THE INFLUENCE OF RELIGION AND MESSAGES FROM RELIGIOUS AUTHORITIES:
ATTITUDES ABOUT SCIENCE AND ENVIRONMENTAL CONCERN

By

John M. Clements

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Sociology – Doctor of Philosophy

2013

ABSTRACT

THE INFLUENCE OF RELIGION AND MESSAGES FROM RELIGIOUS AUTHORITIES:
ATTITUDES ABOUT SCIENCE AND ENVIRONMENTAL CONCERN

By

John M. Clements

This dissertation explores relationships among religious beliefs and practices, attitudes about
science, and environmental concern. Discussions about conflict, separation, or ambivalence
between science and religion are as old as science itself, with mixed evidence about the
relationships between religion and science. Although there is a general lack of understanding of
scientific concepts by the public, correct scientific knowledge of environmental problems is
often a key predictor of intentions to behave pro-environmentally. At the same time, religion
plays an important part in the daily lives of millions of Americans. If religion plays a role in
guiding the lived experiences of adherents, even in the face of increasing secularization, it is
important to examine the effects of religion, as well as religious messages, on scientific and
environmental matters. The main objectives of this dissertation are to: 1) analyze the ways in
which religious affiliation, belief, and commitment characteristics affect attitudes about science
in contemporary U.S. society, and 2) analyze how scientifically and religiously framed messages
affect specific facets of environmental concern.
This dissertation is based on theoretically driven hypotheses suggested by the current
literature, and is organized into three chapters. In the first empirical chapter, I analyze secondary
data from the General Social Survey to test hypotheses about the influence of religious
affiliation, beliefs, and behavior on attitudes about science. The results of this study provide

some evidence that Christians in general have more negative attitudes about science than do nonChristians and non-religious people, but claims about major conflict between science and
religion may not accurately describe the U.S. general public.
In the second and third essays, I conduct two experiments that test the influence of religious
and scientific messages on two specific types of environmental concern in subjects recruited
using Amazon Mechanical Turk. In the second essay, I use structural equation modeling to
analyze data from an experiment that examines how scientifically framed and religiously framed
messages about water conservation influence attitudes about a proposed policy to restrict water
use. Results indicate that Christians are just as likely as non-Christians and non-religious people
to agree with a policy calling for water use restrictions. However, among all respondents—and
also among Christians—a Christian religious message reduces agreement with the proposed
water use restriction policy. These results suggest that religiously framed messages may not
significantly increase environmental concern.
In the third essay, I use zero-inflated Poisson regression to analyze data from an experiment
that tests the influence of scientifically framed and religiously framed messages about
biodiversity loss on the decision to make a donation to an environmental organization that
protects against biodiversity loss. Although Christianity does not influence the decision to
donate or not, it does affect the amount that donators give; Christians donate less than nonChristians and non-religious subjects. Receiving a religious message has no effect on making a
donation or donation amount. Similar to the first experiment, these results suggest that a
religiously framed message may not influence this type of donation behavior.

Copyright by
JOHN M. CLEMENTS
2013

ACKNOWLEDGEMENTS

I could not have completed this dissertation without the participation of some dedicated,
supportive, and caring people. There are not enough words to express my gratitude to my
dissertation committee, Aaron McCright (Chair), Tom Dietz, Sandy Marquart-Pyatt, and Sean
Valles. Thanks to Aaron who guided, cajoled, listened, let me wander off track and pulled me
back, and made me realize the importance of every word I use. I thank you from the bottom of
my heart for helping me attain this lifelong goal. Even when I had doubts, your well-timed
encouragement kept me going. Thanks to Tom and Sandy for your interest in my work and
valuable feedback and support during the entire process. Thanks to Sean for your timely
assistance and encouragement. I also owe thanks to Soma Chaudhuri and Kyle Whyte for taking
an early interest in my work.
I thank the Graduate School and the Environmental Science and Policy Program at Michigan
State University for providing financial assistance throughout my graduate studies.
Finally, I thank my wife Jennifer and my sons Joshua and Jordan for their support and love
over the last 18 years, and especially during the last five. I’ve ignored you, bored you with my
research, and spent too many hours in front of a computer. You’ve kept me grounded and sane.
Thank you for believing in me, loving me and supporting me. I only hope that I can give back
what you have given to me.

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TABLE OF CONTENTS

LIST OF TABLES

viii

LIST OF FIGURES

ix

CHAPTER 1
INTRODUCTION

1

CHAPTER 2
RELIGIOUS AFFILIATION, COMMITMENT AND BELIEF:
IMPLICATONS FOR PUBLIC ATTITUDES ABOUT SCIENCE
INTRODUCTION
RELIGION AND ATTITUDES ABOUT SCIENCE
HYPOTHESES
DATA AND METHODS
Dependent Variables: Attitudes about Science Indicators
Independent Variables
Statistical Analyses
RESULTS AND DISCUSSION
CONCLUSION

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20
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27

CHAPTER 3
THE INFLUENCE OF RELIGIOUSLY AND SCIENTIFICALLY
FRAMED MESSAGES ON AGREEMENT WITH WATER USE RESTRICTIONS
INTRODUCTION
RELIGION, SCIENCE AND ENVIRONMENTAL CONCERN
Religion, Scientific Knowledge and Environmental Concern
Message Framing
Water Conservation
METHODS
Experimental Design
Sample
Dependent Variable
Experimental Conditions
Religion Predictors
Political, Socio-Demographic and Biophysical Predictors
Environmental Concern Indicators
Statistical Analysis
RESULTS
CONCLUSION

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CHAPTER 4
ACTUAL PAYMENTS FOR BIODIVERSITY PROTECTION:
THE INFLUENCE OF RELIGIOUSLY AND
SCIENTIFICALLY FRAMED MESSAGES
INTRODUCTION
RELIGION, SCIENCE AND ENVIRONMENTAL CONCERN
Scientific Knowledge and Religion
Message Framing
Biodiversity Loss
METHODS
Experimental Design
Sample
Dependent Variable
Experimental Conditions
Manipulation Checks
Religion Predictors
Values Orientation and Environmental Concern Indicators
Political and Socio-Demographic Predictors
Statistical Analysis
RESULTS
CONCLUSION

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CHAPTER 5
CONCLUSION

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APPENDICES
APPENDIX A: TABLES
APPENDIX B: FIGURE

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79
93

REFERENCES

95

vii

LIST OF TABLES

Table 1: General Social Survey Variables Used in the Study

80

Table 2: Attitudes about Science among Different Religious
Subgroups in 2010

82

Table 3: Standardized Coefficients from OLS Regression Models
Predicting Attitudes about Science: Entire Sample

83

Table 4: Standardized Coefficients from OLS Regressions Predicting
Attitudes about Science: Christian Subsample

84

Table 5: Description, Coding, Mean, and Standard Deviation of the
Variables Used in the Study

86

Table 6: Standardized Coefficients from Structural Equation Model
Predicting Agreement with Proposed Water Policy, Entire Sample (N=608)

87

Table 7: Standardized Coefficients from Structural Equation Model
Predicting Agreement with Proposed Water Policy, Christian Subsample (N=206)

88

Table 8: Description, Coding, Mean, and Standard Deviation of
Variables Used in the Study

