, this inference is only made in
109 general, and does not preclude decisions influenced by other categories or informed by other types. What this general finding does, however, is give an insight on the slight differences across jurisdictions, and between the decision making behavior of actors within jurisdictions. Key Actors: The Community Partners Both RCP jurisdictions agree on the importance of including the community in the planning of the operational model and the implementation of the reentry court. Community service providers are important partners in both the supervision and treatment of reentering offenders. An important consideration of the RCP model is that all treatment should be local if possible in order to familiarize the offender with the resources that are in the local community (halfway houses, etc.), and to develop a sense of ownership in their own rehabilitation. The benefit of returning an offender to the community for treatment is aided by partners who not only provide treatment and counseling, but who involve the offenders’ families as much as possible in the process. An economy of effort and resources is achieved if the thinking and decision making process of the offender and their family is synchronized in this way. Community partners in many ways can best encourage family members to keep in contact with the offender before release, join the offender at RCP hearings, and get them involved in the overall program of offender supervision and treatment. Ohio Community Partners by Decision Type In looking at the general agreement scores for Ohio community partners (Table 4.7), the first thing that becomes obvious is the large degree of significant difference between partner scores and judges scores (CPO : 1A). This significant difference should not immediately be interpreted as a criticism of community partners because there are two other possible causes of the discrepancy. First, as already seen in comparing judges and administrator agreement scores, respondent attention is focused on only one judge in most cases, but can be considering several administrators, or in this case, community partners. Second, the judge occupies a unique role in the RCP model with the ultimate authority to legally sanction or reward offender behavior. Community partners do not
110 Table 4.7: Ohio Reentry Court Community Partners’ Mean Scores by Decision Type (Lower Scores = Higher Agreement) SPSS Partner: Judges: Admin: Decision T Variable All All (PO):(1A) All (CPO) : (AO) Type: R y Variety (CPO) (1A) t test/ (AO) t test/ SPSS a p Names Mean/ Mean/ Signif. Mean/ Signif. Variable n e (3x) Std Dev Std Dev (2-tail) Std Dev (2-tail) Mean/ Std k N=57 N=57 N=57 Dev COMPCPO 2.4000 1.6226 **7.716 2.2794 1.197 1A, AO .7606 .8286 .000 .7065 .236 PersoOc CONSCPO 2.5526 1.4902 **8.909 2.1419 **3.444 2 1A, AO .9003 .6373 .000 .8165 .001 2.5084 COOPCPO 2.5946 1.7451 **7.899 2.2901 *2.831 .6500 1A, AO Personal .8120 .8418 .000 .8854 .006 COMMCPO 2.4865 2.0213 **5.231 2.1907 *3.326 1A, AO .6714 1.0087 .000 .8068 .002 FAIRCPO 2.6286 1.9167 **6.510 2.4909 1.259 1A, AO .8256 .8626 .000 .8511 .213 ProceOc OPENCPO 2.2895 1.6600 **6.116 1.9589 *3.212 1 1A, AO .7771 .8369 .000 .7102 .002 2.4390 CONSICPO 2.5676 1.8980 **6.051 2.1716 **3.579 .5966 1A, AO .8354 .9111 .000 .7876 .001 Procedural CONSECPO 2.2703 1.9574 **3.830 2.1917 .962 1A, AO .6167 .8855 .000 .7149 .340 EFFECCPO 2.5556 2.0000 **5.840 2.2748 *2.951 1A, AO .7182 .8660 .000 .7898 .005 ProfesOc EFFICCPO 2.4474 1.9592 **6.263 2.2200 *2.917 3 1A, AO .5885 .8443 .000 .7031 .005 2.5165 JUDGECPO 2.7297 1.8200 **8.651 2.2179 **4.867 .6051 1A, AO .7939 1.0297 .000 .9478 .000 Professional COMPECPO 2.3333 1.4286 **8.519 1.8705 4.358 1A, AO .8018 .6547 .000 .8272 .000 RESPOCPO 2.4737 1.7083 **6.715 2.1767 *2.605 1A, AO .8606 .7309 .000 .9038 .012 PolitiOc PERSUCPO 2.4474 1.8571 **7.210 2.1083 **4.142 4 1A, AO .6181 .7792 .000 .6569 .000 2.5593
Political Political BARGACPO 2.7568 2.3469 **4.172 2.3829 **3.805 .5749 1A, AO .7417 .9920 .000 .7992 .000 - Variety Variables Reliability Coefficients (15 items) alpha = .9389, Standardized item alpha = .9403. - Decision Type Variables Reliability Coefficients (4 items) alpha = .9364, Standardized item alpha = .9375. - Independent variable names correspond to actor variety variables from Table 2.4. For example, COMPCPO is the Compassion scores for all respondents concerning community partners. COMPA1_O is all respondents for judges only, and COMPAO is all respondents for Administrators. - Highest agreeability scores for each type in bold, lowest in italics (lower score = higher agreement). - Degrees of Freedom (df) for ((CPO) : (1A)) = N-1. “One-Sample t Test” function used in SPSS for t scores and significance (2-tailed). Two tailed test level of significance (.05) at 56 degrees of freedom is 2.021. * significant at the .05 level of probability (p < .05). ** significant at the .01 level of probability (p < .01).
