PUBLIC TRUST IN GOVERNMENT: AN EXAMINATION OF CITIZEN TRUST
DIFFERENTIALS IN PUBLIC ADMINISTRATORS AND OTHER GOVERNMENT
OFFICIALS AT THE FEDERAL, STATE AND LOCAL LEVELS
A Dissertation
Presented to
The Graduate Faculty of The University of Akron
In Partial Fulfillment
of the Requirements for the Degree
Doctor of Philosophy
Eric J. Mundy
May, 2007 PUBLIC TRUST IN GOVERNMENT: AN EXAMINATION OF CITIZEN TRUST
DIFFERENTIALS IN PUBLIC ADMINISTRATORS AND OTHER GOVERNMENT
OFFICIALS AT THE FEDERAL, STATE AND LOCAL LEVELS
Eric J. Mundy
Dissertation
Approved: Accepted:
Advisor Department Chair Raymond W. Cox, III Sonia A. Alemagno
Committee Member Dean of the College Ralph P. Hummel Robert F. Levant
Committee Member Dean of the Graduate School Julia Beckett George R. Newkome
Committee Member Date Jesse F. Marquette
Committee Member Jennifer Alexander
ii ABSTRACT
This study assesses public trust in various government officials, including public administrators, elected executives, politically appointed agency officials, and legislatures, across the three levels of United States government. The study utilizes primary data from a random sample telephone survey conducted in 2004 of 1,078 adult residents of Stark County,
Ohio.
The study yielded evidence to support the assertion that the general public has a higher level of trust in federal and state public administrators compared to elected and politically appointed officials, but this was not the case for county government public administrators. Although public administrators tended to be trusted more than other government officials, they were trusted less than people in general. Likewise, most groups of government officials were trusted less than people in general.
The study also yielded evidence to support the assertion that government officials are trusted more at the local level compared to similar officials at the state and federal level. For instance, county public administrators were trusted more than their state and federal counterparts, while state public administrators were trusted more than federal administrators.
General support for government was found to be directly related to public trust in elected executives and their appointed agency executives, regardless of the level of
iii government. When controlling for the effects of trust in other government officials, trust in public administrators had no significant relationship to government support, regardless of the level of government.
Another finding of the study was that trust in public administrators was a function of respondent trust in people in general and support for the associated level of government, with societal trust being the dominant variable. This model held for all three levels of government with no other explanatory variables influencing trust in public administrators. Explanatory variables for public trust in other government were varied and dissimilar to the public administrator model with variables such as political ideology, political party affiliation and household financial status being more prominent.
iv TABLE OF CONTENTS
Page
LIST OF TABLES ...... xii
LIST OF FIGURES ...... xiv
CHAPTER
I. INTRODUCTION ...... 1
Statement of the Problem ...... 1
Lackluster Public Trust in Government ...... 2
Trust in Public Administration Understudied ...... 4
Objectives of the Research ...... 5
Importance of the Study ...... 9
II. BACKGROUND OF THE STUDY ...... 12
Early Discussions of Trust and Government ...... 12
Classical Political Philosophers ...... 13
Early Modernists ...... 14
Founders and Framers ...... 15
Tocqueville on Trust ...... 16
Contemporary Discussions of Trust and Government ...... 17
Importance of Public Trust in Government ...... 18
v Political Participation ...... 18
Citizen Compliance ...... 19
Provision of Resources ...... 20
Public Service ...... 20
Progressive Policy ...... 21
Economic Growth ...... 21
A Notable Controversy ...... 22
Public Administration Considerations ...... 23
Micro-Organizational Considerations ...... 24
Macro-Institutional Considerations ...... 25
Organizational Reform Considerations ...... 26
Conceptualizations of Trust ...... 28
Conceptual Vagueness ...... 28
Some Generalizations of Trust ...... 29
A Simple Trust Model ...... 30
Conceptualizations of Public Trust in Government ...... 31
Risk and Expectations (Barber’s Account of Trust) ...... 32
Trust in the Social Order ...... 32
Technical Competence ...... 33
Fiduciary Responsibility ...... 34
Cognitive, Affective and Behavioral Dimensions (Kim’s Account of Trust) ...... 35
Cognitive Dimensions ...... 35
vi Affective Dimensions ...... 36
Behavioral Dimensions ...... 36
Rational Versus Normative Considerations (Ruscio’s Account of Trust) ...... 37
Trust as Rational Choice ...... 37
Trust as a Normative Construct...... 39
Trust-Related Concepts ...... 40
Previous Survey Research on Trust in Government ...... 42
National Election Studies ...... 42
General Social Survey ...... 46
CEG Trust Studies ...... 48
Other Related Survey Research ...... 50
Explanations of Variations in Trust in Government ...... 55
Government Performance ...... 55
National Mood ...... 56
Political Causes ...... 57
Scope of Government ...... 58
Social/Cultural Considerations ...... 58
National Threats ...... 60
Other Considerations ...... 61
Contributions to Research Design ...... 61
III. RESEARCH DESIGN ...... 64
Scope of the Research ...... 64
vii Major Research Hypotheses ...... 66
Research Hypothesis H1 (Intra-Level Trust in Officials) ...... 70
Research Hypothesis H2 (Inter-Level Trust in Officials) ...... 73
Research Hypothesis H3 (Government Direction and Trust) ...... 77
Research Hypothesis H4 (Explanations of Public Trust) ...... 80
Research Methodology ...... 83
Study Population and Sampling ...... 83
Political-Economic Environment ...... 87
Survey Administration ...... 90
Human Subjects Review ...... 91
Survey Instrument ...... 91
Instrument Pre-Testing ...... 96
Measurement of Variables ...... 98
Statistical Analysis Techniques ...... 102
Study Limitations ...... 108
IV. RESEARCH FINDINGS ...... 112
Characteristics of the Sample ...... 112
Summary Scores: Trust In Government ...... 116
Results for Research Hypothesis H1 (Intra-Level Trust in Officials) ...... 119
H1A: Intra-Level Trust, Federal Level ...... 119
Results of H1A Sub-Hypotheses ...... 119
H1A Results Summary ...... 121
viii H1B: Intra-Level Trust, State Level ...... 124
Results of H1B Sub-Hypotheses ...... 124
H1B Results Summary ...... 126
H1C: Intra-Level, County Level ...... 128
Results of H1C Sub-Hypotheses ...... 128
H1C Results Summary ...... 130
Results for Research Hypothesis H2 (Inter-Level Trust in Officials) ...... 133
H2A: Inter-Level Trust, Public Administrators ...... 133
Results of H2A Sub-Hypotheses ...... 134
H2A Results Summary ...... 136
H2B: Inter-Level Trust, Elected Executives ...... 137
Results of H2B Sub-Hypotheses ...... 137
H2B Results Summary ...... 139
H2C: Inter-Level Trust, Executive Appointees ...... 140
Results of H2C Sub-Hypotheses ...... 140
H2C Results Summary ...... 142
H2D: Inter-Level Trust, Legislators ...... 143
Results for Research Hypothesis H3 (Government Direction and Trust) ...... 145
H3A: Government Direction and Trust, Federal Level ...... 145
Results of H3A Sub-Hypotheses ...... 146
H3A Results Summary ...... 148
H3B: Government Direction and Trust, State Level ...... 150
ix Results of H3B Sub-Hypotheses ...... 150
H3B Results Summary ...... 153
H3C: Government Direction and Trust, County Level ...... 155
Results of H3C Sub-Hypotheses ...... 155
H3C Results Summary ...... 158
Results for Research Hypothesis H4 (Explanations of Trust) ...... 160
H4A: Explanatory Variables, Federal Level ...... 160
Results of H4A Sub-Hypotheses ...... 161
H4A Results Summary ...... 164
H4B: Explanatory Variables, State Level ...... 166
Results of H4B Sub-Hypotheses ...... 166
H4B Results Summary ...... 169
H4C: Explanatory Variables, County Level ...... 172
Results of H4C Sub-Hypotheses ...... 172
H4C Results Summary ...... 175
V. CONCLUSIONS AND FUTURE DIRECTIONS ...... 178
Summary and Analysis of Results ...... 178
Summary: Research Hypothesis H1 (Intra-Level Trust in Officials) ...... 179
Summary: Research Hypothesis H2 (Inter-Level Trust in Officials) ...... 183
Summary: Research Hypothesis H3 (Government Direction and Trust) ...... 186
Summary: Research Hypothesis H4 (Explanations of Trust) ...... 190
Study Conclusions ...... 193
x Implications for Public Administration Practice ...... 194
Recommendations for Public Administration Practice ...... 198
Future Directions ...... 202
BIBLIOGRAPHY ...... 205
APPENDICES ...... 216
APPENDIX A. SURVEY INSTRUMENT ...... 217
APPENDIX B. BASIC RESPONSE FREQUENCIES ...... 239
APPENDIX C: FITTED REGRESSION TRUST MODELS ...... 283
xi LIST OF TABLES
Table Page
1.1 Summary of Research Questions ...... 9
3.1 General Research Questions and Associated Hypotheses ...... 69
3.2 Sub-Hypotheses for Research Hypothesis H1 ...... 72
3.3 Sub-Hypotheses for Research Hypothesis H2 ...... 76
3.4 Sub-Hypotheses for Research Hypothesis H3 ...... 79
3.5 Sub-Hypotheses for Research Hypothesis H4 ...... 82
3.6 Comparison Census Statistics: Stark County, Ohio, United States ...... 86
3.7 Trust-Related Variables and Measurement ...... 100
3.8 Key Demographic Variables and Measurement ...... 101
3.9 Statistical Analysis Techniques By Hypothesis ...... 107
4.1 Comparison Demographics: Census Versus Stark Poll ...... 115
4.2 Summary Scores: Trust in Government Questions ...... 118
4.3 Comparison of Means: Trust at the Federal Level ...... 123
4.4 Comparison of Means: Trust at the State Level ...... 127
4.5 Comparison of Means: Trust at the County Level ...... 132
4.6 Comparison of Means: Trust in Government Employees ...... 136
4.7 Comparison of Means: Trust in Elected Executives ...... 139
xii 4.8 Comparison of Means: Trust in Executive Appointees ...... 143
4.9 Comparison of Means: Trust in Legislatures ...... 144
4.10 Associations: Government Support and Trust in Federal Officials ...... 149
4.11 Associations: Government Support and Trust in State Officials ...... 154
4.12 Associations: Government Support and Trust in County Officials ...... 159
4.13 Fitted Regression Models: Trust in Federal Government Officials ...... 165
4.14 Fitted Regression Models: Trust in State Government Officials ...... 171
4.15 Fitted Regression Models: Trust in County Government Officials ...... 177
5.1 Summary Results: Research Hypothesis H1 ...... 182
5.2 Summary Results: Research Hypothesis H2 ...... 185
5.3 Summary Results: Research Hypothesis H3 ...... 189
5.4 Summary Results: Research Hypothesis H4 ...... 192
xiii LIST OF FIGURES
Figure Page
2.1 NES Trust in Federal Government, 1964-2004 ...... 44
2.2 NES Trust in Government Index, 1964-2004 ...... 46
2.3 CEG Confidence in Government, 1995-1999 ...... 50
xiv CHAPTER I
INTRODUCTION
Whereas the issue of public trust in government continues to garner increased attention, within both the academic and professional communities in the United States as well as internationally, many facets of the subject remain unstudied or understudied. For instance, although public trust in political leaders has been studied for decades, trust in public administrators is relatively understudied. This study seeks to contribute to a better understanding of public trust in government, focusing on trust in various government officials, including public administrators, at the three basic levels of U.S. government.
Statement of the Problem
It is generally believed that public trust and confidence in institutions and formal organizations is important for a productive society, especially with respect to government institutions in a representative democracy. With this as a guidepost, two motivations drive the research outlined herein. First, studies over the past four decades have indicated that public trust in government, in broad terms, is either lower than desired or on the decline.
1 Second, existing research on the various facets of public trust in government is lacking, especially with respect to the public administration component of government, as well as the dynamics of public trust in officials across the different major levels of U.S. government
– federal, state and local.
Lackluster Public Trust in Government
Survey research over the past forty years or so has shown diminished public trust in government. Indeed, Ruscio (1996) has commented that declining trust is one of the central problems of modern politics.
The wellspring of historical and current discussions regarding trends in, and importance of, public trust in government has been the National Election Studies (NES), a biennial national random sample telephone poll which first started in the 1940s. Since the mid 1960s, NES has asked a standardized battery of questions regarding public attitudes toward U.S. government, including a question specifically focusing on public trust in the federal government.
The NES studies have indicated that, up until the mid 1990s, the overall trend has been one of declining trust in the federal government. For instance, whereas just over three- quarters, 76%, of all survey respondents in 1964 indicated they trusted the federal government to do what is right most of the time or just about always, only 21% of respondents made similar claims in 1994. Although trust in the federal government, as measured by this NES indicator, has rebounded to some degree since 1994, public trust
2 remains substantially diminished from the favorable levels of the so-called halcyon days of political trust and support of the 1950s and 1960s.
From the onset, the data generated from the NES surveys have spurred discussions aimed at explaining public trust in government and related concepts such as confidence, cynicism and alienation, as well as whether or not diminished trust is a significant problem, and, if so, identify the undesirable effects or consequences of low trust or confidence in government. The bulk of these discussions have appeared in the political science literature, and to a lesser degree literature related to sociology. More recently, the topic of public trust in government has received the attention of some in the field of public administration ( for instance see Ruscio, 1996; Marlowe, 2004; Kim, 2005), as well as a handful of national non- profit organizations interested in good government, such as the Brookings Institution, Center for Excellence in Government, and the Pew Research Center for People and the Press.
Nye (1997) notes that declining trust and confidence in institutions is not limited to government. There appears to be more generalized trends toward declining trust and confidence at both the interpersonal and societal levels , which may be linked to declining social capital, i.e., the ability of people to work together (Putnam 1995) or an erosion of respect of authority (Mansbridge 1997), which in turn may be linked to the complexities of a modern, fragmented society due to postmaterialist or postmodern values (Inglehart 1997).
Both the General Social Survey (GSS), a national random household in-person or face-to- face survey, and the Harris Poll, a national random household telephone survey, have tracked national public confidence in major institutions in the U.S. since the early 1970s.
In general, public confidence in major institutions, such as the three branches of the federal
3 government, the news media, higher education, medicine, and major corporations, has trended downward over the past three decades.
The trend toward decreasing or lackluster trust in institutions and government is not indicative of only the United States. Many other advanced industrialized countries have seen declines in trust in government as well (Norris, 1999), such as Japan (Pharr 1997) and many Western European countries (Lipset & Schneider, 1987; Inglehart 1997). In addition, trust has been stressed as an important component in the transition of post-communist or post-socialist countries to democratic forms of governance (Mishler & Rose, 1997).
Trust in Public Administration Understudied
The second motivation for this research study is the lack of research with respect to public trust in the public administration side of government, in particular those administrators not elected or politically appointed to office. Some research regarding public confidence or public opinion in government administrators exists, but research specifically aimed at public trust is rather limited in scope, especially with respect to examining differentials in public trust between public administrators and other government officials.
This is not to say, however, that the subject has not been broached.
The Pew Research Center for the People and the Press and the Brookings Institution have been some of the first to delve into public opinion with respect to the public administration side of government. A first step was to gauge public opinion of different departments or agencies of the federal government, such as the Federal Bureau of
Investigation, the Environmental Protection Agency, the Food and Drug Administration, and
4 the Internal Revenue Service. Pew (1998) indicates that all of these departments or agencies saw declines in favorable public opinion ratings over the 1980s and 1990s. Pew also found that the majority of the public tends to trust federal government workers more than politicians in general. Some social research organizations have begun to assess public trust and confidence in the public administration side of government.
More recently, the Brookings Institution (2002) has delved further into public opinion with respect to additional federal public officials falling into the category of public administrators, namely federal government employees as well as presidential appointees that run different departments and agencies of the federal government. Brookings indicated that in 2002 the President had a higher opinion rating than federal government workers in general as well as officials appointed by the President to run federal agencies and departments, both of which had higher opinion ratings than members of Congress in general.
Objectives of the Research
The primary objective of the research is to shed more light on the subject of public trust in U.S. government. Whereas many studies have addressed the general issue of public trust in government, many facets of public trust in government have been overlooked, especially with respect to the public administration component of government and how trust in public administrators fits into the larger picture of trust in government.
Existing research has tended to focus on trust in political regimes, political leaders, or simply government in its broadest terms. For instance, consider the classic trust in
5 government question used in the National Election Studies as well as other national surveys such as those of the Pew Research Center and the Council for Excellence in Government:
How much of the time do you think you can trust the government in Washington to do what is right? Here, the definition of what is right and what constitutes the government in
Washington is rather vague and measurement error is a significant issue. There are many facets of government that are inclusive to this general notion of government. Of course, the
President, Congress, and Supreme Court would be included. However, this definition also includes a mix of elected, politically appointed and hired civil servants, as well as government bureaucracy and the various departments and agencies of federal government, in general. Moreover, the federal government is not indicative of only Washington, D.C.; that is, the federal government has offices throughout the United States as well as overseas.
Weatherford (1992) notes that trust and trustworthiness, especially with respect to government, are multi-level concepts, with notions of trust differing upon context (e.g., level of government, particular institution or bureaucracy, type of public official, etc.). As such, meaningful research and discussions of the public’s trust in government should be focused on individuals or specific entities at specific government levels.
Some existing research has attempted to de-construct public trust in government by specifically asking trust questions oriented toward specific government institutions and political leaders. What has been largely overlooked, however, is trust in public administrators or the public administration side of government, as well as how public trust in these entities differs from public trust in elected officials. The research seeks to amend
6 this shortcoming by seeking to further knowledge on a group of related questions which are outlined below.
The first general research question of this study is: does the general public trust public officials differently? More specifically, this study seeks to address the difference in public trust in public administrators and elected or politically appointed government officials, and the degree to which various government officials are trusted. Moreover, this difference, if any, will be examined across the three levels of American government. Here, four general groups of government officials – elected executives (e.g., President, state Governor), persons appointed by elected executives to run government agencies, legislatures, and public administrators – will be examined across the three levels of U.S. government: federal, state and county. As such, a total of twelve groups of government officials will be examined.
The second general research question is: does the general public trust public officials differently depending on the level of government? More specifically, this study will compare trust in local government officials to similar state and federal government officials, and assess whether or not local government officials are trusted more than state or federal public administrators. Again, four general groups of government officials – elected executives, executive appointees, legislatures, and public administrators – will be examined across the three levels of U.S. government.
The third general research question is: is public trust in government related to public support or disposition toward government? More specifically, this study will investigate the existence of a relationship between the general public’s trust in public officials and general support or disposition toward government at the federal, state and local levels, and if a
7 relationship is found, the type of relationship, positive or inverse. Moreover, the similarities of this relationship will be examined across the three levels of American government. In addition, the effects of trust in public administrators on support for government will be explored.
The fourth general research question of this study is: is the general public’s trust in government officials explained differently depending on the type of official and level of government? The variables which explain the level of trust for public administrators will be compared to other public officials. For instance, the demographic factors, if any, that influence public trust in public administrators and other government officials will be examined as well as the possibility that these explanatory variables differ depending on the level of government.
Flowing from the general research questions of interest, the specific objectives of the research are (1) to determine to what degree the public trusts public officials, both public administrators and elected officials, for each of the three levels of American government – federal, state and local government; (2) to determine if the public trusts public administrators differently than elected officials; (3) to determine if public trust in public officials influences public support for each of three levels of government; and (4) to identify demographic or political attributes that might influence public trust in public officials as well as support for each of the three levels of government.
8 Table 1.1 Summary of Research Questions
Does the general public trust public officials – elected executives, executive appointees, 1 legislatures, and public administrators – differently? Are public administrators trusted more than elected or appointed government officials?
Does the general public trust public officials differently depending on the level of 2 government – federal, state and local? Are local government officials trusted more than state and federal government officials?
Is there a relationship between the general public’s trust in public officials and general 3 support or disposition toward government at the federal, state and local levels? If there is a relationship, is it a direct relationship?
Is the general public’s trust in government officials explained differently depending on the 4 type of official and level of government? Are there different explanatory variables for public administrators compared to other officials?
Importance of the Study
This research will contribute to both the literature and the profession of public administration and democratic governance in three ways: (1) it will build upon existing knowledge and continue a trend toward the deconstruction of public trust in government,
9 and thus enhance a better understanding of the dynamics of public trust in government; (2), more specifically, it will address the lack of research on public trust in the public administration component of government; and (3) it will better inform public administrators as to citizen perceptions regarding their field, and thus set the stage for a policy response on the part of public administrators and other government officials.
First, as noted previously, research and discussion of public trust in government is evolving from generalized notions of public trust in government to more specific aspects of public trust in government. Whereas trust in government was first examined from a more global perspective, i.e., trust in the government in Washington, recent studies are increasingly focusing on different aspects of trust in government, such as confidence in specific agencies and leadership, and trust in the three basic levels of American government.
By focusing on an understudied aspect of public trust in government, that of public administration, the research will add to a better understanding of public trust in government in general.
Second, beyond facilitating a better understanding of public trust in government in general, this research will shed light on public trust in the public administration side of government. Although some studies have addressed public confidence or public opinion of various government agencies and personnel, the more focused aspect of public trust in public administration has been largely overlooked. This research will help amend this discrepancy.
Lastly, this research will better inform public administrators, as well as elected officials, as to citizen perceptions and attitudes regarding their profession. This is not to say
10 the research will address the full range of citizen perceptions and attitudes, but rather focus on an aspect of trust in public officials related to what Barber (1983) refers to as fiduciary responsibility or what Tyler and Degoey (1996) refer to as relational trust for public officials. The results of this research are expected to set the stage for future discourse regarding public trust in American public administration.
11 CHAPTER II
BACKGROUND OF THE STUDY
This research is an extension of current knowledge regarding public trust in government and builds upon existing studies. Within the broader academic community, this research is also inextricably linked to four primary schools of thought. These include the sociology literature, which has laid the theoretical foundations of trust and related concepts such as alienation; the political science literature, which has generated the most empirical evidence and discussion of public trust in government; organizational theory literature, which stresses organizational development and change with respect to enhancing public trust in institutions; and the public administration literature, which has recently begun to address issues of public trust in government. These schools of thought are not wholly isolated and much overlap occurs in terms of theory and objectives of research.
Early Discussions of Trust and Government
From a historical perspective, trust as an aspect of government has been discussed by classical political philosophers, such as Plato and Thucydides, early modernists of political
12 theory such as Hobbes, Locke and Hume, and the framers of the U.S. Constitution. This section outlines contributions from these early contributors of notions of trust in government. For the purposes of this research, early contributors are defined as those prior to the contemporary discussions, circa 1960s and onward, of trust in government.
Classical Political Philosophers
In classical political philosophy, political trust was discussed to some degree by Plato in the dialogue Protagoras and by Thucydides representation of the debate over the city of
Mytilene in The Peloponnesian War (Mara 2001). According to Mara, each text considers the question of why particular forms of trust are good for political communities, especially those guided by democratic deliberation. For instance, Thucydides’ treatment of the
Mytilenean debate indicates that political trust is central to the quality of democratic political life because it allows its members to engage difficult and controversial questions about the common good. Mara goes on to note that Plato’s dialogue extended this discussion to suggest that warranted trust in the outcomes of these engagements requires the presence of citizens who practice certain virtues, which includes a type of mistrust of the status quo.
With respect to the Republic, Price (2006i) asserts Plato’s ideal state is founded on trust, however, it is a trust that runs only one way. Ordinary citizens are expected to trust their rulers without question. But as Price goes on to note, Plato does not ask as to accept this vision, rather he presents it to us as philosophers to question and challenge.
13 Early Modernists
During early modernity, Hobbes also broaches the subject of trust in government. Per
Wolff (2006i), it is Hobbes’ contention in Leviathan that the public needs an absolute sovereign as a ruler that would have unlimited powers of rule and punishment. This is because the miseries of life, in the state of nature, can only be remedied by a sovereign with absolute powers. Such a sovereign is needed, not so much to threaten or punish, but rather to create safe conditions where citizens can trust each other and safely act as morality requires. Once the sovereign is in place to enforce rules of conduct, conditions would be created that allow citizens to do the right thing without exposing themselves to exploitation from others.
Wolff goes on to note that Hobbes’ arguments were contested by Locke in his Second
Treatise on Civil Government. For instance, Locke worried that an absolute sovereign would be even more of a danger to the public than life in the state of nature, and argued that although we need a sovereign to settle disputes and administer justice, constitutional limits are needed to temper the sovereign’s rule. For Locke, societies emerge from a state of nature as a result of a contract made among individuals to submit themselves to a ruler or rulers, i.e., the social contract. The ruler's powers are given to him as a trust for the good of the citizens, and if the trust is broken his powers can be taken away. More specifically, Dunn
(1984, 1988) asserts trust is the core of Locke’s political philosophy: the relationship of citizens to government is one of trust, not a relationship of contract.
According to Matrevers (2006i), like Hobbes, Hume in his Treatise of Human Nature also appreciated the role that trust and mistrust play in social life. However, whereas Hobbes
14 required an absolute sovereign to ensure that trust was honored in order to bring about the mutual benefits of society, Hume had a more positive outlook of humanity. Hume believed human nature makes us naturally sympathetic to the concerns of others which would in turn encourage trust. In order to bring about trust with others, he saw a process of reassurance as being necessary as opposed to coercion.
Founders and Framers
Beyond the early modernist philosophers such as Locke and Hume, trust in government was also an important issue for the founders of the United States and the framers of the U.S. Constitution. For some, such as Hetherington (2005), the founding of the United States provides a useful example regarding the desirability of public trust in government. In discussing the framing of the Constitution, Hetherington notes the framers were more distrustful of power than of the government itself. As a results, they created a system of government that fragmented power throughout government such that it would be difficult for one person or faction to capture full control.
Although the issue of trust is not explicitly stated in the Declaration of Independence or the U.S. Constitution, the issue of trust is discussed throughout the Federalist Papers. In
Federalist #70, Hamilton states “Man, in public trust, will ... act in such a manner as to render him unworthy of being any longer trusted ...” Likewise, Madison echoes this sentiment in Federalist #10 and #51. With this as a backdrop, it is widely asserted that the need for the separation of powers and a system of checks and balances is needed at least in part to distrust in the motivations of individuals. For instance, in Federalist #55, which
15 discusses the size of the House of Representatives, the authors note that a small number of men (sic) cannot be safely trusted with so much power, hence, a call for a relatively large body of representatives. Also of note, the authors also consider elected office to be synonymous with fulfilling a public trust.
In discussing constitutional law, Ely (1980) asserts such law exists for those situations where representative government cannot be trusted, and does not exist for those situations where we know representation government can be trusted. Overlooked by the federalists in outlining the Constitution was the need for a the Bill of Rights. Although the federalists did not feel a Bill of Rights was needed, the anti-federalists felt otherwise and pushed for its passage. Whereas the federalists sought to ensure trust at one level, the anti-federalists sought to ensure level on another level, namely ensuring that citizens rights would be explicitly protected.
In sum, according to Hetherington (2005), since the founders wanted to temper the natural human impulse to accumulate power, it follows that they would have wanted ordinary people to trust the institutions designed to check the worst human ambitions. As such, government with strong public trust would do a better job than government without public trust.
Tocqueville on Trust
Although the founders were focused on perhaps negative aspects of trust, such as developing a constitution that would protect from abuses of power, there were positive aspects of trust in the early history of the United States. This is illustrated in de
16 Tocqueville’s observations of American life in Democracy in America, which occurred in the 1820s. For de Tocqueville, civic community in the early United States was marked by a social fabric of trust and cooperation and reliant upon the activities of a public spirited citizenry (Szekelyi, Orkeny & Barna 2004). For him, trust permeated through American society. It was positively influenced by the presence of democracy, as well as in turn positively influencing the democratic form of government. For instance, trusting persons were more likely to participate and cooperate in willful associations, including participating in government.
Contemporary Discussions of Trust in Government
Contemporary discussions of trust in government in the political science literature began in the 1960s, spurred by the results of the NES trust in government survey questions.
For the first three decades or so, discussions were focused on elected officials. However, in the 1990s, as efforts to deconstruct the meaning of public trust in government continued, attention turned toward examining public trust in the public administration sphere of government. Similarly, organization theorists began to examine the notion of institutional trust in the 1990s, both from an internal, i.e., intra-organizational trust, and external perspective, i.e., public trust in organizations. Contemporary discussions of trust in government generally focus on explanations of public trust in government, the importance of public trust in government, and the consequences of lack of public trust in government.
17 Importance of Public Trust in Government
Trust is inextricably linked to the productive functioning of society. It is an important aspect of all social relationships (Barber 1983). Trust is considered essential for stable social relationships (Blau 1964; Luhmann 1980) and necessary for economic transactions to occur (Hirsch 1978; Fukuyama 1995). Trust is also necessary for creating the conditions for good government and democratic practices (Seligman 1997; Brathwaite 1998) as well as being a prerequisite for a representative form of governance (Mayhew 1974; Bianco
1994). Indeed, Levi and Brathwaite (1998) maintain good governance implies a mutual trust between citizens and governors as well as mutual trust among citizens themselves.
More specifically, research has focused on the importance of public trust in a democratic form of government to facilitate a variety of government functions. For instance, political trust is considered fundamentally important for cooperation and collective action, the basic building blocks of democratic governance (Gambetta 1988; North 1990; Fukuyama
1995; Levi 1997, 1998; and Weingast 1998).
Political Participation. It is widely asserted trust in government can affect political participation. However, there are two divergent claims regarding how trust actually influences political participation. One assertion is that those who trust government should be expected to participate to a greater extent than those who distrust government, at least in conventional activities such as voting and campaign involvement (Levi & Stoker 2000).
The idea that distrust might discourage political engagement was inspired by early theorizing about political disaffection and alienation (Stokes 1962; Almond & Verba 1963;
Finifter 1970) and that an ongoing decline in voter turnout coincided with a decline in trust
18 for government. Here, the logic is that, if government could not be trusted or lacked trustworthiness, citizens felt alienated from government and thus chose not to participate in government.
On the other hand, the second assertion regarding public trust and political participation is that distrust, and not trust, actually stimulates political participation (Levi
& Stoker 2000). This claim was articulated early by Gamson (1968, 1975). In this case, the logic is that those who are distrusting of government are more likely to participate in political processes as a means to change the status quo. Evidence supporting this assertion is lacking and models attempting to explain the associated dynamics are rather complex. For instance, the link between government trust or distrust with voter turnout and other forms of political participation has not been verified. As Levi and Stoker point out, a proper model linking distrust and political participation, if one were developed, would likely involve complex interactions and contingencies. Perhaps distrust may generate higher levels of participation, but only under some circumstances, for some people, and with respect to only some kinds of political activities.
Citizen Compliance. Another logical assumption regarding trust in government is that the more trustworthy citizens perceive government to be, the more likely citizens will be to comply with government laws, regulations and policies (Levi & Stoker 2000). In other words, when government is perceived as trustworthy, citizens are more likely to comply with its demands. For instance, Tyler (1990, 1998) has found that citizens are more likely to accept the mandates of courts and other government authorities. Furthermore, Levi (1988)
19 and Scholz (1998) maintain that citizens who trust the government are more likely to comply with taxation.
Ayers and Brathwaite (1992) also assert that trustworthy government increases compliance, but they also add an additional dynamic. They maintain that the trust that regulators have in citizens in turn spurs compliance with regulations. This account of trust views citizens as persons who respect the norms of trust as an obligation of citizenship in circumstances where it may or may not be rationally self-interested to do so (Brathwaite &
Makkai 1994) and implies that regulation will be most effective if it keeps punishment in the background and uses persuasion and trust to induce compliance (Ayers & Brathwaite
1992).
Provision of Resources. Beyond compliance factors, political trust may affect the willingness of the public to provide the resources necessary, such as tax dollars, to support government. This is especially the case at the state or local level where citizens have the right to vote on tax levies and other fiscal measures such as bond issues. The logic here is that, if a person is distrusting of government they will be inclined to vote against revenue issues. On the other hand, if citizens are trusting of government they will be more likely to support or vote for such revenue issues.
Public Service. Another dynamic that may be affected by levels of trust in government is the willingness of persons to enter public service (Nye 1997). That is, distrust of government may negatively affect the ability of government to recruit people to work in the public sector. The 1998 Pew Research Center study found a moderately strong relationship between trust in government and opinions about employment in politics and government.
20 In sum, those who distrusted the federal government were less likely, than those who trusted the government, to believe the federal government was a good place to work, to recommend to young people to start their careers in government, or to say they would personally prefer working for the government over business.
Progressive Policy. Hetherington (2005) asserts that the trust deficit has played a central role in the demise of progressive public policy in the United States. Whereas many attribute the current demise of progressive policy to trends toward conservatism,
Hetherington refutes this, saying it is a matter or trust, or rather the lack of trust in the federal government. He maintains that, if people do not trust the service delivery system, and they currently do not, they will not want the associated government agencies to provide policy solutions. This limits the range of possibilities available to government to implement effective policies.
Economic Growth. A trustworthy government may also generate the interpersonal trust necessary to promote a more peaceful and cooperative society and economic growth
(Fukuyama 1995; Levi 1997, 1998). Levi and Stoker (2000) note that some scholars argue the major source of societal trust is the government’s credible commitment to uphold property rights and provide a system of justice. For instance, Weingast (1998) contends trust results when government institutions make it far less likely that one group will be able to capture power and take advantage of another group. For him, trust can therefore be constructed and institutionalized. In other words, government institutions, such as justice and a system of property rights, are fundamental to a productive society. If the public lacks trust in such institutions, economic growth will be negatively affected.
21 A Notable Controversy
At this juncture a notable controversy require address. The contention revolves around the debate regarding whether or not lack of trust, on the part of the public, toward government is undesirable or detrimental for democratic governance.
Perhaps lack of trust or even distrust for government does not matter. Nye (1997) notes the United States was founded with a mistrust of government and a long Jeffersonian tradition attests that we should not worry too much about the level of confidence in government. As such, perhaps lack of trust in government or dissatisfaction with government is a sign of good health in governance as opposed to a symptom of a larger problem. This is not to say, however, that cynicism, hatred, or alienation is good for a democratic form of governance.
Hardin (1999) contends the contemporary vision that citizens should trust government is starkly contrary to traditional liberalism. Hardin (2002) also asserts trust is not a major consideration in the working of government or even modern society. He even asserts that we should not generally want trust in government for the simple reason that typical citizens cannot be in the relevant relation to government, or to the overwhelming majority of government officials, to be able to trust them except by mistaken inference. This is because the knowledge demanded to form trust, regardless of the conceptualization of trust, is largely unavailable to ordinary citizens.
The research of this dissertation takes the stance that, regardless of whether or not lack of trust in government is desirable, the low levels of public trust in government warrant
22 further investigation as to its structure, causes and consequences. Even if low levels of political trust are considered healthy, this is still a symptom of a larger problem that needs addressed, and low levels of public trust warrant a policy response by public officials. That is, implicit to the notion of healthy distrust in government is the assumption that public officials will respond to that facet of public opinion in a healthy manner. However, similar to firms in the marketplace responding to customer dissatisfaction, public officials must first be aware of the lack of trust or distrust before they can respond to it in kind.
Public Administration Considerations
As most of the established discussions pertaining to trust in government have originated within the political science field, the subject of such discussions has tended to focus on elected officials, namely elected executives such as the President, and legislatures such as Congress. However, recent discussions have begun to address the public administration aspect of trust in government.
Ruscio (1997) asserts trust lies at the nexus of the practice and theory of public administration. He notes that the inherent problem of democracy in the administrative state is reconciling the political imperative of accountability with the managerial imperatives of flexibility and responsiveness. Trust lies at the heart of the tension between the two imperatives. As trust varies so does the tension between the two competing imperatives. It should be noted that a high level of trust does not eliminate mechanisms for accountability, however, it can make such mechanisms less intrusive and provide discretion for managers and a greater willingness to delegate.
23 Behn (1995) believes that trust is one of the three big questions facing scholars of public management. For him, and others, the lack of trust leads to excessive micro- management, among other things. As such, political accountability is obtained in ways that run against the grain of sound management, and flexibility and discretion become severely constrained. Zand (1997) contends that trust is one of the three components of his leadership triad. For him, trust is important because it enriches relationships, thereby fostering cooperation, creativity and commitment. Thus, it is difficult for a leader to lead without trustworthiness.
Ruscio (1996) notes that, beyond the clearly identifiable trust problem per Behn, there are much wider implications. For instance, distrust permeates contemporary political life, affecting the tone of political discourse, shaping the perspectives of political actors, and sometimes changing the basic reasons they participate in politics. The distrust also exists between citizens and their government, between the branches of government, and between political appointees and civil servants. The distrust also hinders informal relationships and leads to excessive dependence on rules, formal procedures, and regulations.
Efforts to increase trust in the public administration side of government generally come from the organizational development literature. In discussing such efforts for the sake of clarity it is important to distinguish between efforts at what Kim (2001) refers to as the micro-organizational level and the macro-institutional level.
Micro-Organizational Considerations. Trust at the micro-organizational level occurs within an organization. Included here is trust between organizational members, which may
24 include interpersonal trust between employees or between subordinates and managers, as well as trust between groups within the organization.
The implications for low trust at the micro-organizational level is that eroded trust tends to create conflict, interrupt communication, and retard cooperation between employers and employees in the workplace. The norm is that authoritarian control dominates the employer-employee relationship, reducing employee participation, the degree of discretion which employees exercise over their work, and their motivation for creative knowledge for problem solving (Carnevale 1995, Golembiewski 1979). Kim (2001) notes such an organizational climate could seriously impair performance because it can stifle organizational innovation and reform. Because of poor organizational performance, thsi can indirectly influence public trust in government organizations.
Although Carnevale (1995) focuses his trust discussions on the micro-organizational level, he maintains that improving public trust in public organizations must begin in-house.
The best way for public administrators to build trust in their organization is by addressing micro-organization trust issues within the organization, namely maintaining and building interpersonal or intergroup trust. In doing so, institutions will become high performance organizations, and thereby earn the confidence and trust of the public.
Macro-Institutional Considerations. Trust at the macro-institutional level is trust in organizations as opposed to trust within organizations. Public trust in government organizations falls into this category, as does the trust elected officials might have in public organizations.
25 Low macro-institutional trust can also negatively impact organizational performance.
For instance, low public trust in government may erode employee attitudes that should be values and encouraged, such as a sense of calling to their jobs, motivation for job performance, and support for government programs (Kim 2001). Kim has identified a degenerative cycle of trust relationships between the government and the public, where low organizational performance, begets public distrust, which in turn begets low organizational commitment on the part of public employees, which in turn begets low organizational performance. The unfavorable image of government also dissuades persons from entering public service. Instead they tend to pursue careers in the private sector (Holzer & Rabin
1987). In addition, the demoralization of experienced public employees, as well as the difficulty of recruiting qualified applicants, also undermines government performance
(Rainey 1997).
Organizational Reform Considerations. Assuming there is a deficit of public trust in the public administration side of government in the U.S., remedial action may be in order.
According to Kim (2001), such effort to build trust in government must encompass both micro-organizational and macro-institutional levels of trust in government agencies.
Although the literature is sparse, especially with respect to the public sector, a few scholars of some advice to public administrators.
At the micro-organizational level, Nyhan (2000) proposes that management include employees as participants in decision making processes, facilitate feedback to and from employees, and empower employees to act. For him, such efforts would lead to increased
26 interpersonal trust within organizations. Furthermore, these trust-building practices can lead to increased productivity and strengthened organizational commitment.
Kim (2005) suggests a model in which public administrators can key on five primary trustworthy factors that can promote public trust in government organizations. These five dimensions of trustworthiness include credible commitment, benevolence, honesty, competency and fairness. As a rule of thumb, public administrators should strive to exhibit these five characteristics as a means of instilling public trust in themselves as well as their organizations. Thomas (1998) also adds that there should generally be an increased emphasis on ethics education for public administrators as a means to increase public trust in government organizations.
Marlowe (2004), in his analysis of the 1996 General Social Survey data, found that, although public administrators are relatively detached from the more visible aspects of electoral politics, they appear to be included in the broad citizen assessment of the governmental system. Thus, trust in public administrators is closely related to trust in the governmental system and the specific institutions that comprise it. If this is the case, than public administrators would be waging a losing battle to instill public trust in themselves and their organizations. The public’s trust may be lodged in general notions of the governmental regime.
27 Conceptualizations of Trust
Although it is not the purpose of this dissertation to thoroughly define or develop a theory of public trust in government, defining the subject to be studied is generally a prerequisite to the systematic analysis of a given topic. As such, the following discussion is meant to shed light on the development of related literature and subject to be studied in this dissertation research.