89

Table 9: Zero-Inflated Poisson Regression Predicting Donation to
Protect against Biodiversity Loss, Entire Sample

91

Table 10: Zero-Inflated Poisson Regression Predicting Donation to
Protect against Biodiversity Loss, Christian Subsample

92

viii

LIST OF FIGURES

Figure 1: Analytical Model

94

ix

CHAPTER 1
INTRODUCTION
This dissertation explores relationships among religious belief and practice patterns, attitudes
about science, and environmental concern. Secularization theory posits that as the influence of
religious authority on everyday life decreases, society becomes more secularized (Chaves 1994;
Christiano, Swatos, and Kivisto 2008; Yamane 1997). Smith (1985) characterizes secularization
as the decrease of religious authority on public life, while arguing that religion still influences
private life. Apart from trying to define secularization, others argue that a decline in church
membership and religious activity is evidence of an increasingly secularized society (Berger
1967, Stark 1999). However, Peter Berger (2008:23), one of the key observers of secularization,
recently has pointed out, “Religion has not been declining. On the contrary, in much of the
world there has been a veritable explosion of religious faith.”
Over 80% of the U.S. public reports some religious affiliation (Pew Research Center 2013),
suggesting that religion plays at least some role in the lives of millions of Americans. Among
industrialized nations, the US is unique in this regard, thus making it an interesting case to
explore. Therefore, it is important to understand how religion influences attitudes about different
social issues, including science and the environment. This dissertation contributes to the
literature on religious belief and practice, environmental concern, and attitudes about science in
two ways. First, this research explores the influence of religious belief and commitment patterns
on attitudes about science. Second, the research studies the influence of religiously and
scientifically framed messages on two aspects of environmental concern: support for a proposed
policy addressing water rights and actual donations to protect against biodiversity loss.

1

Most of the existing literature examining religion as a predictor of attitudes about science
focuses narrowly on Christian religious affiliation (mostly Evangelical Protestantism) and
typically uses only single measures of religious behaviors (i.e., attendance at services or
frequency of prayer) to examine the relationship between religion and attitudes about science.
Investigators assume that those who attend church more often or pray with greater frequency, for
example, are more religious than those who perform these activities with lesser frequency. A
few patterns do emerge. In general, Christians are less supportive of science than non-Christians
and non-religious people. Evangelical Protestants are generally less supportive of science and
have more negative attitudes about science than do the non-religious, Mainstream Protestants,
and Catholics. In addition, people who are more religious or fundamentalist in their belief
systems appear to be less supportive of science.
Understanding the relationship between religion and science becomes even more important
in light of the need to solve problems that require an understanding of science, including
environmental problems. Most people tend to get information about science and environmental
problems from the media, which obtains information from original scientific sources and
interprets this information for the general public. However, religion can also interpret
information about science and the environment for adherents of a specific faith. Since the 1990s
there has been a supposed “greening” of Christianity in the United States, with organizations
such as the Evangelical Environmental Network, the Southern Baptist Environment, and the
Evangelical Climate Initiative, advocating for care of creation. However, recent research
indicates that advocacy for creation care at the organizational and elite levels of the green
Christian movement has not yet been effective in increasing concern for the environment within
rank-and-file Christians (Clements, McCright, and Xiao 2014).

2

Much of the existing literature about the relationship between religion and environmental
concern provides evidence of a negative relationship between religion and environmental
concern (e.g., Eckberg and Blocker 1989, 1996; Kanagy and Nelson 1995). Other studies
suggest a positive relationship (Boyd 1999; Guth et al. 1995; Kanagy and Willits 1993), and
some studies find no relationship at all (Hayes and Marangudakis 2000; Woodrum and Hoban
1994). Although the general public generally lacks understanding of scientific concepts (Dunlap
1998; Jenkins 2003), correct scientific knowledge of environmental problems is a key predictor
of intentions to participate in effective decision making about environmental issues (Bord,
O’Connor, and Fisher 2000). Given the general negative relationship between Christian
religious behavior and attitudes about science, as well as environmental concern, it is important
to determine how religious affiliation, commitment, and belief characteristics influence attitudes
about environmental problems that require scientific solutions.
The previous discussion leads to the following questions about how religion and messages
from religious authorities influence attitudes about science and the environment:
1. How do religious belief and commitment characteristics influence attitudes about
science in contemporary U.S. society?
2. Do religiously and scientifically framed messages differently influence specific facets
of environmental concern?
The dissertation directly addresses these questions in two ways. First, I analyze secondary
data from the General Social Survey to test hypotheses relevant to the first question. Second, I
conduct two experiments testing the effects of religiously and scientifically framed messages on
1) support for a proposed water use restriction policy, and 2) actual donation behavior to prevent

3

loss of biodiversity. Guided by these questions, I organized the dissertation into three empirical
chapters.
In the first essay (Chapter 2), I use nationally representative data from the 2010 General
Social Survey to test hypotheses about the influence of religious affiliation, beliefs, and behavior
on attitudes about science. I compare the influence of Christian and non-Christian affiliations,
and also compare attitudes about science among Christian affiliations: Mainline Protestants,
Evangelical Protestants, Black Protestants, and Catholics. I also use composite, rather than
single-item (e.g. church attendance or biblical literalism), indicators of religiosity and
fundamentalism to test their influence on attitudes about science. Finally, I test whether
Christian religiosity and fundamentalism moderate the relationship between Christian religious
affiliation and attitudes about science.
Recent research finds no significant greening among Christians in the U.S. approximately 20
years into a supposed “greening” of Christianity (Clements, McCright, and Xiao 2014). In
addition, previous research reports that Christians are less supportive of science than nonChristians and non-religious people (Ellison and Musick 1995; Evans 2002, 2012; Gauchat
2008). Despite these results, it remains an interesting empirical question whether religiously or
scientifically framed messages increase environmental concern about different environmental
problems among U.S. citizens. The second and third essays report the results of experiments that
test the influence of religiously and scientifically framed messages on two specific types of
environmental concern: support for a water use restriction policy (Chapter 3) and donations to
protect against biodiversity loss (Chapter 4). For each experiment, I recruited subjects using
Amazon Mechanical Turk, which allows “requesters” (such as myself) to solicit “workers” to
complete “Human Intelligence Tasks,” (HIT) (i.e., the experiments). Amazon Mechanical Turk

4

samples are closer to the U.S. general public than are typical university samples (Mason and Suri
2012; Paolacci, Chandler, and Ipeirotis 2010) and tend to be more diverse than typical Internet
samples (Buhrmester, Kwang and Gosling 2011). Amazon Mechanical Turk provides a quick,
inexpensive method to collect experimental data from a wide cross-section of the general public.
The second essay (Chapter 3) examines how religiously and scientifically framed messages
about water conservation influence attitudes about policies that restrict water use. Worldwide,
over seven billion people depend on one percent of water on earth that is available for use
(Shiklomanov 1993). In the summer of 2012, approximately 81% of the U.S. was classified as
abnormally dry by the United States Geological Survey, and 67% of the U.S. was in a moderate
to extreme drought (United States Drought Monitor 2013). As drought events increase
nationwide, it becomes increasingly important to understand how governments, municipal water
suppliers, and water conservation organizations can elicit support for different methods to
conserve water to meet our present and future needs. The second essay uses structural equation
modeling to test whether religiously or scientifically framed messages mediate the relationship
between various socio-demographic, religious, and environmental concern characteristics, and
support for a fictional water use restriction policy.
The third essay (Chapter 4) explores how religiously and scientifically framed messages
about biodiversity influence the choice to make donations to protect against biodiversity loss.
Over the last 100 years there have been over 100 well-documented extinctions worldwide,
mostly due to habitat loss and ecosystem destruction from human activities. In the United States
alone, it costs hundreds of millions of dollars per year to control invasive species and respond to
floods and fires that are becoming more extreme as ecosystem changes increase (Millennium
Ecosystems Assessment 2005). These costs are covered by taxes collected by governments, as