111 have this focus of legal attention. It is interesting, however, that there are still many statistically significant differences apparent when comparing partner scores to those of administrators (CPO : AO). This may indicate a general belief that community partners are not yet fully integrated into the operational process of the RCP, and that the implementation process still needs to consider a more direct connection with them before the court is considered fully consolidated. As far as individual decision types are concerned, community partner in Ohio are ranked first overall in their consideration of Procedural matters (2.4390). Within this decision type, partners gain the most agreement in their ability to form a consensus when making decisions (2.2703), but are scored lowest on their application of fairness (2.6286). There is a significant difference between this high and low score (**-4.387 @ .000; not shown in Table 4.7). Comparatively in the procedural type of decision, judges are given the least level of agreement on building a consensus. Partners are ranked second in Personal type decision making. They are scored highest in agreement on the variable variety of compassion (2.4000), compared to judges and administrators that are scored highest in agreement on conscientiousness. Professionally, community partners, like judges and administrators, are scored highest in agreement for their competence (2.3333) in decision making, but partners are rated lowest on their judgement (2.7297). The difference between these high and low scores is significant (**-3.732 @ .000; not shown in Table 4.7). Ranked least likely to make Political type decisions, community partners, like judges and administrators, are scored least likely to bargain with others when deciding a case. Indiana Community Partners by Decision Type In looking at Indiana community partner agreement scores (Table 4.8) for variable varieties compared to those of the judge (CPI : JA), as in Ohio, there is a significant difference noted for every one. Also as in Ohio, much of this difference can be attributed to community partners being many, and the judge being a single point of reference for survey respondents. Additionally, the judge occupies a unique position both operationally and psychologically in the life of the RCP and its implementation. The significant difference across all variable varieties between partners and the judge may, however,
112 indicate a disconnect in the operational decision making process of the RCP model that needs greater coordination to overcome. Indiana community partners are rated highest in agreement in the Professional decision type. Within this decision type community partners, like the judge and administrators, are ranked highest in agreement on their competence (2.0000) in decision making. Second ranked decision type in agreement scores for community partners is the Personal type decision. Here partners, like the judge and administrators, are scored highest in agreement in the variable variety of conscientiousness (1.8378). In fact, this is the highest agreement score of all fifteen variable varieties for community partners. surprisingly, however, partners are scored lowest in agreement on communication (2.2535). There is a significant difference between these two scores (**-5.812 @ .000). Procedurally, partners are scored highest in openness (2.0563) and lowest in agreement on consistency (2.2639). These high and low scores are matched by Indiana administrators. Interestingly, the procedural type decision is the only one that exhibits no significant difference between the scores of community partners and administrators. Community partners in Indiana are scored identically to the judge and administrators in order of agreement for their Political decisions, with responsiveness gaining the highest agreement (2.0411) and bargaining the least (2.3014). Ohio and Indiana Community Partner Decisions by Category and Division Discretion: Responsibility and Accountability In remembering that Accountability is the most influential category in the decisions of judges and administrators, it is not surprising that survey respondents in both jurisdictions concur that community partners share this tendency. In fact, when comparing the rank order of Indiana community partners by category with the previous rankings of the Indiana judge and administrators (Tables 4.3 and 4.6), an identical match in order is observed. Even though the rank orders are the same across the three actor categories in Indiana, the category scores comparatively are significantly different. The strength of agreement is strongest with the judge, and weakest with the community
113 Table 4.8: Indiana Reentry Court Community Partners’ Mean Scores by Decision Type (Lower Scores = Higher Agreement) SPSS Partner: Judge: Admin: Decision T Variable All All (CPI) : (JA) All (CPI) : (INA) Type: R y Variety (CPI) (JA) t test/ (INA) t test/ SPSS a p Names Mean/ Mean/ Signif. Mean/ Signif. Variable n e (3x) Std Dev Std Dev (2-tail) Std Dev (2-tail) Mean/ Std k N=89 N=89 N=89 Dev COMPCPI 2.1507 1.6914 **4.746 1.9428 *2.148 JA, INA .9129 .8068 .000 .7535 .034 PersoIc CONSCPI 1.8378 1.4691 **5.156 1.7268 1.553 2 JA, INA .6747 .6232 .000 .6223 .124 2.1112 COOPCPI 2.2027 1.7564 **4.473 1.9006 *3.028 .7548 JA, INA Personal .9412 .8553 .000 .8178 .003 COMMCPI 2.2535 1.7200 **5.298 1.9134 **3.377 JA, INA .9501 .7317 .000 .6912 .001 FAIRCPI 2.1268 1.6667 **4.943 1.9631 1.758 JA, INA .8781 .8483 .000 .7333 .082 ProceIc OPENCPI 2.0563 1.6923 **4.045 1.8835 1.915 3 JA, INA .8513 .7120 .000 .7122 .059 2.1563 CONSICPI 2.2639 1.8421 **4.123 2.1288 1.320 .7831 JA, INA .9652 .9421 .000 .8671 .190 Procedural CONSECPI 2.1781 1.7792 **4.459 2.0744 1.159 JA, INA .8440 .8611 .000 .8110 .250 EFFECCPI 2.0676 1.6329 **4.283 1.8402 *2.240 JA, INA .9574 .7099 .000 .6839 .028 ProfesIc EFFICCPI 2.0704 1.7500 **3.703 1.9742 1.112 1 JA, INA .8164 .7091 .000 .6833 .269 2.0780 JUDGECPI 2.1739 1.5714 **6.470 1.9149 *2.782 .7558 JA, INA .8785 .7140 .000 .7004 .007 Professional COMPECPI 2.0000 1.4935 **5.886 1.6933 **3.564 JA, INA .8118 .6147 .000 .6393 .001 RESPOCPI 2.0411 1.5641 **5.410 1.8856 1.764 JA, INA .8317 .7005 .000 .6936 .081 PolitiIc PERSUCPI 2.2329 1.8400 **4.525 2.0277 *2.363 4 JA, INA .8191 .9796 .000 .6479 .020 2.1918
Political Political BARGACPI 2.3014 2.0000 **3.299 2.2133 .964 .7591 JA, INA .8619 .9045 .001 .7627 .338 - Variety Variables Reliability Coefficients (15 items) alpha = .9628, Standardized item alpha = .9633. - Decision Type Variables Reliability Coefficients (4 items) alpha = .9404, Standardized item alpha = .9406. - Independent variable names correspond to actor variety variables from Table 2.4. For example, COMPCPI is the Compassion scores for all respondents concerning community partners. INJALL1-15 is all respondents for judges only, and COMPINA is all respondents for Administrators. - Highest agreeability scores for each type in bold, lowest in italics (lower score = higher agreement). - Degrees of Freedom (df) for ((CPO) : (1A)) = N-1. “One-Sample t Test” function used in SPSS for t scores and significance (2-tailed). Two tailed test level of significance (.05) at 88 degrees of freedom is 2.000. * significant at the .05 level of probability (p < .05). ** significant at the .01 level of probability (p < .01).