Conceptual Vagueness
Regardless of discipline, the notion of trust has been viewed as an elusive or intractable term (Golembiewski & McCronkie1975; Gambetta 1988). Indeed, Luhmann
(1998) has asserted trust is a concept surrounded by conceptual vagueness. This is the case regardless of area of study, and is the case for such fields as psychology, sociology, organizational studies, economics, political science, and public administration. In addition, not only is trust generally not well defined in the literature, related concepts such as faith and confidence are also not well defined (Barber 1983). Scholars have generally seemed to waffle in their discussions of trust or have avoided clarifying the concept because doing so might provoke controversy (Kim 2005).
This conceptual difficulty in defining trust is basically driven from the complex and multi-dimensional nature of the construct that permeates both interpersonal and institutional levels (Lewis & Weigert 1985; Thomas 1998). Trust has also been seen as an attitude or behavioral aspect that is subject to influence from countless directions (Kim 2005).
28 Consequently, the general definition of trust has become formless, varying depending on the factors being observed (Dasgupta 1988; Jennings 1998).
Because of the complexity of the notion of trust, trust is generally operationalized differently depending on the context in which it is studied and the field in which it is studied
(Rousseau 1998). In other words, trust is used to describe or reference different things or constructs. For instance, psychologists view trust as an internal cognitive process between trustors and trustees (Rotter 1967). Economists and some sociologists perceive trust as a calculative or rational expectation about outcomes generated by another party (Coleman
1990; Williamson 1993). On the other hand, some sociologists view trust as a property of collective attributes among people or institutions (Lewis & Weigert 1985). Organization theorists view trust in terms of multiple paradigms depending on context (Sitkin & Roth
1993; Lewicki & Bunker 1995; Bigley & Pearce 1998).
Kim (2005) notes that these interdisciplinary differences introduce significant inconsistencies to the interpretation of trust. However, a better conceptualization of trust begins by recognizing its multifaceted character (Lewis & Weigert 2005).
Some Generalizations of Trust
Levi and Stoker (2000) note that. although trust is a much contested term, there appears to be some minimal consensus about some of its dynamics. For instance, they point out that trust is considered relational – trust involves an individual making themselves vulnerable to another individual, group or institution. In addition, trust is generally conditional – trust is given to specific individuals or institutions over specific domains. They
29 also note that trust is conceived as either a dichotomy – one either trusts or distrusts – or conceived in a more graded fashion – one trusts or distrusts to a degree. With respect to the latter, Ullmann-Margalit (2004), trust falls on a continuum ranging from full trust to full distrust. In the center of the continuum is what she refers to as trust agnosticism, when a person neither trusts not distrusts.
Most contributors also distinguish between three types or levels of trust. These include interpersonal trust, i.e., trust in friends, relatives or significant others; societal trust, i.e., trust in strangers; and institutional trust, i.e., trust in various institutions in society. Trust in government of course falls in the latter category.
A Simple Model of Trust
Trust generally also implies a three part relationship involving at least two actors and one action: an individual trusts a specific individual or specific institution to do a specific thing (Luhmann 1979; Baier 1986; Guinnane 2005). According to Cleary and Stokes (2006), if A and B are actors and X is the action that is in A’s interest, then if A believes B will do
X, then A trusts B. In other words, A trusts B to provide X. Trust in then someone’s (A) belief of someone else (B) about the likely action (X).
Trust and trustworthiness are different concepts. Trust is a belief, that is, A’s belief that B will do X. On the other hand, trustworthiness is a quality or predisposition. In the case of the simple three-part model, trustworthiness is B’s predisposition to do X. Trust may therefore be ill-founded. For instance, A may trust B to do X, even though B is unlikely to provide X, and hence A is trustworthy. With respect to the notion of distrust, it can be stated
30 as the contrapositive of trust. That is, A distrusts B if A does not believe that B will provide
X (again, X is an action that A wishes B to undertake).
Pettit (1995) notes that trust develops reliably among individuals to the extent they have beliefs about each other that make trust sensible to adopt, and this trust survives to the extent that those beliefs prove to be correct. Furthermore, trust judgements are also expected to inspire courses of action, such as the monitoring, sanctioning or severing a relationship
(Levi and Stoker 2000) or continuing or discontinuing trust in the trustee.
Conceptualizations of Public Trust in Government
Not only are there divergent conceptualizations of trust in general, there are also differing conceptions specifically with respect to trust in government. For instance, with respect to the notion of political trust, some consider such trust as a commodity that helps political actors achieve their goals (Luhmann 1979). Others conceptualize political trust as people’s willingness to follow the political leadership of others (Warren 1999). Still others define political trust more broadly as a sense of shared moral political and social community with an agreement on what values a society ought to pursue (Fukuyama 1995). For
Hetherington (2005), political trust is the degree to which people perceive that government is producing outcomes consistent with their expectations. Hetherington also goes on to note that political trust is a general evaluation of the entire government as opposed to trust in a specific individual.
31 At this juncture, a distinction needs to be made between the concept of political trust and the notion of trust in government. Although the concept of political trust is often used interchangeably in the literature with the notion of trust in government, this dissertation research treats political trust as a subset of trust in government in general. As such, trust in government is an umbrella term that includes trust in a wide variety of government officials and institutions, including elected officials, appointed officials, non-appointed public administrators, and so on. To demonstrate the diversity of conceptualizations, and to discuss conceptualizations that are pertinent to trust in government officials in general, the contributions of three authors are discussed, including Barber (1983), Kim (2005) and
Ruscio (1996).
Risk and Expectations (Barber’s Account of Trust)
For Bernard Barber (1983), trust is inherently about risk and expectations. He notes that trust embodies at least three different meanings in this respect. These include a general type of trust and two specific types of trust. In each case, Barber links the essence of trust to expectations, which are the meanings individuals attribute to themselves and others as they make choices about which actions and reactions are rationally effective and emotionally and morally appropriate. In addition he notes that all social interaction is an endless process of acting upon expectations, which are part cognitive, part emotional, and part moral.
Trust in the Social Order. The most general type of trust is the expectation of the persistence and fulfillment of the natural and moral social orders. In the most fundamental aspect, it is the belief that the world will continue to exist, i.e., the natural order, and society
32 will continue to function, i.e., the social order. These are general expectations which all persons in society basically internalize, and such expectations are necessary for the effective and moral human action. With respect to the social order, to trust a person or thing is to assume their reliability, to believe that they will act as they should. This ability to trust is important in reducing complexity in social interaction to allow society to function. As such, expectations are necessary for effective and moral human action (Luhmann 1979). An example of trust in the social order would included expectations that the established system of government will continue to exist and function.
Barber’s notes that against the background of this general and comprehensive definition of trust, as expectation of the persistence of moral and social order, we can proceed to discuss two more specific types of trust, each of which is important for understanding social relationships and social systems.
Technical Competence. The first of Barber’s two specific definitions is trust involving technical competence. This is the expectation, by those involved in social relationships and systems, of technically competent role performance of others in the relationship or system.
To trust a person or thing in terms of technical competence is to assume they will perform to their expected capabilities. So within the three-part model of trust previously mentioned
(X trusts Y to provide Z), the latter variable would represent technical competence.
Barber goes on to note that in modern society, where there is an accumulation of knowledge and technical expertise, expectations of trust in this sense are very common. The expected competent performance may involve such aspects as expert knowledge, technical facility or everyday routine performance. Technically competent performance can be
33 monitored or assessed to the extent that it is based on shared knowledge and expertise.
Barber’s trusting in technical competence is similar to what Tyler and Degoey (1996) refer to as instrumental trust – trust based on another person, group or institution making the competent decisions. An example of instrumental trust in the case of government would be trust in public officials making the right decisions regardless of fairness or moral considerations.
Fiduciary Responsibility. The second specific meaning of trust, for Barber, is that of the expectation of fiduciary obligation and responsibility; that is, the expectation that others in our social relationships have moral obligations and responsibility to demonstrate a special concern for other’s interests above their own. To trust a person or thing in terms of fiduciary responsibility is to assume they will meet their moral obligations in the role or position in which they serve.
Trust as a fiduciary responsibility goes beyond technically competent performance to the moral dimension of human interaction. When technically competent performance can be monitored, then there is a need for trust, in this case based on fiduciary responsibility.
Trust of this kind is a social mechanism that makes possible the effective and just use of the power that knowledge and position allows, and forestalls abused of that power. Barber notes that such trust is essential for the relatively orderly functioning of society. However, trust as fiduciary obligation is never wholly sufficient or fully effective as a control mechanism and requires functional alternatives and complements, such laws and regulations. This notion of trust is similar to what Tyler and Degoey (1996) refer to as relational trust – trust based on the expectation of good intentions or fairness and good faith. In the case of
34 government, it is a belief in good faith and fairness on the part of government officials. A person may meet fiduciary obligations but fail in terms of technical competence.
Barber cautions that trust is multi-dimensional and, when discussing or examining trust, whether looking at technical competence, fiduciary responsibility or more generalized trust, context is important. The social relationship or social system of reference must always be specified. For instance, what is regarded as competence or fiduciary responsibility among friends may be different from the trust exhibited within or between formal organizations.
Cognitive, Affective and Behavioral Dimensions (Kim’s Account of Trust)
After and extensive review of the trust literature, Kim (2005) notes there are three somewhat distinctive, but loosely coupled, concepts of trust, especially with respect to trust in government, that illustrate its multifaceted character. These include cognitive, affective and behavioral dimensions. For Kim, these three dimensions can be merged into a mutually supporting construct that is collectively called trust, which is the willingness of a trustor to be vulnerable based on the belief that the trustee will meet the expectations of the trustor, even in situations where the trustor cannot monitor or control the trustee.
Cognitive Dimensions. First for Kim, trust is a cognitive decision by individuals who are willing to grant discretion based on their evaluative beliefs in the trustee (Berman 1996;
Carnevale 1995; Hardin 1998; LaPorte & Metlay 1996; McAllister 1995; Ruscio 1996).
This is the case as well for when the trustee is government or a government agent. The trust decision could be based on a number of different considerations including affects, attitudes and cognitive judgement. For instance, many citizens tend to form attitudes toward
35 government despite having little or no interaction with government. These attitudes may be based on such attributes as individual socialization, political affiliation, and socioeconomic status. On the other hand, direct experiences with government provide citizens with affective and cognitive foundations for trust in government. Whatever the cognitive foundations of trust development, trust must fall somewhere along the continuum from total knowledge to total ignorance as either extreme would make trust unnecessary (Lewis &
Weigert 1985).
Affective Dimensions. Next for Kim, trust is an affective notion that demonstrates an emotional attachment by those in the trust relationship. The affective foundation of trust implies a willingness to be vulnerable to another’s actions and abandons or significantly reduces the desire for a controlling mechanism to monitor the relationship (Butler 1999;
Mayer, Davis & Schoorman 1995; Onyx & Bullen 2000; Rousseau, Sitkin, Burt & Camerer
1998; Warren 1999; Zand 1972). In the case of government, this reduces the desire for controlling mechanisms to check government decisions. Nevertheless, the disillusion that results from the betrayal of public trust is likely to spur citizens to pressure government to increase the level of mutual trust. In effect, as trust decreases, citizen attempts to monitor government actions increases. Likewise, efforts to ensure that government acts consistently with citizen interests increases (Mayer, Davis & Schoorman 1995).
Behavioral Dimensions. Lastly for Kim, trust involves a behavior character. Although some scholars rely heavily on psychological attitudes in conceptualizing trust (Carnevale
& Wechsler 1992; Gamson 1968; Giffin 1968; Rousseau, Sitkin, Burt & Camerer 1998) many others recognize the importance of social or behavioral components in the trust
36 relationship (Berman 1996; Creed & Miles 1996; Cummings & Bromiley 1996; Deutsch
1962; Jones & George 1998; Zand 1972). In the case of government, citizen’s attitudes vary depending on the ways that government approaches trust relationships. For instance, government actions, such as ignorance of citizen interests, incompetence or broken promises, can intensify public distrust. On the other hand, public trust will increase if the government heeds the interests of citizens, keeps promises and maintains a competent and fair administration. In sum, public trust in government is contingent on how the government behaves toward citizens.
Rational Versus Normative Considerations (Ruscio’s Account of Trust)
Ruscio (1996) asserts that most theories of trust are generally divided between trust being viewed as the consequence of rational and calculative behavior, or trust being a normative concept better explained in the context of culture and societal values. Thus, trust is viewed as either an aspect of psychology or a component of sociology.
Trust as Rational Choice. For some, such as Coleman, Hardin and Bianco, trust is a calculative behavior or a matter of rational decision making. Coleman (1990) asserts that whether or not someone chooses to trust is based on the expectation of gain or loss. This requires prediction regarding the actions of somebody else and depends on the particular circumstances and the information one has about the other individual. The decision to trust also depends on the relationship between potential gains or loses resulting from granting or withholding trust. As such, trust is a subcategory of risk.
37 According to Coleman, the decision to grant trust comes from a calculation involving p (the probability that the trustee is trustworthy), L (the potential loss if the trustee is untrustworthy), and G (the potential gain if the trustee is trustworthy). Trust will occur if the potential gain is worth the risk, or if (p/(1-p)) > (L/G). For Coleman, this expression is based on the postulate of maximization of utility under risk. It is nothing different from the considerations a rational actor applies is deciding whether or not to engage in a risky endeavor. If it suits someone’s interest, they will grant trust or withhold trust Likewise, in return the trustee will fulfill, or not fulfill, that trust if it suits their interests.
Coleman also sees trust in terms of power because trust gives one the freedom to act.
For instance, one seeking to maximize power, discretion and flexibility has an incentive to maximize trust received from the trustors (Ruscio 1996). The link between trust and power was the focus of some of the first sociological discussions on the importance of trust. For instance, Blau (1964) and Gamson (1968) touched on the issue of trust in some of their writings.
Hardin is another theorist that subscribes to the notion that trust is based on rational choice, but adds the notion of incentives and knowledge effects to Coleman’s model. For
Hardin (1993, 2001), trust is simply about encapsulated interest. That is, a trustor’s trust is a trustee is encapsulated in the trustee’s interest in fulfilling the trust. So for Hardin, a person trusts a trustee if they have adequate reason to believe it will be in the trustee’s interest to be trustworthy in a relevant way at a relevant time. One’s trust in another turns not on one’s own interests but rather on the interests of the trusted. Trust is therefore encapsulated in the trustor’s judgement of those interests.
38 Ruscio notes that Bianco (1996) takes a similar approach to Coleman in his model of rational trust between constituents and government representations. Whereas Coleman considers trust a variant of risk, Bianco considers trust the equivalent of leeway. Here, trust allows a government representative to make decisions for the public rather than be constantly at the demands of the public. That is, trust grants discretion, flexibility and power. For Bianco, the decision to grant trust is a product of rational calculation on the part of citizens, although it is a process where government representatives have more information about government affairs compared to constituents. So trust depends on two interacting variables. One is the constituent’s perception than the government representative shares the constituent’s interests, and the other is the constituent’s uncertainty caused by the lack of understanding or limited access to information.
Ruscio notes that the theories of Coleman and Bainco provide some basic insights into trust. First, trust is contextual and conditional rather than totally or absolutely granted or denied. Second, trusting grants the trustee power to act, and trust only has meaning when the trustee is capable of violating the trust relationship. In addition, rational choice definitions of trust must include references to discretion and flexibility in terms of free will, as well as references to a shared interest.
Trust as a Normative Construct. Despite the above conclusions about trust, Ruscio goes on to note something is lacking or unspecified in the rational behavior models. Namely, trust is often something else other than a calculation of anticipated benefits. It may include noncalculative behavior based on some principle or principles other than furthering a private interest.
39 Ruscio maintains that trust is a function of what of March (1994) refers to as the logic of appropriateness, which is behavior based on considerations of what is appropriate given a wide variety of institutional rules, norms and expectations. The logic of appropriateness is opposed to the logic of consequences, which is based on identifying objectives and alternatives for achieving objectives and then calculating the costs, benefits and optimal solutions. In specifically addressing the issue of trust, March and Olsen (1989) note that the core idea of trust is not based on an expectation of its justification, but rather trust is sustained by socialization into a structure of rules and expectations. Furthermore, they maintain that trust is rarely a deliberate willful action.
Ruscio goes on to note that this noncalculative approach to trust does not entirely reject the possibility of rational choice and strategic considerations will enter a decision as to whether to grant trust. That is, the noncalculative approach may still involve some elements of strategy and calculation. What distinguishes the noncalulative or normative approach to trust is that it inherently includes at least some ethical or moral obligations.
Herein, is a link to Barber’s (1983) fiduciary responsibility and Tyler and Degoey’s (1996) notion of relational trust, as well as the behavioral dimension in Kim’s (2005) analysis of trust.
Trust-Related Concepts
The concept of trust should not be mistaken for its related concepts. Citrin and Muste
(1999) note that the concept of political trust, or trust in government, belongs to a large family of terms regarding the subjective level of support citizens give their government
40 system. Prominent relatives or correlates include the notions of confidence, satisfaction, faith, efficacy, and legitimacy. Negative correlates include cynicism, alienation, disaffection and estrangement. As Citrin and Muste note, these concepts share the common goal of capturing the public’s attitudinal underpinnings regarding the activities of government.
Kim (2001) has argued that an overwhelming glut of definitions of trust has also created confusion between concepts of trust and similar constructs such as faith, confidence and satisfaction. Of these, confidence is probably the most frequently used construct in place of trust (Berman 1997; La Porte & Metlay 1996; Lipset & Schneider 1987). But as Kim notes, confidence has a different meaning from trust. Confidence represents a feeling or belief that another can act in a proper or effective way. It arises from another party’s capacity to function properly based on past experience, and from past experience, ability has been tested and confirmed. In contrast, trust can arise from a momentary perception or other conditions that may be unproven.
Trust-related concepts are often referred to as correlates because, from a tautological standpoint, it can be inferred there is either a positive or indirect bivariate relationship between trust as one variable and a trust-related concept as another variable. For instance, people that trust government logically more likely to have faith and confidence in government. On the other hand, people that distrust or lack trust in government logically are more likely to be cynical about or alienated from government.
41 Previous Survey Research on Trust in Government
The existing empirical research on trust in government has traditionally been survey- based and focused on the general populace at the national level, with the biennial National
Election Studies polls laying the foundation and time series data regarding political trust in the United States since the late 1950s. The General Social Survey of the National Opinion
Research Center as has also addressed trust in government attitudes. More recently, some non-profit organizations with an interest in better government or citizen attitudes toward government have conducted surveys addressing particular aspects of trust in government, as well as related issues such as confidence and satisfaction with government. In general, the results of these surveys have indicated confidence gaps in public trust, declining public trust, or widely fluctuating trust in the federal government during the past four decades.
National Election Studies
The wellspring of historical and current discussions regarding trends in, and importance of, trust in government is the National Election Studies (NES), a biennial national, random sample, telephone poll of citizens political participation and attitudes which first started in 1948. The first trust-related questions on the NES appeared in 1958, and the poll has collected consistent time series data regarding public trust indicators since
1964. In addition, NES has asked trust-related questions regarding alienation and cynicism toward government. The NES studies have been traditionally been administered by research centers of the University of Michigan.
42 Figure 2.1 depicts the results of the traditional trust-in-government question of the
National Election Studies (NES): How much of the time do you think you can trust the government in Washington to do what is right – just about always, most of the time, or only some of the time? Although the wording of this question is flawed to some degree, NES has continued to use the same question for comparison purposes across years. In addition, other organizations conducting trust in government research have also used the same question as a means of directly comparing their results to the NES surveys. It should be noted that the vagueness of classic NES trust in government question was the genesis of this dissertation
research, especially Research Hypothesis H2. That is, this dissertation research is an effort to delve into a more intricate examination of citizen trust in government.
A cursory exam of the NES results indicates that there have been ebbs and flows in trust in government over the past forty years and that there appears to be a downward trend in trust over time. The highpoint of political trust was in 1964, when just over three- quarters, 76%, of all survey respondents (n=1,445) indicated they trusted the federal government to do what is right most of the time or just about always. There was a noticeable decline in trust in government over the 1964 to 1980 period, with a slight rebound during the 1980 to 1984 period. Trust in government continued to decline over the 1984 to 1994.
In 1994 trust reached its low point, when less than one-quarter, 21%, of respondents
(n=1,769) indicated they trusted the federal government to do what is right most of the time or just about always. Trust improved over the 1994 to 2002 period, when, for the first time in thirty years, the majority of respondents indicated they trusted the federal government
43 to do what is right right most of the time or just about always. However, following 2002, trust in government started another downward trend.
Question: How much of the time do you think you can trust the government in Washington to do what is right? – just about always, most of the time, or only some of the time?
Source: National Election Studies, 1964-2004
Besides the results of trust in government question outlined in the previous table, the
NES also derives a Trust in Government Index. The index is derived from the results of four survey questions. These include the general trust in government question already mentioned, as well as three other questions, including a question pertaining to whether or not the
44 respondent felt the government is run for a few big interests, a question regarding whether or not the government wastes tax dollars, and a question pertaining to whether or not the respondent felt the people running government are corrupt. The index has a possible value ranging from a low of zero to a maximum of 100. A score of 100 represents a state of full trust.
The biennial results of the NES Trust in Government Index for 1964 to 2004 are outlined in Table 2.2 and is offered as an exhibit regarding the assertion that there is a trust gap in terms of how citizens view the federal government. To a large degree the Trust in
Government Index mirrors the results for the NES trust in government question. What is important to note in the results is that, with the exception of the mid 1960s, the index has not broached the mid-point of 50. As such, the index indicates citizens tend to lack trust in government as opposed to be trusting of government. In addition, there appears to be ongoing trend of diminished trust in government. Regardless of the trend, there appears to be a significant confidence gap regarding trust in the federal government.
45
The Trust in Government Index is derived from the results of the NES trust in government question and three related survey questions. The range of the index spans from zero to a maximum of 100.
Source: National Election Studies, 1964-2004.
General Social Survey
The General Social Survey (GSS) conducted by the National Opinion Research Center
(NORC) at the University of Chicago has tracked public confidence in major societal institutions since 1972. Similar to the declines in political trust measures by NES, this survey has tracked diminished confidence in a variety institutions over the past three
46 decades. In general, public confidence in major institutions, such as the three branches of the federal government, the news media, higher education, medicine, and major companies, has trended downward over the past three decades. Irrespective of the declines, the Supreme
Court tends to have more public confidence than the President, who tends to have more public confidence than Congress. Non-government institutions, such as the higher education, medical and scientific communities, have tended to enjoy more public confidence than government in general. Private pollsters such as Gallop and the Harris Poll have confirmed these trends.
In 1996, the General Social Survey asked respondents a specific question regarding public trust in public administrators. It was worded as follows: Most government administrators can be trusted to do what is right for the country. Respondents were then asked whether they strongly agreed, agreed, disagreed, strongly disagreed, or if they were neutral. The results were scaled where one equaled strongly agree, three represented neutral, and five equaled strongly disagree. The mean score for all respondents was 3.58 (n=401).
Thus, the results indicated that respondents tended to disagree with the assertion, that administrators cannot be trusted to do what is right for the country.
Marlowe (2004) found that trust in federal administrators was closely linked to perceptions of government performance as well as their confidence in particular institutions such as the executive branch and Congress. On the other hand, he found that trust in public administrators was not a function of demographic characteristics, attitude’s toward an individual’s life circumstances, or a general sense of anti-institutionalism.
47 CEG Trust Studies
The general trends of declining or lackluster trust and confidence in government indicated in the NES and NORC studies, have spurred recent attempts by a host of non- profit organizations, and some private organizations, to gauge different facets of public trust and confidence in government. These surveys, although generally lacking longitudinal data, have shed more light on the issue of trust and confidence in government.
With the inclusion of more research interests, the examination of trust and confidence in government appears to be evolving toward more sophisticated approaches or methods.
For instance, whereas trust in government was first examined from a more global perspective, i.e., trust in the federal government in general, recent studies are increasingly focusing on different aspects of trust in government, such as confidence in specific agencies and leadership, and trust differentials across the three basic levels of American government: federal, state and local governments.
One non-profit organization that has been prolific in their research on trust has been the Council for Excellence in Government (CEG), which has a special Partnership for Trust in Government unit. They commissioned from Hart-Teeter three random sample, nationwide polls of adults in 1995 (n=1,003), 1997 (n=1,003), and 1999 (n=1,214). Questions deal with trust in government or trust-related concepts such as confidence in government.
A different dynamic that the Center for Excellence in Government examined for all three years was public confidence in the three levels of American government. The results for all three years are depicted in Figure 2.3. The results of the surveys indicate there is an underlying structure of devolution in confidence toward government. That is, people tend
48 to have more confidence in local government compared to state and national government, and people tend to have more confidence in state government compared to national government. The Pew Research Center also found similar results. As such, these findings suggest that the general public tends to have more confidence in state and local government compared to the federal government. It should be noted this aspect of citizen attitudes towards government, i.e., devolution in opinion depending on level of government, was the
impetus for Research Hypothesis H1 of this dissertation research.
The Council for Excellence in Government also asked the classic NES trust in government question on their 1999 survey. The results of the CEG study were even less favorable than the NES results for 1998 and 2000. For 1999, only 29% of respondents trusted the government in Washington to do what is right most of the time or just about always. CEG found that persons who trusted the government tended to feel connected to government, while people with little trust for government were more likely to not feel connected to government.
The trust and confidence in government research of CEG was culminated with the publication of their report A Matter of Trust: Americans and Their Government, 1958-2004.
The report outlines their research as well as related survey research regarding citizen perceptions of government. A drawback of the CEG studies is that they tended to treat confidence in government as synonymous with trust in government.
49
* Proportion of respondents stating they had a great deal or a lot of confidence in the associated level of government.
Source: Council for Excellence in Government.
Other Related Survey Research
Besides the Council for Excellence in Government, several other non-profit organizations have engaged in survey research related to trust in government during the late
1990s and early 2000s. As with CEG, these organizations tended to have an interest in good governance and citizen attitudes toward government. These organizations also tended to
50 confuse the concept of confidence with trust in government. Examples of these organizations and studies the Pew Research Center for People and the Press (1998); the
Center for Policy Attitudes (1999); National Public Radio and the Kaiser Family Foundation
(2000), and the Brookings Institution (2002). All of their survey research consisted of large, national random household telephone surveys.
Pew Research Center. The Pew Research Center for the People and the Press conducted their own national poll in 1997, but also synthesized their results with other surveys such as the General Social Survey and several polls conducted by Gallop. Besides the GSS in 1996, Pew was one of the first to delve into public opinion with respect to the public administration side of government. Whereas the GSS addressed trust in federal public administrators in general, Pew sought to gauge public opinion on different departments or agencies of the federal government, such as the Federal Bureau of Investigation (FBI), the
Environmental Protection Agency (EPA), and the Food and Drug Administration (FDA), and the Internal revenue Service (IRS). Pew (1998) indicates that all of these departments or agencies saw declines in public opinion ratings, in terms of very favorable ratings, over the 1980s and 1990s. Nevertheless, when counting the mostly favorable responses, most respondents had a favorable opinion of most all federal agencies. Pew goes on to note that the federal government as an abstraction elicits a much more negative reaction on the part of respondents compared to specific federal agencies or departments, or even specific branches of the federal government.
As with the 1999 CEG Study, Pew also asked the classic NES trust in government question on their 1997 survey. They found that only 38% of respondents (n=1,762) trusted
51 the government in Washington to do what is right most of the time or just about always.
They found not significant difference in how key demographic groups trusted government, including sex, age and race. Educational attainment also did not influence the level of trust in government, however political party affiliation did influence trust in government. For
1997, persons who identified themselves as democrats were more likely to trust government, while republicans and independents were less likely to trust government. Pew found that trust in government was strongly associated with opinions of government performance, i.e., how well federal government programs were administered. In general there was a positive or direct relationship between trust and performance. Persons who had favorable opinions of government performance were more likely to be trusting of government. Pew also found that the public’s mood about the nation is strongly related to trust in the federal government, and this was a trend that held over the 1964 to 1997 period. Persons who had favorable perceptions of national direction were more likely to be trusting of government.
Pew (1998) also asked an addition general trust in government question to gauge differences in public trust for elected officials and civil servants. The question was worded as follows: who do you trust more to do the right thing – the politicians who lead the federal government or the civil service employees who run federal government departments and agencies? The results indicated that the public is more favorably disposed toward non- elected government officials as opposed to elected officials. Nearly three-quarters, 72%, of valid respondents (n=1,643) indicated they trusted civil servants more than elected officials, while 17% of respondents indicated they trusted politicians more than civil servants. The
52 remaining ten percent of respondents indicated they trusted both groups the same or trusted neither group.
Pew also asked respondents another interesting trust in government question, which was worded as follows: do you think people will mistrust government no matter what, or do you think there are things the government can do to increase the public’s trust? On a positive note, three-quarters or 75% of respondents said the government can do things to increase the public’s trust in government. On the other hand, nearly one-quarter, 23%, of respondents stated that people will mistrust the government regardless of any actions on the part of government.
Center for Policy Attitudes. The Center for Policy Attitudes fielded their trust in government poll in 1999 to gauge many of the same questions of NES but in between the
NES survey years of 1998 and 2000. Most questions focused on trust-related issues such as confidence and political efficacy. CPA did, however, ask the classic NES trust in government question and recorded the lowest ever trust scores for that particular question.
For 1999, Only 19% of respondents (n=1,204) stated they trusted the government in
Washington to do what is right most of the time or just about always. Nearly three-quarters,
73%, of respondents said they trusted government only some of the time, while seven percent asserted they trust government none of the time.
NPR/Kaiser Foundation. Whereas the CEG survey addressed public confidence in government, the 2000 National Public Radio/Kaiser Family Foundation survey specifically addressed public trust in government across the three primary levels of government.
Respondents were asked: how much of the time do you trust the [federal/state/local]
53 government to do what is right, just about always, most of the time, only some of the time, or none of the time? Thirty-nine percent of respondents (n=1,557) indicated they trust state or local government, respectively, to do what is right just about always or most of the time, compared to 29% with respect to the federal government. Respondents were also more likely to have a lot or a great deal of confidence in state and local government to solve problems. NPR/Kaiser found that African-Americans were significantly less likely to trust government than Caucasians or Latinos, regardless of the level of government. Leading reasons offered for distrusting the federal government included, in order of importance, government waste and inefficiency, partisan bickering, special interests having too much influence, a lack of honesty and integrity among elected officials, and high taxes.
Brookings. More recently, the Brookings Institution (2002) has delved further into public opinion in 2001 and 2002 with respect to additional federal public officials falling into the category of public administrators, namely federal government employees and presidential appointees that run different departments and agencies of the federal government. Here, respondents were asked: general speaking, what is your opinion of [a given government official], is it very favorable, somewhat favorable, somewhat unfavorable, or very unfavorable? The results indicated that the President generally had a higher opinion rating than federal government workers in general as well as officials appointed by the
President to run federal agencies and departments. These government officials in turn had higher opinion ratings than members of Congress as a group.
54 Explanations of Variations in Trust in Government
The deficiencies and changes in political trust, as indicated by the NES and other studies, have spawned numerous efforts to explain such dynamics, i.e., identify what factors contribute to political trust or lack of trust in government. The reasons for changes in trust in government over time are varied and include such considerations as government performance, mood of the nation or economic considerations, opinions of political leaders, social and cultural considerations such as demographics, and other considerations such as world events and influence of the news media.
Government Performance
Lack of trust in government is often related to poor performance of government (Bok
2001). The performance approach to trust has two main parts (Bouckaeart, et al 2002). First, macro-performance theory explains variations in trust over time due to variations in macroeconomic dynamics such as unemployment, inflation and economic growth. Logically it follows that if the economy is favorable, the public will have more trust in the government. On the other hand, if economic conditions are unfavorable, the public will have less trust in government. Second, micro-performance theory relates variations in trust to changes in the quality of government service delivery. Here, if the public is satisfied with service delivery, they will be more likely to trust the government. Conversely if the public is dissatisfied with service delivery they will be inclined to distrust government.
55 A variant of government performance is presidential and congressional approval rates.
According to Bishop (2003), people who approve of the performance of the president are more trusting of the government in general. Indeed, Citrin and Green (1986) attribute the rebound of trust in the 1980s, as indicated by the NES data, to presidential leadership and evaluations of the national economy during that period. Similarly, Citrin and Luks (1998) have linked to NES trust data to congressional approval rates.
National Mood
The Pew Research Center (1998) identified a broader influence by pointing out the parallel between how the public views the state of the nation and how they trust government.
That is, measures of national mood have closely tracked fluctuations in the NES trust in government indicators. As national mood became more favorable, trust in the federal government increased. Conversely, as national mood trended downward, trust in the federal government decreased.
Similar to mood of the nation, the health of the national economy has also mirrored the NES trust in government indicators. Thus, some contend that trust in the federal government is driven by public assessments of the national economy. This ties into notions of government performance especially with respect to macro-performance issues. Whereas the bulk of the public views the handling of the national economy to be the responsibility of the federal government, it can be argues that fluctuations in the economy influence citizen perceptions of the government. It should be noted that the low points or troughs in the NES trust in government indicators over the 1964 to 2004 period coincided with economic
56 recessions. However, Lawrence (1997) maintains that public trust in the federal government is much more complex then simply be driven by the health of the national economy.
Political Causes
There are also a wide variety of political causes of trust or distrust in government.
King (1997) links the decline in the NES trust in government indicators to partisanship or the polarization of political parties. In this respect, partisan battles or bickering have left the public with a negative view of government. Furthermore, Neustadt (1997) asserts public trust in government is hurt by a politics of mistrust that pervades the federal government.
King (1997) also alludes to the possibility that the public at large is become less trusting of government because of trends toward conservatism. Regardless, there appears to be a strong relationship between political ideology and political party affiliation with trust in government. In particular, persons who identify themselves as the same political party as the incumbent tend to be more trusting of government in general, while persons who identify themselves as being affiliated with the opposing political party tend to be less trusting of government (Pew 1998).
Other political causes associated with the public trust deficit may include general attitudes toward politicians, the occurrence of political scandals, perceptions of the influence of special interest groups, and changes in public attitudes regarding political efficacy or cynicism.
57 Scope of Government
Nye (1997) posits that the current dissatisfaction and lack of trust in government in the
U.S. is that its scope and size has expanded too much, that is, government has gotten too big and has intruded into areas best left to private life. The results of many of the trust in government polls (NES, CEG, etc.) echo this sentiment. In general, persons who feel the federal government is too power tend to be less trusting of government.
But as Hetherington (2005) notes, the public wants the government to actually provide more services. As such, trust in government might be more of a function of failed expectations.
As public expectations regarding government have expanded, trust in government has declined.
Social/Cultural Considerations
Mansbridge (1997) contends social and cultural changes can cause trust in government to decline both indirectly, by affecting government performance, and directly by affecting citizen attitudes. For Mansbridge, most of the effect of social and cultural changes on the degree of trust in the federal government have worked indirectly by reducing the caliber of government performance. Socio-cultural changes have produced new problems with concomitant demands for government solutions. At the same time, socio-cultural changes have also produced rising expectations of government action. She goes on to note that these two trends have generated government overload, which is a situation in which citizens expect the government to solve more problems than it can solve, expect the government to provide more services than it can provide, and expect the government to solve problems
58 without a willingness to sustain taxation adequate to finance the efforts to produce a favorable outcome.
In terms of specific demographic groups, evidence has been lacking with respect to identifying specific groups that are more likely to trust or distrust government. For instance, males are just as likely as females to trust government. Likewise, few studies have found a relationship between age and trust in government. On the other hand, some studies, such as the 2000 NPR/Kaiser study found that African-Americans were significantly less likely to trust government than Caucasians or Latinos.
One socio-cultural dynamic that has received increasing attention is the impact of trust in people in general and trust and government. According to proponents of this theory, such as Brehm and Rahm (1997), when people feel good about government, they are more willing to cooperate with each other. Hence, when people trust government, they tend to trust other people in general. CEG (2004) notes that the decline in trust in the federal government, as evidenced by the NES trust in government indicators, has been mirrored by the decline of interpersonal or societal trust, i.e., trust between individuals. In other words, at the aggregate level, interpersonal trust and trust and government have tracked each other closely over the
1968 to 2004 period.
Despite the apparent strong connection between interpersonal trust and trust in government at the aggregate level, Uslaner (2002) contends that the linkage between the two types of trust is suspect, in particular trust in people and trust in government are not strongly correlated at the individual level. He argues that interpersonal trust is a stable, long-term
59 value, while trust in government is based on transitory evaluations of government performance.
National Threats
Alford (2001) provides another theory that attempts to explain the rise and fall of political trust in the U.S. His theory concerns the presence or absence of external threats to the nation. He suggests that distrust of government may actually be the norm and that people are only lifted out of this state during special circumstances such as when a national security threat arises. He claims that in the face of a broadly perceived national threat, the public focuses from internal targets to an external one. As such, the public becomes more patriotic and more trusting of the national government, albeit temporarily. Regarding the NES trust in government indicators, Alford notes that during periods when concern over foreign policy and defense was high, such as in the early 1960s and 1980s, trust rebounds.
The public’s response to the terrorist attacks of 2001 seem to support this external- threat theory (CEG 2004). This is because there was an upward spike in the NES trust in government indicators for 2002 following the attacks, raising political support to its highest levels in 30 years. MacKenzie and Labiner (2002) have attributed this burst of support for federal government to the September 2001 terrorists attacks, which created a “government moment,” a time for citizens to recognize and appreciate their government. However, citing results of a 2002 Brookings Institution study, they assert this rise in trust in government was short-lived and is now on the decline. This assertion seems to be supported by the Harris
Poll results, which include more recent results for 2003 and 2004.
60 Other Considerations
The news media and the information revolution offers other examples of possible explanations for the decline in public trust in government over the 1964 to 2000 period. On one hand the ongoing decline in political trust may be attributable to the growth of television and more recently cable television and the Internet. The public simply has much more information upon which to evaluate or judge government. Orren (1997) notes that non- governmental factors such as the media play an important role in the erosion of public trust in government. More specifically, CEG (2003) asserts that press coverage of government and political affairs has become more negative and conflict-oriented. Television, with its dramatic pictures and themes, has only intensified these tendencies. Thus, this evolving media role has coincided with the decline in trust in government as well as other institutions.
Nye (1997) notes that declining trust and confidence in institutions is not limited to government. There appears to be more generalized trends toward declining trust and confidence at both the interpersonal and societal levels , which may be linked to declining social capital, i.e., the ability of people to work together (Putnam 1995) or an erosion of respect of authority (Mansbridge 1997), which in turn may be linked to the complexities of a modern, fragmented society due to postmaterialist or postmodern values (Inglehart 1997).
Contributions to the Research Design
This literature review has shown that trust is an immensely challenging concept
(Ruscio 1997). With respect to the public sector, especially for public administration, trust
61 in government is a relatively understudied subject. This dissertation research seeks to shed more light on the issue of public trust in government. It will build upon existing empirical research, namely a host of survey research such as the National Election Studies, General
Social Survey and a host of other public opinion polls.
Whereas trust is a multi-level concept (Weatherford 1992), this dissertation research will seek to examine public trust in government across the different levels of U.S. government: federal, state and local. In addition, within each level of government, trust in four key groups of public officials will be examined. These groups will include the elected executive or executives (President, state governor, county commissioners), persons appointed by the elected officials to run government agencies, government employees, and other elected officials such as legislators. Each of these groups will be asked basically the same question with minor adjustments to denote the officials in question.
Although trust is a concept surrounded by conceptual vagueness (Bouckaert, et at.
2002), enough can be gleamed to operationalize the term trust for use in survey questions.
The survey questions will be oriented toward the notion of Barber’s (1983) fiduciary trust or what Tyler and Degoey (1996) refer to as relational trust. Fiduciary trust is basically trusting in good intentions. The wording of the associated questions will be oriented toward a general notion of fiduciary trust that respondents will be able to comprehend and formulate a response.
Besides the trust in government officials questions, two other key questions will be asked as part of respondents. One will be a questions regarding trust in people in general, which will be used as a benchmark for the trust in government questions. Another question
62 will be a simple evaluative question for each level of government. The motivation for asking these additional questions is grounded in the literature. It has been hypothesized or shown that trust in people in general, or disposition toward government, is related to trust in government. Selected demographics and other personal characteristics of respondents will also be collected.
Overall, this dissertation research continues a trend in research toward digging deeper into examining different facets of trust in government. It is expected this research will shed more light on the issue of trust in government, especially with respect to the public administration side of government.