5

well as through donations to nongovernmental organizations that work to prevent further
biodiversity loss. In order to continue this work, it is important that governments and NGOs
understand what influences peoples’ willingness to pay or sacrifice for environmental protection.
Investigations about willingness to pay for environmental protection use indicators that measure
a person’s self-rated willingness to pay higher taxes, pay higher prices, and change their standard
of living to protect the environment. However, these measures typically ask people to rate their
hypothetical willingness to pay or sacrifice to deal with an environmental problem. The third
essay reports results of an experiment that is unique to the willingness to pay literature in that it
measures actual donation behavior to a nonprofit organization that operates to protect against
biodiversity loss.
Considered together, the three essays provide additional evidence about the role of religion in
influencing attitudes about science and environmental concern. While some people perceive a
conflict between religion and science, evidence suggests both negative and positive relationships
between religion and attitudes about science. However, there is a consistent negative
relationship between Christian religious affiliation and environmental concern. In addition, there
is a general lack of understanding about science by the US public which is troubling when
effective solutions to environmental problems require an understanding of science. Because
religion plays an important part in the daily lives of millions of Americans, and because of
possible negative relationships between religion and science, and religion and environmental
concern, it is important to examine the effects of religion and religious messages on matters
related to science and the environment. My research adds to the current literature by updating
evidence about the relationship between religion and attitudes about science using data from
2010. In addition, I also test the influence of religiously and scientifically framed messages on

6

environmental concern which allows me to make some observations about the conflicts between
religion and science, as well as a possible “greening” of Christianity.

7

CHAPTER 2
RELIGIOUS AFFILIATION, COMMITMENT AND BELIEF: IMPLICATONS FOR PUBLIC
ATTITUDES ABOUT SCIENCE

INTRODUCTION
Science is an integral part of contemporary U.S. society, as it helps drive our economy,
promotes technological developments, and gives us significant power to change our world in
noticeable ways. While the U.S. general public lacks knowledge of basic scientific facts (e.g.,
Dunlap 1998; Jenkins 2003; Miller 2004), it nevertheless does trust scientists who have relevant
expertise (e.g., Shapin 2007; VCU Center for Public Policy 2010). In fact, 80% of the general
public believes that science is essential to the country’s economy, healthcare system, and global
reputation (California Academy of Sciences 2009; Miller 2004). In spite of this support, 58% of
U.S. adults believe that scientific research does not pay enough attention to the moral values of
society, and 50% believe that scientific research has created as many problems for society as it
has solutions (VCU Center for Public Policy 2010). Further, some scientific issues (e.g.,
embryonic stem cell research, vaccines) and technological developments (e.g., genetically
modified foods) provoke significant opposition to science by the U.S. public.
Public understanding of science (PUS) scholarship aims to explain public understanding of,
involvement in, and trust in science. The deficit model posits that a lack of support for science is
due to a lack of understanding about science; if scientists can find a way to fill this ‘knowledge
deficit’, then support for science will increase (Lach and Stanford 2010; Maranta et al. 2003;
Powell and Colin 2008; Sturgis and Allum 2004). Others find mixed results as to whether
increased knowledge leads to positive attitudes about science in the general public (Allum et al.

8

2008; Bhaduri 2003; Critchly 2008; Miller 2004), among women (Simon 2010), and among
political conservatives (Gauchat 2012), specifically.
A more contemporary model holds that what is deficient is not the public’s knowledge, but
rather its trust in science, and in scientific experts specifically (Gauchat 2012; Lewenstein 1992;
Solomon 1993; Wynne 1992, 1993). PUS scholarship also provides some evidence that females
(Bak 2001; Baker 2012; Gauchat 2012; Hayes and Tariq 2000; Trankina 1993), conservatives
(Gauchat 2012), older adults (Bak 2001; Gauchat 2012), and non-whites (Gauchat 2008) report
lesser trust and confidence in science (and increased worry about the risks due to science) than
their respective counterparts. The relationships between these demographic and political
characteristics and attitudes about science are well documented, but less so are the relationships
between religion and attitudes about science. Current scholarship that investigates relationships
between religion and attitudes about science depends heavily upon single-item indicators of
religion—too rarely measuring the concept with multidimensional composite indicators. As
religion is a multi-faceted experience, a single measure of only one facet of religious practice
likely does not represent the full range of religious belief systems. Composite indicators of
religious life might better represent the range of religious beliefs and behaviors.
Because religion plays a vital role in the everyday life of over a hundred million U.S. citizens
and because the content of religious ideas and values may be challenged by the methods and
substantive knowledge of science, it is important to determine the extent of the conflict between
religion and science in this country. Some studies indicate that religious strength correlates
negatively with support for science funding (e.g., Brossard et al. 2009) and with the belief that
science does not pay enough attention to the morals of society (VCU Center for Public Policy
2010). Other studies indicate that biblical literalism, theological orthodoxy, and perceived

9

ubiquity of sin are associated with moral criticism of science (e.g., Baker 2012; Ellison and
Musick 1995; Nisbet and Goidel 2007).
Most of the existing PUS literature examining religion as a predictor of attitudes about
science focuses narrowly on Christian religious affiliation (mostly Evangelical Protestantism)
and typically uses only single measures of religious behaviors (i.e., attendance at services or
frequency of prayer) to examine the relationship between religion and science. Investigators
assume that those who attend church more often or pray with greater frequency, for example, are
more religious than those who perform these activities with lesser frequency. Unfortunately, we
don’t know if these single item measures reflect the same characteristic (Evans 2013). For
instance, people may pray several times per day, but never attend religious services. By one
measure they would be very religious, but by the other, not religious at all. Religiosity and
fundamentalism indicators comprised of several individual measures may provide better
measures of these concepts.
Investigators generally consider affiliation, religiosity, and fundamentalism separately in
their analyses. However, they infer that those with a specific affiliation who perform more
religious behaviors or hold more fundamentalist beliefs than others are more faithful and will
follow the tenets of their faith with greater fervor. This suggests that religiosity and
fundamentalism may influence the strength or direction of affiliation on attitudes about science.
To my knowledge, no studies investigate if religious behaviors and beliefs moderate
denominational affiliation to influence attitudes about science. By addressing the preceding
limitations, this study contributes to the scholarship that addresses this question: How do
religious belief and commitment characteristics influence attitudes about science in
contemporary U.S. society?