114 partners. In contrast, the rank orders are not the same across actor categories in Ohio. Like Indiana, however, the strength of agreement is highest for the judges and weakest for the community partners. This again is an indication of the central importance of the judges in the RCP model. The identical progression of highest to lowest agreement scores from the judges through administrators to the community partners is a stable trend that warrants further investigation. Responsibility agreement scores for Ohio (2.5145) and Indiana (2.0965) community partners ranks third and second most influential respectively. Within each jurisdictional category, Ohio partners are ranked highest in compassion (2.4000), while Indiana partners are ranked lowest in this variety (2.1507). Another direct reversal in agreement scores is seen within the Accountability category, where Ohio partners are scored lowest in conscientiousness (2.5526), while Indiana partners are scored highest in agreement for this same variety (1.8378). Regardless of this opposite ranking, accountability remains the most influential category in the decision making behavior of community partners in both jurisdictions. Resources: Expertise and Material For both jurisdictions of community partners, material resources (communication + consensus + competence + bargaining) are a more important influence on decision making than is expertise (cooperation + consistency + judgment + persuasion). In comparing category agreement scores within jurisdictions, however, there is no statistical difference between material and expertise, or any other category. An opposition of ratings is observed again across jurisdictions in the Expertise category, with judgment receiving the lowest scores in Ohio (2.7297), and the highest agreement scores in Indiana (2.1739). Survey respondents in both jurisdictions are unanimous in their low agreement scores in the category of Material resources concerning the bargaining behavior of community partners (2.7568 and 2.3014 respectively). The Community Partners’ Implementation Decisions It is apparent from the discussion in the precious section that the external/formal and rational/regime influence of Accountability is the most influential factor in the decisions of community partners. This primary influence is shared by the other actors in both jurisdictions. When analyzed at the aggregate level in the division scores of
115 Table 4.9: Reentry Court Community Partners’ Decisions by Division & Category (Lower Scores = Higher Agreement) C SPSS Ohio Ohio R Indiana Indiana R OH/IN Division A Variable Partner: Partner: A Partner: Partner: A Discretion Variety Variety Category N Variety Category N Resources T K K Y. (2x) Mean/ Mean/Std Mean/ Mean/Std Division Std Dev Dev Std Dev Dev Mean/Std Dev COMPCPO, 2.4000 2.1507 CPI .7606 ResponOc .9129 ResponIc DiscreOc FAIRCPO, 2.6286 2.1268 CPI .8256 2.5145 3 .8781 2.0965 2 2.4721 EFFECCPO, 2.5556 .6273 2.0676 .7540 .6036 CPI .7182 .9574 (Normative/Ind.) Internal/Informal Responsibility RESPOCPO, 2.4737 2.0411 CPI .8606 .8317 DiscreIc CONSCPO, 2.5526 1.8378 Discretion CPI .9003 AccounOc .6747 AccounIc 2.0424 .7070 OPENCPO, 2.2895 2.0563 CPI .7771 2.4298 1 .8513 1.9882 1 .6280 .6973 EFFICCPO, 2.4474 2.0704
External/Formal CPI (Rational/Regime) Accountability .5885 .8164 COOPCPO, 2.5946 2.2027 CPI .8120 ExpertOc .9412 ExpertIc ResourOc CONSICPO, 2.5676 2.2639 CPI .8354 2.5848 4 .9652 2.2183 4 2.5233 JUDGECPO, 2.7297 .5655 2.1739 .7606 .5465 CPI
Expertise .7939 .8785 Internal/Formal PERSUCPO, 2.4474 2.2329 (Normative/Regime) (Normative/Regime) CPI .6181 .8191 ResourIc COMMCPO, 2.4865 2.2535 CPI 6714 MateriOc .9501 MateriIc 2.2008 Resources CONSECPO, 2.2703 2.1781 .7274 CPI .6167 2.4617 2 .8440 2.1832 3 COMPECPO 2.3333 .5888 2.0000 .7263 CPI Material .8018 .8118 (Rational/Ind.)
External/Informal BARGACPO, 2.7568 2.3014 CPI .7417 .8619 Data for Ohio Administrators: N=57. Variety Variables Reliability Coefficients (15 items) alpha = .9389, Standardized item alpha = .9403. Category Variables Reliability Coefficients (4 items) alpha = .9473, Standardized item alpha = .9478. Division Variables Reliability (2 items) alpha = .9440, Standardized item alpha = 9464. Data for Indiana Administrators: N=89. Variety Variables Reliability Coefficients (15 items) alpha = .9628, Standardized item alpha = .9633. Category Variables Reliability Coefficients (4 items) alpha = .9671, Standardized item alpha = .9673. Division Variables Reliability (2 items) alpha = .9536, standardized item alpha = .9538.
116 Discretion and Resources, discretion is more influential in the decision making behavior of community partners than is resources. The difference between the agreement scores is significant in Indiana (*-2.114 @ .037; not shown in Table 4.9), but not in Ohio. Aggregated Findings How are RCPs being implemented? The answer is found in the values-based decisions of the actors in the process whose intent it is to solve real problems in their communities. Solving social problems is not an exact science, and neither is the implementation of RCPs. A key assumption of this study is that there is no clear distinction between operational and implementation decisions in examples of bottom-up, experimental policy implementation. RCPs as an example of experimental implementation are an interesting mix of inter and intra-governmental cooperation, with private and nonprofit partnership relationships added for needed effect. In realizing this, and in answering the fundamental research question, both similarities and disparities in how each of the key actors in the RCP implementation process make decisions is expected. The systematic way in which the data is presented in this study serves not only to illustrate the combinations of values-based influences on the decision making process of policy implementation, but to give the key actors an insight into their own and others’ decision making behavior. The intended results of both of these aspects of presentation is to better enable the social science understanding of policy implementation, and to assist policy practitioners as they move forward in the daily performance of their craft. Decision Making as the Key to Understanding Policy Implementation Table 4.10 is an overall presentation of the two main ways in which the decisions of policy implementation actors are measured in this study: by type and category. Presenting the data in this consolidated way after already discussing in detail the specifics of variable values and varieties, type and category, and actor and jurisdiction, provides for a conclusionary foundation for overall study findings and recommendations. The following sections will discuss by jurisdiction and actor the types and category combinations of variable varieties that inform and influence operational and implementation decision making.