63 CHAPTER III
RESEARCH DESIGN
This chapter outlines the research questions to be addressed and the specific hypotheses associated with the research questions. In addition, this chapter outlines the research methodology of the study, scope of the research, and techniques for analyzing the data generated from the research, collected by survey administered by telephone to a random sample. Strengths and limitations associated with the research design will also be discussed.
The survey instrument is outlined in Appendix A.
Scope of the Research
The primary objective of the dissertation is to shed more light on the subject of trust in government in the United States. Most studies have examined public trust in government in broad or general terms, such as having a focus on the President or the federal government in general. As such, many facets of public trust in government have been overlooked, especially with respect to the public administration component of government. This study seeks to examine the public trust in government in greater detail.
64 There are two distinguishing characteristics of this study. First, it will examine public trust in public administrators as well as the trust differentials between public administrators and elected and politically appointed government officials. Second, this study will examine public trust in government officials across the three general levels of U.S. government – federal, state and county.
Most of the existing trust in government studies have been conducted by telephone as public opinion polls at the national level. Examples include the National Election Studies, conducted biennially over the past five decades, and, more recently, studies conducted by non-profit organizations such as the Council of Excellence in Government, the Brookings
Institution, and the Pew Research Center for the People and the Press.
Data collected for this study will also take the form of a public opinion poll. However, the focus of this study will be a single county (Stark County, Ohio) as opposed to a nationwide survey. One distinct advantage of using a single county as the unit of analysis is that it will allow greater precision in examining trust differentials in public officials across the three levels of government. That is, with a study focused on residents of a specific county, each respondent shares the same county and state, whereas a statewide survey would convolute the responses across several counties, and a nationwide survey would convolute the responses across 50 states and well over 1,000 counties. Whereas a design allowing statewide or national responses to this question of public trust would be advantageous, the resources needed to administer a study of that scope would be considerable and not available for the administration of this study.
65 Major Research Hypotheses
This research has four general hypotheses that address the research questions outlined in the first chapter. The general research questions and associated research hypotheses are outlined in Table 3.1. These general hypotheses are then addressed with several sub- hypotheses that will be examined to establish evidence to support or reject the broader, general hypotheses.
The first general question of this research seeks to address varying levels of public trust in government officials. More specifically, trust in public administrators is compared to trust in elected or politically appointed government officials. There is initial research to suggest the general populace trusts public administrators more than elected officials. For instance, Pew (1998) has found that government employees are trusted more than elected officials.
In this study, four general types of government officials will be examined, including elected executives (President, state governor, etc.), persons appointed by elected executives to run government agencies, legislatures or other elected officials, and public administrators.
In addition, these groups will be examined at the federal, state and county levels. This leads
to the first general research hypothesis H1 – the general public has a higher level of trust for public administrators compared to elected executives and other elected officials and politically appointed agency officials, regardless of the level of government.
The second general question this research seeks to answer is if the general public trust in government officials differ depending on the level of government. More specifically, it
66 will be determined if local government officials are trusted more than state and federal government officials. Examples of researchers who have found that state or local governments are trusted more than the federal government include Jennings (1998), Shaw
& Reinhart (2001), and Hetherington and Nugent (2001).
To address the second general research question, the same four general types of government officials will be examined as in the first general question: elected executives, executive appointees, other elected officials, and public administrators. Here, a given group of public officials at one level of government will be compared to similar public officials
at another level of government. This leads to the second general research hypothesis H2 – the general public has a higher level of trust for local government officials compared to similar state and federal officials, and a higher level of trust in state government officials compared to similar federal officials.
The third general question this research seeks to address is the relationship between the general public’s trust in government officials and general support or disposition toward government at the federal, state and local levels. More specifically, if there is a significant relationship, assess whether or not the association is a direct or positive relationship, and if an increase in public trust of government officials relate to an increase in support for government. Examples of researchers that have established this general relationship include
Citrin (1974), Muller (1979), and Hetherington (1998).
The attempt to address the third general research question leads to the third general
research hypothesis H3 – there is a direct relationship between public trust in various
67 government officials and the general public support for government, regardless of the level of government.
The fourth general question this research seeks to address is the general public’s trust in government officials explained differently depending on the type of official and level of government. That is, the study will examine which explanatory variables explain trust in the various public officials and assess whether these explanatory variables differ between the various government officials studied. Some researchers have found that some demographic groups trust the government more than other demographic groups. For instance, persons who share the same political ideology or political party affiliation with elected representatives in office tend to have a higher level of trust in government (Pew, 1998;
Anderson & LoTempio, 2002; Keele, 2005). In addition, Howell and Fagan (1988) have found that racial minorities are less trusting of government, while Fischer (1975) has found that urban residents are less trusting of government.
An attempt to answer the fourth general research question leads to the fourth general
research hypothesis H4 – explanatory variables for public trust in public administrators are different from variables explaining trust in other officials at the same level of government, including elected officials and politically appointed agency officials.
68 Table 3.1 General Research Questions and Associated Hypotheses
Does the general public trust public officials – elected executives, executive Question appointees, legislators, and public administrators – differently? Are public administrators trusted more than elected or appointed government officials? The general public has a higher level of trust for public administrators
H1 compared to elected and politically appointed agency officials, regardless of the level of government.
Does the general public trust public officials differently depending on the Question level of government – federal, state and local? Are local government officials trusted more than state and federal government officials? The general public has a higher level of trust for local government officials
H2 compared to similar state and federal officials, and a higher level of trust in state government officials compared to similar federal officials.
Is there a relationship between the general public’s trust in public officials and Question general support or disposition toward government at the federal, state and local levels? There is a direct relationship between public trust in various government
H3 officials and general public support for government, regardless of the level of government.
Is the general public’s trust in government officials explained differently Question depending on the type of official and level of government? Are there different explanatory variables for public administrators compared to other officials? Explanatory variables for public trust in public administrators are
H4 different from variables explaining trust in other officials at the same level of government.
69 Research Hypothesis H1 (Intra-Level Trust in Officials)
To assemble evidence to support or reject the first research hypothesis H1 – the general public has a higher level of trust for public administrators compared to elected and politically appointed agency officials, regardless of the level of government – a series of sub-hypotheses will be examined (see Table 3.2).
First, trust in government officials will be evaluated at the federal level. This leads to
the first branched sub-hypothesis H1:A – the general public has a higher level of trust for federal public administrators compared to federal elected officials and politically appointed agency officials. To this end, three specific sub-hypotheses will be examined that compare trust in federal public administrators individually to the President, persons appointed by the
President to run federal government agencies, and members of U.S. Congress. The formal
sub-hypotheses in this respect include H1:A1, the public trusts federal public administrators
more than the President; H1:A2, the public trusts federal public administrators more than
presidential appointees; and H1:A3, the public trusts federal public administrators more than
Congress.
Second, trust in government officials will be evaluated at the state level, in this case
officials of Ohio state government. This leads to the second branched sub-hypothesis H1:B
– the general public has a higher level of trust for state government public administrators compared to state elected officials and politically appointed agency officials. To this end, three specific sub-hypotheses will be examined that compare trust in state public administrators separately to trust in the governor, gubernatorial appointees who run state
agencies, and the state legislature. The formal sub-hypotheses in this respect include H1:B1,
70 the public trusts state public administrators more than the state governor; H1:B2, the public
trusts state public administrators more than gubernatorial appointees; and H1:B3, the public trusts state public administrators more than the state legislature.
Lastly, government officials will be evaluated at the county level, in this case officials
of Stark County government. This leads to the third branched sub-hypothesis H1:C – the general public has a higher level of trust for county government public administrators compared to county elected officials and politically appointed agency officials. To this end, three specific sub-hypotheses will be examined that compare trust in county public administrators individually to trust in the elected county executives, persons appointed by the elected executives to run county government agencies, and other elected county officials.
At the county level, other elected government officials are examined in place of a county legislature, which was not present in the county of study. The formal sub-hypotheses in this
respect include H1:C1, the public trusts county public administrators more than the county
elected executives; H1:C2, the public trusts county public administrators more than county
executive appointees; and H1:C2, the public trusts county public administrators more than other elected county officials.
Although the research included most government officials across the three levels of government in a global sense, it should be noted that the twelve groups of government officials outlined above are not meant to be all-inclusive. For instance, some elected officials at the state level, such as state auditor and treasurer, are not considered for simplicity. Likewise, elected and politically appointed judges are not considered at any level.
71
Table 3.2
Sub-Hypotheses for Research Hypothesis H1 The general public has a higher level of trust for public administrators compared to elected and politically appointed agency officials, regardless of the level of government.
Federal Level: H1:A The general public has a higher level of trust for federal government public administrators compared to federal elected officials and politically appointed agency officials.
H1:A1 The public trusts federal public administrators more than the President.
H1:A2 The public trusts federal public administrators more than presidential appointees.
H1:A3 The public trusts federal public administrators more than Congress.
State Level: H1:B The general public has a higher level of trust for state government public administrators compared to state elected officials and politically appointed agency officials.
H1:B1 The public trusts state public administrators more than the state Governor.
H1:B2 The public trusts state public administrators more than gubernatorial appointees.
H1:B3 The public trusts state public administrators more than the state legislature.
Local Level: H1:C The general public has a higher level of trust for county government public administrators compared to county elected officials and politically appointed agency officials. The public trusts county public administrators more than the county elected H 1:C1 executives. The public trusts county public administrators more than county executive H 1:C2 appointees. The public trusts county public administrators more than other elected county H 1:C3 officials.
72 Research Hypothesis H2 (Inter-Level Trust in Officials)
As with research hypothesis H1, a series of sub-hypotheses will be employed to
assemble evidence to support or reject the second general research hypothesis H2 – the general public has a higher level of trust for local government officials compared to similar state and federal officials, and a higher level of trust in state government officials compared to similar federal officials (see Table 3.3).
First, the focus will be on public administrators across the three levels of U.S.
government. This leads to the first branched sub-hypothesis H2:A – the general public has a higher level of trust for county government public administrators compared to state and federal public administrators, and a higher level of trust in state public administrators compared to federal public administrators. To this end, three specific sub-hypotheses will be examined that compare trust in public administrators at one level of government to public administrators in another level of government. The formal sub-hypotheses in this respect
include H2:A1, the public trusts county public administrators more than state public
administrators; H2:A2, the public trusts county public administrators more than federal public
administrators; and H2:A3, the public trusts state public administrators more than federal public administrators. Here, public administrators are considered synonymous with government employees in general.
Second, the focus will be elected government executives across the three levels of U.S. government. These executives include the President, state governor, and three county commissioners in the case of the study county. This leads to the second branched sub-
hypothesis H2:B – the general public has a higher level of trust in elected county executives
73 compared to the state governor and President, and a higher level of trust in the state governor compared to the President. To this end, three specific sub-hypotheses will be examined that compare trust in elected executives at one level of government to elected executives at another level of government. The formal sub-hypotheses in this respect include
H2:B1, the public trusts the elected county executives more than the state governor; H2:B2, the
public trusts elected county executives more than the President; and H2:B3, the public trusts the governor more than the President.
Next, the focus will be on political appointees, i.e., persons appointed by the top elected executive (President, governor, county commissioners) to run government agencies.
This leads to the third branched sub-hypothesis H2:C – the general public has a higher level of trust in county executive appointees compared to gubernatorial and presidential appointees, and a higher level of trust in gubernatorial appointees compared to presidential appointees. To this end, three specific sub-hypotheses will be examined that compare trust in executive appointees at one level of government to executive appointees at another level
of government. The formal sub-hypotheses in this respect include H2:C1, the public trusts
county executive appointees more than gubernatorial appointees; H2:C2, the public trusts
county executive appointees more than presidential appointees; and H2:C3, the public trusts gubernatorial appointees more than presidential appointees.
Lastly, the focus will be on elected legislative bodies. This leads to the fourth branched
sub-hypothesis H2:D – the general public trusts local legislatures more than the state legislature Congress, and trusts the state legislature more than Congress. As there is no associated county legislative body for the county of study, one specific sub-hypothesis will
74 be examined that compares trust in the state legislature to trust in U.S. Congress. The formal
sub-hypothesis is H2:D1, the public trusts the state legislature more than Congress.
75 Table 3.3
Sub-Hypotheses for Research Hypothesis H2 The public has a higher level of trust for local government officials compared to similar state and federal officials, and a higher level of trust in state officials compared to similar federal officials.
Public Administrators: H2:A The general public has a higher level of trust in county government public administrators compared to state and federal public administrators, and a higher level of trust in state public administrators compared to federal public administrators. The public trusts county public administrators more than state public H 2:A1 administrators.
H2:A2 The public trusts county public administrators more than federal administrators. The public trusts state public administrators more than federal public H 2:A3 administrators.
Elected Executives: H2:B The general public has a higher level of trust in elected county executives compared to the state governor and President, and a higher level of trust in the state governor compared to the President.
H2:B1 The public trusts elected county executives more than the state governor.
H2:B2 The public trusts elected county executives more than the President.
H2:B3 The public trusts the state governor more than the President.
Executive Appointees: H2:C The general public has a higher level of trust in county executive appointees compared to gubernatorial and presidential appointees, and a higher level of trust in gubernatorial appointees compared to presidential appointees.
H2:C1 The public trusts county executive appointees more than gubernatorial appointees.
H2:C2 The public trusts county executive appointees more than presidential appointees.
H2:C3 The public trusts gubernatorial appointees more than presidential appointees.
Legislative Officials: H2:D The public has a higher level of trust in county legislative bodies compared to the state legislature and Congress, and a higher level of trust in the state legislature compared to Congress.
H2:D1 The public trusts the state legislature more than Congress. Note, comparative data is not available regarding county legislatures.
76 Research Hypothesis H3 (Government Direction and Trust)
As with the previous general hypotheses, a series of sub-hypotheses will be employed
to assemble evidence to support or reject the third general research hypothesis H3 –there is a direct relationship between public trust in government officials and public support for government, regardless of the level of government (see Table 3.4).
First, the relationship between support for the federal government and trust in the four groups of federal government officials studied in this research will be evaluated. This leads
to the first branched sub-hypothesis H3:A – there is a direct relationship between public trust in federal government officials and public support for federal government. To this end, four
specific sub-hypotheses will be examined. The formal sub-hypotheses include H3:A1, there is a direct relationship between public trust in federal public administrators and support for
federal government; H3:A2, there is a direct relationship between public trust in the President
and support for federal government; H3:A3, there is a direct relationship between public trust
in presidential appointees and support for federal government; and H3:A4, there is a direct relationship between public trust in Congress and support for federal government.
Next, the relationship between support for the state government and trust in the four groups of state government officials studied in this research will be evaluated. This leads
to the second branched sub-hypothesis H3:B – there is a direct relationship between public trust in state government officials and public support for state government. To this end, four
specific sub-hypotheses will be examined. The formal sub-hypotheses include H3:B1, there is a direct relationship between public trust in state government public administrators and
support for state government; H3:B2, there is a direct relationship between public trust in the
77 state governor and support for state government; H3:B3, there is a direct relationship between
public trust in gubernatorial appointees and support for state government; and H3:B4, there is a direct relationship between public trust in members of state legislature and support for state government.
Lastly, the relationship between support for county government and trust in the four groups of county government officials studied in this research will be examined. This leads
to the third branched sub-hypothesis H3:C – there is a direct relationship between public trust in county government officials and public support for county government. To this end, four
specific sub-hypotheses will be examined. The formal sub-hypotheses include H3:C1, there is a direct relationship between public trust in county public administrators and support for
county government; H3:C2, there is a direct relationship between public trust in the elected
county executives and support for county government; H3:C3, there is a direct relationship between public trust in county executive appointees and support for county government; and
H3:C4, there is a direct relationship between public trust in other elected county officials and support for county government.
78 Table 3.4
Sub-Hypotheses for Research Hypothesis H3 There is a direct relationship between public trust in government officials and general public support for government, regardless of the level of government.
Federal Level: H3:A There is a direct relationship between public trust in federal government officials and public support for federal government.
There is a direct relationship between public trust in federal public administrators H 3:A1 and support for federal government.
There is a direct relationship between public trust in the President and support for H 3:A2 federal government.
There is a direct relationship between public trust in presidential appointees and H 3:A3 support for federal government.
There is a direct relationship between public trust in Congress and support for federal H 3:A4 government.
State Level: H3:B There is a direct relationship between public trust in state government officials and public support for state government.
There is a direct relationship between public trust in state public administrators and H 3:B1 support for state government.
There is a direct relationship between public trust in the state governor and support H 3:B2 for state government.
There is a direct relationship between public trust in gubernatorial appointees and H 3:B3 support for state government
There is a direct relationship between public trust in the state legislature and support H 3:B4 for state government.
Local Level: H3:C There is a direct relationship between public trust in county government officials and public support for county government.
There is a direct relationship between public trust in county public administrators and H 3:C1 support for county government.
There is a direct relationship between public trust in elected county executives and H 3:C2 support for county government.
There is a direct relationship between public trust in county executive appointees and H 3:C3 support for county government.
There is a direct relationship between public trust in other elected county officials H 3:C4 and support for county government.
79 Research Hypothesis H4 (Explanations of Public Trust)
Once again as with the previous general hypotheses, a series of sub-hypotheses will be employed to assemble evidence to support or reject the fourth general research hypothesis
H4 – explanatory variables for public trust in public administrators are different from variables explaining trust in other officials at the same level of government (see Table 3.5).
First, explanations for public trust in the four groups of federal government officials
studied in this research will be explored. This leads to the first branched sub-hypothesis H4:A
– public trust in federal public administrators is explained differently than for the President, presidential appointees, and Congress. To this end, three specific sub-hypotheses will be examined that compare the trust model for federal public administrators separately with the trust models for the other three groups of federal government officials. The formal sub-
hypotheses include H4:A1, the explanatory model for public trust in federal public
administrators is different from the trust model for the President; H4:A2, the explanatory model for public trust in federal public administrators is different from the trust model for
presidential appointees; H4:A3, the explanatory model for public trust in federal public administrators is different from the trust model for Congress.
Next, explanations for public trust in the four groups of state government officials studied in this research will be explored. This leads to the second branched sub-hypothesis
H4:B – public trust in state government public administrators is explained differently than for the governor, gubernatorial appointees, and the state legislature. To this end, three specific sub-hypotheses will be examined that compare the trust model for state public
80 administrators separately with the trust models for the other three groups of state
government officials. The formal sub-hypotheses include H4:B1, the explanatory model for public trust in state public administrators is different from the trust model for the governor;
H4:B2, the explanatory model for public trust in state public administrators is different from
the trust model for gubernatorial appointees; H4:B3, the explanatory model for public trust in state public administrators is different from the trust model for the state legislature.
Lastly, explanations for public trust in the four groups of county government officials
studied in this research will be explored. This leads to the third branched sub-hypothesis H4:C
– public trust in county government public administrators is explained differently than for elected county executives, executive appointees, and other elected county officials. To this end, three specific sub-hypotheses will be examined that compare the trust model for county government public administrators separately with the trust models for the other three groups
of county government officials. The formal sub-hypotheses include H4:C1, the explanatory model for public trust in county public administrators is different from the trust model for
the elected county executives; H4:C2, the explanatory model for public trust in county public
administrators is different from the trust model for county executive appointees; H4:C3, the explanatory model for public trust in county public administrators is different from the trust model for other elected county officials.
81 Table 3.5
Sub-Hypotheses for Research Hypothesis H4 Explanatory variables for public trust in public administrators are different from variables explaining trust in other officials at the same level of government.
Federal Level: H4:A Public trust in federal public administrators is explained differently than for the President, presidential appointees, and Congress. The explanatory model for public trust in federal public administrators is different H 4:A1 from the trust model for the President. The explanatory model for public trust in federal public administrators is different H 4:A2 from the trust model for presidential appointees. The explanatory model for public trust in federal public administrators is different H 4:A3 from the trust model for Congress.
State Level: H4:B Public trust in state government public administrators is explained differently than for the governor, gubernatorial appointees, and the state legislature. The explanatory model for public trust in state public administrators is different H 4:B1 from the trust model for the governor. The explanatory model for public trust in state public administrators is different H 4:B2 from the trust model for gubernatorial appointees. The explanatory model for public trust in state public administrators is different H 4:B3 from the trust model for the state legislature.
County Level: H4:C Public trust in county government public administrators is explained differently than for elected county executives, executive appointees, and other elected county officials. The explanatory model for public trust in county government public administrators H 4:C1 is different from the trust model for the elected county executives. The explanatory model for public trust in county government public administrators H 4:C2 is different from the trust model for the county executive appointees. The explanatory model for public trust in county government public administrators H 4:C3 is different from the trust model for other elected county officials.
82 Research Methodology
The following section outlines the research methodology for this research study. Like many other studies examining public trust in government, this research will utilize a public opinion poll to collect data to support or reject the hypotheses outlined in the previous section. This survey will be conducted via telephone by trained interviewers and focus on one county within the state of Ohio.
Study Population and Sampling
This research will be conducted in conjunction with the 2004 Stark County Omnibus
Poll conducted by the Center for Policy Studies, a unit of the Institute for Health and Social
Policy at The University of Akron. The Center for Policy Studies conducts the Stark Poll each year as a non-partisan county-wide community survey. The 2004 Stark Poll, as well as this dissertation research, is sponsored and subsidized in part by the Ohio Urban
University Program.
The study population will encompass adult residents of Stark County, Ohio. The sample population will be a random probability sample of these residents. The sample of telephone numbers will be drawn at random from all working residential telephone numbers within the county, both listed and unlisted numbers. Using a random digit dialing protocol, the initial procedures will generate a representative sample of working telephone numbers.
The respondent from each household, an adult 18 years or older, will be chosen at random
83 to ensure a representative cross-section of the population. This is accomplished by choosing the household resident who had the most recent birthday.
The final sample size for the Stark Poll will consist of a minimum of 1,067 respondents. That is, the survey will be administered until this number of respondents have completed the survey. The general population statistics derived from this sample size will provide an overall sampling margin of error of plus or minus three percent at a confidence interval of 95%, and of plus or minus four percent at a confidence interval of 99% (Rea &
Parker, 2005). In the end, residents from about one out of 150 Stark County households will have completed the survey.
Stark County is one of 88 counties within the state of Ohio. It has a population of approximately 380,000 and roughly 148,000 occupied households. Stark County is characterized by moderate urbanization and exhibits both urban, suburban and rural characteristics. Canton constitutes the urban core of the county.
Table 3.6 provides comparative demographics from the United States Census 2000 of
Population and Housing for Stark County, state of Ohio, and the United States. Median household income and per capita income within Stark County are consistent with Ohio and national figures, as are other demographics such as those for gender and major age groupings. However, the demographics diverge along racial and ethnic lines, especially comparing Stark County and the national population . For instance, Stark County is characterized as having fewer racial minorities, persons of Hispanic descent, and foreign- born persons compared to the United States population as a whole.
84 Although national news media often come to Stark County to gauge the political pulse of the nation, no claim is made herein that the Stark County population is representative of the national population as a whole.
85 Table 3.6 Comparison Census 2000 Statistics: Stark County, Ohio, United States Stark United Demographic Ohio County States Population 379,098 11,353,140 281,421,906 Population Growth (1990-2000) 2.9% 4.7% 13.1% Occupied Households 148,316 4,445,773 104,480,101 Average Household Size 2.49 2.49 2.59 Median Household Income $39,824 $40,956 $41,994 Per Capita Income $20,417 $21,003 $21,587 Home Ownership Rate 72.4% 69.1% 66.2% Persons Below Poverty 9.2% 10.6% 12.4% Male 48.0% 48.6% 49.1% Female 52.0% 51.4% 50.9% Caucasian 90.3% 85.0% 75.1% African-American 7.2% 11.5% 12.3% Other/Multiple Designations 2.5% 3.5% 12.6% Hispanic or Latino 0.9% 1.9% 12.5% Not Hispanic or Latino 99.1% 98.1% 87.5% Foreign Born Persons 1.8% 3.0% 11.1% Language Other Than English Spoken at Home 4.3% 6.1% 17.9% Persons Under 18 Years of Age 24.8% 25.4% 25.7% Persons 18 to 64 Years of Age 60.1% 61.3% 61.9% Persons 65 Years of Age and Older 15.1% 13.3% 12.4% High School Graduate 83.4% 83.0% 80.4% Bachelor’s Degree or Higher 17.9% 21.1% 24.4% Persons Per Square Mile 656.3 277.3 79.6 Source: United States Census 2000: Population and Housing.
86 Political-Economic Environment
As public trust in government is often tied to such factors as political ideology, political party affiliation, and economic status (Citrin & Green, 1986; Lawrence, 1997), special mention of the Stark County political and economic environment at the time of the survey administration, including the larger political-economic environment in which this county is situated. The survey was administered during June and July, 2004.
At the federal level, the President of the United States was republican. In addition, republicans had a narrow majority of both houses of the 108th Congress, Second Session.
At the time of the survey, the U.S. Senate consisted of 51 republicans, 48 democrats, and one independent. The U.S. House of Representatives consisted of 228 republicans (52.5%),
205 democrats (47.2%), and one independent (0.2%). Both Senators from the state of Ohio were republican as well as the U.S. Representative from the 16th District in Ohio, which encompasses all of Stark County.
The national mood of the U.S. population was focused on the 2004 presidential campaign. Key issues included the economy, the war in Iraq, and potential scandals in the current administration. The presidential approval rating was relatively low, although the
President would be re-elected. The national unemployment rate amounted to 5.5% for 2004.
Although the national economy was generally considered lackluster, real gross domestic product grew by three percent for the previous year (Statistical Abstract of the United States,
2005).
Within Ohio, at the time of the survey, most of the elected state-wide officials were republican, including the governor, treasurer, auditor, secretary of state, and attorney
87 general. Likewise, the Ohio Supreme Court consisted mostly of republican judges, and republicans held majorities in both houses of the 125th General Assembly. The state senator representing most of Stark County in the 29th Senate District was republican, while the state senator from the 33rd Senate District was democrat. Two of the three state representatives representing the county, from the 50th and 51st House Districts, were republican, while the third representative, from the 52nd House District was a democrat.
In terms of the Ohio economy, the state continued to see a state economy adversely impacted by the decline of manufacturing. Whereas the national real gross domestic product grew by three percent the previous year, the gross state product for Ohio increased by 1.7%.
The unemployment rate was also higher in Ohio, amounting to 6.3% in 2004. (Statistical
Abstract of the United States, 2005).
Within Stark County, as the time of the survey, two of the three elected county commissioners were republican while the third was a democrat. Most of the elected judges were republican, but most other elected county officials were democrat, including the auditor, treasurer, sheriff, engineer, prosecutor, and clerk of courts. In terms of the general population within the county, the previous Stark Poll indicated that 37.7% of respondents identified themselves as democrat, 32.9% republican, 19.8% independent, and 9.7% considered themselves something else. Although the plurality considered themselves democrats, in terms of political ideology, the plurality considered themselves conservative.
Just over one-third, 33.8% of respondents considered themselves conservative, while 31.4% indicated they had moderate political views, 19.4% were liberal, and 15.7% identified
88 themselves as something else. In terms of voter registration status, 83.6% of respondents were registered to vote.
As an urban area that once had a strong manufacturing section, the Stark County economy saw lackluster growth, reflecting statewide trends in the decline of manufacturing.
The unemployment rate for Stark County at the time of the survey amounted to 6.6%, which was higher than state and national averages. The previous Stark Poll indicated an unemployment rate of 7.8%. Nearly half, 44.3%, of respondents reported their household was worse off financially from the previous year, while 30.2% indicated their household was about the same. Only one-quarter, 25.5%, of respondents indicated their household was better off financially (Stark County Regional Omnibus Poll, 2003).
In sum, the political environment at the federal level was characterized by a republican presence in the White House and majority control of both houses of Congress. The political environment in Ohio was characterized by an even stronger republican presence, with the governor and most other state elected officials being republican and nearly two-thirds of both houses of the General Assembly being republican. Within Stark County, although republicans controlled two-thirds of the Board of County Commissioners, democrats played a larger role in other elected county offices. The economies of Stark County and Ohio tended to see more unemployment and less economic growth compared to the nation in general.
89 Survey Administration
The 2004 Stark Poll will be administered by professionally trained personnel employed by the Center for Policy Studies. These personnel will have completed a comprehensive training program, which concludes with both a skills assessment and screening exam, as well as a briefing of the Stark Poll survey instrument before it is fielded.
As part of the quality control process, supervisors will monitor all aspects of the interviewing process, which includes silent monitoring protocols of actual interviews..
Interviewing will be conducted using Computer Assisted Telephone Interviewing
(CATI) technology, which improves the interviewing process itself. With a CATI system, interviewers read the script of survey from a computer monitor and enter responses directly into the computer system. This system also offers the opportunity to carefully monitor all aspects of the data collection process and ensures rigorous quality control and data validation immediately upon entry.
Each household will be given an introduction explaining the purpose of the survey and the topics being surveyed. Non-Stark County residents will be screened out. Most calling will take place between the evening hours of 5:15 pm and 9:30 pm. However, some interviews will take place during daytime hours to accommodate respondent schedules.
Frequent call-backs will be made to households which do not answer the first call, as are specially supervised attempts to convert initial refusals by respondents into completed interviews. The length of these telephone interviews is expected to average about 15 minutes per interview. The survey is expected to be in the field for about six weeks.
90 Human Subjects Review
Each year the Center of Policy Studies submits their Standard Operating Procedures for Public Policy Surveys for review and approval by the Institutional Review Board for the
Protection of Human Subjects (IRB) of the Office of Research Services and Sponsored
Programs at The University of Akron. Internal Review Board approval for the polling activity conducted by the Center for Policy Studies, including the Stark Poll and the survey questions of the research discussed herein, was secured for the 2004 calendar year in
December 2003. The associated IRB application number was #20001204-4. The IRB application and approval documents are on file with the Center for Policy Studies.
The Standard Operating Procedures of the Center for Policy Studies outline the standards of protection for the respondents of polling surveys. The following guidelines are observed for telephone surveys: (1) adequate identification of the institution and caller, (2) adequate explanation of the research, including reference to the length of the survey and an assurance that participation and responses are voluntary without penalty for non- participation, (3) restriction of calling times to reasonable hours, and (4) protection of the respondent’s identity through data security procedures. For instance, the names and addresses of respondents are not recorded.
Survey Instrument
The actual survey instrument, including exact wording of the questions, is outlined in
Appendix A of this document. The following is a narrative of some of the dynamics of the survey instrument.
91 As mentioned previously, the dissertation research questions were fielded as part of the 2004 Stark County Omnibus Poll. It should be noted that the Stark Poll was actually longer, i.e., had more questions, than is specified here. This is because additional questions will also be posed on behalf of other researching entities. As an omnibus poll, researchers and local government and non-profit organizations are invited to participate on a cost-share basis. As such, several research topics may be addressed during the same survey administration. Besides the dissertation researcher, four community organizations fielded questions on the poll. These included the United Way of Greater Stark County, Children’s
Hospital Medical Center of Akron, the Stark County Health Department, and Stark County
Children Services.
The dissertation researcher posed eighteen questions on the 2004 Stark Poll. These included thirteen trust-specific questions, three support or disposition toward government questions, one interest in government affairs question, and one voting activity question. The exact wording and ordering of these questions is outlined in Appendix A: Survey
Instrument. The dissertation researcher appreciates the sponsoring of these questions by the
Center for Policy Studies and the Ohio Urban University Program.
The trust battery constitutes the first thirteen questions posed by the researcher on the
2004 Stark Poll. One question assesses the level of public trust in people in general, regardless of whether or not they work in government, while twelve questions directly evaluate public trust in various government officials at the three levels of U.S. government.
These questions will be used to address all four general research hypotheses: H1, H2, H3 and
H4. These questions are derived to some degree from existing survey questions from the
92 National Election Studies (NES) and other polls, but have been modified to suit the methodology of this specific research. The questions are similar to existing polls in that they attempt to gauge a generalized form of relational trust.
Again, for the purposes of this research, trust is operationalized to be what Tyler and
Degoey (1996) refer to as relational trust – trust based on government actors having good intentions or a belief in good faith and fairness in government actions. The notion of relational trust is similar to Barber’s (1983) notion of fiduciary responsibility. Relational trust is differentiated from instrumental trust, which is trust based on the government making the right choices (Tyler & Degoey 1996). Instrumental trust can be considered somewhat equivalent to Barber’s (1983) notion of technical competence.
The term “relational trust” will not be used in the question wording nor will a definition be offered to the respondent. Rather, the wording of the questions will be oriented toward gauging feelings of relational trust for government officials in general. This trust will be gauged in global terms; that is, the respondent’s feeling of trust for government officials in general, as opposed to specific individuals. The respondents will be asked to rate their level of trust in a given set of government officials on a scale from one to ten, where one is the least trust and ten is the most trust.
There are basically three lines of trust in government questioning, aimed specifically at federal, state and county government officials. Categorically, government officials, for the purposes of this research are of four types: (1) government employees, which will considered synonymous with public administrators; (2) elected government executives, i.e.,
The President, state governor, and county commissioners; (3) persons appointed by the
93 elected executive to run government agencies; and (4) legislators. As there is not an associated legislative body at the county level, trust in other elected county officials will be gauged instead.
The four groups of government officials outlined above are not meant to be all- inclusive, but rather focus on significant and similar groups of government officials across the three levels of government, targeting the executive and legislative branches. Some groups of government officials will not be examined. Examples include state elected officials, such as the secretary of state, auditor and treasurer, and elected and appointed officials on the judiciary. Appointees to some boards and commissions are also not examined. Moreover, local governments other than the county government, such as cities and townships and special districts, are not examined.
The term of “public administrators” will not be used in the questions due to the problems associated with semantics. Many people in the general public may not be able to relate to this term, as such, the term “government employee” will be used as a proxy for public administrators. Many public administration theorists, such as Appleby (1945) and
Waldo (1984), consider all government employees to be public administrators. When assessing public trust in public administrators, the focus will be on government employees in general at the three levels of government as opposed to specific groups of government employees such as law enforcement and human services personnel.
Also of note, proper names for government officials will not be used in the survey questions. Rather the focus is on the given office title (President, governor, etc.) or groups of officials, as opposed to specific persons. In addition, when trust is gauged for legislators,
94 the focus will be on the legislative body in general, as opposed to specific representatives serving the constituency of the sample population. With respect to executive appointees, i.e., presidential appointees and gubernatorial appointees, the focus will be on persons appointed to run various government agencies, in general. As such, specific government agencies will not be named.
The government support battery will consist of three survey questions. These questions are similar and consistent with how other researchers have sought to gauge political support, for instance see Reef and Knoke (1999). To complement these trust questions, which examine citizen attitudes toward government officials across the three levels of American government, support for government will be gauged for each of the three levels of government: federal, state and local. The questions used to gauge political support will entail whether or not the respondent feels the associated level of government is headed in the right direction. As with the trust questions, these support questions were developed
especially for this research and will be used to assess general research hypotheses H3 and
H4.
Two other questions will be asked of respondents that are related to political support.
These include how often the respondent votes in general elections, and the respondent’s general interest in government and public affairs. The former is a question used on Pew
Research Center studies while the latter is a question posed on National Election Studies.
These questions are not copyrighted and are considered public domain. These questions will
be used to assess research hypothesis H4 and will complement other political characteristics
95 of the respondents normally asked as part of the demographic section of the Stark Poll, namely voter registration status, political ideology and political party affiliation.
Besides the supplementary questions regarding political characteristics, several other demographic characteristics of respondents will also be recorded. These questions are traditionally asked as part of the Stark Poll, and, as such, these questions have established wording that cannot be amended by the dissertation researcher. These supplementary questions are listed in Appendix A: Survey Instrument.
Many of the supplementary questions identify characteristics of respondents and will
be used to address research hypothesis H4. Some of the questions will be utilized more frequently than others based on their utility. These demographics can be distinguished by four general categories. These include politics, economic status, location variables, and demographic variables. The variables measuring the economic status of respondents include employment status, annual household income, change in finances, and whether or not the respondent’s family rents or owns their home. Location variables include city or township of residence and zip code. Demographic variables to be collected include respondent’s gender, age, level of education, race, origin, marital status, and religious preference.
Instrument Pre-Testing
The Center for Policy Studies generally prepares the questions for the Stark Poll with direction from the participating researchers or organizations. In the case of the research questions outlined herein, the researcher took the lead in formulating the questions with
96 significant input from the Director of the Center for Policy Studies as well as other CPS staff.
The survey instrument was pre-tested before fielding in two stages. First, a focus group was held to discuss the face validity of the dissertation research questions, namely the clarity and ordering of the questions. The focus group consisted of eight persons of varying demographics from outside of the Center for Policy Studies and lasted for about an hour.
The participants were carefully read each proposed survey question and asked if they could relate to the question if they were an actual survey participant and if they thought the public at large could relate to the survey questions.
Based on feedback from the focus groups participants some minor wording changes were made to the survey questions. For instance, the trust in people in general question was moved from a subset of the federal government trust questions to its own distinct question and worded appropriately. In addition, the wording “federal government workers” within the trust questions was changed to “federal government employees.” Likewise, similar wording changes were made in the case of state and county workers. Another wording amendment was to refer to Stark County most times as “Stark County” instead of just as
“county.” “Elected officials” serving in the Ohio General Assembly was changed to “elected representatives.” “Elected County Commissioners” was changed to “county commissioners elected to run Stark County.”
In addition to the focus group, the Center for Policy Studies also conducted careful pre-testing of the questionnaire, performed prior to fielding the instrument. Here, the survey instrument was tested on mock respondents via telephone using the Computer Assisted
97 Telephone Information system. Such test respondents were of course not included in the final data set.
Measurement of Variables
Table 3.7 outlines the levels of measurement for the dissertation research questions.
The response categories for the thirteen trust questions will be a scale from one to ten, with one being the lowest level of trust in a given group of persons and ten being the highest level of trust. As such, the measurement level of these variables will be interval or scalar.
Most of the other variables will have ordinal or nominal measures. In the case of the three government support questions, the response categories regarding whether a given level of government is headed in the right direction will included strongly agree, agree, neither agree nor disagree, disagree, and strongly disagree. These responses will be coded on a numeric continuum so that the measurement level will be ordinal for these variables. In addition, the responses for the government interest and voting activity questions will be coded on a numeric continuum so that their measurement level will be ordinal.
Table 3.8 outlines the levels of measurement for the key supplementary questions that will be used to complement the dissertation research questions. Most of these questions are demographic in nature. Other than age, the measurement of these variables is either ordinal or nominal. Some nominal variables were recoded to dichotomous variables for incorporation into regression models. Key supplementary variables utilized in the analysis included political ideology, political party affiliation, gender, age, race, Hispanic origin, educational attainment, employment status, household income, household financial status,
98 home ownership status, and city or township of residence. The latter was often utilized as an urban-suburban dichotomous variable, where residents of Canton, Massillon and Alliance were coded as urban, with the remainder of the county coded as suburban.
99 Table 3.7 Trust-Related Variables and Measurement Response Variable Measurement Categories Trust: People in General Ten categories: 1 to 10 Interval/Scale Trust: President Trust Presidential Appointees Trust: Congress Trust: Federal Employees Trust: Governor Trust: Gubernatorial Appointees Trust: State General Assembly Trust: State Employees Trust: County Executives Trust: County Executive Appointees Trust: Other County Elected Officials Trust: County Employees Right Direction: Federal Government Five categories: ranging Ordinal from Strongly Agree to Right Direction: State Government Strongly Disagree. Right Direction: County Government Interest in Government Affairs Five categories ranging Ordinal from Hardly At All to Most of the Time. Voter Registration Status Registered or Nominal Not Registered Voting Activity Five categories: ranging Ordinal from Always to Never Note, more information regarding response categories, coding and response frequencies is outlined in Appendix B.
100 Table 3.8 Key Demographic Variables and Measurement Response Variable Measurement Categories Political Ideology Four categories: Liberal, Nominal; recoded Moderate, Conservative, to ordinal for some Something Else analyses Political Party Affiliation Four categories: Democrat, Nominal; recoded Republican, Independent, to dichotomy for Something Else some analyses Sex Two categories: Male or Nominal Female Age Several ages; sometimes Interval recoded into groupings Race Six categories: Caucasian, Nominal; recoded African-American, Asian, to dichotomy for etc. some analyses Hispancity Two categories: Hispanic or Nominal Not Hispanic Educational Attainment Six categories, ranging from Ordinal grade school to post college graduate. Household Income Five categories. Ordinal
Household Finances Three categories: Better Off, Ordinal Worse Off, About the Same Home Ownership Three categories: Own, Rent, Nominal; recoded or Other to dichotomy for some analyses Employment Status Seven Categories Nominal; recoded to dichotomy for some analyses City/Township of Residence Thirty-seven possible Nominal; recoded categories to dichotomy for some analyses Note, more information regarding response categories, coding and response frequencies is outlined in Appendix B of the Dissertation.