10

I use nationally representative data from the 2010 General Social Survey to test hypotheses
about the influence of religious affiliation, beliefs, and behavior on attitudes about science. This
study makes three contributions to the literature. First, I move away from limited considerations
of religious affiliation (e.g. only Evangelical Protestantism) to examine how attitudes about
science are influenced by a wider range of religious affiliation. Specifically, I compare the
influence of Christian and non-Christian affiliations and—within Christianity—compare the
influence of Mainline Protestant, Evangelical Protestant, Black Protestant, and Catholic
affiliations. Second, I include more comprehensive measures of religiosity and religious
fundamentalism than typically are utilized in the literature. Most studies use single-item
measures of religiosity (e.g., attendance at religious services) and fundamentalism (e.g., belief in
the Bible as the literal word of God). As is the nature of most large data sets that poll the U.S.
public, measures of religious belief and commitment focus on Christian religious beliefs and
behaviors. However, I employ composite, rather than single-item, indicators of these
characteristics. Third, I test whether Christian religiosity and fundamentalism moderate the
relationship between Christian religious affiliation and attitudes about science, by examining the
performance of interaction terms in my analytical models.
In the next section I review the literature on the relationship between science and religion,
focusing first on religious affiliation and then on religious strength, activity, and beliefs. I follow
this by developing specific hypotheses for testing and by describing my analytical model. After
that I detail my dataset and methods, before presenting and discussing my results and ending
with suggestions for future research.

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RELIGION AND ATTITUDES ABOUT SCIENCE
Scholars cite many examples as evidence of conflict between religion and science. Among
these are the harsh treatment of Galileo and Copernicus by the Catholic Church, the response to
Darwin’s The Origin of Species by Samuel Wilberforce (Bishop of Oxford) as “contrary to
scripture and unsupported by theology” (Eister 1978: 352), and Thomas Aquinas’s thought of
“Eternal law” as “existing in the Mind of God and governing the whole universe” (Eister 1978:
350). Over the last 100 years, social scientists have contemplated this conflict. Max Weber
(1946 [1918]) alludes to a tension between religion and the world, explaining that science is not
useful for explaining the fundamental questions of life such as why we are here and how we
should live our lives. Robert Merton (1938) identifies organized religion as an institution
inherently in conflict with the organized skepticism of science, as the former demands
unqualified faith—something that science fundamentally challenges.
In recent decades several scholars have investigated the relationship between religion and
science in the U.S. (see e.g., Campbell and Curtis 1996; Eister 1978; Evans 2002; Evans and
Evans 2008) as well as in other countries (Buckser 1996; Campbell and Curtis 1996). This
literature on the relationship between religion and attitudes about science focuses on three main
aspects of religion: affiliation (what religion people are), religiosity (how strong their religious
belief or commitment is, usually measured as attendance at church services or frequency of
prayer) and fundamentalism (adherence to orthodox beliefs, usually represented by belief in a
literal interpretation of the bible).
Studies examining the relationship between religious affiliation and attitudes about science
generally investigate Christian religions and mainly focus on Evangelical Protestant affiliation
(Binder 2007; Ellison and Musick 1995; Evans 2002; Gauchat 2008). Others study the influence

12

of faith traditions such as Mainline Protestantism, Black Protestantism, Catholicism, and
Judaism, as well as people with no religious affiliation (Evans 2002, 2012; Freeman and Houston
2011; Hayes and Tariq 2000; Hochschild, Crabill, and Sen 2012; Nisbet 2005; Scheitle 2005).
Some studies find that Evangelical Protestantism is associated with negative perceptions of
science in general (e.g. Ellison and Musick 1995; Gauchat 2008). These studies show that
Evangelical Protestant affiliation is related to beliefs that science pries into inappropriate areas
and impairs people’s ideas of right and wrong (Ellison and Musick 1995), that we believe too
much in science and not enough in faith, that changes caused by science make things worse, and
that science does more harm than good (Gauchat 2008).
Other studies report opposition by Evangelical Protestants to specific types of science-related
issues (Binder 2007; Evans 2002). Evans (2002:756) provides evidence that Evangelical
Protestants are more opposed to unrestricted research on human cloning than other Protestants,
and Catholics, likely due to a view that “cloning usurps God’s role.” In addition, most of the
opposition to teaching evolution in public schools, as well as support for including intelligent
design as a scientific theory, comes from Evangelical Protestant traditions (Binder 2007).
Further, Freeman and Houston (2011) find that compared to Jews and Mainline and Black
Protestants, Evangelical Protestants report less support for federal funding for scientific research,
especially stem cell research. While the influence of Evangelical Protestantism is fairly
consistent across studies, Evans (2013) finds no association between conservative Protestant
affiliation and confidence in the scientific institution. However, this ethnographic study does not
define which Protestant affiliations are conservative.
Another group of studies investigates the influence of other Christian affiliations such as
Catholicism (Evans 2002; Hayes and Tariq 2000; Nisbet 2005; Scheitle 2005), Mainline

13

Protestantism (Freeman and Houston 2011), and Black Protestantism (Freeman and Houston
2011) on attitudes about science. A few studies investigate the influence of non-Christian
affiliation (Freeman and Houston 2011; Scheitle 2005) and no religious affiliation (Evans 2012;
Hochschild, Crabill, and Sen 2012), on attitudes about science. Hayes and Tariq (2000) find that
Catholics have more positive attitudes about science than do non-Catholics in the U.S., but this is
not observed in other Anglo countries. Evans (2002) finds that Catholics show greater support
for unrestricted research on human cloning than Evangelical Protestants, but Nisbet (2005)
reports that Catholics show greater opposition to stem cell research compared to Protestant
traditions. Scheitle (2005) reports no difference in optimism about biotechnology among
Catholics, Jews, and Protestants, while members of a group of other religions (e.g., Hindu,
Buddhist, Mormons, among others) are more optimistic about biotechnology than are
Protestants. Freeman and Houston (2011) find that Mainline Protestants and Catholics believe
we spend too much on scientific research compared to non-religious people, but there is no
difference in support among Black Protestants, Evangelical Protestants, Jews, and non-religious
people. In an ethnographic study, Evans (2012) finds no difference in support for science
between religious people (regardless of tradition) and non-religious people. Finally, Hochschild,
Crabill, and Sen (2012) find that religious affiliation has no influence on optimism about science
and technology.
The above group of studies has several limitations. First, with the exception of Ellison and
Musick (1995) and Evans (2002), these studies only include religion as a statistical control in
their analytical models. Thus, they spend minimal time analyzing the relationship between
religious affiliation and attitudes about science. Some of these studies use data sets from the late
1980s or 1990s (Ellison and Musick 1995; Gauchat 2008; Scheitle 2005), so they have limited