117 Table 4.10: All Actors’ Mean Scores Compared by Decision Type and Category (Lower Scores = Higher Agreement) (A) (B) (C) (D) C (E) (F) (G) (H) T Ohio: Ohio: Indiana: Indiana: A Ohio: Ohio: Indiana: Indiana: y ALL (j : a, c) ALL (j : a, c) T ALL (j : a, c) ALL (j : a, c) p Rank & t test/ Rank & t test/ E Rank & t test/ Rank & t test/ e Variable Signif. Variable Signif. G Variable Signif. Variable Signif. O Mean/ Std (2-tailed) Mean/ Std (2-tail) R Mean/ Std (2-tailed) Mean/ Std (2-tailed) Dev Dev Y Dev Dev 1. Personj 2. PersoIj 2. Responsj 2. ResponIj
1.7198 ------1.6592 ------1.8119 ------1.6388 ------y .6878 .6079 .6777 .6117 4. PersoOa 2. PersoIa 4. ResponOa 2. ResponIa 2.2255 **-5.551 1.8709 **-3.285 2.3055 **-5.499 1.9079 **-4.151 onsibilit
.6922 .000 .6437 .001 p .7059 .000 .6107 .000 Personal 2. PersoOc 2. PersoIc 3. ResponOc 2. ResponIc 2.5084 **-8.656 2.1112 **-7.014 Res 2.5145 **-7.827 2.0965 **-7.059 .6500 .000 .7548 .000 .6273 .000 .7540 .000 3. Procedj 3. ProceIj 1. Accountj 1. AccounIj
1.8580 1.7451 ------1.7031 ------1.6371 ------y .6868 .6703 .6800 .5752 2. ProceOa 3. ProceIa 1. AccounOa 1. AccounIa 2.2033 **-3.796 2.0124 **-3.762 2.1069 **-4.483 1.8615 **-3.680 .6442 .000 .6423 .000 .6677 .000 .6000 .000
Procedural 1. ProceOc 3. ProceIc 1. AccounOc 1. AccounIc 2.4390 **-6.387 2.1563 **-5.788 Accountabilit 2.4298 **-8.068 1.9882 **-5.758 .5966 .000 .7831 .000 .6280 .000 .6973 .000 2. Professj 1. ProfesIj 3. Expertj 4. ExpertIj 1.8019 ------1.6120 ------1.8301 ------1.7525 ------.7270 .6129 .6979 .6572 1. ProfesOa 1. ProfesIa 3. ExpertOa 4. ExpertIa
2.1458 **-3.571 1.8556 **-3.750 ertise 2.1970 **-3.970 1.9930 **-3.453 .7326 .001 .5913 .000 p .6620 .000 .6102 .001 Ex
Professional 3. ProfesOc 1. ProfesIc 4. ExpertOc 4. ExpertIc 2.5165 **-7.421 2.0780 **-7.173 2.5848 **-8.165 2.2183 **-6.687 .6051 .000 .7558 .000 .5655 .000 .7606 .000 4. Politicj 4. PolitiIj 4. Materiaj 3. MateriIj 1.9708 ------1.8014 ------1.9386 ------1.7482 ------.6679 .6554 .6718 .5683 3. PolitiOa 4. PolitiIa 2. MateriOa 3. MateriIa 2.2226 *-2.846 2.0422 **-3.467 2.1518 *-2.396 1.9736 **-3.742 .6399 .006 .6045 .001 .6467 .020 .5742 .000 Political Political 4. PolitiOc 4. PolitiIc Material 2. MateriOc 3. MateriIc 2.5593 **-6.652 2.1918 **-5.620 2.4617 **-5.879 2.1832 **-7.221 .5749 .000 .7591 .000 .5888 .000 .7263 .000 - Degrees of freedom (df) for Ohio variable t test is 56; for Indiana it is 88. ** Significant at the p < .01 * Significant at the p < .05
118 Ohio RCP Actor Decisions Informed by Type The premise of this research model is that all decision making is values-based and occurs along a spectrum of values from the purely altruistic, or selfless to the purely rational, or self-interested. This assumption is operationalized in the basic research model as presented in Table 2.4 and transferred to the survey instrument in Appendix C. With this firmly in mind, and building upon the data presented in Tables 4.1 through 4.9, the organization of Table 4.10 is best understood, from left to right and top to bottom, as representing this values-based informed and influenced decision making spectrum. In this model, type informs decisions, category influences decision. This basic definition has been utilized in previous sections. A simple distinction between the two is that the category is generally considered to be the “strongest” factor of the two in decision making, even though this can vary in individual cases. In Ohio RCP implementation, the Personal type considerations (compassion + conscientiousness + cooperation + communication) in decision making inform actors in various strengths. Ohio RCP judges are most strongly informed by this type of consideration in implementation decision making (number 1 appears beside the SPSS variable Personj in column A). In contrast, administrators are rated least in agreement (number 4 appears beside the SPSS variable PersoOa), and community partners at the second highest level of agreement (PersoOc). An interesting pattern that is observed in this type and continues throughout the entire table is that judges are uniformly scored higher in agreement regardless of the overall ranking, followed by administrators, and then community partners. This is further indication of the unique and influential position that the judges hold in the RCP model. The testing of the significance of agreement scores of judges compared to administrators and community partners is presented in column B. Not only do the rankings of these three actors differ for the Personal type, but the difference between the agreement scores is significant at the p < .001 level in both cases (-5.551 and -8.656 respectively). When Procedural considerations inform decision making (fairness + openness + consistency + consensus), community partners are rated number 1 in agreement scores, administrators second, and judges third. This seems to indicate that community partners in Ohio are much more informed by procedural guidelines and limitations as members of
119 the private and nonprofit sector than are the government representatives in the RCP implementation process. Professional type considerations (effectiveness + efficiency + judgment + competence) are ranked as the most important aspect of information in the decisions of Ohio administrators. Judges and community partners are ranked second and third respectively. The number one ranking of Ohio administrators in this type may indicate a manifestation of self-developed professional training and administrative learning programs internally to the RCP that are intended to establish and routinize RCP supervision.106 Political considerations (responsiveness + persuasion + bargaining) least inform the decisions of judges and community partners, and are ranked third for administrators. This finding is interesting particularly for judges as they are the only elected officials directly involved in RCP implementation. It seems that their political allegiance remains directed outward, and closely linked to the category of Accountability through the variable variety of responsiveness, to the community rather than inward toward RCP implementation decisions. Indiana RCP Actor Decisions Informed by Type In looking at the decision types for Indiana actors in column C of Table 4.10, the pattern is repeated in one sense as seen for Ohio actors, but surprisingly different in another sense. Like Ohio judges, the Indiana RCP judge is uniformly scored at higher levels of agreement in all types of decisions. The differences between the agreement scores in each type when compared by actor are also significant as with Ohio. A distinct and interesting dissimilarity is apparent between the Ohio agreement rankings by actor versus that of Indiana. Ohio actors were each ranked differently from one another by type but Indiana actors all received the identical ranking orders. For example, the ranking order for actors in Ohio for the Personal type decision for judges, administrators, and community partners is first, fourth, and second respectively. In contrast Indiana actors’ Personal type rankings are uniformly placed second. This identical ranking pattern is
106 This program in practice pushes more power down to the parole/probation officers and has the effect of motivating and incentivising coordination and the cooperative monitoring of offenders. Workloads are high at face value, but in fact there are many more people monitoring offenders than just the assigned officer. Officers know they have the judges’ ear, and that the judge will back them up in their actions in enforcing the judge’s intent for the offender (based on courtroom and pre-staffing meeting guidance). In order to ensure the integrity of the program and develop this positive chemistry, the Ohio RCP is staffed with volunteer officers who are selectively qualified based on their training and prior work habits.