101 Statistical Analysis Techniques
The research data will be processed with SPSS (Statistical Package for the Social
Sciences) for Windows, Version 12.0 software on a desk top computer. Table 3.9 outlines the various statistical analysis techniques to be employed to assess the four general research hypotheses. The techniques used will vary depending upon each given research hypothesis and sub-hypothesis.
For research hypotheses H1 and H2, and associated sub-hypotheses, the primary method of analysis will be to compare the means of the responses for the trust in government officials questions. The appropriate statistical analysis technique in this instance is to utilize paired samples, i.e, paired difference, t-tests to compare two means at a time.
The purpose of a paired samples t-test is to compare the means of two survey responses for a given respondent.
As research hypotheses H1 and H2 assert that some means will be greater than others, these t-tests will be gauged at a one-tailed level of significance. However, as there is little existing research that confirms these relationships, i.e., that one mean will be greater than another, paired sample t-tests at a two-tail level of significance will also be examined. The margin of error used to decide whether or not a mean difference is statistically significant or not will be the standard 95% confidence interval. Occasionally in the narrative of the statistical analysis results, reference may be made to 99% confidence intervals, if a given statistical relationship happens to meet this more stringent confidence interval.
102 For research hypothesis H3 the relationship, or lack of a relationship, between public support for a given level of government and public trust in the four associated groups of government officials will be evaluated. The initial analysis will be based on tests of bivariate correlation, examining Pearson correlation coefficients, between responses for the government support questions and responses for trust and government responses.
Subsequently, four-order partial correlation coefficients will be examined applying public trust in the four groups of government officials in concert against public support for government. In sum, the fourth-order partial correlations will calculate adjusted Pearson coefficients for each trust variable adjusting for the effects of the other three trust variables.
As research hypothesis H3 asserts there is a direct or positive relationship between public support for government and trust in government officials, the statistical relationships between variables will be primarily examined at the one-tail level of significance. Two-tail levels of significance may be considered when appropriate. The margin of error used to decide whether or not a correlation coefficient is statistically significant or not will be the standard 95% confidence interval. The narrative of the statistical analysis results may occasionally reference a 99% confidence interval, if a given statistical relationship happens to meet this more stringent confidence interval.
To complete the analysis regarding research hypothesis H3 a multiple regression models will be fitted where public support for government serves as the dependent variable and public trust in government officials serves as the four possible explanatory variables.
Stepwise regression will be utilized to examine the statistical relationships of the four independent variables in concert. Trust variables found not to have a significant relationship
103 with public support for government will be omitted from the fitted model. Three such models will be fitted, one for each of the three levels of government.
At this juncture, a mention is warranted regarding a causality paradox. That is, it is possible that the level of public support or disposition toward government affects public trust in government officials on one hand, but the converse may also be true, that public trust in government officials impacts public disposition toward government. It is also possible that the relationship is a dual-causality relationship, where both variables can have a dynamic impact on the other. There is no current consensus in the literature regarding this relationship and arguments have been made for each of the possibilities (Citrin & Muste,
1999; Hetherington, 2005).
In the final analysis of research hypothesis H3, public support for government will be used as a dependent variable, which is logical in this instance as the issue at hand will be examining a group of the four trust variables on a dependent variable. This could of course be accomplished with the partial correlations, but for the sake of further analysis and discussion, a regression model was employed where public support for government was designated as the dependent variable and the four related trust in government variables designated as independent variables. However, the objectives of this research are not to establish causal relationships, but to candidly examine and discuss general relationship between public support for government and trust in government officials, where either may serve as the dependent and independent variable depending on the context of the a given research hypothesis.
104 With the goal of research hypothesis H4 to examine if there are divergent explanations for public trust in various government officials, multiple regression will be employed where trust in a given government official serves as the dependent variable. Regression models will be fitted for each of the twelve classifications of government officials examined in this study. In these regression models, public support for government will be examined as an explanatory variable. For a given trust in government official independent variable, e.g., trust in the President, the other three associated trust in government officials variables, e.g., trust in presidential appointees, will not be regressed independent variable. The purpose of these omissions are two-fold. First, the goal is to examine the effect of non-trust explanatory variables, such as demographics, on a given trust dependent variable, irrespective of the influence of trust in other government officials. Second, there is a high degree of co-linearity among the various trust variables, such as between trust in the state governor and trust in gubernatorial appointees, which makes incorporating other trust variables into a given trust model problematic.
Initial analysis prior to fitting the twelve trust regression models will include a cursory exam of correlation coefficients between the designated dependent variable and possible variables as candidates for inclusion in a multiple regression model. The initial possible candidates of independent variables include the non-trust variables listed in Tables 3.7 and
3.8. Some important likely explanatory variables, which are nominal measures, such as political party affiliation and respondent race, will be dichotomized for incorporation into the regression models.
105 To complete the analysis for research hypothesis H4, the twelve trust models will be fitted with stepwise regression techniques. Independent variables found not to have a statistically significant relationship with the given dependent variable will be omitted from the fitted model. The fitted multiple regression models will be compared to see if different variables explain public trust in the various government officials.
106 Table 3.9 Statistical Analysis Techniques By Hypothesis General Hypothesis Analytical Techniques
µ: Trust in Public Administrators Primary Analysis: One-tailed, paired > samples t-tests for comparison of means for the associated trust variables. µ: Trust in Elected Executives, H1 Two-tail significance also examined due to µ: Trust in Executives Appointees, a lack of existing research that defines variable relationships. µ: Trust in Other Elected Officials
µ: Trust in County Officials Primary Analysis: One-tailed, paired > samples t-tests for comparison of means for the associated trust variables. µ: Trust in State Officials H2 Two-tail significance also examined due to > a lack of existing research that defines µ: Trust in Federal Officials variable relationships.
$: Trust in Public Administrators > 0, Initial Analysis: One-tail tests of bivariate and partial correlations between the $: Trust in Elected Executives > 0, $ associated trust variables and support for : Trust in Executive Appointees > 0, government. $ H3 : Trust in Other Elected Officials > 0, Primary Analysis: Multiple regression with where Government Support is the Government Support as the dependent dependent variable ("). variable and associated trust variables as the independent variables.
Trust in Public Administrators = Initial Analysis: Tests of bivariate
X1+X2+X3+ ...... Xn correlations between the associated trust variables and support for government. Trust in Elected Executives = Primary Analysis: Twelve multiple X +X +X + ...... X , 1 2 3 n regression models with Trust in government H4 Trust in Executive Appointees = officials as the dependent variables; trust in X +X +X + ...... X , 1 2 3 n other officials not used as independent Trust in Legislatures = variables. X1+X2+X3+ ...... Xn, regardless of the level of government.
107 Study Limitations
Most research studies, especially those involving the social sciences, are imperfect, having limitations regarding research designs and the meaning of the data collected. This research study is no exception. Below is a candid discussion of the limitations associated with this trust in government study.
In broad view, survey research in general, including polling, has fundamental shortcomings. As Nye (1997) observes, public opinion polls are snapshots of moving targets. That is, the data collected are inherently temporal, reflecting attitudes at a particular point in time. In other words, survey data reflect a particular instance within a dynamic environment where attitudes are often changing on an ongoing basis. In the case of this research study, the data collected during the summer of 2004 may not reflect current opinions at the time of its formal presentation.
In a similar vein, Babbie (1998) notes that survey research seldom deals with the complexities of social life. Such research does not reveal the total life situation in which respondents think and act. As such, the data collected through survey research are often incomplete and do not explain all the facets of public opinion. For instance, this study is more descriptive regarding public trust in government rather than outlining explanations regarding such trust.
Sampling bias, when the sample is not representative of the larger population, is an issue that requires address. Although the survey was in essence based on a random
108 probability sample, the selection criteria was based on household telephone numbers. As such, this survey research was basically limited to those households with land-line telephones, which may preclude certain groups such as lower income persons and persons with only wireless telephone service. In addition, for those persons with telephones, some actively screen their telephone calls. For such reasons, the final sample population may not be truly representative of the overall population.
Similar to sampling bias, a primary limitation of this research is its generalizability to larger populations, such as at the state and national level. As noted previously, the study population for this research includes only Stark County residents. Many demographic characteristics of the study population are dissimilar to state and national demographics, more so at the national level. For instance, significantly fewer racial minorities, persons of
Hispanic descent, and immigrants reside in Stark County. As such, it is not possible to assert that Stark County residents, and their views, are representative of state and national populations.
Measurement error is another limitation of studies of this scope. Validity of the survey questions and the extent to which the measures reflect the meaning of the given concept also warrants consideration. In particular face validity, the common agreement of terms, is a concern. For instance, within this study the concept of “trust” and to trust a government official “to do what is right” are vague notions that may mean different things to different people. As such, respondents may not interpret the questions the same. This was addressed to some degree with a focus group examination of the clarity of the survey questions, as well as whether or not the general public could relate to these questions.
109 In addition, content validity, how much a measure covers the range of meanings included in a concept, is also an issue. As trust is a complex and multi-level concept
(Barber, 1983; Weatherford, 1992), the opinions of respondents may not fit into the close ended response categories of the survey questions. In addition, responses of respondents may not reflect the respondent’s true reality. For instance, just because a respondent indicates they always vote, does not mean this is the case. Also, a respondent may not have considered the concepts of a survey question prior to being asked the survey question. For instance, some people will not have thought about trust in a given government official prior to being queried about the issue. As such, the opinion given at the time of the interview may not be fully developed or the respondent may have a non-opinion. It may be that questions are asked of respondents for which they do not know how to respond, for which they do not have a clear opinion.
Hardin (1998) questions the ability of the general public to truly trust government officials and government in general. He asserts civilians simply do not have enough information to form an opinion regarding trust in government. There are just too many officials, contexts and circumstances. In sum, because of content validity issues, the data collected are only approximate indicators of social reality.
Another limitation of this study related to content validity is that, whereas this research study seeks to link public trust in government officials to political support of government, trust is not the only determinant of political support. Other factors include confidence, alienation, responsiveness on the part of government officials, and so on. A thorough examination of the determinants of public support for government, although a worthy
110 endeavor, would require a more comprehensive study that would take the focus of research away from the issue of trust.
Instrument reliability, whether or not the survey instrument would yield the same result when repeatedly applied to the same study population, also warrants mention, but is less of an issue compared to validity concerns. Reliability will be addressed to a large degree through to the use of a carefully worded standardized survey, interviewing conducted by appropriately trained using CATI technology, and the random sampling of the study population.
Despite the limitations of this research study, it is expected to generate useful data worthy of analysis and discussion. When possible, the concerns mentioned herein will be addressed and remediated.
111 CHAPTER IV
RESEARCH FINDINGS
This chapter outlines the general results of the questions regarding trust in government officials and other survey questions. Complete basic response frequencies for all survey questions are outlined in Appendix B. The data are used as evidence to justify support or
reject research hypotheses H1, H2, H3 and H4, which were outlined in the previous chapter.
The general hypotheses are examined with forty specific sub-hypotheses.
Characteristics of the Sample
The sample survey population generated by the 2004 Stark County Omnibus Poll amounted to 1,078 completed surveys. The general population statistics from this sample size provide for a margin of error of plus or minus three percent within a 95% confidence interval, and plus or minus four percent within a 99% confidence interval (Rea & Parker,
2005). That is, results or estimates for simple response questions are accurate to plus or minus three percent in 95 out of 100 cases.
112 A total of 3,557 households were contacted as part of the Stark Poll during June and
July, 2004. Allowing for 2,479 survey refusals, the cooperation rate for the survey amounted to 30.6% of contacted households.
Since the Stark Poll is a random probability survey of adults in Stark County, the demographics of the 2004 Stark Poll respondent population should closely match the statistics generated for Stark County from the United States Census 2000. Table 4.1 compares the demographics of respondents from the 2004 Stark Poll to statistics from the last Census of Population and Housing. In comparing the demographics, two issues should be considered. First, the 2000 Census and the 2004 Stark Poll offer statistics that are snapshots in time, with a four year difference between the two advents. Second, some demographics, especially educational attainment and employment, are not fully comparable due to definition and categorical differences.
For the most part the demographics of the 2004 Stark Poll respondents tend to mirror the demographics for the general population from the 2000 Census. For instance, the proportion of males and females surveyed is comparable to Census figures, as were figures on home ownership and average number of persons in participant households. In the case of racial minorities and persons of Hispanic descent, a slightly higher proportion of these individuals were surveyed as part of the Stark Poll.
Nevertheless, it should be noted that the 2004 Stark Poll tended to include some demographic groups disproportionately. For instance, a higher proportion of persons ages
55 and older were surveyed compared to Census figures, while a lesser proportion of persons ages 18 to 44 were surveyed. In addition, a greater proportion of widowed persons
113 were surveyed compared to Census figures, while a smaller proportion of single persons were surveyed. The Stark Poll was also more likely to include persons with higher levels of educational attainment.
114 Table 4.1 Comparison Demographics: Census Versus Stark Poll(1) Stark Census Stark Poll Demographic 2000 2004 Male 48.0% 48.3% Female 52.0% 51.7% Caucasian 90.3% 88.7% African-American/Other/B-Racial 9.7% 11.3% Hispanic or Latino 0.9% 2.1% Persons 18 to 34 Years of Age 27.1% 18.6% Persons 35 to 44 Years of Age 20.9% 17.8% Persons 45 to 54 Years of Age 19.2% 19.0% Persons 55 to 64 Years of Age 12.6% 17.8% Persons 65 Years and Older 20.1% 26.8% Married 56.6% 54.7% Single, Never Married 23.8% 15.6% Divorced or Separated 12.0% 15.6% Widowed 7.6% 14.0% High School Graduates, Age 25 and Over 83.4% 92.8% At Least Some College, Age 25 and Over 42.2% 56.8% College Graduates, Age 25 and Over 23.3% 29.6% Labor Force: Employed 61.2% 56.6% Labor Force: Unemployed 2.3% 6.0% Retired/Students/Homemakers/Other 36.5% 37.4% Home Ownership Rate 72.4% 72.6% Average Household Size (Persons) 2.49 2.58
(1) For some demographics, especially education and employment, statistics are not directly comparable due to categorical differences between Census 2000 and the Stark Poll.
115 Summary Scores: Trust In Government
The summary results for the thirteen trust questions on the survey instrument are outlined in Table 4.2. Respondents were asked to rate their level of trust in twelve groups of government officials on a scale from one to ten, with one being the lowest level of trust and ten being the highest level of trust. For instance, respondents were asked to rate their level of trust in the President, presidential appointees, members of Congress, and federal government employees to do what is right for the country. Similarly, respondents were asked to rate their level of trust in the Ohio governor, gubernatorial appointees, state legislators, and state government employees to do what is right for the state, and to rate their level of trust in Stark County elected executives, county executive appointees, other elected county officials, and county government employees to do what is right for the county. Trust in government employees will be used as a measure for trust in public administrators.
The mean scores for the trust in government officials questions fall in a tight band within the one to ten rating scale, ranging from 5.40 to 6.60. There does not appear to be great differences with respect to the public’s level of trust in various government officials.
However, many of these mean scores are statistically different from other scores. These results are further analyzed in subsequent sections to support or reject research hypotheses
H1 and H2.
Another preliminary finding regarding the mean trust scores is that they are somewhat unimpressive. On a scale from one to ten, an average score is 5.5. Thus, a few groups of
116 government officials received below-average mean trust scores, while others were only slightly above average.
In addition to the twelve trust in government officials questions, as a benchmark, respondents were asked to rate their level of trust in people in general, regardless of whether or not they work in government. The average score for this measure was 6.69. As such, respondents tended to rate their level of trust in people in general higher than for any of the twelve groups of government officials. That is, respondents trusted most government officials, including public administrators, less than people in general.
117 Table 4.2 Summary Scores: Trust in Government Questions Mean Standard Sample Trust Variables(1) Score(2) Error Size(3) Trust in People in General 6.69 0.056 1,066 Trust in U.S. President 5.73 0.097 1,067 Trust in Presidential Appointees 5.44 0.081 1,056 Trust in U.S. Congress 5.40 0.066 1,060 Trust in Federal Employees 5.88 0.062 1,057 Trust in Ohio Governor 5.52 0.083 1,063 Trust in Ohio Gubernatorial Appointees 5.40 0.070 1,059 Trust in Ohio General Assembly 5.98 0.063 1,047 Trust in Ohio State Employees 6.15 0.058 1,056 Trust in Stark County Executives 6.32 0.066 1,048 Trust in Stark County Appointees 6.10 0.062 1,046 Trust in Other Elected County Officials 6.60 0.065 1,062 Trust in Stark County Employees 6.29 0.058 1,056 (1)More detailed results are outlined in Tables B.1 to B.13 in Appendix B. (2)Average of scores on a scale from 1 to 10, where one is the lowest level of trust and ten is the highest level of trust. (3)Sample sizes vary due to the number of valid responses for each question.
118 Results for Research Hypothesis H1 (Intra-Level Trust in Officials)
The following section outlines the statistical analysis and discussion of the sub-
hypotheses related to research hypothesis H1 – the general public has a higher level of trust for public administrators compared to elected and politically appointed agency officials, regardless of the level of government. Of the nine specific sub-hypotheses examined, seven support this general hypothesis. The following analysis is organized by level of U.S. government: federal (Table 4.3), state (Table 4.4) and county (Table 4.5).
H1A: Intra-Level Trust, Federal Level
Research hypothesis H1:A – the general public has a higher level of trust for federal government public administrators compared to federal elected officials and politically
appointed agency officials – is examined with three specific hypotheses: H1:A1, H1:A2 and
H1:A3. Each hypothesis compares public trust in federal public administrators separately with the President, presidential appointees selected to run federal agencies, and Congress.
Overall, the public does distinguish between the four groups of federal government officials.
The results support hypothesis H1:A;; the public has more trust in federal government employees compared to the other three classifications of federal government officials.
Results of H1:A Sub-Hypotheses. Sub-hypothesis H1:A1 – the public trusts federal public administrators more than the President – is assessed using the first comparison pair of means from Table 4.3. As expected, the recorded mean for trust is federal government employees
119 exceeded the mean for trust in the President. The mean difference between trust in federal employees and the President amounted to 0.17, which generated a t-statistic with a one-tail significance level of 0.047 and a two-tailed level of significance of 0.093. Both levels of significance are calculated to be thorough. Although the theory underlying research
hypothesis H1 assumes public administrators are trusted more than elected officials, thus indicating a one-tail examination, few studies have examined and established this relationship, thus suggesting a two-tail examination should also be considered.
With the null hypothesis being that there is no difference between the means of the trust ratings between federal government public administrators and the President, the null hypothesis is rejected at the one-tail level of significance within a 95% confidence interval, but not rejected at the two-tail level of significance. Although the data nearly fails to reject the null hypothesis, i.e., the statistical difference between means just barely meets the
criteria of a 95% confidence interval, research sub-hypothesis H1:A1 is supported at the one- tail level of significance. As such, for the study population, the results indicate that the general public tends to trust federal government employees, in general, more than the
President.
Sub-hypothesis H1:A2 – the public trusts federal public administrators more than presidential appointees, i.e., those persons appointed by the President to run different government agencies – is assessed using the second comparison of means from Table 4.3.
As anticipated, the recorded mean for trust in federal government employees was greater than the mean for trust in the presidential appointees. The mean difference between these
120 two groups amounted to 0.45, which generated a t-statistic with both a one-tail and two-tail significance level within a 99% confidence interval.
With the null hypothesis being that there is no difference between the means of the trust ratings between federal public administrators and presidential appointees, the null hypothesis is rejected both at the one-tail and two-tail level of significance within a 95% confidence interval. As such, for the study population, the evidence supports research sub-
hypothesis H1A.2 that federal public administrators are trusted more by the general public than presidential appointees to head federal agencies.
Sub-hypothesis H1:A3 – the public trusts federal public administrators more than members of the U.S. Congress – is assessed using the third comparison pair of means from
Table 4.3. As expected, the recorded mean for trust in federal government employees exceeded the mean for trust in Congress. The mean difference between these two groups amounted to 0.48, which generated a t-statistic with both a one-tail and two-tail significance level well within a 99% confidence interval.
With the null hypothesis being that there is no difference between the means of the trust ratings between federal public administrators and members of the U.S. Congress, the null hypothesis is rejected both at the one-tail and two-tail level of significance within a
99% confidence interval. As such, the evidence supports research sub-hypothesis H1:A3 that federal public administrators are trusted more by the general public than members of
Congress, at least for the study population.
H1:A Results Summary. In sum, research hypothesis H1:A – the general public has a higher level of trust for federal government public administrators compared to federal
121 elected officials and politically appointed agency officials – was supported by the data for all three sub-hypothesis. For the study population, federal public administrators were trusted more by the general public than the President, presidential appointees, and the U.S.
Congress.
Besides the comparison of trust in the four groups of federal government officials, trust in federal public administrators was compared to respondent trust in people in general, regardless of whether or not they worked in government. This is assessed with the fourth comparison pair of means in Table 4.3. The recorded mean for trust in federal public administrators was less than that for people in general, with a mean difference of -0.56 which yielded a t-statistic for both a one-tail and two-tail significance level well within a
99% confidence interval.
Thus, the evidence indicates the general public trusts federal public administrators less than people in general. Likewise, the public trusts other federal government officials, namely the President, presidential appointees, and Congress, less than people in general. All four groups of federal government officials are trusted less than people in general, regardless of whether or not they work in government.
122 Table 4.3 Comparison of Means: Trust at the Federal Level
Results for Research Hypothesis H1:A Comparison Statistics(1)
Comparison Groups Paired Mean t Significance Sample Means Difference Statistic (p) Size
Federal Employees 5.89 0.047(T1) 1 U.S. President 0.166 1.684 (T2) 1,048 5.72 0.093
Comment: Hypothesis H1:A1 is supported.
Federal Employees 5.88 0.000(T1) 2 0.448 5.487 (T2) 1,042 Presidential Appointees 5.44 0.000
Comment: Hypothesis H1:A2 is supported.
Federal Employees 5.88 0.000(T1) 3 0.476 7.707 (T2) 1,045 U.S. Congress 5.40 0.000
Comment: Hypothesis H1:A3 is supported.
Federal Employees 5.88 0.000(T1) 4 -0.825 -11.69 (T2) 1,048 People in General 6.70 0.000 Comment: Supplementary hypothesis.
(1) Statistics generated using paired difference t-test procedures. (T1)One-tailed probability of statistical significance. (T2)Two-tailed probability of statistical significance.
123 H1B: Intra-Level Trust, State Level
Research hypothesis H1:B – the general public has a higher level of trust for state government public administrators compared to elected state officials and political appointees selected to run federal departments and agencies – is also examined with three
specific sub-hypotheses: H1:B1, H1:B2 and H1:B3. Each hypothesis compares public trust in state public administrators to the state governor, gubernatorial appointees selected to run state agencies, and the state legislators. Overall, the public does distinguish between the four
groups of state government officials. The results support hypothesis H1:A; the public has more trust in state government employees compared to the other three classifications of federal government officials.
Results of H1:B Sub-Hypotheses. Sub-hypothesis H1.B1 – the public trusts state public administrators more than the state governor – is assessed using the first comparison pair of means from Table 4.4. As expected, the recorded mean for trust in state public administrators exceeded the mean for trust in the state governor. The mean difference between trust in state public administrators and the governor amounted to 0.63, which generated a t-statistic with both a one-tail and two-tail level of significance level within a
99% confidence interval.
With the null hypothesis being that there is no difference between the means of the trust ratings between state public administrators and the governor, the null hypothesis is rejected at both the one-tail and two-tail level of significance within a 95% confidence
interval. As such, the evidence supports research sub-hypothesis H1:B1 that state public
124 administrators are trusted more by the general public than the state governor, at least for the study population.
Sub-hypothesis H1:B2 – the public trusts state public administrators more than gubernatorial appointees – is assessed using the second comparison pair of means from
Table 4.4. As anticipated, the recorded mean for trust in state public administrators exceeded the mean for trust in gubernatorial appointees. The mean difference between trust in state public administrators and gubernatorial appointees amounted to 0.75, which generated a t-statistic with both a one-tail and two-tail level of significance level within a
99% confidence interval.
With the null hypothesis being that there is no difference between the means of the trust ratings for these two groups, the null hypothesis is rejected both at the one-tail and two- tail level of significance within a 95% confidence interval. As such, for the study
population, the evidence supports research hypothesis H1:B2 that state government public administrators are trusted more by the general public than gubernatorial appointees selected to run state agencies.
Sub-hypothesis H1:B3 – the public trusts state public administrators more than members of the state legislature – is assessed using the third comparison pair of means from Table
4.4. As anticipated, the recorded mean for trust in state public administrators exceeded the mean for trust in members of the state legislature. The mean difference between trust in state public administrators and members of the state legislature amounted to 0.17, which generated a t-statistic with both a one-tail and two-tail level of significance level within a
99% confidence interval.
125 With the null hypothesis being that there is no difference between the means of the trust ratings between state public administrators and members of the state legislature, the null hypothesis is rejected both at the one-tail and two-tail level of significance within a
95% confidence interval. As such, the evidence supports research sub-hypothesis H1:B3 that state government public administrators are trusted more by the general public than the state legislatoes as a whole.
H1:B Results Summary. In sum, research hypothesis H1:B – the general public has a higher level of trust for state government public administrators compared to elected state officials and political appointees selected to run federal departments and agencies – was supported by the data for all three sub-hypothesis. For the study population, state public administrators were trusted more by the general public than the governor, gubernatorial appointees, and the state legislators.
In addition to the comparison of trust in the four groups of state government officials, trust in state public administrators was compared to respondent trust in people in general, regardless of whether or not they worked in government. This is assessed with the fourth comparison pair of means in Table 4.4. As was the case with federal public administrators, the recorded mean for trust in state public administrators was less than that for people in general. The mean difference was -0.56 which yielded a t-statistic for both a one-tail and two-tail significance level well within a 99% confidence interval.
Thus, the evidence indicates the general public trusts state public administrators less than people in general. Similarly, the public trusts other state government officials, namely the governor, gubernatorial appointees, and the state legislature, less than people in general.
126 As at the federal level, all four groups of state government officials are trusted less than people in general, regardless of whether or not they work in government.
Table 4.4 Comparison of Means: Trust at the State Level
Results for Research Hypothesis H1:B Comparison Statistics(1)
Comparison Groups Paired Mean t Significance Sample Means Difference Statistic (p) Size
Ohio State Employees 6.15 0.000(T1) 1 0.627 7.817 (T2) 1,047 Ohio Governor 5.52 0.000
Comment: Hypothesis H1:B1 is supported.
Ohio State Employees 6.15 0.000(T1) 2 0.753 12.05 (T2) 1,045 Gubernatorial Appointees 5.40 0.000
Comment: Hypothesis H1:B2 is supported.
Ohio State Employees 6.14 0.000(T1) 3 0.165 3.300 (T2) 1,038 Ohio State Legislature 5.97 0.000
Comment: Hypothesis H1:B3 is supported.
Ohio State Employees 6.15 0.000(T1) 4 -0.561 -8.855 (T2) 1,048 People in General 6.71 0.000 Comment: Supplementary hypothesis.
(1) Statistics generated using paired difference t-test procedures. (T1)One-tailed probability of statistical significance. (T2)Two-tailed probability of statistical significance.
127 H1C: Intra-Level Trust, County Level
Research hypothesis H1:C – the general public has a higher level of trust for county government public administrators compared to elected officials and political appointees
selected to run county agencies – is examined with three sub-hypotheses: H1:C1, H1:C2 and
H1:C3. Each hypothesis compares public trust in county public administrators separately with the elected county executives, executive appointees chosen to run county agencies, and other elected officials such as the county auditor and treasurer. Overall, the results do not support
hypothesis H1:A; only one of the three sub-hypotheses is supported by the evidence. As such, at the local level, the public tends to have the same level of trust in both public administrators and elected and politically appointed government officials.
Results of H1:C Sub-Hypotheses. Sub-hypothesis H1:C1 – the public trusts county government public administrators more than the elected county executives, i.e., three commissioners in the case of the study county – is assessed using the first comparison pair of means from Table 4.5. The recorded mean for trust in county public administrators was not significantly different from the mean for trust in county elected executives. The mean difference between the two groups amounted to only -0.03, which generated a low t-statistic that did not fall within a 95% confidence interval for both one-tail and two-tail levels of significance.
With the null hypothesis being that there is no difference between the means of the trust ratings between county public administrators and elected county executives, the null hypothesis fails to be rejected at both the one-tail and two-tail levels of significance, within
128 a 95% confidence interval. As such, the evidence does not support sub-research hypothesis
H1:C1 that county government public administrators are trusted more by the general public than elected county executives. There was no statistical difference between the paired means for these two groups.
Sub-hypothesis H1:C2 – the general public has a higher level of trust for county government public administrators compared to politically appointed county agency officials
– is assessed using the second comparison pair of means from Table 4.5. As expected, the recorded mean for trust in county public administrators exceeded the mean for trust in county executive appointees. The mean difference between trust in county public administrators and county appointees amounted to 0.18, which generated a t-statistic with both a one-tail and two-tail level of significance level within a 99% confidence interval.
With the null hypothesis being that there is no difference between the means of the trust ratings for these two groups, the null hypothesis is rejected both at the one-tail and two- tail level of significance within a 95% confidence interval. As such, for the study
population, the evidence supports research sub-hypothesis H1:C2 that county public administrators are trusted more by the general public than county executive appointees.
Sub-hypothesis H1:C3 – the public trusts county government public administrators more than other elected county officials – is assessed using the third comparison pair of means from Table 4.5. There was no county legislature for the county of study, as such other elected officials in this case include the county auditor and treasurer. Here, it appears the public has a higher regard for other elected county officials than county public administrators. The recorded mean for trust in county public administrators was smaller than
129 the mean for trust in other elected county officials. The mean difference between trust in county public administrators and other elected officials amounted to -0.30, which generated a t-statistic with both a one-tail and two-tail level of significance level within a 99% confidence interval. Although the difference is statistically significant, it is in the wrong direction.
With the null hypothesis being that there is no difference between the means of the trust ratings between county public administrators and other elected county officials, the null hypothesis is rejected both at the one-tail and two-tail level of significance within a 95% confidence interval. However, the evidence still does not support research sub-hypothesis
H1:C3 that county government public administrators are trusted more by the general public than other elected county officials, as the public trusts the latter more than local public administrators.
H1:C Results Summary. In sum, research hypothesis H1:C – the general public has a higher level of trust for county government public administrators compared to elected officials and political appointees selected to run county agencies – was supported in the case of county executive appointees, but not in the case of the elected county executives and other elected county officials. At the local level, county public administrators are trusted at about the same level as other county officials.
In addition to the comparisons of trust in the four groups of county government officials, trust in county government public administrators was compared to trust in people in general, regardless of whether or not they worked in government. This is assessed with the fourth comparison pair of means in Table 4.5.
130 As was the case with state and federal public administrators, the recorded mean for trust in county public administrators was less than that for people in general. The mean difference was -0.41 which yielded a t-statistic for both a one-tail and two-tail level of significance level within a 99% confidence interval. Thus, the evidence indicates the general public trusts county public administrators less than people in general. Similarly, for the study population, the public trusts elected county executives and county executive appointees less than people in general, but there is no statistical difference in trust levels for other elected county officials and people in general.
131 Table 4.5 Comparison of Means: Trust at the County Level
Results for Research Hypothesis H1:C Comparison Statistics(1)
Comparison Groups Paired Mean t Significance Sample Means Difference Statistic (p) Size
Stark County Employees 6.28 0.259(T1) 1 -0.034 -0.648 (T2) 1,034 Elected County Executives 6.32 0.517
Comment: Hypothesis H1:C1 is not supported.
Stark County Employees 6.28 0.000(T1) 2 0.182 4.275 (T2) 1,039 Executive Appointees 6.10 0.000
Comment: Hypothesis H1:C2 is supported.
Stark County Employees 6.29 0.000(T1) 3 -0.304 -6.032 (T2) 1,048 Other Elected Stark Officials 6.59 0.000
Comment: Hypothesis H1:C3 is not supported.
Stark County Employees 6.29 0.000(T1) 4 -0.408 -6.670 (T2) 1,048 People in General 6.69 0.000 Comment: Supplementary hypothesis.
(1) Statistics generated using paired difference t-test procedures. (T1)One-tailed probability of statistical significance. (T2)Two-tailed probability of statistical significance.
132 Results for Research Hypotheses H2 (Inter-Level Trust in Officials)
The following section outlines the statistical analysis and discussion of the sub-
hypotheses related to research hypothesis H2 – the general public has a higher level of trust in county government officials compared to similar state and federal officials, and a higher level of trust in state government officials compared to similar federal officials. Of the ten sub-hypotheses examined, nine support this general hypothesis. The following analysis is organized by type of government official: public administrators (Table 4.6), top elected executives such as the President and state governor (Table 4.7), persons appointed by elected executives to run government agencies (Table 4.8), and legislative bodies (Table
4.9).
H2A: Inter-Level Trust, Public Administrators
Research hypothesis H2:A – the general public has a higher level of trust in county government public administrators compared to state and federal public administrators, and a higher level of trust in state government public administrators compared to federal public
administrators – is examined with three specific hypotheses: H2:A1, H2:A2 and H2:A3. Each hypothesis compares the level of trust in two different groups of public administrators, and
each supports hypothesis H2:A. Overall, the public does distinguish between public administrators at different levels of government. The results indicate that public trust in
133 local public administrators is greater than public trust in state public administrators which in turn is greater than public trust in federal public administrators.
Results of H2:A Sub-Hypotheses. Sub-hypothesis H2:A1 – the public trusts county government public administrators more than state government public administrators – is assessed using the first comparison pair of means from Table 4.6. As expected, the recorded mean for trust in county public administrators exceeds the mean for trust in state public administrators. The mean difference between these two groups amounted to 0.14, which yielded a t-statistic with a two-tail level of significance of 0.003 and a one-tail level of significance of 0.002. Both levels of significance are calculated for consideration. Although
the theory underlying research hypothesis H2 assumes local government officials are trusted more than officials at higher levels of government, thus indicating a one-tail level of significance should be examined, few studies have examined and demonstrated this relationship, thus suggesting a two-tail level of significance should also be considered.
With the null hypothesis being that there is no difference between the means of the trust ratings between county government public administrators and state government public administrators, the null hypothesis is rejected both at the one-tail and two-tail levels of significance within a 95% confidence interval. As such, for the study population, the
evidence supports research sub-hypothesis H2:A1 that county public administrators are trusted more than state public administrators.
Sub-hypothesis H2:A2 – the public trusts county government public administrators more than federal government public administrators – is assessed using the second comparison pair of means from Table 4.6. As anticipated, the recorded mean for trust in county public
134 administrators exceeds the mean for trust in federal public administrators. The mean difference between these two groups amounted to 0.42, which was greater than the mean difference between county and state public administrators. This yielded a t-statistic with both a one-tail and two-tail level of significance well within a 99% confidence interval.
With the null hypothesis being that there is no difference between the means of the trust ratings between county government public administrators and federal government public administrators, the null hypothesis is rejected both at the one-tail and two-tail levels of significance within a 95% confidence interval. As such, for the study population, the
evidence supports research sub-hypothesis H2:A2 that county public administrators are trusted more than federal public administrators.
Sub-hypothesis H2:A3 – the public trusts state government public administrators more than federal government public administrators – is assessed using the third comparison pair of means from Table 4.6. As expected, the recorded mean for trust in state public administrators exceeds the mean for trust in federal public administrators. The mean difference between these two groups amounted to 0.26, which yielded a t-statistic with both a one-tail and two-tail level of significance well within a 99% confidence interval.
With the null hypothesis being that there is no difference between the means of the trust ratings between state government public administrators and federal government public administrators, the null hypothesis is rejected both at the one-tail and two-tail levels of significance within a 95% confidence interval. As such, for the study population, the
evidence supports research sub-hypothesis H2:A3 that state public administrators are trusted more than federal public administrators.
135 H2:A Results Summary. Research hypothesis H2:A – the general public has a higher level of trust in county government public administrators compared to state and federal public administrators, and a higher level of trust in state government public administrators compared to federal public administrators – is supported by the data. The general public tends to trust local public administrators the most, and federal public administrators the least.
Table 4.6 Comparison of Means: Trust in Government Employees
Results for Research Hypothesis H2:A Comparison Statistics(1)
Comparison Groups Paired Mean t Significance Sample Means Difference Statistic (p) Size
Stark County Employees 6.29 0.002(T1) 1 0.142 3.023 (T2) 1,047 Ohio State Employees 6.15 0.003
Comment: Hypothesis H2:A1 is supported.
Stark County Employees 6.29 0.000(T1) 2 0.423 7.334 (T2) 1,044 Federal Employees 5.87 0.000
Comment: Hypothesis H2:A2 is supported.
Ohio State Employees 6.14 0.000(T1) 3 0.264 5.336 (T2) 1,045 Federal Employees 5.88 0.000
Comment: Hypothesis H2:A3 is supported.
(1) Statistics generated using paired difference t-test procedures. (T1)One-tailed probability of statistical significance. (T2)Two-tailed probability of statistical significance.
136 H2B: Inter-Level Trust, Elected Executives
Research hypothesis H2:B – the general public has a higher level of trust in elected county executives compared to the state governor and President, and a higher level of trust in state governor compared to the President – is also examined with three specific
hypotheses: H2:B1, H2:B2 and H2:B3. Each hypothesis compares the level of trust in two different groups of elected government executives. Overall, the public does distinguish between elected executives at the different levels of government. The results indicate that public trust in elected county executives is greater than public trust in the state governor and
President. However, the public tends to trust the President more than the state governor.
Results of H2:B Sub-Hypotheses. Sub-hypothesis H2:B1 – the public trusts elected county executives more than the state governor – is assessed using the first comparison pair of means from Table 4.7. As anticipated, the recorded mean for trust in county elected executives exceeds the mean for trust in the state governor. The mean difference between these two groups amounted to 0.78, which yielded a t-statistic with both a one-tail and two- tail level of significance well within a 99% confidence interval.
With the null hypothesis being that there is no difference between the means of the trust ratings between local government executives and the state governor, the null hypothesis is rejected both at the one-tail and two-tail levels of significance within a 95% confidence interval. As such, for the study population, the evidence supports research sub-hypothesis
H2:B1 that elected county executives are trusted more than the state executive.
137 Sub-hypothesis H2:B2 – the public trusts elected county executives more than the U.S.
President – is assessed using the second comparison pair of means from Table 4.7. As expected, the recorded mean for trust in county elected executives exceeds the mean for trust in the U.S. President. The mean difference between these two groups amounted to 0.58, which yielded a t-statistic with both a one-tail and two-tail level of significance well within a 99% confidence interval.
With the null hypothesis being that there is no difference between the means of the trust ratings between county government executives and the President, the null hypothesis is rejected both at the one-tail and two-tail levels of significance within a 95% confidence interval. As such, for the study population, the evidence supports research sub-hypothesis
H2:B2 that elected county executives are trusted more than the President.
Sub-hypothesis H2:B3 – the public trusts the state governor more than the U.S. President
– is assessed using the third comparison pair of means from Table 4.6. The mean difference between these two groups amounted to -22, which yielded a t-statistic with a two-tail level of significance of 0.021, which falls within a 95% confidence interval. The means of the trust levels of state executive and President were statistically different; however, whereas it was predicted that the level of trust in the governor would be greater than the President, this was not the case. Trust was higher for the President than the state governor.
With the null hypothesis being that there is no difference between the means of the trust ratings between the state governor and the President, the null hypothesis is rejected both at the one-tail and two-tail levels of significance within a 95% confidence interval.
138 However, research sub-hypothesis H2:B3 is still not supported, as the level of trust in the
President exceeded trust in the state governor.
H2:B Results Summary. In sum, research hypothesis H2:B – the general public has a higher level of trust in elected county executives compared to the state governor and
President, and a higher level of trust in the state governor compared to the President – is supported partially by the data. The public tends to trust county elected executives more than the governor and President, but the state governor was not trusted more than the President.
Table 4.7 Comparison of Means: Trust in Elected Executives
Results for Research Hypothesis H2:B Comparison Statistics(1)
Comparison Groups Paired Mean t Significance Sample Means Difference Statistic (p) Size
Stark Elected Executives 6.32 0.000(T1) 1 0.779 10.06 (T2) 1,039 Ohio Governor 5.55 0.000
Comment: Hypothesis H2:B1 is supported.