14

efficacy for explaining more recent patterns in the relationship between science and religion.
Other studies use interview and media data (Binder 2007; Evans 2012) that is difficult to
quantitatively analyze. Finally, there is a wide diversity in operationalizing attitudes about
science. Some studies ask about attitudes towards science funding (Freeman and Houston 2011)
or the compatibility of science and faith and harm to society from science (e.g. Ellison and
Musick 1995; Gauchat 2008). Still others focus on attitudes about specific types of science such
as reproductive cloning (Evans 2002) or embryonic stem cell research (Nisbet 2005).
Another group of studies examines the relationship between religiosity and attitudes about
science. One limitation here is the use of a few single-item indicators to measure religiosity,
including attendance at religious services, the perception that religion is a guide to daily decision
making, and self-rated strength of beliefs. These measures suggest that religiosity (especially
attendance at religious services) negatively influences attitudes about science (e.g. Brossard et al
2009; Ellison and Musick 1995; Gauchat 2008, 2011, 2012). However, as described earlier,
single-item indicators may not effectively measure a multi-faceted construct such as religiosity in
the same way (Evans 2013).
One set of studies operationalizes religiosity as perceptions that religion is a guide to daily
decision making. These studies report a negative relationship between those who report that
religion has a great deal of influence on their daily decision making and support for science
funding for general nanotechnology, likely due to the influence of strong religious belief systems
(Brossard et al. 2009) or concerns that science and technology tamper “with nature by playing
God” (Ho, Scheufele and Corely (2010:2709). Nisbet and Goidel (2007) find that people who
report that religion has a great deal of influence on their daily life have negative opinions of
embryonic stem cell research and therapeutic cloning.

15

Another group of studies that examines the relationship between religiosity and attitudes
about science includes measures such as frequency of prayer and attendance at religious services.
These studies find that prayer and attendance at religious services are negatively related to
attitudes about science (Gauchat 2008; Sturgis and Allum 2004) and confidence in science
(Gauchat 2011, 2012). However, when people understand that scientific activities have well
established methods and review processes, then this relationship disappears (Gauchat 2011).
Increased attendance at religious services is also related to a lack of confidence in political
institutions, suggesting that increased religiosity is related to a general lack of confidence in
social institutions (Gauchat 2012). Finally, Freeman and Houston (2011) note a correlation
between attendance and decreased support for government funding of stem cell research. In
contrast, other studies find that attendance is not related to skepticism about genomic science
(Hochschild, Crabill, and Sen 2012), optimism about biotechnology (Scheitle 2005), or support
for science funding (Freeman and Houston 2011).
There is some evidence to suggest that religiosity characteristics moderate the relationship
between religious affiliation and attitudes about science. Among people who frequently attend
church, there is a negative relationship between Evangelical Protestantism and opinions about
therapeutic cloning, which is not observed in frequent church attending Catholics or liberal
Protestants (Evans 2002). In addition, Evans (2013) also suggests that frequent church
attendance and biblical literalism together moderate the relationship between Protestantism and
confidence in scientific institutions. However, frequent church attendance alone does not
moderate the respective relationships between Evangelical Protestantism, Mainline
Protestantism, Black Protestantism, and Catholicism, and confidence in scientific institutions.

16

A final group of studies considers the influence of fundamentalist religious beliefs on
attitudes about science (e.g. Baker 2012; Ellison and Musick 1995, Evans 2013; Freeman and
Houston 2011; Nisbet and Goidel 2007; Scheitle 2005). Most operationalize fundamentalism as
the belief that the Bible is the literal word of God. Such studies find that biblical literalism
negatively influences attitudes about science (Ellison and Musick 1995, Nisbet and Goidel
2007), confidence in science as an institution (Evans 2013), and support for federal science
funding and stem cell research funding more specifically (Freeman and Houston 2011). Further,
biblical literalism is positively associated with the belief that there is a conflict between science
and religion (Baker 2012).
One study suggests that fundamentalist religious beliefs may moderate the relationship
between religious affiliation and attitudes about science. Evans (2012) finds that the only
participants in his ethnographic study who do not support science are Protestants who report
fundamentalist religious beliefs. This suggests that it may be worthwhile to investigate whether
fundamentalism moderates the relationship between religious affiliation and attitudes about
science.
One limitation of existing studies that include measures of religiosity and fundamentalism is
that they generally use single item indicators to measure religiosity and fundamentalism when
multidimensional composite indicators may better measure these concepts. Religious belief is a
multifaceted construct and one measure cannot reliably discern more religious people from less
religious people (Evans 2012). Measures of religiosity such as frequency of church attendance
and self-rated religious strength do not provide the same information about religiosity. Inclusion
of disparate religiosity measures in separate studies makes it difficult to make conclusions about
the influence of religiosity on attitudes about science. Similarly, the use of one main measure of

17

fundamentalism ignores the influence of other facets of fundamental beliefs such as being “born
again”, or behaviors such as trying to get others to accept Jesus Christ as their savior. Different
denominations within Christianity have different patterns of church attendance and beliefs about
the Bible (Evans 2013) that may differently influence attitudes about science.
In summary, Evangelical Protestants are generally less supportive of science and have more
negative attitudes about science than do the non-religious, Mainstream Protestants, and
Catholics. In addition, people who are more religious and fundamentalist in their belief systems
appear to be less supportive of science. These results suggest several hypotheses for testing.
HYPOTHESES
Following previous studies that report negative attitudes about science by adherents of
Christian denominations (e.g. Binder 2007; Ellison and Musick 1995; Evans 2002, 2012;
Gauchat 2008), I expect that those who report no religious affiliation have more positive
attitudes about science than those who report a Christian religious affiliation (Hypothesis 1).
Much of the existing literature only examines the relationship between the Christian faith and
attitudes about science. Few studies examine the relationship between non-Christian religions
and attitudes about science, yet this is an important comparison. Because of the negative
relationship between Christian affiliation and attitudes about science (e.g. Ellison and Musick
1995, Evans 2002, Freeman and Houston 2011), and because of a recent trend of U.S. Christian
opposition to stem cell research, reproductive cloning, climate change, and teaching evolution, I
expect that non-Christians have more positive attitudes about science than Christians (H2).
As described earlier, some evidence suggests that attitudes about science vary across
Christian denominations. While Catholics have more positive attitudes about science than nonCatholics in the U.S. (Hayes and Tariq 2000), they may not support science funding (Freeman

18

and Houston 2011) and are opposed to stem cell research (Nisbet 2005). Mainline Protestants
are generally as supportive of science as the non-religious, while Black Protestants have similar
attitudes as Evangelical Protestants. Therefore, I expect that Mainline Protestants have more
positive attitudes about science than Catholics, Evangelical Protestants, and Black Protestants
(H3).
Many studies find a negative relationship between religiosity (e.g. Brossard et al. 2009;
Gauchat 2008 2011, 2012; Nisbet and Goidel 2007; Sturgis and Allum 2004) or fundamentalism
(e.g. Baker 2012; Ellison and Musick 1995, Evans 2013; Scheitle 2005) and attitudes about
science. Almost all of these studies consider religiosity or fundamentalism in the context of
Christianity, generally Evangelical Protestantism. Items that commonly measure religiosity and
fundamentalism are based on Christian belief or practice. For instance, attendance at a religious
service as a measure of religiosity is inadequate for some non-Christians who do not attend
services as part of their faith, and non-religious people who generally do not attend at all.
Similarly, fundamentalism is often times measured by belief in the Bible as the literal word of
God, or reporting that a person has tried to get another to accept Jesus Christ as their savior.
These measures are clearly inadequate for non-Christians. Thus, I only examine the effects of
religiosity and fundamentalism among Christians. Some studies find that prayer and attendance
at religious services are negatively related to attitudes about science (Gauchat 2008; Sturgis and
Allum 2004) and confidence in science (Gauchat 2011, 2012). Therefore, I expect that
religiosity negatively relates to attitudes about science among Christians (H4). Further, Ellison
and Musick (1995) and Nisbet and Goidel (2007) report that biblical literalism is negatively
associated with attitudes about science. Therefore, I expect that fundamentalism negatively
relates to attitudes about science among Christians (H5).