120 repeated not only for every other decision type, but is also registered in every category of decision. The presence of this interesting pattern warrants further investigation. Possible explanations may be found in the fact that Indiana has established a uniform statewide legal basis in legislation for the operation and funding of community corrections and reentry programs whereas Ohio has not. A further development of this explanation may be that the Indiana RCP has utilized its well established and integrated community corrections organization as the operational and implementation foundation for its RCP program. Professional considerations (effectiveness + efficiency + judgment + competence) mark the highest respondent agreement scores for all Indiana actors’ decision making behavior. It is interesting that even though the rank scores are identical, there still remains a significant difference between the strength of the agreement scores compared across categories of actors. When the agreement score for the judge’s Professional type decisions (ProfesIj; 1.6120) is compared to both the administrators’ (ProfesIa; 1.8556) and the community partners’ (ProfesIc; 2.0780) in column D, a statistically significant difference is observed for both at the p < .001 level (-3.750 and -7.173 respectively). This is further evidence of the unique and influential position occupied by the judge in the RCP model, even when the rank order of importance for decision type variables is otherwise identical. Political type decisions (responsiveness + persuasion + bargaining) are agreed to be least informational in the decisions of all Indiana RCP actors. Again, this may be best explained by the underlying and well established organization and routinized operations of community corrections in the Indiana jurisdiction. Ohio RCP Actor Decisions Influenced by Category There is unanimous agreement among survey respondents that the category of Accountability (conscientiousness + openness + efficiency + responsiveness) is the most influential in the decision making behavior of all Ohio RCP actors. Within this category again, however, is significant difference between agreement scores compared across actors (-4.483 and -8.068). In other words, even though all survey respondents agree that accountability is most influential in the decision making behavior of judges, administrators, and community partners, their strength of agreement differs significantly by actor. It should be apparent at this point in the analysis of survey data that the RCP
121 judges are the focal point of participant attention and interest. The unanimous finding of the high importance of accountability of all actor behavior in the RCP implementation process in conjunction with the significant differences between actor scores seemingly validates the central tenant of the RCP operational model. This central tenant, simply stated in negative terms, is that without the direct involvement of a politically selected judge, the program’s intent of offender reentry into the community is without an operational and legal anchor that other actors cannot replace. The respondent survey agreement scores as analyzed throughout this chapter reinforce this assumption, and seem to lend it operational and implementational credence. The second most important category that influences the Ohio judges’ decision making is Responsibility. Combined with the category scores of Accountability, it is shown that Ohio respondents agree in the highest numbers that Discretion (responsibility + accountability) is the most influential factor in judges’ decisions. This finding does not eliminate the influence of Resources (expertise + material) from the equation, but does indicate a predisposition of the judges to readily apply discretion to decision making both in the open courtroom, and in staffing meetings. It also may indicate that responsibility for the reentry of offenders is transferred conceptually from the administrators that directly supervise the offender (Responsibility rated least in agreement for administrators) to the judges in the RCP model. Material influences (communication + consensus + competence + bargaining) are rated second in importance by Ohio respondents for both administrator and community partner decision making behavior (least important for judges). This may be an indication of the closer working relationship that administrators and community partners share outside the formal setting of the courtroom. Probation and parole officers frequently have contact with community partners in the daily performance of the supervisory role of the offender. This extra-organizational contact provides a basis for the application of the variable varieties that compose the category of Material, and the opportunity for administrators to deliver a ready-made solution concerning an offender to the judge at RCP pre-meetings. Indiana RCP Actor Decisions Influenced by Category Just as for the types of information effecting decision making, the categories of influence for all Indiana actors displayed in column G of Table 4.10 show a uniform
122 ranking order (1. accountability, 2. responsibility, 3. material, 4. expertise). Within this uniformity is the only matching concurrence between jurisdictions; that of Accountability sharing the overall highest agreement scores in Ohio and Indiana. An additional interesting finding in the Indiana data is that Responsibility is the second highest in agreement scores for all actors. Not only is discretionary decision making (accountability + responsibility) most likely practiced by the judge in Indiana (as in Ohio), it is also just as likely to be practiced by administrators and community partners in Indiana. This indicates that for all actors in the implementation process of the Indiana RCP, discretionary influences are more often consulted than are resource related influences. This is not to say that resources (expertise + material) are not important, but that operationally, the application of discretion is believed to be more important for problem solving than the application of resources. The prime importance of discretion to the decision making behavior of all Indiana actors may be partially explained in the well established foundation of community corrections. The legal and organizational benefits of this arrangement have been previously discussed (chapter 3). Actors in the community corrections environment, being freed from the initial complications of establishing working relationships with other government agencies and community partners, may now be able to focus on the goal at hand: successful offender reentry. The survey data presented in this chapter for Indiana may indicate that initial operational and implementation related concerns have been overcome, and discretionary decisions informed by professional considerations have become routine. Findings and Recommendations The RCP programs that are part of this study began when a group of concerned citizens, elected judges among them, started to imagine ways that they could positively address a problem in their communities. These self-selected judges, administrators, and community partners agreed that the traditional means of dealing with post-release offenders was failing. Additionally, agreement was reached in both jurisdictions that the best way to attack the problem of offender recidivism was to create and implement a new operational model. The RCP models for both jurisdictions in this study have been described and discussed at length. The collected data has been presented and analyzed in order to answer the fundamental research question. In so doing, the qualitative discussion
123 and quantitative analysis has lead to a fundamental finding: judges at the community level can be powerful agents for social change. This finding was not apparent when this study first began. In fact, for both jurisdictions in this study, the judges simply wanted to compare in practice the RCP model with the traditional way of doing post-release supervision. The initial hope was to find a community-based way to reduce recidivism rates. The intent was to provide a working model to observe and measure any differences in the life of the offender and the community. In fact, an atypical and socially influential role for elected judges has been created and operationalized. This new role for judges will be the subject of future research. The future discussion and analysis of RCP judges’ self- selecting behavior and commitment to solving community crime problems will be framed in perspectives ranging from public policy innovation to judicial activism. Another key finding of this study is that an actor’s sense of accountability is the strongest influence on decision making in the implementation process. This is true across actor category and jurisdiction. At the top of the RCP model, and as the only politically selected participant, the judge uniquely represents and is accountable to the community in the execution of his largely voluntary duties in RCP implementation decisions. It can be said as well that it is the judge’s sense of accountability to the community that compelled participation in this experimental program in the first place. A judge’s decisions in the implementation process can and do have a community-wide impact. Without the direct accountability the judge has to the community, the RCP model would be headless and likely aimless. Administrators in both jurisdictions, on the other hand, are accountable to their respective government agencies, which in turn are accountable to the community. Professional concerns are the most likely considerations to inform administrators’ decisions in both jurisdictions, and without their innovation and expertise, RCPs would be without the technical and tactical knowledge necessary to organize and operate. Community partners, as the private and nonprofit representatives in the RCP model, also exhibit a high degree of accountability to the community through the application of their treatment and counseling services. Funding is the primary agent of accountability in the
124 case of private agencies, and moral accountability is fundamental to the many faith-based organizations involved in RCP implementation.107 The results reported in this study are preliminary and limited. They serve to illustrate the dynamic processes involved in public policy implementation. The presentation of qualitative program information in chapter three orients the reader to the administrative structures influencing decisions of the implementation actors. This final chapter presents quantitative data in raw form that is interpreted and informed by the qualitative structure previously provided. In following this arrangement, the decisions of actors are explained in relation to the complex convergence of individual actor perspectives and influences in the implementation process. This exercise serves first to paint a descriptive picture of the craft of public administration from a RCP participant’s perspective. Second and most important for the study and development of RCPs generally, it sets the stage for the prescriptive discussion of operational preconditions necessary to direct future court development. This important first step in understanding the decisions of actors in this extremely dynamic process also provides current courts with a limited program evaluation, and potential RCP jurisdictions with a baseline of program and process information. Given the qualitative and quantitative discussion and analysis contained in this study, and the singular importance of the judge to the reentry model, the preconditions necessary for the successful operation of RCPs are found in three areas: • Mandatory offender participation • Judicial/Executive branch communication • State legal codification
Without a system to ensure the mandatory participation of offenders returning to the community, the RCP will fail for lack of a focal point of action. The RCP that originated and quickly dissolved in Florida failed because of no post-release supervision authority (no state parole system and determinate sentencing). The Florida RCP
107 In the words of one RCP judge: “Get the local churches involved. I know that offenders are much more likely to have a change of heart if there is a religious component involved. I have seen it over and over again in people I thought were beyond hope. I want offenders to associate with winners as much as possible. The greatest predictor of whether or not an offender will make it on the outside is the people that he is associating with. The best sources of winners are those associated with the church because they are always encouraging and offering to help the offender.”