Stark Elected Executives 6.32 0.000(T1) 2 0.584 6.112 (T2) 1,039 U.S. President 5.74 0.000
Comment: Hypothesis H2:B2 is supported.
Ohio Governor 5.53 0.011(T1) 3 -0.215 -2.303 (T2) 1,055 U.S. President 5.74 0.021
Comment: Hypothesis H2:B3 is not supported.
(1) Statistics generated using paired difference t-test procedures. (T1)One-tailed probability of statistical significance. (T2)Two-tailed probability of statistical significance.
139 H2C: Inter-Level Trust, Executive Appointees
Research hypothesis H2:C – the general public has a higher level of trust for county executive appointees compared to state gubernatorial appointees and presidential appointees, and a higher level of trust in gubernatorial appointees compared to presidential appointees
– is examined with three sub-hypotheses: H2:C1, H2:C2 and H2:C3. Each hypothesis compares the level of trust in two different groups of persons politically appointed to run government agencies. Overall, the public does distinguish between political appointees at the different levels of government. The results indicate that public trust in county political appointees is greater than public trust in state gubernatorial appointees and presidential appointees.
Results of H2:C Sub-Hypotheses. Sub-hypothesis H2:C1 – the public trusts county executive appointees more than state gubernatorial appointees – is assessed using the first comparison pair of means from Table 4.8. As expected, the recorded mean for trust in county executive appointees exceeds the mean for trust in gubernatorial appointees. The mean difference between these two groups amounted to 0.69, which yielded a t-statistic with both a one-tail and two-tail level of significance well within a 99% confidence interval.
With the null hypothesis being that there is no difference between the means of the trust ratings between county executive appointees and gubernatorial apointees, the null hypothesis is rejected both at the one-tail and two-tail levels of significance within a 95% confidence interval. As such, for the study population, the evidence supports research sub-
hypothesis H2:C1 that county executive appointees are trusted more than the state gubernatorial appointees.
140 Sub-hypothesis H2:C2 – the public trusts county executive appointees more than the presidential appointees – is assessed using the second comparison pair of means from Table
4.8. As anticipated, the recorded mean for trust in county executive appointees exceeds the mean for trust in presidential appointees. The mean difference between these two groups amounted to 0.67, which yielded a t-statistic with both a one-tail and two-tail level of significance well within a 99% confidence interval.
With the null hypothesis being that there is no difference between the means of the trust ratings between county executive appointees and presidential appointees, the null hypothesis is rejected both at the one-tail and two-tail levels of significance within a 95% confidence interval. As such, for the study population, the evidence supports research
hypothesis H2:C2 that county executive appointees are trusted more than persons appointed by the President to run federal agencies.
Sub-hypothesis H2:C3 – the public trusts state gubernatorial appointees more than the presidential appointees – is assessed using the third comparison pair of means from Table
4.8. There was no statistical difference between the means in trust levels for these two groups.
With the null hypothesis being that there is no difference between the means of the trust ratings between state gubernatorial appointees and presidential appointees, the null hypothesis fails to be rejected both at the one-tail and two-tail levels of significance within a 95% confidence interval. As such, for the study population, the evidence does not support
research sub-hypothesis H2:C3 that state gubernatorial appointees are trusted more than
141 persons appointed by the President to run federal agencies. The general public tends to trust both groups at relatively the same level.
H2:C Results Summary. In sum, research hypothesis H2:C – the general public has a higher level of trust for county executive appointees compared to the state gubernatorial appointees and presidential appointees, and a higher level of trust in gubernatorial appointees compared to presidential appointees – was partially supported by the data. The general public trusts county executive appointees more than state gubernatorial and
Presidential appointees, but there was no difference in trust between gubernatorial appointees and Presidential appointees.
142
Table 4.8 Comparison of Means: Trust in Executive Appointees
Results for Research Hypothesis H2:C Comparison Statistics(1)
Comparison Groups Paired Mean t Significance Sample Means Difference Statistic (p) Size
Stark County Appointees 6.10 0.000(T1) 1 0.693 11.02 (T2) 1,040 Ohio Gubernatorial Appointees 5.41 0.000
Comment: Hypothesis H2:C1 is supported.
Stark County Appointees 6.11 0.000(T1) 2 0.669 8.330 (T2) 1,033 Presidential Appointees 5.44 0.000
Comment: Hypothesis H2:C2 is supported.
Ohio Gubernatorial Appointees 5.41 0.328(T1) 3 -0.033 -0.447 (T2) 1,045 Presidential Appointees 5.44 0.655
Comment: Hypothesis H2:C3 is not supported.
(1) Statistics generated using paired difference t-test procedures. (T1)One-tailed probability of statistical significance. (T2)Two-tailed probability of statistical significance.
H2D: Inter-Level Trust, Elected Legislators
Research hypothesis H2:D – general public has a higher level of trust for county legislatures compared to the state legislature and U.S. Congress, and a higher level of trust for the state legislature compared to Congress – is examined with only one specific
143 hypothesis: H2:D1. As there was no legislative body at the local level, the sub-hypothesis will focus on the state legislature and Congress.
Research hypothesis H2.D1 – the public trusts the state legislature more than the U.S.
Congress – is assessed in Table 4.9. As expected, the recorded mean for trust in the state legislature exceeded the mean for trust in Congress. The mean difference between these two groups amounted to 0.58, which yielded a t-statistic with both a one-tail and two-tail level of significance well within a 99% confidence interval.
With the null hypothesis being that there is no difference between the means of the trust ratings for the state legislature and Congress, the null hypothesis is rejected both at the one-tail and two-tail levels of significance within a 95% confidence interval. As such, for
the study population, the evidence supports research hypothesis H2:D1 that the state legislature, as a whole, is trusted more than the U.S. Congress as a whole.
Table 4.9 Comparison of Means: Trust in Legislatures
Results for Research Hypothesis H2:D Comparison Statistics(1)
Comparison Groups Paired Mean t Significance Sample Means Difference Statistic (p) Size
Ohio State Legislature 5.98 0.000(T1) 1 0.579 9.396 (T2) 1,038 U.S. Congress 5.40 0.000
Comment: Hypothesis H2:D is supported.
(1) Statistics generated using paired difference t-test procedures. (T1)One-tailed probability of statistical significance. (T2)Two-tailed probability of statistical significance.
144 Results for Research Hypotheses H3 (Government Direction and Trust)
The following section outlines the statistical analysis and discussion of the sub-
hypotheses related to research hypothesis H3 – there is a direct relationship between public trust in government officials and general support for government, regardless of the level of government. For example, as trust in federal government officials increases, support for federal government should also increase. Likewise, if trust in federal government officials declines, support for federal government should also decline. Of the twelve sub-hypotheses examined, seven support this general hypothesis. At all three levels of government, trust in public administrators was found to not be related to support for government. The following analysis is organized by the three levels of U.S. government: federal (Tables 4.10), state
(Tables 4.11), and county (Tables 4.12).
H3A: Government Direction and Trust, Federal Level
Research hypothesis H3:A – there is a direct relationship between public trust in federal government officials and public support for federal government – is examined with four
specific sub-hypotheses: H3:A1, H3:A2, H3:A3 and H3:A4. Each hypothesis examines the relationship between support for federal government and the four classifications of federal government officials. Bivariate correlations are initially calculated between support and trust variables. Fourth-order partial correlations are calculated to assess the relationship between support for government and a trust in government officials, adjusting for the effects of trust
145 in other federal government officials (see Table 4.10). Lastly, a regression model is fitted where support in federal government is the dependent variable and the four trust in federal government officials are the independent variables.
Results of H3:A Sub-Hypotheses. Sub-hypothesis H3:A1 – there is a direct relationship between trust in federal public administrators and support for federal government – was not supported by the data. The bivariate correlation between support for federal government and trust in federal public administrators yielded a Pearson Coefficient of 0.173, which was statistically significant within a 95% confidence interval. The partial correlation, adjusting for the effects of trust in the President, presidential appointees and Congress, amounted to
-0.055. Curiously, the sign of the coefficient was negative, indicating trust in public administrators had an indirect relationship with support for government. Although the partial correlation was statistically significant at the one-tail level, it was not statistically significant at the two-tail level, which is a better measure in this case.
The null hypothesis that there is no relationship between support for federal government and trust in federal public administrators was not rejected. As such, the
evidence does not support research sub-hypothesis H3:A1. For the sample population, there is no relationship between support for federal government and trust in federal public administrators.
Sub-hypothesis H3:A2 – there is a direct relationship between trust in the President and support for federal government – was supported by the data. The bivariate correlation between support for federal government and trust in the President yielded a high Pearson
Coefficient of 0.666, which was statistically significant within a 95% confidence interval.
146 When controlling for the effects of trust in presidential appointees, Congress and federal public administrators, the partial correlation amounted to about half of the bivariate correlation but was still significant. The Pearson Coefficient of the partial correlation between trust in the President and support for federal government amounted to 0.332, which was significant within a one-tail, 99% confidence interval. This was the largest partial correlation of the four trust in federal government officials variables.
With the null hypothesis being that there is no relationship between trust in the
President and support for the federal government, the null hypothesis is rejected based on data from the sample population. As such, the evidence supports research sub-hypothesis
H3:A2. There is a direct relationship between trust in the President and support for the federal government.
Sub-hypothesis H3:A3 – there is a direct relationship between trust in presidential appointees and support for federal government – was also supported by the data. The bivariate correlation between support for federal government and trust in presidential appointees yielded a high Pearson Coefficient of 0.618, which was statistically significant within a 95% confidence interval. When controlling for the effects of trust in the President,
Congress and federal public administrators, the partial correlation amounted to less than one-third of the bivariate correlation but was still significant. The partial Pearson Coefficient between trust in presidential appointees and support for federal government amounted to
0.136, which was significant within a one-tail, 99% confidence interval.
With the null hypothesis being that there is no relationship between trust in presidential appointees and support for the federal government, the null hypothesis is
147 rejected based on data from the sample population. As such, the research sub-hypothesis
H3:A3 is supported. There is a direct relationship between trust in presidential appointees and support for the federal government.
Sub-hypothesis H3:A4 – there is a direct relationship between trust in the U.S. Congress and support for federal government – was not supported by the data. The bivariate correlation between support for federal government and trust in the U.S. Congress yielded a Pearson Coefficient of 0.342, which was statistically significant within a 95% confidence interval. The partial correlation, adjusting for the effects of trust in the President, presidential appointees and federal public administrators, amounted to -0.002, which was statistically significant within both a one-tail and two-tail 95% confidence interval.
With the null hypothesis being that there is no relationship between trust in Congress and support for the federal government, the null hypothesis is not rejected based on data
from the sample population. As such, the research sub-hypothesis H3:A4 is not supported.
There appears to be no relationship between trust in the U.S. Congress and support for the federal government.
H3:A Results Summary. In sum, research hypothesis H3:A – there is a direct relationship between public trust in federal government officials and public support for federal government – is supported in the case of the President and presidential appointees, but not for Congress and federal public administrators. A multiple regression analysis, where trust in the four groups of federal government officials served as an independent variable and support for federal government served as the dependent variable, also verifies the results
(see Table 4.10).
148 Table 4.10 Associations: Government Support and Trust in Federal Officials
Results for Research Hypothesis H3:A Bivariate Correlation Statistics
Bivariate Correlations Pearson Significance Sample Coefficient (p) Size
U.S. Trust: U.S. President 0.666 0.000(T1) 1,059 Government (T1) Direction Trust: Presidential Appointees 0.618 0.000 1,050 Trust: U.S. Congress 0.342 0.000(T1) 1,055 Trust: Federal Employees 0.173 0.000(T1) 1,053 Partial Correlation Statistics
Partial Correlations: Fourth Order Pearson Significance Sample Coefficient (p) Size
U.S. Trust: U.S. President 0.332 0.000(T1) Government (T1) Direction Trust: Presidential Appointees 0.136 0.000 1,024 Trust: U.S. Congress -0.002 0.940(T2) Trust: Federal Employees -0.055 0.078(T2) Regression Statistics (1) Multivariate Regression: Fitted Standardized t Significance Coefficient Statistic (p)
U.S. Trust: U.S. President 0.515 11.45 0.000(T1) Government (T1) Direction Trust: Presidential Appointees 0.184 4.089 0.000 Trust: U.S. Congress Variable Omitted From Fitted Model Trust: Federal Employees Variable Omitted From Fitted Model
Fitted Analysis of Variance (F) 440.65 0.000(T1) Model Summary Adjusted R Square 0.461 Standard Error of Estimate 0.880
(p)Probability levels are designated as either two tail(T2) or one tail(T1) distributions. (1) Fitted regression model with federal Government Direction as the dependent variable and Trust in the four groups of government officials examined as independent variables.
149 H3B: Government Direction and Trust, State Level
Research hypothesis H3:B – there is a direct relationship between public trust in state government officials and public support for state government – is also examined with four
specific sub-hypotheses: H3:A1, H3:A2, H3:A3 and H3:A4. Each hypothesis examines the relationship between support for state government and the four classifications of state government officials. Bivariate correlations are initially calculated between government support and trust variables. Fourth-order correlations are calculated to assess the relationship between support for state government and trust in government officials, adjusting for the effects in other state government officials (see Table 4.11). Lastly, a regression model is fitted where support for state government is the dependent variable and the four trust in state government officials are the independent variables.
Results of H3:B Sub-Hypotheses. Sub-hypothesis H3:B1 – there is a direct relationship between trust in state public administrators and support for state government – was not supported by the data. The bivariate correlation between support for state government and trust in state public administrators yielded a Pearson Coefficient of 0.231, which was statistically significant within a 95% confidence interval. The partial correlation, adjusting for the effects of trust in the governor, gubernatorial appointees and the state legislature, amounted to -0.063. As was the case at the federal level, the sign of the coefficient was negative, indicating trust in public administrators had an indirect relationship with support for government. The partial correlation was barely statistically significant within a two-tail,
95% confidence interval. When combined with the other trust variables in a multiple
150 regression model, trust in state public administrators was omitted from the fitted model due to a lack of statistical significance.
The null hypothesis that there is no relationship between support for state government and trust in state public administrators was not rejected. As such, the evidence does not
support research sub-hypothesis H3:B1. For the sample population, there is no relationship between support for state government and trust in state public administrators.
Sub-hypothesis H3:B2 – there is a direct relationship between trust in the state governor and support for state government – was supported by the data. The bivariate correlation between support for state government and trust in the governor yielded a high Pearson
Coefficient of 0.567, which was statistically significant within a 95% confidence interval.
When controlling for the effects of trust in gubernatorial appointees, state legislature and state public administrators, the partial correlation amounted to less than half of the bivariate correlation, but was still significant. The Pearson Coefficient of the partial correlation between trust in the state governor and support for state government amounted to 0.244, which was significant within a one-tail, 99% confidence interval. This was the largest partial correlation of the four trust in state government officials variables.
With the null hypothesis being that there is no relationship between trust in the governor and support for the state government, the null hypothesis is rejected based on data
from the sample population. As such, the evidence supports research sub-hypothesis H3:B2.
There is a direct relationship between trust in the state governor and support for state government.
151 Sub-hypothesis H3:B3 – there is a direct relationship between trust in state gubernatorial appointees and support for state government – was also supported by the data. The bivariate correlation between support for state government and trust in gubernatorial appointees yielded a high Pearson Coefficient of 0.537, which was statistically significant within a 95% confidence interval. When controlling for the effects of trust in the governor, state legislature and state public administrators, the partial correlation amounted to less than one- third of the bivariate correlation, but was still significant. The Pearson Coefficient of the partial correlation between trust in gubernatorial appointees and support for state government amounted to 0.133, which was significant within a one-tail, 99% confidence interval.
With the null hypothesis being that there is no relationship between trust in gubernatorial appointees and support for the state government, the null hypothesis is rejected based on data from the sample population. As such, the evidence supports research sub-
hypothesis H3:B3. There is a direct relationship between trust in gubernatorial appointees and support for the state government.
Sub-hypothesis H3:B4 – there is a direct relationship between trust in the state legislature and support for state government – was not supported by the data. The bivariate correlation between support for state government and trust in the state legislature yielded a Pearson Coefficient of 0.387, which was statistically significant within a 95% confidence interval. However, the partial correlation, adjusting for the effects of trust in the governor, gubernatorial appointees and state public administrators, amounted to 0.032, which was not statistically significant within both a one-tail and two-tail 95% confidence interval.
152 With the null hypothesis being that there is no relationship between trust in the state legislature and support for the state government, the null hypothesis is not rejected based on data from the sample population. As such, the evidence does not support research sub-
hypothesis H3:A4. There appears to be no relationship between trust in the state legislature and support for state government.
H3:B Results Summary. In sum, research hypothesis H3:B – there is a direct relationship between public trust in state government officials and public support for state government
– is supported in the case of the governor and gubernatorial appointees, but not for the state legislature and state public administrators. A multiple regression analysis, where trust in the four groups of federal government officials served as the independent variable and support for federal government served as the dependent variable, also verifies the results (see Table
4.11). Although the partial correlation for trust in state public employees was negative and somewhat statistically significant , this variable was omitted from the fitted regression model due to lack of statistical significance.
153 Table 4.11 Associations: Government Support and Trust in State Officials
Results for Research Hypothesis H3:B Bivariate Correlation Statistics
Bivariate Correlates Pearson Significance Sample Coefficient (p) Size
Ohio Trust: Ohio Governor 0.567 0.000(T1) 1,049 Government (T1) Direction Trust: Gubernatorial Appointees 0.537 0.000 1,045 Trust: Ohio General Assembly 0.387 0.000(T1) 1,035 Trust: Ohio State Employees 0.231 0.000(T1) 1,042 Partial Correlation Statistics
Partial Correlations: Fourth Order Pearson Significance Sample Coefficient (p) Size
Ohio Trust: Ohio Governor 0.244 0.000(T1) Government (T1) Direction Trust: Gubernatorial Appointees 0.133 0.000 1,015 Trust: Ohio General Assembly 0.032 0.306(T2) Trust: Ohio State Employees -0.063 0.046(T2) Regression Statistics (1) Multivariate Regression: Fitted Standardized t Significance Coefficient Statistic (p)
Ohio Trust: Ohio Governor 0.389 8.392 0.000(T1) Government (T1) Direction Trust: Gubernatorial Appointees 0.211 4.537 0.000 Trust: Ohio General Assembly Variable Omitted From Fitted Model Trust: Ohio State Employees Variable Omitted From Fitted Model
Fitted Model Analysis of Variance (F) 253.53 0.000(T1) Summary Adjusted R Square 0.331 Standard Error of Estimate 0.834
(p)Probability levels are designated as either two tail(T2) or one tail(T1) distributions. (1) Fitted regression model with state Government Direction as the dependent variable and Trust in the four groups of government officials examined as independent variables.
154 H3C: Government Direction and Trust, County Level
Research hypothesis H3:C – there is a direct relationship between public trust in county government officials and public support for county government – is also examined with four
specific sub-hypotheses: H3:C1, H3:C2, H3:C3 and H3:C4. Each hypothesis examines the relationship between support for county government and the four classifications of county government officials. Bivariate correlations are initially calculated between government support and trust variables. Fourth-order correlations are calculated to assess the relationship between support for county government and trust in government officials, adjusting for the effects of other county government officials (see Table 4.12). Lastly, a regression model is fitted where support for county government is the dependent variable and the four trust in county government officials are the explanatory variables.
Results of H3:C Sub-Hypotheses. Sub-hypothesis H3:C1 – there is a direct relationship between trust in county public administrators and support for county government – was not supported by the data. The bivariate correlation between support for state government and trust in state public administrators did yield a Pearson Coefficient of 0.377, which was statistically significant within a 95% confidence interval. However, the partial correlation, adjusting for the effects of trust in the county executives, executive appointees and other elected county officials, amounted to only -0.004, which was not statistically significant. As was the case at the federal and state level, the sign of the coefficient was negative.
The null hypothesis that there is no relationship between support for county government and trust in county public administrators was not rejected. As such, the
155 evidence does not support research sub-hypothesis H3:C1. For the sample population, there is no relationship between support for county government and trust in county public administrators. This mirrors the results of the federal and state level.
Sub-hypothesis H3:B2 – there is a direct relationship between trust in the elected county executives and support for county government – was supported by the data. The bivariate correlation between support for state government and trust in the governor yielded a high
Pearson Coefficient of 0.474, which was statistically significant within a 95% confidence interval. When controlling for the effects of trust in trust in executive appointees, other elected county officials and county public administrators, the partial correlation amounted to less than one-quarter of the bivariate correlation, but was still significant. The Pearson
Coefficient of the partial correlation between trust in elected county officials and support for county government amounted to 0.103, which was significant within a one-tail, 99% confidence interval.
With the null hypothesis being that there is no relationship between trust in the elected county executives and support for the county government, the null hypothesis is rejected based on data from the sample population. As such, the evidence supports research sub-
hypothesis H3:C2. There is a direct relationship between trust in the county executives and support for county government.
Sub-hypothesis H3:C3 – there is a direct relationship between trust in county executive appointees and support for county government – was also supported by the data. The bivariate correlation between support for county government and trust in executive appointees yielded a high Pearson Coefficient of 0.487, which was statistically significant
156 within a 95% confidence interval. When controlling for the effects of trust in county executives, other elected officials and county public administrators, the partial correlation amounted to less than one-quarter of the bivariate correlation, but was still statistically significant. The Pearson Coefficient of the partial correlation between trust in county executive appointees and support for county government amounted to 0.117, which was significant within a one-tail, 99% confidence interval.
With the null hypothesis being that there is no relationship between trust in county executive appointees and support for county government, the null hypothesis is rejected based on data from the sample population. As such, the evidence supports research sub-
hypothesis H3:C3. There is a direct relationship between trust in county executive appointees and support for county government.
Sub-hypothesis H3:C4 – there is a direct relationship between trust in other elected county officials and support for county government – was also supported by the data. The bivariate correlation between support for county government and trust in executive appointees yielded a high Pearson Coefficient of 0.470, which was statistically significant within a 95% confidence interval. When controlling for the effects of trust in the county executives, executive appointees and county public administrators, the partial correlation amounted to less than one-quarter of the bivariate correlation, but was still statistically significant. The Pearson Coefficient of the partial correlation between trust in other elected county officials and support for county government amounted to 0.117, which was significant within a one-tail, 99% confidence interval.
157 With the null hypothesis being that there is no relationship between trust in other elected county officials and support for county government, the null hypothesis is rejected.
As such, the evidence supports research sub-hypothesis H3:C4. There is a direct relationship between trust in other elected county officials and support for county government.
H3:C Results Summary. In sum, research hypothesis H3:C – there is a direct relationship between public trust in county government officials and public support for county government – is supported in the case of the elected county executives, executive appointees and other elected county officials, but in the case of county state public administrators. A multiple regression analysis, where trust in the four groups federal government officials served as the independent variable and support for federal government served as the dependent variable, also verifies the results (see Table 4.12).
158 Table 4.12 Associations: Government Support and Trust in County Officials
Results for Research Hypothesis H3:C Bivariate Correlation Statistics
Bivariate Correlates Pearson Significance Sample Coefficient (p) Size
Stark Trust: County Executives 0.474 0.000(T1) 1,027 County (T1) Government Trust: Executive Appointees 0.487 0.000 1,027 Direction Trust: Other Elected Stark Officials 0.470 0.000(T1) 1,040 Trust: Stark County Employees 0.377 0.000(T1) 1,036 Partial Correlation Statistics
Partial Correlations: Fourth Order Pearson Significance Sample Coefficient (p) Size
Stark Trust: County Executives 0.103 0.001(T1) County (T1) Government Trust: Executive Appointees 0.117 0.000 1,004 Direction Trust: Other Elected Stark Officials 0.117 0.000(T1) Trust: Stark County Employees -0.004 0.898(T2) Regression Statistics (1) Multivariate Regression: Fitted Standardized t Significance Coefficient Statistic (p)
Stark Trust: County Executives 0.161 3.297 0.001(T1) County (T1) Government Trust: Executive Appointees 0.208 4.086 0.000 Direction Trust: Other Elected Stark Officials 0.190 3.739 0.000(T1) Trust: Stark County Employees Variable Omitted From Fitted Model Fitted Model Analysis of Variance (F) 24.88 0.000(T1) Summary Adjusted R Square 0.269 Standard Error of Estimate 0.808 (p)Probability levels are designated as either two tail(T2) or one tail(T1) distributions. (1) Fitted regression model with Government Direction as the dependent variable and Trust in the four groups of government officials examined as independent variables.
159 Results for Research Hypotheses H4 (Explanations of Public Trust)
The following sections outline the statistical analysis and discussion of the sub-
hypotheses related to research hypothesis H4 –explanatory variables for public trust in public administrators are different from variables explaining trust in other officials at the same level of government. Of the nine sub-hypotheses examined, all support this general hypothesis. At all three levels of government, the trust regression model for public administrators is consistent and different from that of other government officials. The following analysis is organized by the three levels of U.S. government: federal (Table 4.13), state (Table 4.14) and county (Table 4.15).
H4A: Explanatory Variables, Federal Level
Research hypothesis H4:A – public trust in federal public administrators is explained differently than trust in the President, presidential appointees and Congress – is examined
with three specific sub-hypotheses: H4:A1, H4:A2 and H4:A3. Each sub-hypothesis compares the fitted regression model for trust in federal public administrators with the other three groups of federal government officials. In this analysis, trust in a given government official serves as the dependent variable, while support for federal government and a host of demographic variables are examined as independent variables. When fitting the individual regression models, trust in the three other government officials were not examined as independent variables.
160 Results of H4:A Sub-Hypotheses. Sub-hypothesis H4:A1 – the explanatory model for public trust in federal public administrators is different from the trust model for the
President – was supported by the data. The fitted regression model for trust in federal public administrators included two explanatory variables: trust in people in general and support for federal government. Trust in people had the largest impact on explaining trust in federal public administrators, with a standardized coefficient of 0.284, which was significant within a 95% confidence interval (see Column 4, Table 4.13). The standardized coefficient for support for the federal government amounted to 0.158, which was also statistically significant. Since the signs for both variables is positive, these variables are directly related to trust in public administrators. The adjusted R2 for this model amounted 0.108, indicating that, combined, these two independent variables explain roughly 11% of the variance in trust in federal public administrators. With respect to analysis of variance, the model generated a F-statistic of 34.8, which was significant within a 99% confidence interval.
The fitted model for trust in the President was more robust than the trust model for public administrators. Eight independent variables were statistically significant within the model. These included, in order of importance, support for federal government, republican party affiliation, political ideology, household financial status, trust in people in general, racial minority inclusion, voting activity and urban residence (see Column 1, Table 4.13).
As with federal public administrators, support for the federal government and trust in people in general contributed positively to trust in the President. Persons who indicated they were republican or conservative were more likely to trust the President compared to democrats or independents and liberals or moderates. Persons from households that were better off
161 financially from the previous year were more likely to have higher levels of trust in the
President compared to those from households that were worse off financially. Racial minorities and urban residents were more likely to have lower levels of trust in the President compared to Caucasians and suburban residents. Persons who vote less frequently were more likely to have higher levels of trust in the President compared to persons who vote more frequently. This model attained a relatively high R2 value of 0.558 and an F-statistic of 131.5, which was significant within a 99% confidence interval.
With the null hypothesis being that there is no difference between the explanatory variables in the fitted regression models for trust in federal public administrators and trust in the President, the null hypothesis is rejected. As such, the evidence supports research sub-
hypothesis H4:A1 that there are divergent explanations for trust in federal public administrators and trust in the President.
Sub-hypothesis H4:A2 – the explanatory model for public trust in federal public administrators is different from the trust model for presidential appointees – was also supported by the data. Five independent variables were statistically significant within the fitted trust model for presidential appointees, and all five were inclusive of the trust model for the President. These included, in order of importance, support for federal government, republican party affiliation, trust in people in general, household financial status and political ideology (see Column 2, Table 4.13). As with the trust model for the President, support for the federal government and trust in people in general contributed positively to trust in presidential appointees. Likewise, persons who indicated they were republican or conservative were more likely to have higher levels of trust in presidential appointees
162 compared to democrats or independents and liberals or moderates. Persons from households that were better off financially from the previous year were also more likely to trust presidential appointees compared to those from households that were worse off financially.
This model attained a relatively high R2 value of 0.459 and an F-statistic of 141.7, which was significant within a 99% confidence interval.
With the null hypothesis being that there is no difference in the explanatory variables for the fitted regression models for trust in federal public administrators and trust in presidential appointees, the null hypothesis is rejected. As such, the evidence supports
research sub-hypothesis H4:A2 that there are divergent explanations for trust in federal public administrators and trust in presidential appointees.
Sub-hypothesis H4:A3 – the explanatory model for public trust in federal public administrators is different from the trust model for Congress – was also supported by the data. Five explanatory variables were statistically significant within the fitted regression trust model for Congress. These included, in order of importance, support for the federal government, trust in people in general, gender, household financial status and racial minority inclusion (see Column 3, Table 4.13). As with the other trust models, support for the federal government and trust in people in general contributed positively to trust in Congress.
Likewise, persons from households that were better off financially from the previous year were also more likely to have higher levels of trust in Congress appointees compared to persons from households that were worse off financially. Females were more likely to have higher levels of trust in Congress compared to males, and racial minorities were more likely to have lower levels of trust in Congress compared to Caucasians. This model attained a R2
163 value of 0.160 and an F-statistic of 40.0, which was significant within a 99% confidence interval.
With the null hypothesis being that there is no difference in the explanatory variables in the fitted regression models of trust in federal public administrators and trust in Congress,
the null hypothesis is rejected. As such, the evidence supports research sub-hypothesis H4:A3 that there are divergent explanations for public trust in federal public administrators and public trust in Congress.
H4:A Results Summary. In sum, research hypothesis H4:A – public trust in federal public administrators is explained differently than trust in the President, presidential appointees and
Congress – is supported. Two independent variables were inclusive to all four fitted regression models for trust in federal government officials. These included support for federal government and trust in people in general. However, the impact of these variable in explaining trust in a given government official varied. For instance, support for federal government was the dominant explanatory variable in trust models for the President, presidential appointees and Congress, but played a lesser role in the trust model for federal public administrators. Likewise, trust in people in general played a larger role in explaining trust in federal public administrators compared to trust in the other federal government officials.
Also of note, the fitted trust models for the President and presidential appointees were more robust, having more explanatory variables and attaining relatively high R2 values and analysis of variance F-statistics. On the other hand, the fitted trust model for federal public
164 administrators was relatively parsimonious, sustaining relatively low high R2 values and F- statistics.
Table 4.13 Fitted Regression Models: Trust in Federal Government Officials
Results for Research Hypothesis H4:A Individual Trust Models (Trust as the Dependent Variable)
(1) (2) (3) (4)
Trust: Trust: Trust: Trust: Independent Variables Presidential Federal President Congress Appointees Employees
U.S. Government Direction 0.494 0.501 0.310 0.158 Trust in People (General) 0.081 0.112 0.163 0.284 Republican (1/0) 0.212 0.157 -- -- Political Ideology 0.122 0.083 -- -- Household Financial Status 0.106 0.102 0.085 -- Racial Minority (1/0) -0.068 -- -0.077 -- Voting Activity -0.059 ------Urban Resident (1/0) -0.057 ------Female (1/0) -- -- 0.092 -- 9 9 9 9
Model Adjusted R2 0.558 0.459 0.160 0.108 Summaries ANOVA (F) 131.54 141.68 40.02 34.8
(1,2,3,4)Four separate fitted trust models with trust in the given government official serving as the dependent variable. Standardized coefficients are listed for the independent variables that were statistically significant within a given model. More specific model statistics are outlined in Appendix C.
165 H4B: Explanatory Variables, State Level
Research hypothesis H4:B – public trust in federal public administrators is explained differently than trust in the state governor, gubernatorial appointees and the state legislature
– is also examined with three specific sub-hypotheses: H4:B1, H4:B2 and H4:B3. Each sub- hypothesis compares the fitted regression model for trust in state public administrators with the other three groups of state government officials. In this analysis, trust in a given state government official serves as the dependent variable, while support for state government and a host of demographic variables are examined as independent variables. When fitting the individual regression models, trust in the three other government officials were not examined as independent variables.
Results of H4:B Sub-Hypotheses. Sub-hypothesis H4:B1 – the explanatory model for public trust in state public administrators is different from the trust model for the state governor – was supported by the data. As was the case at the federal level, the fitted regression model for trust in state public administrators included two explanatory variables: trust in people in general and support for state government (see Column 4, Table 4.14). Both variables had a direct relationship with the dependent variable. Trust in people in general had the largest impact on explaining trust in state public administrators, with a standardized coefficient of 0.385, which was significant within a 95% confidence interval. The standardized coefficient for support in state government amounted to 0.216, which was also statistically significant. The adjusted R2 for this model amounted to 0.201 and the model generated an analysis of variance F-statistic of 131.3.
166 As was the case at the federal level, the fitted model for trust in the state executive, i.e., governor, was more robust than the trust model for state public administrators. Four independent variables were statistically significant within the fitted model. These included, in order of importance, support for state government, political ideology, household financial status, and trust in people in general (see Column 1, Table 4.14). Both support for state government and trust in people in general had a positive relationship with trust in state public administrators. Persons who indicated they had conservative political views were more likely trust to have higher levels of trust in the governor compared to persons with liberal or moderate political ideologies. Persons from households that were better off financially from the previous year were more likely to have higher levels of trust in the state executive compared to persons from households that were worse off financially from the previous year. This model attained a adjusted R2 of 0.356 and an F-statistic of 117.2.
With the null hypothesis being that there is no difference in the explanatory variables for the fitted regression models for trust in state public administrators and the governor, the null hypothesis is rejected. As such, the evidence supports research sub-hypothesis
H4:B1.There are differing explanations for trust in state public administrators and trust in the state governor.
Sub-hypothesis H4:B2 – the explanatory model for public trust in state public administrators is different from the trust model for state gubernatorial appointees – was also supported by the data. Five independent variables were statistically significant within the fitted regression trust model for gubernatorial appointees. These included, in order of importance, support for state government, trust in people in general, household financial
167 status, gender, and political ideology (see Column 2, Table 4.14). Four of these variables were inclusive of the trust model for the state governor. Both support for state government and trust in people in general had a positive relationship with trust in gubernatorial appointees. Persons who indicated they had conservative political views were more likely to have higher levels of trust in gubernatorial appointees compared to persons with liberal or moderate political ideologies. Persons from households that were better off financially from the previous year were more likely to have higher levels of trust in gubernatorial appointees compared to persons from households that were worse off financially from the previous year. In addition, females were more likely to have higher levels of trust in gubernatorial appointees compared to males. This model attained an adjusted R2 of 0.332 and an analysis of variance F-statistic of 84.4.
With the null hypothesis being that there is no difference in the explanatory variables in the fitted regression models for trust in state public administrators and gubernatorial appointees, the null hypothesis is rejected. As such, the evidence supports research sub-
hypothesis H4:B2.There are differing explanations for trust in state public administrators and trust in gubernatorial appointees.
Sub-hypothesis H4:B3 – the explanatory model for public trust in state public administrators is different from the trust model for state legislators – was also supported by the data. Four explanatory variables were statistically significant within the fitted regression trust model for state legislators. These included, in order of importance, support for state government, trust in people in general, racial minority inclusion, and household financial status (see Column 3, Table 4.14). Three of these variables were inclusive of the trust
168 models for the governor and gubernatorial appointees. Both support for state government and trust in people in general had a positive relationship with trust in state legislators.
Persons from households that were better off financially from the previous year were more likely to have higher levels of trust in the state legislature compared to persons from households that were worse off financially from the previous year. In addition, persons that were racial minorities were more likely to have lower levels of trust in state legislators compared to Caucasians. This model attained a adjusted R2 of 0.229 and an analysis of variance F-statistic of 60.7.
With the null hypothesis being that there is no difference in the explanatory variables in the fitted regression models for trust in state public administrators and the state legislators, the null hypothesis is rejected. As such, the evidence supports research sub-
hypothesis H4:B3.There are differing explanations for trust in state public administrators and trust in the state legislature.
H4:B Results Summary. In sum, research hypothesis H4:B – public trust in federal public administrators is explained differently than trust in the state governor, gubernatorial appointees and the state legislators – is supported. As was the case at the federal level, two independent variables, support for state government and trust in people in general, were inclusive to all four fitted regression models for trust in state government officials.
However, the impact of these variable in explaining trust in a given government official varied. For instance, support for state government was the dominant explanatory variable in trust models for the governor, gubernatorial appointees and state legislators, but played a lesser of a role in the trust model for state public administrators. Likewise, trust in people
169 in general played a larger role in explaining trust in state public administrators compared to trust in the other state government officials.
As was the case at the federal level, the fitted trust models for the executive and executive appointees were more robust, having more explanatory variables and attaining relatively high R2 values and analysis of variance F-statistics, compared to the trust model for state public administrators.
The fitted trust models for the four groups of state government officials mirrored to some degree the associated trust models for the four groups of federal government officials.
For instance, all four of the explanatory variables in the fitted trust model for the governor were also explanatory variables in the fitted trust model for the President. Likewise, four of the five explanatory variables in the fitted trust model for gubernatorial appointees were also explanatory variables in the fitted trust model for presidential appointees. Also, all four of the explanatory variables in the fitted trust model for state legislators were also explanatory variables in the fitted trust model for the U.S. Congress.
The fitted trust model for state public administrators was exactly the same for the fitted trust model for federal public administrators. Both trust in people in general and support for state government were the sole explanatory variables, with the former having the most impact as a predictor of trust in public administrators, as evidenced by the standardized coefficients. The two variables, however, did a better job of explaining trust in state public administrators, than as evidenced by a larger adjusted R2 and F-statistic at the state level compared to federal public administrators.
170 Table 4.14 Fitted Regression Models: Trust in State Government Officials
Results for Research Hypothesis H4:B Individual Trust Models (Trust as the Dependent Variable)
(1) (2) (3) (4)
Trust: Trust: Trust: Trust: Independent Variables State Gubernatorial State State Governor Appointees Legislature Employees
State Government Direction 0.542 0.493 0.363 0.216 Trust in People (General) 0.084 0.146 0.259 0.385 Political Ideology 0.102 0.067 -- -- Household Financial Status 0.085 0.136 0.074 -- Female (1/0) -- 0.081 -- -- Racial Minority (1/0) -- -- -0.098 -- 9 9 9 9
Model Adjusted R2 0.356 0.332 0.229 0.201 Summaries ANOVA (F) 117.20 84.35 60.69 131.29
(1,2,3,4)Four separate fitted trust models with trust in the given government official serving as the dependent variable. Standardized coefficients are listed for the independent variables that were statistically significant within a given model. More specific model statistics are outlined in Appendix C.
171 H4C: Explanatory Variables, County Level
Research hypothesis H4:C – public trust in county public administrators is explained differently than trust in the elected county executives, county executive appointees and other
elected officials – is also examined with three specific sub-hypotheses: H4:B1, H4:B2 and H4:B3.
Each sub-hypothesis compares the fitted regression model for trust in county public administrators with the other three groups of county government officials. In this analysis, trust in a given government official serves as the dependent variable, while support for state government and a host of demographic variables are examined as independent variables.
When fitting the individual regression models, trust in the three other government officials were not examined as independent variables.
Results of H4:C Sub-Hypotheses. Sub-hypothesis H4:C1 – the explanatory model for public trust in county public administrators is different from the trust model for the elected county executives – was supported by the data. As was the case at the federal and state levels, the fitted regression model for trust in county public administrators included the same two explanatory variables: trust in people in general and support for county government (see
Column 1, Table 4.15). Both variables had a direct relationship with the dependent variable.
Trust in people in general had the largest impact on explaining trust in state public administrators, with a standardized coefficient of 0.378, which was significant within a 95% confidence interval. The standardized coefficient for support in state government amounted to 0.318, which was also statistically significant. The adjusted R2 for this model amounted to 0.280 and the model generated an analysis of variance F-statistic of 200.6.
172 For the trust model for elected county executives, five independent variables were statistically significant within the fitted model. These included, in order of importance, support for county government, trust in people in general, republican party affiliation, gender, and household financial status (see Column 1, Table 4.15). Both support for state government and trust in people in general had a positive relationship with trust in state public administrators. Persons who indicated they considered themselves republican were more likely trust to have higher levels of trust in the county executives compared to persons considering themselves democrats or independents. Females and persons from households that were better off financially from the previous year were more likely to have higher levels of trust in the county executives compared to persons from households that were worse off financially from the previous year. This model attained a adjusted R2 of 0.288 and an F- statistic of 80.9.
With the null hypothesis being that there is no difference in the explanatory variables for the fitted regression models for trust in county public administrators and the elected county executives, the null hypothesis is rejected. As such, the evidence supports research
sub-hypothesis H4:C1. There are differing explanations for trust in county public administrators and trust in the county executives.