19

Finally, some studies suggest that religiosity and fundamentalism moderate the relationship
between Evangelical Protestant affiliation and attitudes toward science (Evans 2012, Evans
2013). Therefore, I expect that religiosity moderates the relationship between Evangelical
Protestant religious affiliation and attitudes about science (H6) and that fundamentalism
moderates the relationship between Evangelical Protestant religious affiliation and attitudes
about science (H7). In the next section, I discuss the dataset and describe the selected variables
and the statistical techniques I use to analyze the data.
DATA AND METHODS
I use data from the 2010 General Social Survey (GSS) (Smith et al. 2011) to test my
hypotheses. The GSS is a survey of the American public that is conducted every two years to
collect demographic information of U.S. citizens as well as elicit public opinion about
government, daily life, economics, and religion, among other things. I use the 2010 edition of
the GSS because it includes several variables related to opinions about science, theological
orientation, religious affiliation, and socio-demographic information. Table 1 presents
information about all variables used for this study.
Dependent Variables: Attitudes about Science Indicators
I use four indicators of attitudes about science as dependent variables in my models. Each of
the four asks respondents the extent to which they disagree or agree with a statement about
science. One is an indicator of support for scientific funding: “Even if it brings no immediate
benefits, scientific research that advances the frontiers of knowledge is necessary and should be
supported by the federal government.” The other three are indicators of general attitudes toward
science: “Overall, modern science does more harm than good,” “We believe too often in science,

20

and not enough in feelings and faith,” and “One of the troubles with science is that it makes our
way of life change too fast.”
Independent Variables
Religious Affiliation: I classified religious affiliation following the recommendations of
Steensland et al. (2000) using the following GSS items: DENOM – Specific Denomination,
OTHER – Other Protestant Denomination, and RELIG – Respondent’s Religious Preference.
Following Steensland et al. (2000) I recoded these variables to the following dummy variables:
No Religion, Christians, Non-Christian, Catholic, Black Protestant, Evangelical Protestant, and
Mainline Protestant to allow for comparisons as suggested by my hypotheses. Catholics and
Protestants are the majority of Christian religious people in the U.S. Smaller groups of Christian
denominations (e.g., Eastern Orthodox, Latter Day Saints, and Jehovah’s Witnesses, among
others) are represented in the GSS, but because of their small numbers, I exclude them from this
study.
Other Religion Indicators: Past research examining the relationship between religion and
attitudes about science focuses on the levels of respondents’ religiosity and fundamentalism.
The 2010 GSS has several items that I use to create indicators of religiosity and fundamentalism.
For religiosity and fundamentalism, I used exploratory factor analysis and Cronbach’s alpha
reliability test to form composite indicators of each. In each case, items loaded onto one factor
and Cronbach’s alpha tests indicate good reliability. I used exploratory factor score weights to
form composite indicators of religiosity and fundamentalism.
The religiosity indicator is created from seven GSS items (factor loadings between .68 and
.82; Cronbach’s α = .85): how often you attend religious services, the strength of your belief in
God, how often you pray, how often you take part in the activities and organizations of a church

21

or place of worship other than attending service , the strength of your religious group
identification, how hard you try to carry your religious beliefs over into all other dealings in life,
and how religious you consider yourself. Due to the varying number of response categories for
each item (i.e., frequency of attendance is a nine-point scale, while prayer is a six-point scale), I
first standardized each variable prior to creating each composite measure. For purposes of this
analysis higher scores indicate increased levels of religiosity.
The fundamentalism indicator is created from four GSS items (factor loadings between .70
and .80; Cronbach’s α = .76): the strength of your belief in the literal interpretation of the Bible,
the liberalism or fundamentalism of your religion, whether or not you have been “born again,”
and whether or not you have ever tried to encourage someone to believe in Jesus Christ or accept
Jesus Christ as his or her savior. Again, higher scores indicate a respondent who is more
fundamentalist in his or her belief system.
Political and Socio-Demographic Control Variables: I use the following political indicators
in my analyses: political ideology (1=“extremely conservative” to 7=“extremely liberal”) and
party identification (1=“strong Republican” to 7=“strong Democrat”). Finally, I use the
following socio-demographic variables as controls: gender (female), race (white), age in years,
number of years of education, and family income.
Statistical Analyses
I conducted a series of OLS regression models to predict values on each of the four attitudes
about science indicators. First, I ran models to compare the attitudes of non-religious
respondents, Christians, and non-Christians (H1 and H2). Then, I ran a second set of OLS
regressions to test within-Christian variation in attitudes about science (H3). I included
religiosity and fundamentalism in each of my models to test the influence of each on attitudes

22

about science (H4 and H5). In subsequent models in include only Evangelical Protestant
affiliation, and add interaction terms to test the moderating effects of religiosity and
fundamentalism (H6 and H7). I created interaction terms by first centering the affiliation
dummy variable and then multiplying with the appropriate centered religiosity or
fundamentalism composite indicator.
RESULTS AND DISCUSSION
Table 2 presents the percentages of different religious groups in the U.S. reporting selected
attitudes about science. The first column shows that the U.S. public overall has generally
positive attitudes about science with one exception. 87% of Americans agree that scientific
research is necessary and should be supported by the federal government, 62.3% of Americans
disagrees that modern science does more harm than good, and 51.5% of Americans disagrees
that science makes our way of life change too fast. However, only 30.6% of Americans
disagrees with the statement that we believe too much in science and not enough in faith. Of
note, the latter is the only item that asks respondents to directly compare science and faith.
The next three columns in Table 2 present attitudes about science for non-religious,
Christian, and non-Christian respondents. The results in Table 2 provide preliminary evidence
supporting the first two hypotheses, which expect that those who report no religious affiliation
(H1) and non-Christians (H2) have more positive attitudes about science than those who report a
Christian religious affiliation. Significantly greater percentages of those reporting no religious
affiliation than self-identified Christians report positive attitudes about science, except on the
belief about federal government support of science. Also, significantly greater percentages of
non-Christians than Christians report positive attitudes about science, except on the belief that
science makes our way of life change too fast.