125 attempted to organize and rely on post-release volunteer offenders that were under no legal obligation for the supervision required under the RCP program. This reliance on volunteer offenders resulted in only a handful of participants, and the rapid cessation of RCP operations.108 The system of post-release supervision that the Ohio and Indiana RCPs rely on is currently a cooperative hybrid of parole and probation supervision. This hybrid system is incentivised and presented to the offender as a better way to successfully reenter the community, but mandatory participation in post-release supervision is still required by law. The RCP model envisions a unified system of post-release supervision that ultimately allows for the judge alone to direct reentry supervision. This positioning of the judge requires legal codification at the state level and the redefining of judicial and executive branch roles in the post-release supervision of offenders. The current hybrid form of post-release supervision in RCPs relies heavily on the professional lines of communication developed between judicial and executive personnel in the operational model. Once this avenue of two-way communication is established and exercised, workloads of supervising officers are lightened. This economy of scale is not initially found in the total numbers of cases supervised, but in the sharing of supervisory information and contact responsibilities. The sharing of this information is achieved in formal staffing meetings as well as “on the street” as case officers become familiar with all RCP offenders and the judge’s supervisory and reentry program intent for each. In this way each supervising officer frequently updates contact information on others’ caseloads and shares data either electronically through handheld devices, or face-to-face at weekly coordination meetings. Indiana currently has developed an intermediary case officer that supplants in practice both probation and parole officers for post-release supervision. Case officers still rely on probation and parole legal authority for the disposition of cases, but the unification of supervisory responsibility under one legal authority is the goal desired by the RCP model. The new lines of communication and formal organizational practices established between the judicial and executive branches of government in the RCP model need to be formally recognized and codified in state law. Indiana’s Community Corrections
108 At the time that Florida ceased RCP operations, they had only four volunteer offenders participating in the program. This same fate was met by an early RCP experiment in the state of Kentucky.
126 legislation is the best example to date for this formal recognition. It has been revised and adjusted to fit the RCP program in practice. Without statewide legal acknowledgement and authorization for RCP operations, jurisdictions will be hesitant to make the commitment to these new programs. Much of the administrative resistance and constitutional debate of the legal recognition of RCPs will be in the necessity of ceding some authority from the executive to the judicial branch of government. In order for the RCPs to function most efficiently and effectively as designed, the judge needs to have supervisory authority to enforce the expectations of reentry treatment and supervision. Without this legal authority over parole as well as probation cases, judges are merely spectators in the courtroom concerning parolees. Ohio circumvents this problem in current practice by having a state parole board member seated behind the bench with the judge to address parolees. The Indiana RCP also has a state parole director present in the RCP courtroom (although not behind the bench) to formally concur with the judge’s decisions. The question remains unanswered whether state executive authorities will cede post-release supervision to the judicial branch while maintaining only corrections operations for itself as envisioned in the RCP model. Conclusion The focus of this study is on the decision making behavior of current participants in two RCP programs in order to answer the fundamental research question, “How are RCPs being implemented?” The research question has been answered, and the importance of elected judges to the social life of the community has been uncovered. Elected judges acting as social change agents in the community is a controversial suggestion in many places, and there remains a judicial hesitancy to participate in RCPs because of the lack of explicit criminal code that allows judges to assume this role. Whether RCP judges will be seen as cutting edge innovators or judicial activists remains to be seen. Current RCP participants recognize and report on the importance of the judge in the RCP model. Future study is needed to compare these opinions and observations to those that have successfully completed the program and reentered their community as productive citizens, or that were terminated from the program and returned to prison. Nonetheless, the ultimate success or failure of RCP programs is in the comparative recidivism rates of offenders. Longitudinal studies must show that recidivism rates in
127 RCP jurisdictions are statistically lower than in non-RCP jurisdictions before resources are committed on a large scale in other jurisdictions. Most importantly, it will take the personal, professional and political commitment of judges to encourage the legal and administrative changes necessary to promote these interesting, and thus far unique, social policy experiments.