Sub-hypothesis H4:C2 – the explanatory model for public trust in county public administrators is different from the trust model for county executive appointees – was also supported by the data. Four independent variables were statistically significant within the fitted regression trust model for county executive appointees. These included, in order of importance, support for state government, trust in people in general, racial minority
173 inclusion, and gender (see Column 2, Table 4.15). Three of these variables were inclusive of the trust model for the elected county executives. Both support for state government and trust in people in general had a positive relationship with trust in gubernatorial appointees.
Racial minorities were more likely to have lower levels of trust in county executive appointees compared to Caucasians. In addition, females were more likely to have higher levels of trust in county appointees compared to males. This model attained a adjusted R2 of 0.323 and an analysis of variance F-statistic of 96.8.
With the null hypothesis being that there is no difference in the explanatory variables in the fitted regression models for trust in county public administrators and county executive appointees, the null hypothesis is rejected. As such, the evidence supports research sub-
hypothesis H4:C2.There are differing explanations for trust in county public administrators and trust in county executive appointees.
Sub-hypothesis H4:C3 – the explanatory model for public trust in county public administrators is different from the trust model for other elected county officials – was also supported by the data. Four explanatory variables were statistically significant within the fitted regression trust model for other elected county officials. These included, in order of importance, support for county government, trust in people in general, racial minority inclusion, and household financial status (see Column 3, Table 4.15). Both support for county government and trust in people in general had a positive relationship with trust in the state legislature. Persons from households that were better off financially from the previous year were more likely to have higher levels of trust in other elected county officials compared to persons from households that were worse off financially from the previous
174 year. In addition, persons that were racial minorities were more likely to have lower levels of trust in other elected officials compared to Caucasians. This model attained a adjusted R2 of 0.329 and an analysis of variance F-statistic of 125.1.
With the null hypothesis being that there is no difference in the explanatory variables in the fitted regression models for trust in county public administrators and other elected county officials, the null hypothesis is rejected. As such, the evidence supports research sub-
hypothesis H4:C3.There are differing explanations for trust in county public administrators and trust in other elected officials such as the county treasurer and auditor.
H4:C Results Summary. In sum, research hypothesis H4:C – public trust in county public administrators is explained differently than trust in the elected county executives, executive appointees and other elected county officials – is supported by the evidence. As was the case at the federal and state levels, two independent variables, support for county government and trust in people in general, were inclusive to all four fitted regression models for trust in county government officials. However, the impact of these variables in explaining trust in a given government officials varied. For instance, support for county government was the dominant explanatory variable in trust models for the elected county executives, executive appointees and other elected county officials, but played a lesser role in the trust model for county public administrators. Likewise, trust in people in general played a larger role in explaining trust in county public administrators compared to trust in the other county government officials. These assertions hold at the federal and state level as well.
175 As was the case at the federal and state levels, the fitted trust models for the county executives and executive appointees tended to include more explanatory variables compared to the fitted compared to the trust model for county public administrators.
The fitted trust models for the four groups of county government officials administrators mirrored to some degree the trust models for the associated groups of federal and state government officials. For instance, four of the five explanatory variables in the fitted trust model for the county executives were also inclusive of the fitted trust model for the President, and three were inclusive of the fitted trust model for the state governor.
Similarly, three of the four explanatory variables in the fitted trust model for county executive appointees were inclusive in the fitted trust model for gubernatorial appointees, while two were inclusive of the fitted trust model for presidential appointees. Whereas political ideology was an important explanatory variable at the federal and state levels, it was not a significant variable at the county level.
The fitted trust model for county public administrators was exactly the same as for the fitted trust model for both state and federal public administrators. Both trust in people in general and support for state government were the sole explanatory variables, with the former having the most impact as a predictor of trust in public administrators, as evidenced by the standardized coefficients. The two variables, however, did a better job of explaining trust in public administrators, as evidenced by a larger adjusted R2 and F-statistic, at the county level compared to state and federal public administrators.
176 Table 4.15 Fitted Regression Models: Trust in County Government Officials
Results for Research Hypothesis H4:C Individual Trust Models (Trust as the Dependent Variable)
(1) (2) (3) (4)
Trust: Trust: Trust: Trust: Independent Variables Elected Executive Other Elected County Executives Appointees Officials Employees
County Government Direction 0.405 0.420 0.399 0.318 Trust in People (General) 0.238 0.261 0.294 0.378 Republican (1/0) 0.094 ------Female (1/0) 0.082 0.093 -- -- Household Financial Status 0.060 -- 0.084 -- Racial Minority (1/0) -- -0.109 -0.138 -- 9 9 9 9
Model Adjusted R2 0.288 0.323 0.329 0.280 Summaries ANOVA (F) 80.96 96.88 125.15 200.65
(1,2,3,4)Four separate fitted trust models with trust in the given government official serving as the dependent variable. Standardized coefficients are listed for the independent variables that were statistically significant within a given model. More specific model statistics are outlined in Appendix C.
177 CHAPTER V
CONCLUSIONS AND FUTURE DIRECTIONS
This chapter summarizes the results of research hypotheses H1, H2, H3 and H4 and associated sub-hypotheses. Where appropriate, conclusions are derived. In addition, implications and recommendations for the practice of public administration are discussed.
Suggestions for future areas of study are also outlined.
Summary and Analysis of Results
The results of the dissertation research indicate that the general public tends to trust public administrators more than other government officials, especially at the state and federal levels. County public administrators, as well as other county officials, tend to be trusted more than similar state or federal officials. General public support for government, regardless of the level of government, was found to be directly related to citizen trust in some government officials, namely elected executives and executive appointees. Fitted regression models of trust in the twelve individual groups of government officials indicated
178 different sets of explanatory variables. However, the fitted model for public administrators was consistent across all three levels of government examined.
Summary: Research Hypothesis H1 (Intra-Level Trust in Officials)
Research hypothesis H1 was that the general public has a higher level of trust for public administrators compared to elected and politically appointed agency officials, regardless of the level of government. This hypothesis was assessed at the federal, state and county level, using four groups of officials at each level of government. Of the nine sub- hypotheses examined, seven were supported (see Table 5.1).
At the federal level, the data indicated that public administrators were trusted more by the general public than the President. The mean trust score for the sample population amounted to 5.88 for federal public administrators, compared to 5.72 for the President.
Although the mean difference between the two averages was not great, it was just large enough to be statistically significant. Federal public administrators were also trusted more than presidential appointees, i.e., those persons appointed by the President to run federal agencies. With the mean trust score for presidential appointees being 5.44, the mean difference between the two averages was statistically significant. Federal public administrators were also trusted more than members of Congress. The mean trust score for
Congress was 5.40 and the mean difference between the two averages was statistically significant.
Similar results were found at the state level. The data indicated that public administrators were trusted more than the state governor. The mean trust score for the
179 sample population amounted to 6.15 for state public administrators, compared to 5.52 for the governor. The mean difference between the two averages was large enough to be statistically significant. State public administrators were also trusted more than gubernatorial appointees, i.e., those persons appointed by the governor to run state agencies. With the mean trust score for gubernatorial appointees amounting to 5.40, the mean difference between the two averages was statistically significant. State public administrators were also trusted more than members of the state General Assembly. The mean trust score for the state legislature amounted to 5.97 and the mean difference between the two averages was statistically significant.
At the county level, the data indicate that public administrators were trusted at the same level of the elected county executives. Whereas the mean trust score for county public administrators amounted to 6.28, the mean score for the elected county executives amounted to 6.32. There was no statistical significance in terms of difference between the two averages. However, public administrators were trusted more that county executive appointees, i.e., those persons appointed by the elected county executives to run various county agencies. With the mean trust score for county executive appointees amounting to
6.10, the mean difference between the two averages was statistically significant. With respect to other elected county officials, such as the treasurer and auditor, public administrators were actually trusted less.
In sum, the general public tends to distinguish between public administrators and other government officials in terms of fiduciary trust. This study yielded evidence to support the assertion that the general public has a higher level of trust in public administrators compared
180 to elected or politically appointed agency officials. With respect to the national government, federal public administrators were found to be trusted more by the public than the President, presidential appointees and Congress. Similarly, state public administrators were trusted more than the governor, gubernatorial appointees and the state legislature. At the county level, however, the results were somewhat different. Elected county executives and county government public administrators were trusted at about the same level of public administrators, while other elected county officials were trusted more than public administrators.
Although public administrators tended to enjoy higher levels of public trust compared to most other government officials, public administrators were trusted significantly less compared to public trust in people in general. Whereas the mean trust scores for county, state and federal public administrators amounted to 6.28, 6.15 and 5.88, respectively, the mean trust score for public trust in people in general amounted to 6.70. The mean differences were all statistically significant with respondents having a higher level of trust in people in general compared to public administrators. Likewise, most all of the groups of other government officials examined were trusted less than people in general.
181 Table 5.1
Summary Results: Research Hypothesis H1 The general public has a higher level of trust for public administrators compared to elected and politically appointed agency officials, regardless of the level of government.
Trust: Federal Trust: President Hypothesis supported Employees (>) (5.72)* (5.88)* Trust: Presidential Appointees Hypothesis supported (>) (5.44)* Trust: Members of Congress Hypothesis supported (>) (5.40)*
Trust: State Trust: Governor Hypothesis supported Employees (>) (5.52)* (6.15)* Trust: Gubernatorial Appointees Hypothesis supported (>) (5.40)* Trust: State Legislators Hypothesis supported (>) (5.97)*
Trust: County Trust: County Executives Hypothesis not supported Employees (Ý) (6.32)* (6.28)* Trust: Executive Appointees Hypothesis supported (>) (6.10)* Trust: Other Elected Officials Hypothesis not supported (Ý) (6.59)*
(*)Average score for the sample population, on a scale from one to ten, with ten being the highest level of trust. (>)First mean is statistically greater than second mean. (Ý)First mean is not statistically greater than second mean.
182 Summary: Research Hypothesis H2 (Inter-Level Trust in Officials)
Research hypothesis H2 was that the general public has a higher level of trust for local government officials compared to similar state and federal officials, and a higher level of trust in state government officials compared to similar federal officials. This hypothesis was assessed for four groups of government officials, including public administrators. Of the ten sub-hypotheses examined, eight were supported (see Table 5.2).
With respect to public administrators, county administrators were trusted by the public more than state administrators. The mean trust score for county administrators amounted to
6.28 compared to 6.15 for state public administrators. Although the mean difference appears to be small, it was large enough to be statistically significant. County public administrators were also trusted more than federal public administrators. With the mean score for federal public administrators amounting to 5.88, the mean difference between the two averages was statistically significant. Lastly, state public administrators were trusted more than federal public administrators.
With respect to elected executives, county executives were trusted more by the public than the state governor. The mean trust score for county executives amounted to 6.32 compared to 5.53 for the state governor. The difference between the two means was statistically significant. County executives were also trusted more than the President. With the mean trust score for the President amounting to 5.74, the mean difference between the two averages was statistically significant. The hypothesis that the state governor would be trusted more by the general public than the President was not supported. The data indicated
183 that the reverse was true, that the President was trusted more by the public than the state governor. This may have been attributable to respondents identifying with the President more so than the governor.
With respect to persons appointed by the elected executive or executives to run government agencies, as expected county appointees were trusted by the general public more than gubernatorial appointees. The mean trust score for county executive appointees amounted to 6.10 compared to 5.41 for gubernatorial appointees. County executive appointees were also trusted more by the general public than presidential appointees. With the mean trust score for presidential appointees amounting to 5.44, the difference between the two averages was statistically significant. As was the case with the state and federal executive, the hypothesis that gubernatorial appointees were more trusted than presidential appointees was not supported. There was no difference in the trust level for gubernatorial appointees and presidential appointees.
In sum, the general public also tends to distinguish between local, state and federal officials, in terms of fiduciary trust. In general, local government officials were trusted more by the public than state and federal officials. As a case in point, county public administrators were trusted more than their state and federal counterparts, and state public administrators were trusted more than federal public administrators. Similarly, county elected executives were trusted more than the state governor and President, while county executive appointees were trusted more than gubernatorial and presidential appointees. Also, the state legislature was trusted more than the U.S. Congress.
184 Table 5.2
Summary Results: Research Hypothesis H2 The general public has a higher level of trust for local government officials compared to similar state and federal officials, and a higher level of trust in state government officials compared to similar federal officials.
Trust: State Employees Hypothesis supported Trust: County (>) (6.15)* Employees Trust: Federal Employees (6.28)* Hypothesis supported (>) (5.88)* Trust: State Trust: Federal (>) Hypothesis supported Employees Employees
Trust: County Trust: State Governor Hypothesis supported Executives (>) (5.53)* (6.32)* Trust: President Hypothesis supported (>) (5.74)* Trust: State Trust: (Ý) Hypothesis not supported Governor President
Trust: County Trust: Gubernatorial Appointees Hypothesis supported Executive (>) (5.41)* Appointees Trust: Presidential Appointees (6.10)* Hypothesis supported (>) (5.44)* Trust: Trust: Gubernatorial (Ý) Presidential Hypothesis not supported Appointees Appointees
Trust: State Trust: Legislators (>) Congress Hypothesis supported (5.98)* (5.40)* (*)Average score for the sample population, on a scale from one to ten, with ten being the highest level of trust. (>)First mean is statistically greater than second mean. (Ý)First mean is not statistically greater than second mean.
185 Summary: Research Hypothesis H3 (Government Direction and Trust)
Research hypothesis H3 was that there is a direct relationship between trust in various government officials and general public support for government, regardless of the level of government. This hypothesis was examined at the federal, state and county level, using the four groups of officials at each level of government. Seven of the twelve sub-hypotheses examined were supported (see Table 5.3).
At the federal level, initial bivariate correlations indicated there was a moderate correlation between public support for federal government and the four groups of federal officials, which included the President, presidential appointees, Congress, and federal public administrators. However, adjusting for the effects of other trust variables at the federal, only two trust variables were found to be related or correlated with government support. These two variables were trust in the President and trust in presidential appointees. The adjusted, fourth-order correlation Pearson coefficient between federal government support and trust in the President amounted to 0.332, while the adjusted Pearson coefficient between support for federal government and trust in presidential appointees amounted to 0.136. Thus, a positive or direct relationship between federal government support and trust in the President and presidential appointees was indicated, with trust in the President being the stronger association.
The same relationships held up at the state level as at the federal level. Again, initial bivariate correlations indicated there was a moderate correlation between public support for state government and the four groups of state officials, which included the governor,
186 gubernatorial appointees, state assembly, and state public administrators. However, adjusting for the effects of other trust variables at the state level, only two trust variables were found to be related or correlated with government support. These included trust in the governor and trust in gubernatorial appointees. The adjusted Pearson coefficient between state government support and trust in the governor amounted to 0.244, while the adjusted
Pearson coefficient between support for state government and trust in gubernatorial appointees amounted to 0.133. As at the federal level, a direct relationship between support for state government and trust in the governor and gubernatorial appointees was indicated, with trust in the governor being the stronger association.
At the county level, as at the state and federal level, initial bivariate correlations indicated a moderate degree of correlation between public support for county government and trust in the four groups of government officials: elected county executives, executive appointees, other elected officials, and county public administrators. Adjusting for the effects of the other trust variables at the county level, three of the trust variables continued to be correlated with support for county government. These included trust in the elected executives, executive appointees, and other elected officials. The adjusted Pearson coefficient between support for county government and trust in both executive appointees and other elected officials amounted to 0.117, while the adjusted coefficient between county government support and elected executives amounted to 0.103. Although these coefficients are somewhat weak, they were large enough to be statistically significant.
One commonality evident across all three levels of government was that, after controlling for the effects of the other trust variables at a given level of government, trust
187 in public administrators was found not to be correlated with support for a given level of government, regardless of the level of government. Thus, the absence of statistically significant correlations indicates a lack of a relationship between support for government and trust in public administrators.
In sum, general support for government, regardless of the level of government, was found to be directly related to public trust in some government officials, namely elected executives and their political appointees. That is, persons with higher levels of trust in these government officials were more likely to feel the associated level of government was headed in the right direction, while persons with lower levels of trust were more likely to feel the government was headed in the wrong direction.
188 Table 5.3
Summary Results: Research Hypothesis H3 There is a direct relationship between public trust in various government officials and general public support for government, regardless of the level of government.
U.S. 0.332r Trust: President Hypothesis supported Government Direction 0.136r Trust: Presidential Appointees Hypothesis supported Trust: Members of Congress Hypothesis not supported Trust: Federal Employees Hypothesis not supported
State 0.244r Trust: Governor Hypothesis supported Government Direction 0.133r Trust: Governor Appointees Hypothesis supported
Trust: State Legislators Hypothesis not supported
Trust: State Employees Hypothesis not supported
County 0.103r Trust: County Executives Hypothesis supported Government Direction 0.117r Trust: Executive Appointees Hypothesis supported 0.117r Trust: Other Elected Officials Hypothesis supported Trust: County Employees Hypothesis not supported
(r)Fourth-order partial correlation. Only statistically significant coefficients reported.
189 Summary: Research Hypothesis H4 (Explanations of Public Trust)
Research hypothesis H4 was that explanatory variables for public trust in public administrators are different from variables explaining trust in other officials at the same level of government. This hypothesis was examined at the federal, state and county level, using the four groups of officials at each level of government. All of the nine sub- hypotheses examined were supported (see Table 5.4).
At the federal level, the fitted regression model for trust in federal public administrators had two explanatory variables. The variable with the most explanatory power was trust in people in general, followed by support for federal government. These two variables were also present in the fitted models of trust in the President, presidential appointees and Congress, albeit support for the federal government was the dominant explanatory variable. In addition, other explanatory variables were found to influence trust in these other government officials, variables such as republican affiliation and household financial status. As such, trust for federal public administrators was explained differently from trust in the President, presidential appointees and Congress.
At the state level, as with the federal level, the fitted regression model for trust in state public administrators had two explanatory variables including trust in people in general and support for state government. Again, trust in people in general was the dominant explanatory variable. The trust in people in general and support for state government variables were also fixtures in the trust in governor, gubernatorial appointees and state legislature fitted models, however, other independent variables such as political ideology and financial status made it into the fitted models. As such, trust in state public administrators was explained
190 differently from explanatory models of trust in the state governor, gubernatorial appointees and the state legislature.
At the county level, as with the state and federal level, the fitted regression model for trust in county public administrators included only two variables. These were trust in people in general and support for county government, with the former being the dominant explanatory variable. These two variables were fixtures in the explanatory models for trust in the elected county executives, executive appointees and other elected officials, but other variables also made it into the fitted models, variables such as gender and race. As such, trust in county public administrators was explained differently from trust in the other three groups of county government officials.
Regardless of the level of government, trust in public administrators was a function of respondent trust in people in general and support for the associated level of government.
Persons who were more trusting of people in general were more trusting of public administrators, and persons who felt the associated level of government was headed in the right direction were more likely to be more trusting of public administrators. At all three levels trust in people in general was the dominant explanatory variable. Also of note, as the level of government increased from local to federal, the predictive vitality of these variables waned. No other explanatory variables, such as interest in government affairs and political party affiliation or political ideology, were found to be statistically significant in the fitted models where trust in public administrators served as the dependent variable. In addition, demographic variables such as gender, race and household income did not influence trust in public administrators.
191 Table 5.4
Summary Results: Research Hypothesis H4 Explanatory variables for public trust in public administrators are different from variables explaining trust in other officials at the same level of government. Explanatory Variables Model Fit Trust Models Government Trust in Other Adjusted (Dependent Variables) DirectionB PeopleB VariablesE R2 Trust: Federal Employees 0.163 0.284 No 0.108 Trust: President 0.494 0.081 Yes,6 0.558 Trust: Presidential Appointees 0.501 0.112 Yes,3 0.459 Trust: Congress 0.310 0.163 Yes,3 0.160
Trust: State Employees 0.216 0.385 No 0.201 Trust: Governor 0.542 0.084 Yes,2 0.356 Trust: Gubernatorial Appointees 0.493 0.146 Yes,3 0.332 Trust: State Legislators 0.363 0.259 Yes,2 0.229
Trust: County Employees 0.318 0.378 No 0.280 Trust: County Executives 0.405 0.238 Yes,3 0.288 Trust: Executive Appointees 0.420 0.261 Yes,2 0.323 Trust: Other Elected Officials 0.399 0.294 Yes,2 0.329
(B)Numbers reflect standardized Beta coefficients. All coefficients are statistically significant. (E)Other explanatory or independent variables included in the fitted model. Note, all nine sub-hypotheses were supported.
192 Study Conclusions
Overall, the results for the sample population yielded a variety of interesting findings.
It should be noted, however, that the results are contextual, being time and place specific.
The survey data was collected on the adult population of Stark County, Ohio in 2004.
Nevertheless, the study yielded insightful information regarding trust in government, especially with respect to the various officials that comprise government including public administrators. Some of the key findings for the study population were as follows:
• The general public distinguished between public administrators and other
government officials in terms of trust. Public administrators were trusted more by
the citizenry than other government officials, including elected executives, executive
appointees and legislators. This was the case at the state and federal level but not at
the county level.
• The general public trusted public administrators less than people in general.
Although public administrators were trusted more than other government officials, the
general public trusted public administrators less than people in general. This was the
case for most of the other government officials examined as well.
• The general public distinguished between county, state and federal officials in
terms of trust. The public trusted county public administrators more than similar
officials at the state and federal officials, and state public administrators were trusted
more than federal public administrators. In addition, other county officials such as
193 elected executives and agency appointees were trusted more than their similar
counterparts at the state and federal level.
• There was a weak relationship between public support for government and
public trust in public administrators. Bivariate correlations indicated trust in public
administrators was weakly correlated with public support for government, regardless
of the level of government, while trust in elected executives, executive appointees and
legislators was moderately correlated with support for government. Partial correlations
for trust in public administrators and public support for government, adjusting for the
other trust variables, were not found to be statistically significant.
• Public trust in public administrators was explained differently from trust in
other government officials. Of the available explanatory variables, public trust in
public administrators was influenced by just two independent variables, regardless of
the level of government, while the number of variables explaining trust in the other
officials studied ranged from four to eight variables.
• Public trust in public administrators was influenced foremost by trust in people
in general and to a lesser degree public support in government. This derived
explanatory model for public trust in public administrators was consistent across all
three levels of government. The model was strongest at the county level and weakest
at the federal level. Political characteristics, such as political ideology, political party
affiliation and interest in government affairs, and demographic characteristics such as
race and gender, did not influence respondent trust in public administrators.
194 Implications for Public Administration Practice
The results of this dissertation research confirm the findings of other trust in government studies, such as the National Election Studies, that there is a deficit of public trust in government. In this study, trust in public administrators amounted to a moderate 5.9 to 6.3 on a scale from one to ten, depending on the level of government. Although a positive finding for the public administration field was that public administrators were generally trusted more than elected executives and executive appointees, the public tends to trust public administrators less then people in general, regardless of the level of government. It is maintained, herein, that this deficit in trust has implications for the field of public administration.
As mentioned in Chapter II, Ruscio (1997) maintains trust lies at the nexus of public administration theory and practice. This is because the inherent problem of democracy in an administrative state is reconciling the political imperative of accountability with the administrative imperative of discretion. For Ruscio, trust lies at the heart of the tension between the two imperatives. When trust varies so does the tension between the political imperative and administration imperative. For instance, low trust in public administrators begets more mechanisms to ensure accountability, such as rules and regulations, which in turn constrain discretion or flexibility, which subsequently limits administrative performance (Behn 1995).
195 Ruscio (1996) also notes that the implications of lack of trust in public administrators go beyond the accountability-discretion problem. Lack of trust in one component of government can have effects on other activities of government. More fundamentally, trust is considered necessary for creating the conditions for good government and democratic processes (Seligman 1997; Brathwaite 1998) including being a prerequisite for a representative form of governance (Mayhew 1974).
In particular, it is believed lack of public trust in government discourages political participation on the part of the public such as voting and campaign involvement (Levi &
Stoker 2000). The logic here is that, if government or government officials cannot be trusted or there is a deficit of trust, then citizens feel alienated from government and subsequently chose not to participate in government. Likewise, Levi and Stoker maintain that the more trusting the public is of government, the more likely they will be to comply with government laws, regulations and policies. For instance, Tyler (1990, 1998) has found that citizens who trust government are more likely to accept the mandates of the courts. Levi (1988) and
Scholz (1998) have found that citizens who trust the government are more likely to comply with taxation.
Lack of trust in government may also discourage persons from entering public service, e.g., to become public administrators (Nye 1997). In other words, lack of trust in government or government officials may adversely impact the ability of government to retain or recruit new personnel to work in the public sector. The logic here is that, if the public has negative perceptions of government, then the public will be less likely to pursue a career in public service.
196 Lack of trust in government may also stymie efforts to enact and implement new policies. For instance, Hetherington (2005) asserts the trust deficit in government has played a primary role in the demise of progressive public policy. He maintains that if the public does not trust the delivery system of public programs, they will not want the associated government agencies to provide the associated policy solutions. As such, this aspect of trust, or lack of trust, limits the range of possibilities available to government to implement policies.
Although not significantly studied, another consequence of lack of trust in government is the provision of resources on the part of the public to fund government activities. For instance, it can be argued that citizens who trust in government are more inclined to accept taxation, while persons who are distrustful or that lack trust in government are more likely to reject taxation. As such, where citizens play a direct role in funding government agencies, such as where they have the ability to vote for or against tax levies, trust can play an important role.
In sum, lack of public trust in public administrators and other government officials may have profound implications for government. This study, as well as other trust in government studies, have indicated there is a trust deficit with respect to government in the
United States. Some such as Ruscio (1997) and Behn (1995) maintain this trust deficit is a problem that limits the effectiveness of government, especially with respect to the public administration sphere of government.
197 Recommendations for Public Administration Practice
That there is a trust deficit in government begets a policy response on the part of government officials. In this respect, public administrators can take the lead in such a response. A few scholars, most notably Thomas (1998) and Kim (2005), offer some advice in this respect.
For Thomas (1998) trust in government can be generated through Zucker’s (1986) three modes of trust production, including characteristic-based trust, process-based trust, and institutional-based trust. Characteristic-based trust is generally tied to individual personal characteristics, while process-based trust is produced through repeated exchanges, and institutional-based trust is generated through formal institutional processes.
Characteristic-based trust is produced through personal characteristics such as race, gender and family background. These characteristics serve as indicators of membership in a common cultural system (Zucker 1986). Because it is difficult to change personal characteristics, the most viable means for building characteristic-based trust is to socialize with persons possessing similar characteristics (Thomas 1998). For Thomas, agency managers can produce characteristic-based trust by having staffs the mirror client or constituent characteristics. However, Thomas cautions that characteristic-based trust by itself is not a viable means for producing public trust in government agencies and their employees.
Process-based trust is produced through repeated exchanges rather than ascribed personal characteristics and thus develops over time (Zucker 1986). For Thomas (1998), the
198 production of process-based trust can be enhanced via tenure longevity, i.e., working to keep people in the same positions over time so agency clients or constituencies can build trusting relationships with agency personnel. This is not to say that personnel should not be promoted to other positions, but rather efforts can be put in place to discourage job turnover or to not rotate personnel in and out of positions. Process-based trust can also be produced by encouraging a climate that makes the agency experience more pleasant or satisfying for clients.
Institutional-based trust is produced through institutions that have become accepted in society and have become increasingly important in modern, complex societies (Zucker
1986). For Zucker, there are two types of institutional-based trust. The first type is specific to persons or organizations as it rests on membership in a subculture within which there are carefully delineated specific expectations. For Thomas (1998), this type of institutional- based trust can be facilitated through the acquisition of academic or professional credentials for public administrators. The second type of institutional-based trust is produced through intermediary mechanisms such as laws, regulations and insurance. For Thomas (1998), this type of institutional-based trust can be promoted through additional rules and regulations that address ethical standards or expectations.
Thomas (1998) also asserts that, beyond the production of trust, trust must also be maintained to prevent loss of trust. Thomas notes that trust can be lost through excessive or ongoing agency reorganization. Thus, trust can be maintain through agency stability. He goes on to note that trust can also be lost through lying and the misuse of power, and thus public administrators should take care to prevent such abuses. Finally, Thomas indicates that
199 trust in public administrators can be lost through individual incompetence as well as complacency in the social processes through which professional trust is maintained. Thus, public trust in government can be maintained to some degree through professional self criticism and constant peer review.
Kim (2005) offers a conceptual mode of public trust in government agencies that can be used to as a tool for public administrators to promote trustworthiness. Within this model are five primary dimensions or factors affecting trustworthiness in government. These factors include credible commitment, benevolence, honesty, competency and fairness. For
Kim, public administrators should pursue these virtues as a means to facilitate public trust in government. As such, public administrators must discipline their self-interests and focus on common interests for the public good.
Kim asserts credible commitment is the most frequently cited dimension of government trustworthiness among scholars in public administration and politics science.
He notes that two concepts highlight the definition of credible commitment. These include the notion of encapsulated interest and consistency or consistent behavior. Here, encapsulated interest is the willingness of government actors to honor their agreements or to act according to certain standards. Consistency pertains to government actors being able to provide quality services or performance over time, which enables citizens to make reasonable predictions about the future activities of government.
With respect to benevolence, Kim states that citizens tend to trust government when they feel that the government shows genuine care and concern for its citizens. He notes citizens will trust public administrators when administrators use their positions to help
200 people, respect individual citizens, and make every effort to understand the needs of their constituency. Thus, public administrators should take care to make it evident that they are benevolent toward the public at large.
Kim also asserts that citizen cynicism of government is strongly connected to the perception of a lack of honesty on the part of public administrators, and honesty is a major variable affecting public trust in government. He notes if citizens feel public administrators are concealing their activities, or are taking advantage of their position for their own personal benefit, then public trust in government will be shaken. As such, public administrators should demonstrate honest behavior as well as adherence to ethical standards as a means to promote citizen trust in government.
Besides honesty, benevolence and commitment, fairness is another important dimension of public trust in government. Kim (2005) notes that fairness suggests public administrators should treat citizens equally by adhering to a set of principles that are consistent with citizen’s common beliefs about government. For instance, citizens expect the government to be fair in its procedures and in the allocation of its resources. Thus, public administrators should not show favoritism to certain persons or special interest groups, likewise, they should not discriminate against any individual or groups of individuals.
The last important dimension of public trust in government is competency. Kim (2005) notes that competency involves the knowledge and skills necessary for the effective agency operations with the aim of maintaining or increasing organizational productivity. Various scholars have found a direct link between competence and trust. For instance, Berman
201 (1997) has found that ineffective services provided by local government undermine public trust in government. In addition, La Porte and Metlay (1996) have found that the declining competence of agency members in conjunction to increasing demands related to complex problems also causes lack of trust in government. Thus, Kim asserts, better performance on the part of government agencies would improve public trust in government.
In sum, Thomas (1998) asserts that public administrators can proactively seek to build trust in government by addressing the production and maintenance of charactistic-based, process-based and institutional-based trust on one hand, and Kim (2005) specifically maintains that public administrators can build trust in government by focusing on five key dimensions of trust, including benevolence, fairness, honesty, competence and credible commitment to the public good.
Future Directions in Research
This dissertation research was meant to shed further light on the issue of trust in government. It has continued a trend toward more sophisticated empirical research that goes beyond the traditional trust in government question of the National Election Studies. For instance, this dissertation research attempted to gauge citizen trust in a variety of government officials, including public administrators across the three primary levels of
American government. Nevertheless, there continues to be a need for additional research regarding trust in government.
202 With respect to building upon this dissertation research, because the research findings were endemic to Stark County, Ohio, it would be hazardous to generalize these findings to the U. S. population as a whole. As such, this dissertation research should be viewed as a pilot study to be replicated at the national level. A national study would more adequately address the diversity of ethnic and political cultures across the country. Besides the survey questions outlined herein, addition research questions are warranted that further delve into the context of trust in government, namely the underlying attitudes of why people trust or do not trust government. In addition, the collection of longitudinal data would be very useful.
This dissertation research also generated a wealth of data that can continue to be examined. For instance, more sophisticated multivariate techniques can be applied to the trust variables. In addition, a through examination of alpha build-up from the multiple application of t-tests on the data would be warranted.
Furthermore, as Ruscio (1997) notes, trust is an immensely challenging concept. It has been understudied in most all disciplines including psychology, sociology and political science. With respect to the field of public administration, the notion of trust in public administrators first received some attention roughly a decade ago and only a handful of articles have sought to address the subject since then. Besides a national study replicating this dissertation research, further research on the subject is warranted and research is needed in at least three areas.
First, there is a need for more sophistication in how trust is conceptualized. As many academics, such as Barber (1983) and Bouckaert, et al. (2002) have lamented, trust is a
203 concept surrounded by conceptual vagueness. This is not only the case especially with respect to trust in government, but this is also the case with general notions of trust. Overall, there is a lack of systematic analysis of trust. Besides conceptualizations of trust, this is also a need to fully outline the causes and consequences of trust in government. Although there has been much work in the political science field in this respect, the literature is not fully developed in terms of identifying all the causes and consequences of trust and distrust in government. There is also a need for the further study of how trust fits into the larger dynamic of citizen perceptions of government in general.
Second, there is a need for further empirical research. As Bouckaet, et al. (2002) notes, trust is never absolute, it is always conditional and contextual. Furthermore, broad social changes may be affecting the meaning of trust over time (Barber 1983). The meaning of public trust several decades ago may have a much different meaning today, and the meaning of trust in government today may have a much different meaning in the future. Thus, this dissertation research, although a worthy endeavor, represents just a snapshot in time of a particular population. Follow-up studies are warranted to measure the results of the dissertation questions over time. In addition, it would be appropriate to perform larger-scale studies, i.e., statewide and national studies using the dissertation questions.
Third, there is a need for the further development of practical methods that public administrators and other government officials can use to build trust in government. To date, only a few articles have broached this subject. Although Thomas (1998) and Kim (2005) have made useful contributions, the literature is not fully developed.
204 BIBLIOGRAPHY
Alford, J. R. (2001). We’re all in this together: The decline of trust in government, 1958- 1996. In J. R. Hibbing, & E. Theiss-Morse (Eds.), What is it about government that Americans dislike? (pp. 28-46). Cambridge; New York: Cambridge University Press.
Almond, G. A., & Verba, S. (1963). The civic culture: Political attitudes and democracy in five nations. Priceton, NJ: Princeton University Press.
Anderson, C. J., & Lo Tempio, A. (2002). Winning, losing, and political trust in America. British Journal of Political Science, 32, 335-51.
Appleby, P. H. (1945). Big democracy. New York: Knopf.
Ayers, I., & Brathwaite, J. (1992). Responsive regulation. Oxford, U.K.: Oxford University Press.
Babbie, E. (1998). The practice of social research, eighth edition. Belmont, CA: Wadsworth.
Barber, B. (1983). The logic and limits of trust. New Brunswick, NJ: Rutgers University Press.
Baier, A. (1986). Trust and antitrust. Ethics, 96, 231-260.
Behn, R. D. (1995). The big questions of public management. Public Administration Review, 55, 313-324.
Berman, E. M. (1996). Does trust matter?: A survey of local government. Paper presented at the American Society of Public Administration, Atlanta, Georgia.
Berman, E. M. (1997). Dealing with cynical citizens. Public Administration Review, 57, 105-112.
Bianco, W. T. (1994). Trust: Representatives and constituents. Ann Arbor: University of Michigan Press.
205 Bigley, G. A., & Pearce, J. L. (1998). Straining for shared meaning in organization science: Problems of trust and distrust. Academy of Management Review, 23, 405-421.
Bishop, G. (2003). Trust in the ‘Government in Washington’: Fact and artifact. Paper presented at the annual meeting of the American Association for Public Opinion Research. Nashville, Tennessee.
Bouckaert, G., Van de Walle, S., Maddens, B., & Kampan, J.K. (2002). Identity versus performance: An overview of theories explaining trust in government. University of Leuven: Public Management Institute.
The Brookings Institution. (2002). Trust in government survey. Washington, DC: The Brookings Institution.
Blau, P. (1964). Exchange and power in social life. New York: Wiley.
Bok, D. (2001). The trouble with government. Cambridge, MA: Harvard University Press.
Brathwaite, V. (1998). Communal and exchange trust norms: Their value base and relevance to institutional trust. In V. Brathwaite & M. Levi (Eds), Trust and governance (pp. 46-74). New York: Russell Sage.
Brathwaite, J., & Makkai, T. (1994). Trust and compliance. Policing Society, 4, 1-12.
Brehm, J., & Rahn, W. (1997). Individual-level evidence for the causes and consequences of social capital. American Journal of Political Science, 41, 999-1023.
Butler, J. K., Jr. (1999). Trust expectations, information sharing, climate of trust, and negotiation effectiveness and efficiency. Group & Organization Management, 24, 217-238.
Carnevale, D. G. (1995). Trustworthy government: Leadership and management strategies for building trust and high performance. San Francisco: Jossey-Bass.
Carnevale, D. G., & Wechsler, B. (1992). Trust in the public sector: Individual and organization determinants. Administration & Society, 23, 471-494.
The Center on Policy Attitudes. (1999). Expecting more say: A study of American public attitudes on the role of the public in government decisions. Washington, DC: Center on Policy Attitudes.
The Council for Excellence in Government. (1995). From optimism for the future to hope for stability. Washington, DC: The Center for Excellence in Government.
206 The Council for Excellence in Government. (1997). American attitudes toward government. Washington, DC: The Center for Excellence in Government.
The Council for Excellence in Government. (1999). America unplugged: Citizens and their government. Washington, DC: The Center for Excellence in Government.
The Council for Excellence in Government. (2003). Government: In and out of the news. Washington, DC: The Center for Excellence in Government, Center for Media and Public Affairs.
The Council for Excellence in Government (2004). A matter of trust: Americans and their government, 1958 to 2004. Washington, DC: The Center for Excellence in Government.
Citrin, J. (1974). Comment: The political relevance of trust in government. The American Political Science Review, 68, 973-988.
Citrin, J., & Green, D. P. (1986). Presidential leadership and the resurgence of trust in government. British Journal of Political Science, 16, 431-453.
Citrin, J. & Luks, S. (1998). The problem of political trust. Report prepared for the Pew Charitable Trusts. Philadelphia, PA.
Cleary, M. R., & Stokes, S. (2006). Democracy and the culture of skepticism. New York: Russell Sage.
Coleman, J.S. (1990). Foundations of social theory. Cambridge, MA: Belknap Press.
Creed, W. E. D., & Miles, R.E. (1996). Trust in organizations: A conceptual framework linking organizational forms, managerial philosophies, and the opportunity costs of controls. In R. M. Kramer & T. R. Tyler (Eds.), Trust in organizations: Frontiers of theory and research (pp. 16-38). Thousand Oaks, CA: Sage.
Cummings, L. L., & Bromiley, P. (1996). The organizational trust inventory (OTI): Development and validation. In R. M. Kramer & T. R. Tyler (Eds.), Trust in organizations: Frontiers of theory and research (pp. 302-330). Thousand Oaks, CA: Sage.
Dasgupta, P. (1988). Trust as a commodity. In D. Gambetta (Ed.), Trust: Making and breaking cooperative relations (pp. 49-72). New York: Blackwell. de Tocqueville, A. ([1840]1968). Democracy in America. London: Collins.
207 Deutsch, M. (1962). Cooperation and trust: Some theoretical notes. In M. R. Jones (Ed.), Nebraska symposium on motivation (pp. 275-319). Lincoln: University of Nebraska Press.
Dunn, J. (1984). The concept of trust in the politics of John Locke. In R. Rorty, J. B. Schneewind, & Q. Skinner (Eds.) Philosophy and history (pp. 279-301). Oxford: Basil Blackwell.
Dunn, J. (1988). Trust and political agency. In D. Gambetta (Ed.), Trust: Making and breaking cooperative relations (pp. 73-93). Oxford: Basil Blackwell.
Ely, J. H. (1980). Democracy and distrust: A theory of judicial review. Cambridge, MA: Harvard University Press.
Finifter, A. W. (1970). Dimensions of political alienation. American Political Science Review, 64, 389-410.
Fischer, C. S. (1975). The city and political psychology. American Political Science Review, 69, 559-571.
Fukuyama, F. (1995) Trust: The social virtues and the creation of prosperity. New York: Free Press.
Gambetta, D. (1988). Can we trust trust? In D. Gambetta (Ed.), Trust: Making and breaking cooperative relations (pp. 213-237). New York: Blackwell.
Gamson, W. A. (1968). Power and discontent. Homewood, IL: Dorsey Press.