23

The final four columns in Table 2 report attitudes about science for different Christian
denominations. These results provide preliminary evidence partially supporting H3, which
expects that Mainline Protestants report more positive attitudes about science than do
Evangelical Protestants, Black Protestants, and Catholics. Greater percentages of Mainline
Protestants than all others disagree (a) that modern science does more harm than good and (b)
that we believe too much in science and not enough in faith. A greater percentage of Mainline
Protestants than Evangelical Protestants believe that scientific research is necessary and should
be supported by the federal government, but the percentage of Mainline Protestants does not
differ from those of Black Protestants or Catholics. Finally, there is no difference among
Christian denominations in disagreement with the idea that science makes our way of life change
too fast.
Next I discuss the results of models that provide a more rigorous test of all hypotheses.
Table 3 presents the results of models for each of the four attitudes about science indicators for
the entire sample. The models confirm the preliminary evidence in Table 2 and provide support
for the first two hypotheses, which expect that those who report no religious affiliation (H1) and
non-Christians (H2) have more positive attitudes about science than do Christians. Compared to
Christians, non-Christians are more likely to agree that the federal government should support
science. Non-religious respondents are more likely to disagree that science makes our way of
life change to fast. Also, both non-Christians and non-religious people are more likely than
Christians to disagree that science does more harm than good and that we believe too much in
science and not enough in faith. These results are consistent with those of previous studies that
self-identified Christians tend to report more negative attitudes about science than others (e.g.,

24

Binder 2007; Ellison and Musick 1995; Evans 2002, 2012; Freeman and Houston 2011; Gauchat
2008).
The effects of the remaining variables in these models also deserve attention. Political
orientation (party identification and political ideology) has an influence on the first three
attitudes about science. As expected, self-identified Democrats and liberals report more positive
attitudes about science than their Republican and conservative counterparts. Women are more
wary of science than are men in the second model. Also, whites, the more highly educated, and
those making higher income report more positive attitudes about science than their respective
counterparts. Age has no influence on attitudes about science in these models. These results
align with previous studies that find that females (Bak 2001; Baker 2012; Gauchat 2012; Hayes
and Tariq 2000; Trankina 1993), conservatives (Gauchat 2012), and non-whites (Gauchat 2008)
report more negative attitudes about science than their respective counterparts.
Table 4 presents the results of OLS regression models for each of the four attitudes about
science indicators for the Christian subsample. These models also include religiosity and
fundamentalism as predictors. Overall, the religion variables are not strong or robust predictors
of attitudes about science. Among Christians, respondents’ attitudes about science are largely
independent of their denomination, religiosity, and fundamentalism.
H3 predicts that Mainline Protestants have more positive attitudes about science than
Evangelical Protestants, Black Protestants, and Catholics. The results in Table 4 do not provide
definitive support for this hypothesis. When controlling for religiosity and fundamentalism, only
one of the affiliation dummy variables has a statistically significant effect on only one attitude
toward science indicator. Compared to Mainline Protestants, Catholics more strongly believe
that science does more harm than good. Other than this exception, attitudes toward science are

25

largely the same across Christian denomination. These results contradict most literature that
finds a negative relationship between Evangelical Protestant (e.g. Binder 2007; Ellison and
Musick 1995; Evans 2002; Gauchat 2008), Mainline Protestant (Nisbet 2005), and Catholic
(Freeman and Houston 2011; Nisbet 2005) affiliations, and attitudes about science. Most of
these studies use data from the 1990s and early 2000s and it is possible that recent data used in
this study reflects changing attitudes about science over the last 20 years. However, previous
studies use a wide range of measures to reflect attitudes about science, including specific types of
science (e.g. therapeutic cloning or genomic science), as well as some of the indicators I use (e.g.
support for science funding or perceptions about harm from science). While it is possible that
attitudes about science have changed over the last twenty years, definitive conclusions cannot be
made without longitudinal data using comparable measures of attitudes.
The next two hypotheses predict that religiosity (H4) and fundamentalism (H5) relate
negatively to attitudes about science among Christians. The results of models 2, 6, 10, and 14 in
Table 4 offer minimal support for these hypotheses. These two variables only have a statistically
significant effect on one attitude about science indicator: that we believe too much in science and
not enough in faith. Both religiosity and fundamentalism are negatively related to this indicator.
That is, more religious and more fundamentalist Christians are more likely to agree that we
believe too much in science and not enough in faith than their less religious and fundamentalist
counterparts. While this single finding is consistent with the results of earlier studies that found
the same (e.g., Baker 2012; Brossard et al. 2009; Ellison and Musick 1995; Evans 2013;
Freeman and Houston 2011; Gauchat 2008, 2011, 2012; Nisbet and Goidel 2007; Scheitle 2005),
the remaining three models in Table 4 offer no support for H4 or H5.

26

Finally, the results in Table 4 also bear upon the last two hypotheses, which expect that
religiosity (H6) and fundamentalism (H7) moderate the relationship between Evangelical
Protestantism and attitudes about science. While Evans (2002, 2013) and Evans (2012) both
suggested such an effect in earlier research, the performance of the interaction terms in Table 4
indicate that religiosity and fundamentalism do not moderate the relationship between
Evangelical Protestantism and attitudes about science. Thus, not only do religiosity and
fundamentalism generally not have a direct effect on attitudes about science, there also is no
evidence that these two variables influence the relationship between religious affiliation and
attitudes about science. Additional OLS models with religiosity and fundamentalism interaction
terms (not shown here) also found no moderating effect of religiosity and fundamentalism on the
relationship between the other Christian denominations and attitudes about science.
CONCLUSION
This study was designed to determine how religious belief and commitment characteristics
influence attitudes about science. Despite proclamations of an increasingly secularized society,
religion continues to be a vital part of life for a large segment of U.S. society. Scientific
knowledge and practice may challenge the content of religious ideas and values, so it is
important to determine if there is a conflict between religion and science in this country. The
results of this study provide some evidence that Christians in general have more negative
attitudes about science than do non-Christians and non-religious people. However, there is very
little evidence to suggest differences in attitudes about science across Christian denominations.
In addition, composite measures of religiosity and fundamentalism included in this study have
little influence on attitudes about science. Finally, religiosity and fundamentalism do not
moderate the relationship between Evangelical Protestant affiliation, or any other affiliation, and

27

attitudes about science. These results suggest that some observers’ claims about major conflict
between science and religion may not accurately describe the U.S. general public—at least with
regard to the general attitudes about science examined here.
This study has a few limitations. The first one is the reduced sample size of the 2010 GSS,
since the science items used in this study were administered to only 31% (n=1,519) to 66%
(3,234) of respondents. In addition, not all subjects were asked each of science items, and not all
subjects were asked all religion items. The split sample design of the GSS substantially reduced
the sample size of those respondents who were asked all survey items relevant for this study with
final sample sizes ranging from approximately 600 to 1,200. Second, the nationally
representative GSS sample contained only a small percentage of non-Christians. There are not
enough respondents affiliated with non-Christian religions (e.g., Hindus, Muslims, Jews,
Buddhists, etc.) to analyze variation across non-Christian religions. Thus, I pooled respondents
from these non-Christian religions into a single dummy variable of “non-Christian.” Third, the
single-item attitude about science indicators suffer from limited reliability and validity. A few
items not only measure attitudes about science but also attitudes about aspects of other social
institutions: e.g., the role of the federal government in one indicator and religious faith in another
indicator. Further, a third item includes a vague referent (“it makes our way of life change too
fast”) that may not be interpreted as uniformly negative by most respondents.
The above limitations lead to some suggestions for future research. First, future research
should oversample respondents from non-Christian religions to be able to statistically examine
possible differences in attitudes about science among these various faiths. Another option would
be to administer surveys to targeted samples of non-Christians. Also, field-based research of