128 APPENDICES
Appendix A: Case Value Key for Case Selection Table (next page):
Level of Support
City 0 County 1 State 2
Offender Selection
Juvenile 0 Adult Non-violent 1 Violent 2 All Offenders 3
Model + Judge Selection
Diversionary/Other 0 Admin-Law 0 Quasi-Judicial 1 Judicial Appointed 1 Drug Court 2 Judicial Elected 2 Reentry 3
USDOJ Pilot Study
No 0 Yes 1
Partners
Executive Only 0 Judicial Only 1 Executive-Judicial 2
129 Appendix A: Case Selection Table Jurisdictions Case St. Cty. City Offender Model USDOJ Partnership Value Selection Pilot Broward County, Florida 9 X 1 3rd degree non-violent Drug court 3 elected Yes 1 FL Dept. of Corrections Drug Court offenders; screened pre-trial judges; also may use (DOC);Daytona Beach for substance abuse 1 admin law judges 2+2 Community College 2 State of Delaware, Superior 7 X 1 Domestic violence; pre release Dom. Viol., Probation Yes 1 State dept. of corrections; Court (Sussex County) selected by prosecutor officers, only appt. state dept. of health and 2 judge 0+1 social services 2 DE (Newcastle County) 10 X 1 Random selection 6 mo. Prior Drug court w/case Yes 1 “ “ to release, repeat offenders manager and prob. 2 3 officer 2+1 El Paso County, CO, Pikes 6 X 1 High and low risk offenders, Quasi-judicial Yes 1 PPMH; admin law judges; Peak substance abuse, mental (Admin law judge) parole officers 0 Mental Health Mental Health health 3 1+0 Assoc. State of Iowa, Dept. of 6 X Violent offenders who refuse quasi-judicial (admin Yes 1 State dept. of corrections; Corrections (western region – 2 treatment, Pre-release law judges) state parole board; 8 local 1st to be implemented) assessment 2 1+0 community corrections agencies 0 Iowa (eastern region) 5 X Mental health disorders and “ “ 1+0 Yes 1 “ “ 0 2 substance abuse 1 State of KY, Administrative DOW X 1 Felony offenders w/alcohol Drug court w/elected Yes 1 Admin office of the courts; Ofc. of the Courts and drug abuse; split judge Dept. of corrections; Center (Lexington/Fayette Cty.; sentencing scheme; Shock 2+2 on Drug and Alcohol Campbell Cty.) probation population 1 Research, U.K. 2 State of NY, Division of 3 X 0 Non-violent parolees, pre- Admin law judge Yes 1 Harlem neighborhood; admin Parole release assessment 1 1+0 law judge; parole staff; center for court innovation 0 Richland County, Ohio, 11 X 1 All sentenced out of county Drug Court w/elected Yes 1 Cty Adult Probation Dept.; Adult Probation who return for reentry, except judge; Shock Cty Common Pleas Court and Dept. sex offenders or mental probation; split its Court Services Dept.; St. health; (violent and DV); pre- sentencing 2+2 Adult Parole Authority 2 sentencing 3 State of WV, Dept. of 4 X 1 Juvenile 0 Aftercare Program for Yes 1 Division of Juvenile Services; Military Affairs Violent Juvenile 21st Circuit Court District; And Public Safety (3 Cty’s.) Offenders 0+? probation officers; parents 2 Allen County, Indiana 11 X 1 Voluntary all offenders (excl. Pure Reentry Court No 0 IN Dept. of Corrections, IN Reentry Court murder) sentenced and w/elected judge General Ass. Leg., Comm. returning to cty. 3 3+2 Transitions Program, 2 Dallas County, Texas 3 X 1 Drug Offenders after 1 “Divert” Court, 0+? No 0 Probation services, public “Divert” Court mandatory resident treatment diversionary program defenders, drug treatment 1 San Francisco County, CA, DOA X 1 Violent felony offenders Resolve to Stop the Yes SFSD staff; Adult Probation Sheriff’s Office w/suspended sentence; Violence Project Dept.; Courts volunteer/recruited pre-trial (restorative)
Appendix B: System Model for RCP Experimental Implementation
Variables Independent Dependent
General Context for Variables in Democratic Implementation
Responsibility Responsibility + Expertise (Internal/Normative)2 + Informal & Formal
"High" Normative Type 1 "Personal"
Normative Variable Components
Normative "Satisficing" Type 2 "Procedural" (Formal/Regime)2 + Internal & External Expertise Accountability + Expertise Discretion Normative
DM
Resources Rational Accountability Responsibility + Material (Informal/Individual)2 + Internal & External
Rational "Satisficing" Type 3 "Professional" Rational Variable Components
"High" Rational Type 4 "Political" (External/Rational)2 + Informal & Formal Material Accountability + Material
Inputs Conversion Mechanism (Decision Making Process) Outputs (Decisions)
Feedback Outcomes
Appendix C: Participant Survey Spring 2005
(The survey appears in the format necessary to reproduce and assemble it into a booklet, therefore the question numbers appear to be out of sequence). Dear Richland County Re-entry Court Participant:
The Re-entry Court Program is the object of a social science study being conducted by a researcher from Miami University in Oxford, Ohio. The purpose of this survey questionnaire is to assess a variety of issues that Department of Political Science affect you as a re-entry court participant. Areas of interest include: Attn: Craig S. McClure Miami University 1. General individual and community demographic information, 2. general information on your involvement with the re-entry court, 1 Harrison Hall 3. your perceptions of the quality of the re-entry court, and Oxford, Ohio 45056 4. the decisions you have made while a participant in the program.
[email protected] We would appreciate your taking a few minutes to complete the enclosed survey.
The survey must be completed by a current or past participant of the re- entry court program.
Please be assured that your participation is voluntary and that individual responses will remain strictly confidential. Only an aggregated summary of all survey data will be provided in a final report to re-entry court officials.
For your convenience, we have provided a self-addressed, postage paid envelope to return your completed survey. Please return immediately upon completion.
If you have any questions regarding this survey, please contact Craig S. McClure at Miami University (513) 529-2000, or re-entry court representative Dave Leitenberger at (419) 774-5564. You may also contact the Office for the Advancement of Scholarship and Teaching at Miami University (513) 529-3734 with questions regarding your rights as a survey respondent. Thank you very much for your participation.
Craig S. McClure Miami University
Individual and Community/Court Services Information ADDITIONAL COMMENTS
1. How long have you been in the re-entry court program? □ Less than 1 month. □ 1-6 months. □ 7-12 months. □ 13-18 months. □ More than 18 months □ Did not complete □ Graduate (specify date) ______
2. How often do (did) you appear before the re-entry court judge? □ Once every 7-8 weeks. □ Once every 5-6 weeks. □ Once every 3-4 weeks. □ Once every 2 weeks. □ Once every 1 week. □ Other? ______