Gamson, W. A. (1975). Political trust and its ramifications. In G. A. Soule & J. W. Soule (Eds.), Social psychology and political behavior: Problems and prospects (pp. 40-55). Columbus, OH: Merrill.
General Social Survey. National Opinion Research Center, University of Michigan. Electronic resources from the www.icpsr.umich.edu/gss. Ann Arbor, MI: University of Michigan, National Opinion Research Center, 1972-2004.
Giffin, K. (1968). An experimental evaluation of the trust differential. Lawrence: University of Kansas, Communication Research Center.
Golembiewski, R. Y. (1979). Approaches to planned change: Macro-level interventions and change-agent strategies. New York: Marcel Dekker.
208 Golembiewski, R. T. & McConkie, M. L. (1975). The centrality of interpersonal trust in group processes. In C. L. Cooper (Ed.), Theories of group processes (pp. 131-185). New York: John Wiley.
Guinnane, T. W. (2005). Trust: A concept too many. Unpublished report. Economic Growth Center, Yale University.
Hardin, R. (1993). The street-level epistemology of trust. Politics and Society, 21, 505-529.
Hardin, R. (1998). Trust in government. In V. Brathwaite, & M. Levi (Eds.), Trust and governance (pp. 9-27). New York: Russell Sage Foundation.
Hardin, R. (2001). Conceptions and explanations of trust. In K. Cook (Ed.), Trust and society. New York: Russell Sage Foundation.
The Harris Poll. Electronic resources from the Harris Interactive World Wide Web site (www.harrisinteractive.com). Rochester: NY: Harris Interactive, 1971-2004.
Hetherington, M. J. (1998). The political relevance of political trust. The American Political Science Review, 92, 791-808.
Hetherington, M. J. (2005). Why trust matters: Declining political trust and the demise of American liberalism. Princeton, NJ: Princeton University Press.
Hetherington, M. J., & Nugent, J. D. (2001). Explaining public support for devolution: The role of political trust. In J. R. Hibbing & E. Theiss-Morse (Eds.), What is it about government that Americans dislike? (pp. 134-155). New York: Cambridge University Press.
Hirsch, F. (1978). Social limits to growth. Cambridge, MA: Harvard University Press.
Holzer, M., & Rabin, J. (1987). Public service: Problems, professionalism, and policy recommendations. Public Productivity Review, 11, 3-13.
Howell, S. E., & Fagan, D. (1988). Race and trust in government: Testing the political reality model. Public Opinion Quarterly, 52, 343-350.
Inglehart, R. (1997). Postmaterialist values and the erosion of institutional authority. In J. S. Nye, P. D. Zelikow, & D. C. King (Eds.), Why people don’t trust government (pp. 217- 236). Cambrige, MA: Harvard University Press.
Jennings, M. K. (1998). Political trust and the roots of devolution. In V. Brathwaite, & M. Levi (Eds.), Trust and governance (pp. 218-244). New York: Russell Sage Foundation.
209 Keele, L. (2005). The authorities really do matter: Party control and trust in government. Journal of Politics, 67, 873-886.
Jones, G. R., & George, J. M. (1998). The experience and evolution of trust: Implications for cooperation and teamwork. Academy of Management Review, 23, 531-546.
Kim, S. E. (2001). Public trust in government agencies: Basic conceptual considerations. In M. A. Rahim, R. T. Golembieski, & K. D. Mackenzie (Eds.), Current topics in management, Volume 6 (pp. 331-351). Greenwich, CT: JAI Press.
Kim, S. E. (2005). The role of trust in the modern administrative state: An integrative model. Administration & Society, 37, 611-635.
King, D. C. (1997). The polarization of American parties and the mistrust of government. In J. S. Nye, P. D. Zelikow, & D. C. King (Eds.), Why people don’t trust government (pp. 155-178). Cambridge, MA: Harvard University Press.
La Porte, T. R., & Metlay, D. S. (1996). Hazard and institutional trustworthiness: Facing a deficit of trust. Public Administration Review, 56, 341-347.
Lawrence, R. Z. (1997). Is it really the economy, stupid? In Nye, J. S., Zelikow, P. D., & King, D. C. (Eds.), Why people don’t trust government (pp. 111-132). Cambridge, MA: Harvard University Press.
Levi, M. (1988). Of rule and revenue. Berkeley, CA: University of California Press.
Levi, M. (1997). Consent, dissent and patriotism. New York: Cambridge University Press.
Levi, M. (1998). A state of trust. In V. Brathwaite, & M. Levi (Eds.), Trust and governance (pp. 77-101). New York: Russell Sage Foundation.
Levi, M., & Brathwaite, V. (1998). Introduction. In V. Brathwaite & M. Levi (Eds), Trust and governance (pp. 1-6). New York: Russell Sage.
Levi, M., & Stoker, L. (2000). Political trust and trustworthiness. Annual Review of Political Science, 3, 475-507.
Lewicki, R. J. & Bunker, B. B. (1995). Trust in relationships: A model of development and decline. In B.B. Bunker, J.Z. Rubin, & Associates (Eds.), Conflict, cooperation, and justice (pp. 133-174). San Francisco: Jossey-Bass.
Lewis, J. D., & Weigert, A. (1985). Trust as social reality. Social Forces, 63, 967-985.
210 Lipset, S. M., & Schneider, W. (1983). The decline of confidence in American institutions. Political Science Quarterly, 98, 379-402.
Luhmann, N. (1979). Trust and power. New York: John Wiley.
Luhmann, N. (1980). Trust: A mechanism for the reduction of social complexity. In N. Luhmann (Ed.), Trust and power (pp. 24-31). New York: Wiley.
Luhmann, N. (1988). Familiarity, confidence, trust: Problems and Alternatives. In D. Gambetta (Ed.), Trust: Making and breaking cooperative relations. New York: Basil Blackwell.
McKenzie, G. C., & Labiner, J. M. (2002). Opportunity lost: The rise and fall of trust and confidence in government after September 11. Washington, DC: Center for Public Service, The Brookings Institution.
Madison, J., Hamilton, A. & Jay, J. ([1788] 1987). The federalist papers (I. Kramnick, ed.). Penguin: New York.
Mansbridge, J. (1997). Social and cultural causes of dissatisfaction with U.S. government. In J. S. Nye, P. D. Zelikow, & D. C. King (Eds.), Why people don’t trust government (pp. 133-153). Cambridge, MA: Harvard University Press.
March, J.G. (1994). A primer on decision making: How decisions happen. New York: Free Press.
March, J. G. & Olsen, J. P. (1989). Rediscovering institutions: The organizational basis of politics. New York: Free Press.
Marlowe, J. (2004). Part of the solution, or cogs in the system? The origins and consequences of trust in public administrators. Public Integrity, 6, 93-113.
Matravers, M. (2006). Hume on trust. Retrieved on November 26, 2006 from www.open2.net/historyandthearts/philosophy_ethics/hume_on_trust_p2.html.
Mayer, R. C., Davis, J. J., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of Management Review, 20, 709-734.
Mayhew, D. R. (1974). Congress: The electoral connection. New Haven, CT: Yale University Press.
McAllister, D. J. (1995). Affect- and cognition-based trust as foundations for interpersonal cooperation in organizations. Academy of Management Journal, 38, 24-59.
211 Neustadt, R. E. (1997). The politics of mistrust. In J. S. Nye, P. D. Zelikow, & D. C. King (Eds.), Why people don’t trust government (pp. 179-201). Cambridge, MA: Harvard University Press.
Mishler, W. & Rose, R. (1997). Trust, distrust and skepticism: Popular evaluations of civil and political institutions in post-communist societies. The Journal of Politics, 59, 418-451.
Muller, E. N. (1977). Behavioral correlates of political support. The American Political Science Review, 71, 454-467.
The National Election Studies, Center for Political Studies, University of Michigan. Electronic resources from the NES World Wide Web site (www.umich.edu/~nes). Ann Arbor, MI: University of Michigan, Center for Political Studies, 1964-2004.
Norris, P. (1999). Conclusions: The growth of critical citizens and its consequences. In P. Norris (Ed.), Critical citizens: Global support for democratic governance (pp. 257-272). New York: Oxford University Press.
North, D. C. (1990). Institutions, institutional change, and economic performance. New York: Cambridge University Press.
Nye, J. S., Jr. (1997). Introduction: The decline of confidence in government. In J. S. Nye, Jr., P. D. Zelikow, & D. C. King (Eds.), Why people don’t trust government (pp. 1-18). Cambridge, MA: Harvard University Press.
Nyhan, R. C. (2000). Changing the paradigm: trust and its role in public sector organizations. American Review of Public Administration, 30, 87-109.
Onyz, J., & Bullen, P. (2000). Measuring social capital in five communities. Journal of Applied Behavioral Science, 36, 23-42.
Orren, G. (1997). Fall from grace: The public’s loss of faith in government. In J. S. Nye, P. D. Zelikow, & D. C. King (Eds.), Why people don’t trust government (pp. 77-107). Cambridge, MA: Harvard University Press.
Pettit, P. (1995). The cunning of trust. Philosophy and Public Affairs, 24, 202-225.
Pew Research Center. (1998). Deconstructing distrust: How Americans view government. Philadelphia: Pew Research Center for People and the Press.
Pharr, S. J. (1997). Public trust and democracy in Japan. In J.S. Nye, Jr., P.D. Zelikow & D.C. King (Eds.), Why people don’t trust government. Cambridge, MA: Harvard University Press.
212 Price, C. (2006). Trust in Plato’s Republic. Retrieved on November 26, 2006 from www.open2.net/trust/downloads/docs/therepublic.pdf.
Putnam, R. D. (1995). Bowling alone: America’s declining social capital. Journal of democracy, 6, 65-78.
Rea, M. R., & Parker, R. A. (2005). Designing and conducting survey research: A comprehensive guide. San Francisco: Jossey Bass.
Reef, M. J., & Knoke, D. (1999). Political alienation and efficacy. In J. P. Robinson, P. R. Shaver, & L. S. Wrightsman (Eds.), Measures of political attitudes (pp. 413-464). San Diego, CA: Academic Press.
Rotter, J.B. (1967). A new scale for interpersonal trust. Journal of Personality, 35, 651-665.
Rousseau, D. M., Siykin, S. B., Burt, R. S., & Camerer, C. (1998). Not so different after all: A cross-discipline view of trust. Academy of Management Journal, 23, 393-404.
Ruscio, K. P. (1996). Trust, democracy, and public management: A theoretical argument. Journal of Public Administration Research and Theory, 6, 461-477.
Ruscio, K. P. (1997). Trust in the administrative state. Public Administration Review, 57, 454-458.
Scholz, J. T. (1998). Trust, taxes and compliance. In V. Brathwaite, & M. Levi (Eds.), Trust and governance (pp. 135-166). New York: Russell Sage Foundation.
Seligman, A. B. (1997). The problem of trust. Princeton University Press.
Shaw, G. M., & Reinhart, S. L. (2001). Devolution and confidence in government. Public Opinion Quarterly, 65, 369-388.
Sitkin, S. B. & Roth, N. L. (1993). Explaining the limited effectiveness of legalistic remedies for trust/distrust. Organization Science, 4, 367-392.
Statistical Abstract of the United States (2006). Retrieved January 21, 2006 from www.census.gov/compendia/statab/2006/2006edition.html.
Stokes, D. E. (1962). Popular evaluations of government: An empirical assessment. In H. Cleveland, & H. D. Lasswell (Eds.), Ethics and bigness: Scientific, Academic, Religious, Political, and Military (pp. 61-72). New York: Harper.
213 Szekelyi, M., Orkeny, A., & Barna, I. (2004). The interpretation of trust in empirical research. Retrieved December 19, 2006 from www.colbud.hu/honesty-trust/orkeny/ pub01.pdf.
Thomas, C. (1998). Maintaining and restoring public trust in government agencies and their employees. Administration & Society, 30, 166-193.
Tyler, T. R. (1990). Why people obey the law. New Haven, CT: Yale University Press.
Tyler, T. R. (1998). Trust and democratic government. In V. Brathwaite, & M. Levi (Eds.), Trust and governance (pp. 269-294). New York: Russell Sage Foundation.
Tyler, T. R., & Degoey, P. (1996). Trust in organizational authorities: The influence of motive attributions on willingness to accept decisions. In R. M. Kramer, & T. R. Tyler (Eds.), Trust in organizations: Frontiers of theory and research (pp. 331-356). Thousand Oaks, CA: Russell Sage.
Ullmann-Margalit, E. (2004). Trust, distrust, and in between. In Hardin, R., ed. Distrust (pp. 60-82). Russell Sage.
Uslaner, E. M. (2002). The moral foundations of trust. Cambridge, UK: Cambridge University Press.
Waldo, D. (1984). The administrative state, 2nd Ed. New York: Holmes & Meier.
Warren, M. E. (1999). Introduction. In M. E. Warren (Ed.), Democracy and trust (pp. 1-21). New York: Cambridge University Press.
Weatherford, M. S. (1992). Measuring political legitimacy. American Political Science Review, 86, 149-166.
Weingast, B. R. (1998). Constructing trust: The political and economic roots of ethnic and regional violence. In V. Haufler, K. Soltan, & E. Uslaner (Eds.), Where is the new institutionalism now? (pp. 163-200). Ann Arbor: University of Michigan Press.
Williamson, O. E. (1993). Calculativeness, trust, and economic organization. Journal of Law & Economics, 36, 453-486.
Wolff, J. (2006). Trust and the state of nature. Retrieved November 26, 2006 from www.open2.net/trust/downloads/docs/stateofnature.pdf.
Zand, D. E. (1972). Trust and managerial problem solving. Administrative Science Quarterly, 17, 229-239.
214 Zand, D. E. (1997). The leadership triad: Knowledge, trust, and power. New York: Oxford University Press.
Zucker, L. G. (1986). Production of trust: Institutional sources of economic structure, 1840- 1920. Research in Organization Behavior, 8, 53-111.
215 APPENDICES
216 APPENDIX A
SURVEY INSTRUMENT
Table A.1 depicts the survey instrument used for this research endeavor. The dissertation research questions were part of the larger survey instrument, the 2004 Stark
County Omnibus Poll conducted by the Center for Policy Studies at The University of
Akron. Besides the dissertation researcher, four community organizations asked questions as part of the omnibus survey. These other clients included the United Way of Greater Stark
County (Item #2 of the poll), Children’s Hospital Medical Center of Akron (Items #3 through #25 of the poll), the Stark County Health Department (Items #26 through #35 of the poll), and Stark County Children Services (Items #36 and #37 of the poll). Due to confidentiality, the questions asked by these organizations are not included in the Table A.1, however the location of these clients’ questions in the overall survey instrument is noted.
Items #38 to #55 (Dissertation Questions #1 to #18) on the survey instrument are the core questions posed by the dissertation researcher on the 2004 Stark County Omnibus Poll.
Items #56 to #80 (Demographic Questions #1 to #25) are demographic questions normally asked as part of the omnibus poll. These questions were outside of the control of the dissertation researcher. Nevertheless, these demographic questions were used to supplement
217 the dissertation research questions. Examples of key demographics questions used in the analysis included respondent age, sex, race, educational attainment, political ideology, political party affiliation, voting registration status, household income, and household financial status.
The text in Table A.1 generally mirrors what the interviewer would see on their computer screens. Header rows before each survey question and some notations such as
“coding” and “response selections” have been added to clarify the content of the survey instrument. The script of the survey instrument, i.e., words spoken directly by the interviewers to respondents, are in quotations. Unspoken notes provided to the interviewer are in capital letters. The questions were read to respondents in the same order they are listed in the following table.
218 Table A.1 Survey Instrument Introduction Statement “Hello, this is The Center for Policy Studies at the University of Akron is conducting a brief scientific survey with a random sample of Stark County residents about their opinions and views of the local area. These questions should take about fifteen minutes and all your answers will remain confidential. The survey is voluntary and we would greatly appreciate your time and cooperation.”
[IF RESPONDENT VOLUNTEERS THAT THE HOUSEHOLD IS NOT WITHIN STARK COUNTY - CODE AS A 410, INELIGIBLE HOUSEHOLD.]
Survey Item 1 Screening Question “This question helps us decide the correct person to interview. Of the members in your household who are over 18, who was the last person to have a birthday?”
IF RESPONDENT DOESN'T KNOW ALL BIRTHDAYS ASK: “Of those you do know, Who had the last Birthday?”
Other- ATTEMPT TO GET RESPONDENT TO PHONE, ELSE MAKE AN APPOINTMENT
ASK OF RESPONDENT: “For verification purposes, what county do you live in?”
Coding Response Categories (1) Respondent (2) Does not live in Stark County
Survey Item 2 United Way of Greater Stark County Question
Survey Items 3-25 Children’s Hospital Medical Center of Akron Questions
Survey Items 26-35 Stark County Health Department Questions
Survey Items 36-37 Stark County Children Services Questions
219 Survey Item 38 Dissertation Question #1 “Next, I am going to read you a list of people and groups of people. I would like you to rate the level of TRUST in each to do what is RIGHT for the COUNTRY. Please rate your level of trust on a scale from one to ten, with ONE being the lowest level of trust and TEN being the highest level of trust.”
“... First, the President of the United States.”
Coding Response Selections (1) One - Lowest level of trust (2) Two (3) Three (4) Four (5) Five (6) Six (7) Seven (8) Eight (9) Nine (10) Ten - Highest level of trust (88) Refused (99) Don’t Know/Remember
Survey Item 39 Dissertation Question #2 “... Persons appointed by the President to run federal government agencies.”
Coding Response Selections (1) One - Lowest level of trust (2) Two (3) Three (4) Four (5) Five (6) Six (7) Seven (8) Eight (9) Nine (10) Ten - Highest level of trust (88) Refused (99) Don’t Know/Remember
220 Survey Item 40 Dissertation Question #3
“... Members of Congress.”
Coding Response Selections (1) One - Lowest level of trust (2) Two (3) Three (4) Four (5) Five (6) Six (7) Seven (8) Eight (9) Nine (10) Ten - Highest level of trust (88) Refused (99) Don’t Know/Remember
Survey Item 41 Dissertation Question #4
“... Federal government employees.”
Coding Response Selections (1) One - Lowest level of trust (2) Two (3) Three (4) Four (5) Five (6) Six (7) Seven (8) Eight (9) Nine (10) Ten - Highest level of trust (88) Refused (99) Don’t Know/Remember
221 Survey Item 42 Dissertation Question #5 “How about people in general? How would you rate your level of trust in the citizens of this country regardless of whether or not they work in government?”
Coding Response Selections (1) One - Lowest level of trust (2) Two (3) Three (4) Four (5) Five (6) Six (7) Seven (8) Eight (9) Nine (10) Ten - Highest level of trust (88) Refused (99) Don’t Know/Remember
Survey Item 43 Dissertation Question #6 “Now thinking in terms of Ohio, please rate your level of TRUST in the following people or groups of people to do what is RIGHT for the STATE. Again, on a scale from one to ten, with ONE being the LOWEST LEVEL OF TRUST and TEN being the HIGHEST LEVEL OF TRUST.”
“... First, the Governor of Ohio.” Coding Response Selections (1) One - Lowest level of trust (2) Two (3) Three (4) Four (5) Five (6) Six (7) Seven (8) Eight (9) Nine (10) Ten - Highest level of trust (88) Refused (99) Don’t Know/Remember
222 Survey Item 44 Dissertation Question #7
“... Persons appointed by the Governor to run state government agencies.”
Coding Response Selections (1) One - Lowest level of trust (2) Two (3) Three (4) Four (5) Five (6) Six (7) Seven (8) Eight (9) Nine (10) Ten - Highest level of trust (88) Refused (99) Don’t Know/Remember
Survey Item 45 Dissertation Question #8
“... Elected representatives serving in the Ohio General Assembly.”
Coding Response Selections (1) One - Lowest level of trust (2) Two (3) Three (4) Four (5) Five (6) Six (7) Seven (8) Eight (9) Nine (10) Ten - Highest level of trust (88) Refused (99) Don’t Know/Remember
223 Survey Item 46 Dissertation Question #9 “... State government employees.” Coding Response Selections (1) One - Lowest level of trust (2) Two (3) Three (4) Four (5) Five (6) Six (7) Seven (8) Eight (9) Nine (10) Ten - Highest level of trust (88) Refused (99) Don’t Know/Remember
Survey Item 47 Dissertation Question #10 “Now thinking in terms of Stark County, please rate your level of TRUST in the following people or groups of people to do what is RIGHT for the COUNTY. Again, on a scale from one to ten, with ONE being the LOWEST LEVEL OF TRUST and TEN being the HIGHEST LEVEL OF TRUST.”
[MAKE SURE THAT YOU SAY COUNTY AND NOT COUNTRY.]
“The County Commissioners elected to run Stark County.” Coding Response Selections (1) One - Lowest level of trust (2) Two (3) Three (4) Four (5) Five (6) Six (7) Seven (8) Eight (9) Nine (10) Ten - Highest level of trust (88) Refused (99) Don’t Know/Remember
224 Survey Item 48 Dissertation Question #11
“... Other elected Stark County officials, such as the Auditor and Treasurer.”
Coding Response Selections (1) One - Lowest level of trust (2) Two (3) Three (4) Four (5) Five (6) Six (7) Seven (8) Eight (9) Nine (10) Ten - Highest level of trust (88) Refused (99) Don’t Know/Remember
Survey Item 49 Dissertation Question #12
“... Persons appointed by the County Commissioners to run Stark County agencies.”
Coding Response Selections (1) One - Lowest level of trust (2) Two (3) Three (4) Four (5) Five (6) Six (7) Seven (8) Eight (9) Nine (10) Ten - Highest level of trust (88) Refused (99) Don’t Know/Remember
225 Survey Item 50 Dissertation Question #13
“... COUNTY government employees.”
Coding Response Selections (1) One - Lowest level of trust (2) Two (3) Three (4) Four (5) Five (6) Six (7) Seven (8) Eight (9) Nine (10) Ten - Highest level of trust (88) Refused (99) Don’t Know/Remember
Survey Item 51 Dissertation Question #14
“Now I am going to read you some statements about different levels of government. Please indicate if you strongly agree, agree, neither agree nor disagree, disagree, or strongly disagree with the following statements.”
“All in all, the FEDERAL government is headed in the right direction. Do you strongly agree, agree, neither agree nor disagree, disagree, or strongly disagree?”
Coding Response Selections (1) Strongly agree (2) Agree (3) Neither agree nor disagree (4) Disagree (5) Strongly agree (88) Refused (99) Don’t Know/Remember
226 Survey Item 52 Dissertation Question #15 “... All in all, the STATE government is headed in the right direction.”
Coding Response Selections (1) Strongly agree (2) Agree (3) Neither agree nor disagree (4) Disagree (5) Strongly agree (88) Refused (99) Don’t Know/Remember Survey Item 53 Dissertation Question #16 “... All in all, Stark County government is headed in the right direction.”
Coding Response Selections (1) Strongly agree (2) Agree (3) Neither agree nor disagree (4) Disagree (5) Strongly agree (88) Refused (99) Don’t Know/Remember
Survey Item 54 Dissertation Question #17 “Some people like to follow what4s going on in government and public affairs most of the time, whether there’s an election going on or not. Others aren’t that interested. Would you say that you follow what’s going on in government and public affairs most of the time, some of the time, only now and then, or hardly at all?”
Coding Response Selections (1) Most of the time (2) Some of the time (3) Only now and then (4) Hardly at all (88) Refused (99) Don’t Know/Remember
227 Survey Item 55 Dissertation Question #18 “How often would you say you vote? Always, nearly always, part of the time, or seldom?”
Coding Response Selections (1) Always (2) Nearly always (3) Part of the time (4) Seldom (5) Never [IF VOLUNTEERED BY RESPONDENT] (88) Refused (99) Don’t Know/Remember
Survey Item 56 Demographic Question #1: Respondent Age “Now just a few more questions and we will be done. In what year were you born?”
[IF NO ANSWER, PROBE]: “Well roughly, what year was that?”
Survey Item 57 Demographic Question #2: Primary Source of Information “Where do you get MOST of your information about current affairs and entertainment IN STARK COUNTY, newspapers, television, magazines, radio, friends and family members, mailings, the internet, or some other source?”
[PROBE FOR WHERE THEY GET MOST OF THEIR INFORMATION.]
Coding Response Selections (1) Newspapers (2) Television (3) News magazines (4) Radio (5) Friends and family (6) Mailings (7) Internet (9) Other (88) Refused (99) Don’t Know/Remember
228 Survey Item 58 Demographic Question #3: Primary Newspaper “Which newspaper do you read MOST often?”
[DO NOT READ LIST. VERIFY RESPONSE. ENTER NUMBER WHERE POSSIBLE, OTHERWISE ENTER VERBATIM RESPONSE.]
Coding Response Selections (0) Newspapers (1) Akron Beacon Journal (2) Canton Repository (3) Massillon Independent (4) Alliance Review (15) No Preference (88) Refused (99) Don’t Know/Remember
Survey Item 59 Demographic Question #4: Primary Televison Station “Which TV station do you watch MOST often?”
[DO NOT READ LIST. VERIFY RESPONSE. ENTER NUMBER WHERE POSSIBLE, OTHERWISE ENTER VERBATIM RESPONSE. IF YOU ARE UNSURE OF WHETHER THE CHANNEL IS BASIC OR PREMIUM, PLEASE ENTER VERBATIM.]
[IF RESPONDENT GIVES A STATION NUMBER ONLY, PROBE FOR THE NAME OF THE STATION OR NETWORK.]
Survey Item 60 Demographic Question #5: Primary Radio Station “What radio station do you listen to MOST often?”
[DO NOT READ LIST. VERIFY RESPONSE. ONLY ENTER ONE RESPONSE. PROBE FOR MOST OFTEN. ENTER NUMBER WHERE POSSIBLE, OTHERWISE ENTER VERBATIM RESPONSE.]
[IF RESPONDENT GIVES A STATION NUMBER NOT LISTED, PROBE FOR THE CALL LETTER OF THE STATION.]
229 Survey Item 61 Demographic Question #6: Living Arrangements “Do you rent or own your current residence?” Coding Response Selections (1) Rent (2) Own (3) Other arrangement [IF VOLUNTEERED BY RESPONDENT] (88) Refused (99) Don’t Know/Remember
Survey Item 62 Demographic Question #7: Household Type “Would you describe your current residence as ...
[READ LIST] (1) House (2) Town house (3) Apartment (4) Duplex or two family home (5) Assisted living facility (6) Condominium (66) Other [IF VOLUNTEERED BY RESPONDENT] (88) Refused (99) Don’t Know/Remember
Survey Item 63 Demographic Question #8: Respondent Education “What is the highest grade of school or year of college you completed?”
[DO NOT READ LIST. PROBE FOR THE CORRECT COLLEGE ANSWER.] Coding Response Selections (1) Grade school (2) Some high school (3) High school graduate (4) Some college (5) College graduate (6) Post graduate (88) Refused (99) Don’t Know/Remember
230 Survey Item 64 Demographic #9: Children’s School
“What type of school do the children in your household attend, public school, private school, home school OR SOMETHING ELSE?”
[ENTER ALL THAT APPLY.] Coding Response Selections (1) Public (2) Private (3) Home school (4) Other (5) None (88) Refused (99) Don’t Know/Remember
Survey Item 65 Demographic Question #10: Household Income
“Is the total yearly income for your family ...before taxes, under..or over $36,000.”
[IF RESPONDENT OFFERS THE EXACT TOTAL YEARLY INCOME, YOU MAY ENTER THE NUMBER OF THE RANGE THAT THE INCOME FALLS IN.]
[IF UNDER 36 ASK]: “Is it under or over $18,000?”
[IF OVER 36 ASK] : “Is it under or over $54,000?”
[IF OVER 54 ASK]: “Is it under or over $72,000?”
Coding Response Selections (1) Under $18,000 (2) $18,000 to $36,000 (3) $36,000 to $54,000 (4) $54,000 to $72,000 (5) Over $72,000 (88) Refused (99) Don’t Know/Remember
231 Survey Item 66 Demographic Question #11: Household Finances “Would you say that your household is better off financially, about the same, or worse off financially than a few years ago?”
Coding Response Selections (1) Better off (2) About the same (3) Worse off (88) Refused (99) Don’t Know/Remember
Survey Item 67 Demographic Question #12: Respondent Race “And, what is your race, how would you classify yourself? You may choose more than one category.”
[READ LIST. MARK ALL THAT APPLY.] Coding Response Selections (1) White (2) Black/African-American (3) American Indian or Alaska Native (4) Asian (5) Native Hawaiian or other Pacific Islander (6) Something that was not already mentioned (88) Refused (99) Don’t Know/Remember
Survey Item 68 Demographic Question #13: Respondent Origin “Are you of Hispanic origin?”
Coding Response Selections (1) Yes (2) No (88) Refused (99) Don’t Know/Remember
232 Survey Item 69 Demographic Question #14: Respondent Martial Status
“What is your PRESENT marital status, single- never married, divorced, separated, widowed, or married?”
[PROBE FOR THE PRESENT MARITAL STATUS]: “What would you like me to enter as your PRESENT marital status?”
Coding Response Selections (1) Single, never married (2) Divorced (3) Separated (4) Widowed (5) Married (88) Refused (99) Don’t Know/Remember
Survey Item 70 Demographic Question #15: Respondent Employment Status
“Are you currently employed full-time 35 hours or more per week, employed part-time, retired, homemaker not employed outside the home, student not working, or unemployed?”
[PROBE FOR THE PRIMARY EMPLOYMENT STATUS]: “What would you like me to enter as your PRIMARY employment status?’
Coding Response Selections (1) Employed full-time, 35 hours or more per week (2) Employed part-time (3) Retired (4) Homemaker, not employed outside the home (5) Student, not working (6) Unemployed (66) Other (88) Refused (99) Don’t Know/Remember
233 Survey Item 71 Demographic Question #16: Respondent Work Zip Code “What is the zip code for your place of work?”
[BE SURE TO ENTER 5 NUMBERS.] [PROCEED FOR DON'T KNOW/REMEMBER.]
Survey Item 72 Demographic Question #17: Respondent Religion “What is your religious preference, are you Protestant, Catholic, Jewish, Muslim, or something else?”
Coding Response Selections (1) Protestant (2) Catholic (3) Jewish (4) Muslim (5) Other (66) No religious preference [IF VOLUNTEERED BY RESPONDENT] (88) Refused (99) Don’t Know/Remember
Survey Item 73 Demographic #18: City of Residence “What city or township in Stark County do you live in?”
[PLEASE PROBE IF THERE IS A CITY AND TOWNSHIP WITH THE SAME NAME, i.e. GREEN.]
Coding Response Selections (1) Alliance (2) Beach City (3) Bethlehem Township (4) Brewster (5) Canal Fulton (6) Canton (7) Canton Township (8) East Canton (9) East Sparta
234 Survey Item 73 Research Question #18: City of Residence (continued)
(45) Franklin Township (10) Green (11) Greentown (12) Hartville (44) Hill and Dales (13) Homeworth Township (14) Jackson Township (15) Lake Township (16) Lawrence Township (17) Lexington Township (18) Limaville (19) Louisville (20) Magnolia (21) Malvern (22) Marlboro Township (23) Massillon (24) Meyers Lake Village (25) Minerva (26) Navarre (27) Nimishellen Township (28) North Canton (29) Osnaburg Township (30) Paris Township (31) Perry Township (32) Pike Township (33) Plain Township (34) Sandy Valley Township (35) Sugarcreek Township (36) Tuscarawas Township (37) Uniontown (38) Village of Hills and Dales (39) Washington Township (40) Waynesburg (41) Wilmot (42) Other- Not on list (43) Outside Stark County (88) Refused (99) Don’t Know/Remember
235 Survey Item 74 Demographic Question #19: Length of Residence
“How long have you lived in Stark County?”
[READ LIST. THIS IS A FACTUAL QUESTION, YOU CAN ENTER ANSWER IF RESPONDENT GIVES IT BEFORE LIST IS READ.]
Coding Response Selections (1) Under a Year (2) 1 to 5 years (3) 6-10 years (4) 11-15 years (5) 16-20 years (6) Over 20 years (88) Refused (99) Don’t Know/Remember
Survey Item 75 Demographic Question #20: Respondent Political Ideology
“When you think about political issues, would you say you think of yourself as a liberal, a moderate, a conservative, or something else?”
Coding Response Selections (1) Liberal (2) Moderate (3) Conservative (4) Something else (88) Refused (99) Don’t Know/Remember
236 Survey Item 76 Demographic Question #21: Respondent Political Party
“In politics, do you usually think of yourself as a Republican, a Democrat, an independent, or something else?”
Coding Response Selections (1) Republican (2) Democrat (3) Independent (4) Something else (88) Refused (99) Don’t Know/Remember
Survey Item 77 Demographic Question #22: Respondent Registration Status
“Right now, are you registered to vote in Ohio, if you want to?”
Coding Response Selections (1) Registered (2) Not Registered (88) Refused (99) Don’t Know/Remember
Survey Item 78 Demographic Question #23: Household Size
“How many people live in your current residence?”
Survey Item 79 Demographic Question #24: Household Zip Code
“What is your Zip code? “
[PLEASE BE SURE TO ENTER 5 NUMBERS.]
[PROCEED FOR DON'T KNOW/REMEMBER.]
237 Survey Item 80 Demographic Question #25: Respondent Sex [RECORD RESPONDENT GENDER]
Coding Response Selections (1) Male (2) Female
Conclusion Statement “Thank you very much for your time and cooperation. That concludes our interview. For quality control purposes, someone from the Center for Policy Studies may call your household to verify the completion of this survey.”
[IF RESPONDENT VOICES CONCERN ABOUT CONFIDENTIALITY] “Yes, this survey is confidential. After the interview is complete, your phone number is completely separated from your answers. All we will know is that someone in your household completed this survey. No individual responses can ever be identified.”
238 APPENDIX B
BASIC RESPONSE FREQUENCIES
The following tables depict the basic response frequencies for the dissertation questions from the survey instrument (Table B.1 through Table B.18) and the demographics questions (Table B.19 through Table B. 43). Where appropriate, summary statistics such as mean and standard deviation are provided.
239 Table B.1 Respondent Trust in the President Valid Responses Frequency Percent Percent Valid Rating of One 193 17.9% 18.1% Rating of Two 50 4.6% 4.7% Rating of Three 60 5.6% 5.6% Rating of Four 54 5.0% 5.1% Rating of Five 156 14.5% 14.6% Rating of Six 58 5.4% 5.4% Rating of Seven 91 8.4% 8.5% Rating of Eight 166 15.4% 15.6% Rating of Nine 55 5.1% 5.2% Rating of Ten 184 17.1% 17.2% Total Valid Responses 1,067 99.0% Missing Refused (3)/Don’t Know (8) 11 1.0% Total Responses 1,078
Summary Statistics Mean 5.733 Standard Error of Mean 0.097 Standard Deviation 3.162 Dissertation Question #1: “I am going to read you a list of people and groups of people. I would like you to rate the level of trust in each to do what is right for our country. Please rate your level of trust on a scale from one to ten, with one being the lowest level of trust and ten being the highest level of trust. First, the President of the United States.” Comments: This was an interval measure with values ranging from one to ten.
240 Table B.2 Respondent Trust in Presidential Appointees Valid Responses Frequency Percent Percent Valid Rating of One 131 12.2% 12.4% Rating of Two 55 5.1% 5.2% Rating of Three 79 7.3% 7.5% Rating of Four 79 7.3% 7.5% Rating of Five 208 19.3% 19.7% Rating of Six 86 8.0% 8.1% Rating of Seven 129 12.0% 12.2% Rating of Eight 181 16.8% 17.1% Rating of Nine 39 3.6% 3.7% Rating of Ten 69 6.4% 6.5% Total Valid Responses 1,056 98.0% Missing Refused (8)/Don’t Know (14) 22 2.0% Total Responses 1,078
Summary Statistics Mean 5.438 Standard Error of Mean 0.081 Standard Deviation 2.642 Dissertation Question #2: “I am going to read you a list of people and groups of people. I would like you to rate the level of trust in each to do what is right for our country. Please rate your level of trust on a scale from one to ten ... Persons appointed by the President to run different government agencies.” Comments: This was an interval measure with values ranging from one to ten.
241 Table B.3 Respondent Trust in Members of Congress Valid Responses Frequency Percent Percent Valid Rating of One 73 6.8% 6.9% Rating of Two 46 4.3% 4.3% Rating of Three 75 7.0% 7.1% Rating of Four 99 9.2% 9.3% Rating of Five 287 26.6% 27.1% Rating of Six 134 12.4% 12.6% Rating of Seven 144 13.4% 13.6% Rating of Eight 150 13.9% 14.2% Rating of Nine 25 2.3% 2.4% Rating of Ten 27 2.5% 2.5% Total Valid Responses 1,060 98.3% Missing Refused (5)/Don’t Know (13) 18 1.7% Total Responses 1,078
Summary Statistics Mean 5.404 Standard Error of Mean 0.066 Standard Deviation 2.161 Dissertation Question #3: “I am going to read you a list of people and groups of people. I would like you to rate the level of trust in each to do what is right for our country. Please rate your level of trust on a scale from one to ten ... Members of Congress.” Comments: This was an interval measure with values ranging from one to ten.
242 Table B.4 Respondent Trust in Federal Government Employees Valid Responses Frequency Percent Percent Valid Rating of One 47 4.4% 4.4% Rating of Two 25 2.3% 2.4% Rating of Three 50 4.6% 4.7% Rating of Four 69 6.4% 6.5% Rating of Five 268 24.9% 25.4% Rating of Six 166 15.4% 15.7% Rating of Seven 198 18.4% 18.7% Rating of Eight 172 16.0% 16.3% Rating of Nine 29 2.7% 2.7% Rating of Ten 33 3.1% 3.1% Total Valid Responses 1,057 98.1% Missing Refused (4)/Don’t Know (17) 21 1.9% Total Responses 1,078
Summary Statistics Mean 5.877 Standard Error of Mean 0.061 Standard Deviation 2.001 Dissertation Question #4: “I am going to read you a list of people and groups of people. I would like you to rate the level of trust in each to do what is right for our country. Please rate your level of trust on a scale from one to ten ... Federal government employees.” Comments: This was an interval measure with values ranging from one to ten.
243 Table B.5 Respondent Trust in People in General Valid Responses Frequency Percent Percent Valid Rating of One 18 1.7% 1.7% Rating of Two 11 1.0% 1.0% Rating of Three 26 2.4% 2.4% Rating of Four 47 4.4% 4.4% Rating of Five 196 18.2% 18.4% Rating of Six 124 11.5% 11.6% Rating of Seven 237 22.0% 22.2% Rating of Eight 272 25.2% 25.5% Rating of Nine 87 8.1% 8.2% Rating of Ten 48 4.5% 4.5% Total Valid Responses 1,066 98.9% Missing Refused (4)/Don’t Know (8) 12 1.1% Total Responses 1,078
Summary Statistics Mean 6.687 Standard Error of Mean 0.056 Standard Deviation 1.843 Dissertation Question #5: “How about people in general, how would you rate your level of trust in citizens of this country regardless of whether or not they work in government?” Comments: This was an interval measure with values ranging from one to ten.
244 Table B.6 Respondent Trust in the State Governor Valid Responses Frequency Percent Percent Valid Rating of One 147 13.6% 13.8% Rating of Two 57 5.3% 5.4% Rating of Three 54 5.0% 5.1% Rating of Four 74 6.9% 7.0% Rating of Five 176 16.3% 16.6% Rating of Six 109 10.1% 10.3% Rating of Seven 143 13.3% 13.5% Rating of Eight 177 16.4% 16.7% Rating of Nine 60 5.6% 5.6% Rating of Ten 66 6.1% 6.2% Total Valid Responses 1,063 98.6% Missing Refused (4)/Don’t Know (11) 15 1.4% Total Responses 1,078
Summary Statistics Mean 5.522 Standard Error of Mean 0.083 Standard Deviation 2.701 Dissertation Question #6: “Now thinking in terms of Ohio, please rate your level of trust in the following people or groups of people to do what is right for our state. Again, on a scale from one to ten ... First, the Governor of Ohio.” Comments: This was an interval measure with values ranging from one to ten.
245 Table B.7 Respondent Trust in Gubernatorial Appointees Valid Responses Frequency Percent Percent Valid Rating of One 98 9.1% 9.3% Rating of Two 45 4.2% 4.2% Rating of Three 69 6.4% 6.5% Rating of Four 79 7.3% 7.5% Rating of Five 259 24.0% 24.5% Rating of Six 138 12.8% 13.0% Rating of Seven 166 15.4% 15.7% Rating of Eight 146 13.5% 13.8% Rating of Nine 34 3.2% 3.2% Rating of Ten 25 2.3% 2.4% Total Valid Responses 1,059 98.2% Missing Refused (4)/Don’t Know (15) 19 1.8% Total Responses 1,078
Summary Statistics Mean 5.401 Standard Error of Mean 0.070 Standard Deviation 2.268 Dissertation Question #7: “Please rate your level of trust in the following people or groups of people to do what is right for our state. Again, on a scale from one to ten ... Persons appointed by the Governor to run state government agencies.” Comments: This was an interval measure with values ranging from one to ten.
246 Table B.8 Respondent Trust in the General Assembly Valid Responses Frequency Percent Percent Valid Rating of One 43 4.0% 4.1% Rating of Two 35 3.2% 3.3% Rating of Three 42 3.9% 4.0% Rating of Four 68 6.3% 6.5% Rating of Five 240 22.3% 22.9% Rating of Six 154 14.3% 14.7% Rating of Seven 208 19.3% 19.9% Rating of Eight 176 16.3% 16.8% Rating of Nine 53 4.9% 5.1% Rating of Ten 28 2.6% 2.7% Total Valid Responses 1,047 97.1% Missing Refused (3)/Don’t Know (28) 31 2.9% Total Responses 1,078
Summary Statistics Mean 5.975 Standard Error of Mean 0.063 Standard Deviation 2.042 Dissertation Question #8: “Please rate your level of trust in the following people or groups of people to do what is right for our state. Again, on a scale from one to ten ... elected representatives serving in the Ohio General Assembly.” Comments: This was an interval measure with values ranging from one to ten.
247 Table B.9 Respondent Trust in State Government Employees Valid Responses Frequency Percent Percent Valid Rating of One 32 3.0% 3.0% Rating of Two 19 1.8% 1.8% Rating of Three 27 2.5% 2.6% Rating of Four 78 7.2% 7.4% Rating of Five 239 22.2% 22.6% Rating of Six 167 15.5% 15.8% Rating of Seven 231 21.4% 21.9% Rating of Eight 179 16.6% 17.0% Rating of Nine 55 5.1% 5.2% Rating of Ten 29 2.7% 2.7% Total Valid Responses 1,056 98.0% Missing Refused (4)/Don’t Know (18) 22 2.0% Total Responses 1,078
Summary Statistics Mean 6.150 Standard Error of Mean 0.058 Standard Deviation 1.893 Dissertation Question #9: “Please rate your level of trust in the following people or groups of people to do what is right for our state. Again, on a scale from one to ten ... State government employees.” Comments: This was an interval measure with values ranging from one to ten.
248 Table B.10 Respondent Trust in the County Commissioners Valid Responses Frequency Percent Percent Valid Rating of One 43 4.0% 4.1% Rating of Two 27 2.5% 2.6% Rating of Three 38 3.5% 3.6% Rating of Four 67 6.2% 6.4% Rating of Five 180 16.7% 17.2% Rating of Six 124 11.5% 11.8% Rating of Seven 227 21.1% 21.7% Rating of Eight 217 20.1% 20.7% Rating of Nine 75 7.0% 7.2% Rating of Ten 50 4.6% 4.8% Total Valid Responses 1,048 97.2% Missing Refused (2)/Don’t Know (28) 30 2.8% Total Responses 1,078
Summary Statistics Mean 6.320 Standard Error of Mean 0.066 Standard Deviation 2.132 Dissertation Question #10: “Thinking in terms of Stark County, please rate your level of trust in the following people or groups of people to do what is right for our county. Again, on a scale from one to ten ... The County Commissioners elected to run Stark County.” Comments: This was an interval measure with values ranging from one to ten.
249 Table B.11 Respondent Trust in the Appointees of County Commissioners Valid Responses Frequency Percent Percent Valid Rating of One 42 3.9% 4.0% Rating of Two 25 2.3% 2.4% Rating of Three 48 4.5% 4.6% Rating of Four 61 5.7% 5.8% Rating of Five 211 19.6% 20.2% Rating of Six 153 14.2% 14.6% Rating of Seven 230 21.3% 22.0% Rating of Eight 199 18.5% 19.0% Rating of Nine 46 4.3% 4.4% Rating of Ten 31 2.9% 3.0% Total Valid Responses 1,046 97.0% Missing Refused (8)/Don’t Know (24) 32 3.0% Total Responses 1,078
Summary Statistics Mean 6.099 Standard Error of Mean 0.062 Standard Deviation 2.020 Dissertation Question #11: “Thinking in terms of Stark County, please rate your level of trust in the following people or groups of people to do what is right for our county. Again, on a scale from one to ten ... persons appointed by the County Commissioners to run Stark County agencies.” Comments: This was an interval measure with values ranging from one to ten.
250 Table B.12 Respondent Trust in Other Elected County Officials Valid Responses Frequency Percent Percent Valid Rating of One 35 3.2% 3.3% Rating of Two 25 2.3% 2.4% Rating of Three 35 3.2% 3.3% Rating of Four 46 4.3% 4.3% Rating of Five 166 15.4% 15.6% Rating of Six 119 11.0% 11.2% Rating of Seven 226 21.0% 21.3% Rating of Eight 250 23.2% 23.5% Rating of Nine 94 8.7% 8.9% Rating of Ten 66 6.1% 6.2% Total Valid Responses 1,062 98.5% Missing Refused (4)/Don’t Know (12) 16 1.5% Total Responses 1,078
Summary Statistics Mean 6.597 Standard Error of Mean 0.065 Standard Deviation 2.102 Dissertation Question #12: “Thinking in terms of Stark County, please rate your level of trust in the following people or groups of people to do what is right for our county. Again, on a scale from one to ten ... Other elected Stark County officials such as the Auditor and the Treasurer.” Comments: This was an interval measure with values ranging from one to ten.
251 Table B.13 Respondent Trust in County Government Workers Valid Responses Frequency Percent Percent Valid Rating of One 31 2.9% 2.9% Rating of Two 18 1.7% 1.7% Rating of Three 33 3.1% 3.1% Rating of Four 42 3.9% 4.0% Rating of Five 239 22.2% 22.6% Rating of Six 162 15.0% 15.3% Rating of Seven 229 21.2% 21.7% Rating of Eight 210 19.5% 19.9% Rating of Nine 61 5.7% 5.8% Rating of Ten 31 2.9% 2.9% Total Valid Responses 1,056 98.0% Missing Refused (5)/Don’t Know (17) 22 2.0% Total Responses 1,078
Summary Statistics Mean 6.291 Standard Error of Mean 0.058 Standard Deviation 1.896 Dissertation Question #13: “Thinking in terms of Stark County, please rate your level of trust in the following people or groups of people to do what is right for our county. Again, on a scale from one to ten ... County government workers.” Comments: This was an interval measure with values ranging from one to ten.
252 Table B.14 Respondent Perception of Federal Government Valid Responses Frequency Percent Percent Valid Strongly Disagree 194 18.0% 18.1% Disagree 346 32.1% 32.4% Neither Agree Nor Disagree 156 14.5% 14.6% Agree 330 30.6% 30.9% Strongly Agree 43 4.0% 4.0% Total Valid Responses 1,069 99.2% Missing Refused (0)/Don’t Know (9) 9 0.8% Total Responses 1,078
Summary Statistics Mean -0.30 Standard Error of Mean 0.037 Standard Deviation 1.197 Dissertation Question #14: “Please indicate if you strongly agree, agree, disagree, strongly disagree, or neither agree nor disagree, with the following ... All in all, the federal government is headed in the right direction.”
Comments: This was an ordinal measure with numeric values assigned to the responses on a continuum as follows: strongly disagree (-2), disagree (-1), neither agree nor disagree (0), agree (1), strongly agree (2).
253 Table B.15 Respondent Perception of State Government Valid Responses Frequency Percent Percent Valid Strongly Disagree 96 8.9% 9.1% Disagree 386 35.8% 36.5% Neither Agree Nor Disagree 221 20.5% 20.9% Agree 349 32.4% 33.0% Strongly Agree 6 0.6% 0.6% Total Valid Responses 1,058 98.1% Missing Refused (3)/Don’t Know (17) 20 1.9% Total Responses 1,078
Summary Statistics Mean -0.21 Standard Error of Mean 0.031 Standard Deviation 1.019 Dissertation Question #15: “Please indicate if you strongly agree, agree, disagree, strongly disagree, or neither agree nor disagree, with the following ... All in all, the state government is headed in the right direction.”
Comments: This was an ordinal measure with numeric values assigned to the responses on a continuum as follows: strongly disagree (-2), disagree (-1), neither agree nor disagree (0), agree (1), strongly agree (2).
254 Table B.16 Respondent Perception of County Government Valid Responses Frequency Percent Percent Valid Strongly Disagree 51 4.7% 4.9% Disagree 192 17.8% 18.3% Neither Agree Nor Disagree 245 22.7% 23.4% Agree 538 49.9% 51.3% Strongly Agree 22 2.0% 2.1% Total Valid Responses 1,048 97.2% Missing Refused (4)/Don’t Know (26) 30 2.8% Total Responses 1,078
Summary Statistics Mean 0.27 Standard Error of Mean 0.029 Standard Deviation 0.949 Dissertation Question #16: “Please indicate if you strongly agree, agree, disagree, strongly disagree, or neither agree nor disagree, with the following ... All in all, Stark County government is headed in the right direction.”
Comments: This was an ordinal measure with numeric values assigned to the responses on a continuum as follows: strongly disagree (-2), disagree (-1), neither agree nor disagree (0), agree (1), strongly agree (2).
255 Table B.17 Respondent Interest in Government and Public Affairs Valid Responses Frequency Percent Percent Valid Hardly at All 55 5.1% 5.1% Only Now and Then 108 10.0% 10.0% Some of the Time 391 36.3% 36.3% Most of the Time 523 48.5% 48.6% Total Valid Responses 1,077 99.9% Missing Refused (0)/Don’t Know (1) 1 0.1% Total Responses 1,078
Dissertation Question #17: “Would you say that you follow what’s going on in government and public affairs most of the time, some of the time, only now and then, or hardly at all?”
Comments. This was an ordinal measure with numeric values assigned to the responses on a continuum as follows: hardly at all (1), only now and then (2), some of the time (3), and most of the time (4).
256 Table B.18 Respondent Voting Activity Valid Responses Frequency Percent Percent Valid Never 30 2.8% 2.8% Seldom 94 8.7% 8.8% Part of the time 95 8.8% 8.9% Nearly always 239 22.2% 22.3% Always 614 57.0% 57.3% Total Valid Responses 1,072 99.4% Missing Refused (6)/Don’t Know (0) 6 0.6% Total Responses 1,078
Summary Statistics Mean 3.22 Standard Error of Mean 0.034 Standard Deviation 1.102 Dissertation Question #18: “How often would you say you vote? Always, nearly always, part of the time, or seldom?”
Comments: This was an ordinal measure with numeric values assigned to the responses on a continuum as follows: never (1), seldom (2), part of the time (3), nearly always (4), and always (5).
257 Table B.19 Respondent Age Valid Responses Frequency Percent Percent Valid 18 to 24 years old 67 6.2% 6.3% 25 to 34 years old 132 12.2% 12.3% 35 to 44 years old 190 17.6% 17.8% 45 to 54 years old 203 18.8% 19.0% 55 to 64 years old 190 17.6% 17.8% 65 and Over 287 26.6% 26.8% Total Valid Responses 1,069 99.2% Missing Refused (9)/Don’t Know (0) 9 0.8% Total Responses 1,078
Summary Statistics Mean 52.25 Standard Error of Mean 0.552 Standard Deviation 18.05 Demographic Question #1: “In what year were you born?” (This variable was recoded into age.)
Comments: This was an interval measure.
258 Table B.20 Respondent’s Primary Source of Information Valid Responses Frequency Percent Percent Valid Newspapers 646 59.9% 60.2% Television 211 19.6% 19.7% Radio 90 8.3% 8.4% Friends and Family 57 5.3% 5.3% Internet 47 4.4% 4.4% News Magazines 4 0.4% 0.4% Mailings 4 0.4% 0.4% Other 14 1.3% 1.3% Total Valid Responses 1,073 99.5% Missing Refused (2)/Don’t Know (3) 5 0.5% Total Responses 1,078
Demographic Question #2: “Where do you get most of your information about current affairs and entertainment in Stark County?”
Comments: This was a nominal measure. This variable had limited utility as a supplemental variable in the dissertation research.
259 Table B.21 Respondent’s Primary Newspaper Valid Responses Frequency Percent Percent Valid Canton Repository 711 66.0% 66.7% Akron Beacon Journal 119 11.0% 11.2% Massillon Independent 95 8.8% 8.9% Alliance Review 58 5.4% 5.4% Cleveland Plain Dealer 11 1.0% 1.0% National Newspapers 19 1.8% 1.8% Miscellaneous 8 0.7% 0.8% No Preference 12 1.1% 1.1% Do Not Read Newspapers 33 3.1% 3.1% Total Valid Responses 1,066 98.9% Missing Refused (2)/Don’t Know (10) 12 1.1% Total Responses 1,078
Demographic Question #3: “Which newspaper do you read most often?”
Comments: This was a nominal measure. This variable had limited utility as a supplemental variable in the dissertation research.
260 Table B.22 Respondent’s Primary Televison Station Valid Responses Frequency Percent Percent Valid Basic Cable 305 28.3% 28.7% Fox (WWJW) 226 21.0% 21.3% NBC (WKYC) 160 14.8% 15.1% ABC (WEWS) 141 13.1% 13.3% CBS (WOIO) 51 4.7% 4.8% Premium Cable 44 4.1% 4.1% PBS (WVIZ,WNEO,WEAO) 26 2.4% 2.4% PAX23 12 1.1% 1.1% UPN (WUAB) 10 0.9% 0.9% Miscellaneous 14 1.3% 1.3% No Preference 34 3.2% 3.2% Do Not Watch TV 40 3.7% 3.8% Total Valid Responses 1,063 98.6% Missing Refused (0)/Don’t Know (15) 15 1.4% Total Responses 1,078
Demographic Question #4: “Which television station do you watch most often?”
Comments: This was a nominal measure. This variable had limited utility as a supplemental variable in the dissertation research.
261 Table B.23 Respondent’s Primary Radio Station Valid Responses Frequency Percent Percent Valid NPR 75 7.0% 7.0% Miscellaneous FM 628 58.3% 59.0% Miscellaneous AM 212 19.7% 19.9% Unspecified 33 3.1% 3.1% No Preference 29 2.7% 2.7% Do Not Listen to Radio 87 8.1% 8.2% Total Valid Responses 1,064 98.7% Missing Refused (0)/Don’t Know (14) 14 1.3% Total Responses 1,078
Demographic Question #5: “Which radio station do you listen to most often?”
Comments: This was a nominal measure. This variable had limited utility as a supplemental variable in the dissertation research.
262 Table B.24 Respondent’s Living Arrangement Valid Responses Frequency Percent Percent Valid Own Home 780 72.4% 72.6% Rent Home 250 23.2% 23.3% Other Living Arrangement 44 4.1% 4.1% Total Valid Responses 1,074 99.6% Missing Refused (3)/Don’t Know (1) 4 0.4% Total Responses 1,078
Demographic Question #6: “Do you rent or own your home?”
Comments: This was a nominal measure. When examined as an explanatory variable in the dissertation research, this variable was sometimes dichotomized as own home (1) and does not own home (0).
263 Table B.25 Respondent’s Type of Housing Valid Responses Frequency Percent Percent Valid House 858 79.6% 79.7% Apartment 81 7.5% 7.5% Duplex of Two-Family Home 69 6.4% 6.4% Town House 29 2.7% 2.7% Condominium 18 1.7% 1.7% Independent Living Facility 6 0.6% 0.6% Other 16 1.5% 1.5% Total Valid Responses 1,077 99.9% Missing Refused (1)/Don’t Know (0) 1 0.1% Total Responses 1,078
Demographic Question #7: “Would you describe your current residence as a house, town house, apartment, duplex or two-family home, assisted living facility, or condominium?”
Comments: This was a nominal measure. This variable had limited utility as a supplemental variable in the dissertation research.
264 Table B.26 Respondent Education Valid Responses Frequency Percent Percent Valid Grade School 11 1.0% 1.0% Some High School 67 6.2% 6.2% High School Graduate 394 36.5% 36.7% Some College 300 27.8% 27.9% College Graduate 191 17.7% 17.8% Post Graduate 111 10.3% 10.3% Total Valid Responses 1,074 99.6% Missing Refused (4)/Don’t Know (0) 4 0.4% Total Responses 1,078
Demographic Question #8: “What is the highest grade of school or year of college you completed?”
Comments: This was an ordinal measure with numeric values assigned to the responses on a continuum as follows: grade school (1), some high school (2), high school graduate (3), some college or trade school (4), college graduate (5), post graduate (6).
265 Table B.27 Children’s Type of School Responses Frequency Percent Valid Percent Valid Public School Only 264 24.5% 82.0% Private School Only 26 2.4% 8.1% Home Schooled Only 8 0.7% 2.5% Other Arrangements 8 0.7% 2.5% Multiple Types 16 1.5% 5.0% Total Valid Responses 322 29.9% Missing Refused (0)/Don’t Know (29) 29 2.7% No Children in Household 727 70.1% Total Responses 1,078
Demographic Question #9: “What type of school do the children in your household attend, public school private school, home school, or something else?”
Comments: This was a nominal measure. This variable had limited utility as a supplemental variable in the dissertation research.
266 Table B.28 Annual Household Income Valid Responses Frequency Percent Percent Valid Under $18,000 per annum 145 13.5% 14.9% $18,000 to $36,000 286 26.5% 29.3% $36,000 to $54,000 182 16.9% 18.6% $54,000 to $72,000 170 15.8% 17.4% Over $72,000 per annum 193 17.9% 19.8% Total Valid Responses 976 90.5% Missing Refused (70)/Don’t Know (32) 102 9.5% Total Responses 1,078
Demographic Question #10: “What is the total yearly income for your family before taxes?” (Note, this question was branched into five income levels.)
Comments: This was an ordinal measure with numeric values assigned to the responses on a continuum as follows: under $18,000 per annum (1), $18,000 to $36,000 per annum (2), $36,000 to $54,000 per annum (3), $54,000 to $72,000 per annum (4), and $72,000 and over (5).
267 Table B.29 Household Financial Status Valid Responses Frequency Percent Percent Valid Worse Off 386 35.8% 36.3% About the Same 333 30.9% 31.4% Better Off 343 31.8% 32.3% Total Valid Responses 1,062 98.5% Missing Refused (4)/Don’t Know (12) 16 1.5% Total Responses 1,078
Demographic Question #11: “Would you say that your household is better off financially, about the same, or worse off financially than a few years ago?”
Comments: This was an ordinal measure with numeric values assigned to the responses on a continuum as follows: worse off (-1), about the same (0), and better off (1).
268 Table B.30 Respondent Race Valid Responses Frequency Percent Percent Valid White or Caucasian 950 88.1% 88.7% Black or African-American 62 5.8% 5.8% American Indian or Alaskan 8 0.7% 0.7% Hawaiian or Pacific Islander 2 0.2% 0.2% Asian 2 0.2% 0.2% Other 16 1.5% 1.5% Multiple Selections 31 2.9% 2.9% Total Valid Responses 1,071 99.4% Missing Refused (7)/Don’t Know (0) 7 0.6% Total Responses 1,078
Demographic Question #12: “What is your race, how would you classify yourself?”
Comments: This was a nominal measure. When examined as an explanatory variable in the dissertation research, this variable was sometimes dichotomized as Caucasian (1) and not Caucasian (0).
269 Table B.31 Respondent Origin Valid Responses Frequency Percent Percent Valid Hispanic 23 2.1% 2.1% Not Hispanic 1,050 97.4% 97.9% Total Valid Responses 1,073 99.5% Missing Refused (2)/Don’t Know (3) 5 0.5% Total Responses 1,078
Demographic Question #13: “Are you of Hispanic origin?”
Comments: This was a nominal measure. When examined as an explanatory variable in the dissertation research, this variable was dichotomized as Hispanic (1) and not Hispanic (0).
270 Table B.32 Respondent Marital Status Valid Responses Frequency Percent Percent Valid Married 588 54.5% 54.7% Single, Never Married 168 15.6% 15.6% Divorced 152 14.1% 14.1% Widowed 151 14.0% 14.0% Separated 16 1.5% 1.5% Total Valid Responses 1,075 99.7% Missing Refused (3)/Don’t Know (0) 3 0.3% Total Responses 1,078
Demographic Question #14: “What is your present marital status?”
Comments: This was a nominal measure. When examined as an explanatory variable in the dissertation research, this variable was sometimes dichotomized as married (1) and not married (0).
271 Table B.33 Respondent Employment Status Valid Responses Frequency Percent Percent Valid Employed Full-Time 504 46.8% 46.8% Retired 277 25.7% 25.7% Employed Part-Time 105 9.7% 9.8% Homemaker 78 7.2% 7.2% Unemployed 65 6.0% 6.0% Student Not Working 14 1.3% 1.3% Other 33 3.1% 3.1% Total Valid Responses 1,076 99.8% Missing Refused (1)/Don’t Know (1) 2 0.2% Total Responses 1,078
Demographic Question #15: “Are you currently employed full-time 35 hours or more per week, employed part-time, retired, homemaker not employed outside the home, student not working, or unemployed?”
Comments: This was a nominal measure. When examined as an explanatory variable in the dissertation research, this variable was sometimes dichotomized as employed (1) and not employed (0).
272 Table B.34 Place of Employment Zip Code Valid Responses Frequency Percent Percent Valid 44646 71 6.6% 13.7% 44720 53 4.9% 10.2% 44601 32 3.0% 6.2% 44705 27 2.5% 5.2% 44702 26 2.4% 5.0% 44706 23 2.1% 4.4% 44708 22 2.0% 4.2% 44641 21 1.9% 4.1% 44718 21 1.9% 4.1% 44709 18 1.7% 3.5% 44710 15 1.4% 2.9% 44703 14 1.3% 2.7% 44707 13 1.2% 2.5% 44647 11 1.0% 2.1% 44721 11 1.0% 2.1% Other Stark County 57 5.3% 11.0% Outside Stark County 83 7.7% 16.0% Total Valid Responses 518 48.1% Missing Refused (0)/Don’t Know (91) 91 8.4% Not Asked 469 43.5% Total Responses 1,078 Demographic Question #16: “What is the zip code for your place of work?” Comments: This was a nominal measure.
273 Table B.35 Respondent Religious Preference Valid Responses Frequency Percent Percent Valid Protestant 504 46.8% 47.2% Catholic 250 23.2% 23.4% Jewish 7 0.6% 0.7% Muslim 1 0.1% 0.1% Other 266 24.7% 24.9% No Religious Preference 39 3.6% 3.7% Total Valid Responses 1,067 99.0% Missing Refused (10)/Don’t Know (1) 11 1.0% Total Responses 1,078
Demographic Question #17: “What is your religious preference?”
Comments: This was a nominal measure. This variable had limited utility as a supplemental variable in the dissertation research.
274 Table B.36 Household City or Township Valid Responses Frequency Percent Percent Valid Canton 178 16.5% 16.6% Jackson Township 122 11.3% 11.4% Massillon 116 10.8% 10.8% Plain Township 87 8.1% 8.1% Alliance 75 7.0% 7.0% Perry Township 70 6.5% 6.5% North Canton 64 5.9% 6.0% Canton Township 49 4.5% 4.6% Louisville 43 4.0% 4.0% Lake Township 31 2.9% 2.9% Nimishellen Township 24 2.2% 2.2% Lawrence Township 22 2.0% 2.1% Canal Fulton 21 1.9% 2.0% Hartville 13 1.2% 1.2% Tuscarawas Township 13 1.2% 1.2% Lexington Township 13 1.2% 1.2% Other 132 12.2% 12.3% Total Valid Responses 1,073 99.5% Missing Refused (5)/Don’t Know (0) 5 0.5% Total Responses 1,078 Demographic Question #18: “What city or township do you live in?” Comments: This was a nominal variable. This variable was sometimes dichotomized as urban - Canton, Alliance and Massillon (1) and not urban (0).
275 Table B.37 Length of Residence in Stark County Valid Responses Frequency Percent Percent Valid Under One Year 16 1.5% 1.5% One to Five Years 95 8.8% 8.8% Six to Ten Years 70 6.5% 6.5% Eleven to 15 Years 66 6.1% 6.1% 16 to 20 Years 60 5.6% 5.6% Over 20 Years 771 71.5% 71.5% Total Valid Responses 1,078 100.0% Missing Refused (0)/Don’t Know (0) -- -- Total Responses 1,078
Demographic Question #19: “How long have you lived in Stark County?”
Comments: This was an ordinal measure with numeric values assigned to the responses on a continuum as follows: under one year (1), one to five years (2), six to ten years (3), eleven to fifteen years (4), sixteen to twenty years (5), and over twenty years (6).
276 Table B.38 Respondent Political Ideology Valid Responses Frequency Percent Percent Valid Liberal 219 20.3% 21.3% Moderate 291 27.0% 28.3% Conservative 361 33.5% 35.2% Something Else 156 14.5% 15.2% Total Valid Responses 1,027 95.3% Missing Refused (6)/Don’t Know (45) 51 4.7% Total Responses 1,078
Demographic Question #20: “When you think about political issues, would you say you think of yourself as a liberal, a moderate, a conservative, or something else?”
Comments: This was initially a nominal variable which was recoded into an ordinal variable by excluding those responding something else. As an ordinal measure, numeric values were assigned to the responses on a continuum as follows: liberal (-1), moderate (0), and conservative (1).
277 Table B.39 Respondent Political Party Affiliation Valid Responses Frequency Percent Percent Valid Democrat 393 36.5% 37.3% Republican 342 31.7% 32.4% Independent 233 21.6% 22.1% Something Else 87 8.1% 8.2% Total Valid Responses 1,055 97.9% Missing Refused (8)/Don’t Know (15) 23 2.1% Total Responses 1,078
Demographic Question #21: “In politics, do you usually think of yourself as a Democrat, a Republican, an Independent, or something else?”
Comments: This was a nominal measure. When examined as an explanatory variable in the dissertation research, this variable was sometimes dichotomized as Republican (1) and not Republican (0).
278 Table B.40 Voter Registration Status Valid Responses Frequency Percent Percent Valid Registered 959 89.0% 89.7% Not Registered 110 10.2% 10.3% Total Valid Responses 1,069 99.2% Missing Refused (1)/Don’t Know (8) 9 0.8% Total Responses 1,078
Demographic Question #22: “Right now are you registered to vote in Ohio, if you want to?”
Comments: This was a nominal measure. When examined as an explanatory variable in the dissertation research, this variable was dichotomized as registered to vote (1) and not registered to vote (0).
279 Table B.41 Number of People Household Valid Responses Frequency Percent Percent Valid One Person 247 22.9% 23.0% Two Persons 388 36.0% 36.2% Three Persons 178 16.5% 16.6% Four Persons 153 14.2% 14.3% Five Persons 63 5.8% 5.9% Six Persons 28 2.6% 2.6% Seven or More Persons 16 1.5% 1.5% Total Valid Responses 1,073 99.5% Missing Refused (0)/Don’t Know (5) 5 0.5% Total Responses 1,078
Demographic Question #23: “How many people live in your current residence?”
Comments: This was a ordinal measure. This variable had limited utility as a supplemental variable in the dissertation research.
280 Table B.42 Household Zip Code Valid Responses Frequency Percent Percent Valid 44646 153 14.2% 14.3% 44720 114 10.6% 10.7% 44601 102 9.5% 9.6% 44708 83 7.7% 7.8% 44641 66 6.1% 6.2% 44706 58 5.4% 5.4% 44647 50 4.6% 4.7% 44709 46 4.3% 4.3% 44614 36 3.3% 3.4% 44705 34 3.2% 3.2% 44721 32 3.0% 3.0% 44718 29 2.7% 2.7% 44707 26 2.4% 2.4% 44632 25 2.3% 2.3% 44662 25 2.3% 2.3% 44710 22 2.0% 2.1% 44703 20 1.9% 1.9% Other Zip Codes 147 13.6% 13.8% Total Valid Responses 1,068 99.1% Missing Refused (0)/Don’t Know (10) 10 1.0% Total Responses 1,078 Demographic Question #24: “What is your zip code?” Comments: This was a nominal measure.
281 Table B.43 Respondent Sex Valid Responses Frequency Percent Percent Valid Male 521 48.3% 48.3% Female 557 51.7% 51.7% Total Valid Responses 1,078 100.0% Missing Refused (0)/Don’t Know (0) -- -- Total Responses 1,078
Demographic Question #25: Note, interviewer recorded respondent sex based upon observation.
When examined as an explanatory variable in the dissertation research, this variable was dichotomized as female (1) and male (0).
282 APPENDIX C
FITTED REGRESSION TRUST MODELS
The following tables depict the fitted regression models for the trust in government
models used to assess research hypothesis H4 and the subsequent nine sub-hypotheses.
Twelve separate fitted regression models were developed where each of the twelve classifications of government officials were used as dependent variables. These included public trust in the President, trust in presidential appointees, trust in Congress, trust in federal government employees, trust in the state governor, trust in gubernatorial appointees, trust in the state legislature, trust in state government employees, trust in elected county executives, trust in county executive appointees, trust in other elected county officials, and trust in county government employees.
These models are assessed irrespective of the other trust in government officials; that is, trust in other government officials was not examined as an independent variable on other trust in government officials dependent variables due to significant co-linear relationships.
Explanatory variables were included in the fitted regression models if their statistics of association were significant within a 95% confidence interval.
283 Table C.1 Fitted Regression Model: Public Trust in President(1) Multivariate Regression Statistics
Unstandardized Standardized t Significance Independent Variables(2) Coefficient Coefficient Statistic (p)
U.S. Government Direction 1.260 0.494 17.87 0.000 Republican (1/0) 1.373 0.212 7.495 0.000 Political Ideology 0.479 0.122 4.682 0.000 Household Finances 0.401 0.106 4.427 0.000 Trust in People (General) 0.146 0.081 3.452 0.001 Racial Minority (1/0) -0.728 -0.068 -2.849 0.004 Voting Activity -0.185 -0.059 -2.488 0.013 Urban Resident (1/0) -0.380 -0.057 -2.371 0.018 Constant 5.561
Model Summary Analysis of Variance F=131.54 0.000 R Square 0.562 Adjusted R Square 0.558 Standard Error of Estimate 2.078
(1) Fitted regression model with public trust in the President designated as the dependent variable. (2)Independent variables examined but excluded from the model due to lack of significance included: government interest, voter registration status, gender, Hispanic origin, age, education, employment status, household income, home ownership, and marital status.
284 Table C.2 Fitted Regression Model: Public Trust in Presidential Appointees(1) Multivariate Regression Statistics
Unstandardized Standardized t Significance Independent Variables(2) Coefficient Coefficient Statistic (p) U.S. Government Direction 1.066 0.501 16.49 0.000 Republican (1/0) 0.851 0.157 5.136 0.000 Trust in People (General) 0.168 0.112 4.382 0.000 Household Finances 0.319 0.102 3.830 0.000 Political Ideology 0.269 0.083 2.876 0.004 Constant 4.471
Analysis of Variance F=141.68 0.000 Model Summary R Square 0.462 Adjusted R Square 0.459 Standard Error of Estimate 1.916
(1) Fitted regression model with public trust in president appointees designated as the dependent variable. (2)Independent variables examined but excluded from the model due to lack of significance included: government interest, voter registration status, voting activity, gender, race, Hispanic origin, age, education, employment status, household income, home ownership, marital status, and urban residence.
285 Table C.3 Fitted Regression Model: Public Trust in Congress(1) Multivariate Regression Statistics
Unstandardized Standardized t Significance Independent Variables(2) Coefficient Coefficient Statistic (p)
U.S. Government Direction 0.511 0.310 10.40 0.000 Trust in People (General) 0.192 0.163 5.674 0.000 Female (1/0) 0.394 0.092 3.206 0.001 Household Finances 0.217 0.085 2.841 0.005 Racial Minority (1/0) -0.530 -0.077 -2.667 0.008 Constant 4.669
Model Summary Analysis of Variance F=40.02 0.000 R Square 0.164 Adjusted R Square 0.160 Standard Error of Estimate 1.958
(1) Fitted regression model with public trust in member of Congress designated as the dependent variable. (2)Independent variables examined but excluded from the model due to lack of significance included: Political ideology, republican affiliation, government interest, voter registration status, voting activity, Hispanic origin, age, education, employment status, household income, home ownership, marital status, and urban residence.
286 Table C.4 Fitted Regression Model: Public Trust in Federal Employees(1) Multivariate Regression Statistics
Unstandardized Standardized t Significance Independent Variables(2) Coefficient Coefficient Statistic (p)
Trust in People (General) 0.310 0.284 9.699 0.000 U.S. Government Direction 0.264 0.158 5.414 0.000 Constant 3.875
Model Summary Analysis of Variance F=64.34 0.000 R Square 0.110 Adjusted R Square 0.108 Standard Error of Estimate 1.887
(1) Fitted regression model with public trust in federal government employees designated as the dependent variable. (2)Independent variables examined but excluded from the model due to lack of significance included: Political ideology, republican affiliation, government interest, voter registration status, voting activity, gender, race, Hispanic origin, age, education, employment status, household income, household financial status, home ownership, marital status, and urban residence.
287 Table C.5 Fitted Regression Model: Public Trust in Ohio Governor(1) Multivariate Regression Statistics
Unstandardized Standardized t Significance Independent Variables(2) Coefficient Coefficient Statistic (p)
State Government Direction 1.417 0.542 19.02 0.000 Political Ideology 0.341 0.102 3.605 0.000 Trust in People (General) 0.131 0.084 3.047 0.002 Household Finances 0.275 0.085 2.986 0.003 Constant 4.928
Model Summary Analysis of Variance F=117.20 0.000 R Square 0.359 Adjusted R Square 0.356 Standard Error of Estimate 2.153
(1) Fitted regression model with public trust in the state Governor designated as the dependent variable. (2)Independent variables examined but excluded from the model due to lack of significance included: republican affiliation, government interest, voter registration status, voting activity, gender, race, Hispanic origin, age, education, employment status, household income, home ownership, marital status, and urban residence.
288 Table C.6 Fitted Regression Model: Public Trust in Ohio Gubernatorial Appointees(1) Multivariate Regression Statistics
Unstandardized Standardized t Significance Independent Variables(2) Coefficient Coefficient Statistic (p)
State Government Direction 1.076 0.493 16.98 0.000 Trust in People (General) 0.189 0.146 5.151 0.000 Household Finances 0.366 0.136 4.670 0.000 Female (1/0) 0.364 0.081 2.852 0.004 Political Ideology 0.188 0.067 2.313 0.021 Constant 4.200
Model Summary Analysis of Variance F=84.35 0.000 R Square 0.336 Adjusted R Square 0.332 Standard Error of Estimate 1.829
(1) Fitted regression model with public trust in the state gubernatorial appointees designated as the dependent variable. (2)Independent variables examined but excluded from the model due to lack of significance included: republican affiliation, government interest, voter registration status, voting activity, race, Hispanic origin, age, education, employment status, household income, home ownership, marital status, and urban residence.
289 Table C.7 Fitted Regression Model: Public Trust in Ohio General Assembly(1) Multivariate Regression Statistics
Unstandardized Standardized t Significance Independent Variables(2) Coefficient Coefficient Statistic (p)
State Government Direction 0.717 0.363 12.78 0.000 Trust in People (General) 0.291 0.259 9.189 0.000 Racial Minority (1/0) -0.640 -0.098 -3.511 0.000 Household Finances 0.180 0.074 2.601 0.009 Age -0.008 -0.071 -2.519 0.012 Constant 4.638
Model Summary Analysis of Variance F=60.69 0.000 R Square 0.233 Adjusted R Square 0.229 Standard Error of Estimate 1.773
(1) Fitted regression model with public trust in the state General Assembly designated as the dependent variable. (2)Independent variables examined but excluded from the model due to lack of significance included: Political ideology, republican affiliation, government interest, voter registration status, voting activity, gender, Hispanic origin, education, employment status, household income, home ownership, marital status, and urban residence.
290 Table C.8 Fitted Regression Model: Public Trust in Ohio State Employees(1) Multivariate Regression Statistics
Unstandardized Standardized t Significance Independent Variables(2) Coefficient Coefficient Statistic (p)
Trust in People (General) 0.403 0.385 13.86 0.000 State Government Direction 0.402 0.216 7.754 0.000 Constant 3.518
Model Summary Analysis of Variance F=131.29 0.000 R Square 0.203 Adjusted R Square 0.201 Standard Error of Estimate 1.695
(1) Fitted regression model with public trust in the state government employees designated as the dependent variable. (2)Independent variables examined but excluded from the model due to lack of significance included: Political ideology, republican affiliation, government interest, voter registration status, voting activity, gender, race, Hispanic origin, age, education, employment status, household income, household financial status, home ownership, marital status, and urban residence.
291 Table C.9 Fitted Regression Model: Public Trust in Stark County Commissioners(1) Multivariate Regression Statistics
Unstandardized Standardized t Significance Independent Variables(2) Coefficient Coefficient Statistic (p)
County Government Direction 0.898 0.405 14.67 0.000 Trust in People (General) 0.273 0.238 8.728 0.000 Republican (1/0) 0.420 0.094 3.046 0.001 Female (1/0) 0.344 0.082 3.032 0.002 Household Finances 0.151 0.060 2.176 0.030 Constant 3.930
Model Summary Analysis of Variance F=80.96 0.000 R Square 0.292 Adjusted R Square 0.288 Standard Error of Estimate 1.773
(1) Fitted regression model with public trust in the county elected executives designated as the dependent variable. (2)Independent variables examined but excluded from the model due to lack of significance included: Political ideology, government interest, voter registration status, voting activity, race, Hispanic origin, age, education, employment status, household income, home ownership, marital status, and urban residence.
292 Table C.10 Fitted Regression Model: Public Trust in Stark County Appointees(1) Multivariate Regression Statistics
Unstandardized Standardized t Significance Independent Variables(2) Coefficient Coefficient Statistic (p)
County Government Direction 0.885 0.420 15.74 0.000 Trust in People (General) 0.286 0.261 9.906 0.000 Racial Minority (1/0) -0.692 -0.109 -4.169 0.000 Female (1/0) 0.370 0.093 3.550 0.000 Household Finances 0.180 0.075 2.843 0.005 Constant 3.824
Model Summary Analysis of Variance F=96.88 0.000 R Square 0.327 Adjusted R Square 0.323 Standard Error of Estimate 1.642
(1) Fitted regression model with public trust in the county executive appointees employees designated as the dependent variable. (2)Independent variables examined but excluded from the model due to lack of significance included: Political ideology, republican affiliation, government interest, voter registration status, voting activity, Hispanic origin, age, education, employment status, household income, home ownership, marital status, and urban residence.
293 Table C.11 Fitted Regression Model: Public Trust in Other Stark County Elected Officials(1) Multivariate Regression Statistics
Unstandardized Standardized t Significance Independent Variables(2) Coefficient Coefficient Statistic (p)
County Government Direction 0.877 0.399 15.09 0.000 Trust in People (General) 0.336 0.294 11.23 0.000 Racial Minority (1/0) -0.921 -0.138 -5.338 0.000 Household Finances 0.211 0.084 3.228 0.001 Constant 4.209
Model Summary Analysis of Variance F=125.15 0.000 R Square 0.311 Adjusted R Square 0.329 Standard Error of Estimate 1.709
(1) Fitted regression model with public trust in other elected county officials employees designated as the dependent variable. (2)Independent variables examined but excluded from the model due to lack of significance included: Political ideology, republican affiliation, government interest, voter registration status, voting activity, gender, Hispanic origin, age, education, employment status, household income, home ownership, marital status, and urban residence.
294 Table C.12 Fitted Regression Model: Public Trust in Stark County Employees(1) Multivariate Regression Statistics
Unstandardized Standardized t Significance Independent Variables(2) Coefficient Coefficient Statistic (p)
Trust in People (General) 0.392 0.378 14.12 0.000 County Government Direction 0.636 0.318 11.89 0.000 Constant 3.481
Model Summary Analysis of Variance F=200.65 0.000 R Square 0.281 Adjusted R Square 0.280 Standard Error of Estimate 1.603
(1) Fitted regression model with public trust in the county government employees designated as the dependent variable. (2)Independent variables examined but excluded from the model due to lack of significance included: Political ideology, republican affiliation, government interest, voter registration status, voting activity, gender, race, Hispanic origin, age, education, employment status, household income, household financial status, home ownership, marital status, and urban residence.
295