3. What is your age in years? ______
4. What is your sex? □ Male. □ Female.
5. What is your race? □ American Indian or Alaskan Native □ Black or African American □ Native Hawaiian or other Pacific Islander □ Asian □ Hispanic or Latino/Chicano □ White □ Other
6. What is your level of education? You have completed the survey. Thank you for taking the time to answer □ Dropped-out in grade (specify) ______these questions concerning your re-entry court program. □ Completed a vocational or technical training program □ Currently working on GED Please place the survey in the self-addressed, postage paid return □ Completed GED envelope and drop it in the mail. □ High School Diploma □ Some college Thank You! □ 2-year college graduate □ 4-year college graduate
Faced with the following decisions, which one of the four factors do you believe is most important in your decision to:
33. Gain rewards/recognition during the re-entry court program? 7. What is your legal marital status? □ commitment to self/family/friends □ Never married □ commitment to judge/case officer/P.O. □ Legally married living with spouse □ availability of program training/counseling/treatment □ Legally married but separated □ immediate need of financial/subsistence/housing services □ Living as married with partner □ Divorced 34. Follow all the requirements of your re-entry court program? □ Widowed □ commitment to self/family/friends □ commitment to judge/case officer/P.O. 8. What is your religious affiliation? □ availability of program training/counseling/treatment □ Religious, non-affiliated □ immediate need of financial/subsistence/housing services □ Christian □ Jewish 35. Successfully complete and graduate from the re-entry court program? □ Muslim □ commitment to self/family/friends □ Atheist/Agnostic □ commitment to judge/case officer/P.O. □ Other (specify) ______□ availability of program training/counseling/treatment □ immediate need of financial/subsistence/housing services 9. How often do you attend religious services? □ Never 36. Avoid re-offending during the program? □ Once a year □ commitment to self/family/friends □ Every 2-6 months □ commitment to judge/case officer/P.O. □ Once a month □ availability of program training/counseling/treatment □ 2-3 times a month □ immediate need of financial/subsistence/housing services □ Once a week □ More than once a week 37. Avoid re-offending after graduation from the program? □ commitment to self/family/friends 10. Do you have children? □ commitment to judge/case officer/P.O. □ Yes (specify how many) ______□ availability of program training/counseling/treatment □ No □ immediate need of financial/subsistence/housing services 11. If you do have children, do any of them live with you? 38. Overall, which one of the following four factors has been most □ Yes (specify how many)______important in influencing your decisions while in the re-entry court □ No program? □ commitment to self/family/friends 12. As part of your re-entry court program, are you currently assigned a □ commitment to judge/case officer/P.O. (check all that apply): □ availability of program training/counseling/treatment □ Parole officer (P.O.) □ immediate need of financial/subsistence/housing services □ Probation officer (P.O.) □ Case officer □ Community mentor □ other? Specify ______
13. How often does your supervising officer have face to face contact with Responsiveness you? 30. My ______always considers and answers my questions □ Once every 7-8 weeks. &concerns: □ Once every 5-6 weeks. □ Once every 3-4 weeks. Strongly Agree Neutral Disagree Strongly □ Once every 2 weeks. Agree Disagree □ Once every 1 week. Judge □ Other? ______Case Officer/P.O. Police Officer 14. What services have been provided to you through the re-entry court Court Staff program? (check all that apply) Community Services □ A. Drug abuse counseling/treatment. Family □ B. Alcohol abuse counseling/treatment. Friends □ C. Mental health counseling/treatment. □ D. Job search skills training and placement. Persuasiveness □ E. Referrals for job placement. 31. My ______is influential and convinces others in deciding my □ F. Education support for GED or diploma completion. case: □ G. Family counseling/services. □ H. Faith-based counseling/services Strongly Agree Neutral Disagree Strongly □ I. Housing assistance/placement. Agree Disagree □ J. Victim restitution/counseling treatment Judge □ Others? (specify) Case Officer/P.O. ______Police Officer ______Court Staff ______Community Services Family 15. Which one of the services you checked or listed above has been most Friends helpful to you? (specify letter A-J, or other you listed): ______Bargaining 32. My ______negotiates and compromises with others in deciding 16. Overall, how effective have the services provided to you been in my case: helping to solve your problems? □ Very effective. Strongly Agree Neutral Disagree Strongly □ Effective. Agree Disagree □ Neutral Judge Ineffective. □ Case Officer/P.O. □ Very ineffective. Police Officer
Court Staff 17. What service or assistance would you like to have provided to you that has not been part of re-entry court program (specify)? Community Services ______Family ______Friends ______Please check the appropriate box for each person according to your Efficiency level of agreement with the following statements regarding re-entry 27. My ______is creative and innovative in helping resolve my court: case: Compassion Strongly Agree Neutral Disagree Strongly 18. My ______shows sympathy and is concerned about me: Agree Disagree Judge Strongly Agree Neutral Disagree Strongly Case Officer/P.O. Agree Disagree Police Officer Judge Court Staff Case Officer/P.O. Community Services Police Officer Family Court Staff Friends Community Services Family Judgement Friends 28. My ______has the insight and perception to decide my case: Conscientiousness Strongly Agree Neutral Disagree Strongly 19. My ______is honest and treats me with respect: Agree Disagree Judge Strongly Agree Neutral Disagree Strongly Case Officer/P.O. Agree Disagree Police Officer Judge Court Staff Case Officer Community Services Police Officer/P.O. Family Court Staff Friends Community Services Family Competence Friends 29. My ______is qualified and capable to work on my case: Cooperation Strongly Agree Neutral Disagree Strongly 20. My ______knows and understands the details of my situation: Agree Disagree Judge Strongly Agree Neutral Disagree Strongly Agree Disagree Case Officer/P.O. Judge Police Officer Case Officer/P.O. Court Staff Police Officer Community Services Court Staff Family Community Services Friends Family Friends
Communication Consistency 21. My ______informs me about the details of my case: 24. My ______behaves uniformly and routinely in my case:
Strongly Agree Neutral Disagree Strongly Strongly Agree Neutral Disagree Strongly Agree Disagree Agree Disagree Judge Judge Case Officer/P.O. Case Officer/P.O. Police Officer Police Officer Court Staff Court Staff Community Services Community Services Family Family Friends Friends
Fairness Consensus 22. My ______is impartial and unbiased in my case: 25. My ______seeks agreement and unity with others in my case:
Strongly Agree Neutral Disagree Strongly Strongly Agree Neutral Disagree Strongly Agree Disagree Agree Disagree Judge Judge Case Officer/P.O. Case Officer/P.O. Police Officer Police Officer Court Staff Court Staff Community Services Community Services Family Family Friends Friends
Openness Effectiveness 23. My ______is honest and willing to share details of my case: 26. My ______designs clear solutions to resolve my problems:
Strongly Agree Neutral Disagree Strongly Strongly Agree Neutral Disagree Strongly Agree Disagree Agree Disagree Judge Judge Case Officer/P.O. Case Officer/P.O. Police Officer Police Officer Court Staff Court Staff Community Services Community Services Family Family Friends Friends
Appendix D: Richland County, Ohio Reentry Court Process Flowchart
Post-Release Offender
Reentry Judge & State Parole Board Member
County Probation Reentry Court State Parole Authority Coordinator Board Authority
Parole & Probation Officers
Return to Jail or Return to Prison or Electronic Community Electronic Monitoring Policing Monitoring
Probation Community Parole Supervision Partners Supervision
No No Regular appearances Sanction before Reentry Sanction Successful? Successful? Yes Court Yes
NO: Satisfactory NO: Apply Probation Progress? Apply Parole Authority Authority Sanction Sanction
Yes
Reintegrated Offender
138 Appendix E: Allen County, Indiana Reentry Court Process Flowchart
Early Release Offender
Allen County Community Corrections
Reentry Court Transition Director & Transitions Program (Judge) Treatment Staff Program
Case Manager Reentry Director Parole or Probation Supervision Supervision
Electronic Return to Jail Monitoring or Prison
Community Intervention Parole or Partners Staff Probation Monitoring No
Appearances Sanction Successful? before Judge Yes
Judge determines No : Yes satisfactory Apply Sanction progress?
Reintegrated Offender
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