28

non-Christian subjects would allow for deeper understanding of how adherents to these different
faiths perceive and understand science.
Second, future research should strive toward increasing the reliability and validity of our
measures of attitudes about science. The measures used in this study only refer to a general
concept of science. We do not know what the public thinks of when they think of science (e.g.,
biology, chemistry, physics). Nor do we know if they make distinctions between the social and
biophysical sciences, or between the goals of more basic science that adds to a body of
knowledge and more applied science that contributes to economic development. Future
measures of attitudes about science should be developed to distinguish between different types
and goals of science.
Third, future work also should strive to utilize higher quality measures of religiosity and
fundamentalism that do not focus narrowly on Christian practices. Such alternate measures
would allow for improved modeling of beliefs and behaviors in non-Christian samples and
among a range of Christian denominations that may differ in requirements about attending
services or belief in the Bible as the literal Word of God. One measure is the Spirituality
Experience Index-Revised (SEI-R) (Genia 1997) that was conceived as a scale to tap into
spiritual feelings apart from religiosity measures such as church attendance or denomination.
The SEI-R measures faith, spiritual journey, and spiritual connectedness without imposing a
particular faith or belief system as part of the questions (Genia 1997). Versions of this index
have been used extensively in healthcare research (Dein 2005; Kroll and Erikson 2002; Tate and
Forchheimer 2002).
Fourth, most existing research on religion and attitudes about science uses single-item
indicators of religiosity and fundamentalism. Religiosity is typically measured by attendance at

29

religious services (e.g., Brossard et al, 2009; Ellison and Musick 1995; Gauchat 2008, 2011,
2012), while fundamentalism is measured by the belief in the Bible as the literal word of God
(e.g., Baker 2012; Ellison and Musick 1995; Nisbet and Goidel 2007). This study used
composite indicators for religiosity and fundamentalism, each of which included its respective
single item referenced above. The composite indicators in this study did not contribute much to
attitudes about science. Future research should continue to examine composite measures of
religiosity and fundamentalism, and also compare the performance of other single-item
religiosity and fundamentalism indicators on attitudes about science.

30

CHAPTER 3
THE INFLUENCE OF RELIGIOUSLY AND SCIENTIFICALLY FRAMED MESSAGES ON
AGREEMENT WITH WATER USE RESTRICTIONS

INTRODUCTION
Three percent of all water on earth is fresh water, but two percent is locked in glacial ice.
Approximately one percent of water on earth is available for use (Shiklomanov 1993), and over
seven billion people need this water to live. At the peak of the 2012 drought in the United
States, approximately 81% of the U.S. was classified as abnormally dry by the United States
Geological Survey, and 67% of the U.S. was in a moderate to extreme drought. As of August
2013, conditions had improved but nearly 50% of the U.S. still remained in a moderate to
extreme drought (United States Drought Monitor 2013).
Water policy issues have increased in salience in recent years. Municipal water suppliers in
drought-stricken areas in Texas, Nebraska, and Oklahoma continue to impose water use
restrictions. Meanwhile, cities such as Durham, North Carolina, and New York City have passed
water usage laws that will be implemented in the event of future droughts. The media continues
to publish stories of lost crops due to water shortages (Carlton 2013; Wines 2013). In addition,
government agencies such as the U.S. Environmental Protection Agency (U.S. Water Alliance
2013) and the Bureau of Reclamation’s WaterSMART Program (U.S Department of the Interior
2013) promote water conservation to protect the environment and to insure adequate water
supplies. Farm groups such as the American Farm Bureau Federation promote water
conservation for agricultural use (Harke 2008). Environmental nonprofit organizations advocate
for responsible development, management, and use of water (National Ground Water

31

Association 2013), as well as safe water and sanitation in the U.S. and around the world
(Water.org 2013). Many of these organizations call for the public to conserve water, typically
using messages grounded in scientific language to make the case for water conservation.
Although less well known, some religious organizations use messages based on religious
teachings and moral tenets to promote water conservation (e.g., Chamberlain 2008; Chuvieco
2012; Palmer 2010). Some evidence suggests that religious people have negative attitudes about
science (Campbell and Curtis 1996; Eister 1978; Evans 2002; Evans and Evans 2008) and are
less influenced by scientific arguments than scientific communicators expect (Brossard et al.
2009; Ho, Brossard and Scheufele 2007). Given that approximately 80% of the U.S. public
reports some religious affiliation (Pew Research Center 2013), it is important to investigate the
performance of religious and scientific messages for promoting water conservation. In this
study, I report the results of an experiment that examines how messages about water
conservation by scientific and religious leaders influence attitudes about policies that restrict
water use.
RELIGION, SCIENCE, AND ENVIRONMENTAL CONCERN
Dunlap and Jones (2002:485) define environmental concern as “the degree to which people
are aware of problems regarding the environment and support efforts to solve them and/or
indicate a willingness to contribute personally to their solution.” People may demonstrate
concern for environmental problems in many different ways: using less water or driving less,
donating money to environmental organizations, or supporting policy recommendations or
taxation programs to protect the environment. Many studies investigate the influence of social,
demographic, and political factors, as well as value orientations, on environmental concern.
Socio-demographic and political characteristics only explain a small amount of variation in

32

environmental concern, while value orientations typically explain much more. People who
report high levels of environmental concern are more likely to be female, younger, highly
educated, and identify as liberals and/or Democrats (e.g., Dunlap and Jones 2002; Dunlap, Xiao,
and McCright 2001; Xiao and McCright 2012). Much of the values research suggests that
empathy (Berenguer 2007), altruism (Dietz, Fitzgerald, and Shwom 2005; Stern, Dietz, Abel,
Guagnano, and Kalof 1999; Schultz 2001; Stern, Dietz, Kalof, and Guagnano 1995), and other
self-transcendent values (e.g., benevolence, pro-environmental values) (Dietz, Fitzgerald, and
Shwom 2005; Stern, Dietz, Abel, Guagnano, and Kalof 1999) are important drivers of
environmental concern.
A few studies find that proximity to, or experience with, environmental hazards is positively
associated with environmental concern (e.g., Brody, Zahran, Vedlitz and Grover 2008; Spence,
Poortinga, Butler, and Pidgeon 2011), while others do not (e.g., Whitmarsh 2008; Zahran, Brody,
Grover, and Vedlitz 2006). Spence, Poortinga, Butler and Pigeon (2011) report that experience
with previous flooding is positively associated with concern about climate change, while
Whitmarsh (2008) reports no relationship between flood experiences and climate change
concern. Similarly, Brody, Zahran, Vedlitz, and Grover (2008) find that living in coastal regions
is positively associated with concern about climate change, while Zahran, Brody, Grover, and
Vedlitz (2006) report a negative relationship between living in coastal regions and support for
climate change policies. Thus, this group of studies is equivocal about the association of
proximity to local environmental problems and environmental concern, even though none of the
studies consider drought.
The influence of socio-demographic factors and value orientations on environmental concern
is well documented (e.g., Dunlap and Jones 2002; Dietz, Fitzgerald, and Shwom 2005). Socio-

33

demographic factors account for only a small amount of variation in environmental concern, and
while value measures do add explanatory power to models, it is important to investigate the
influence of other likely predictors of environmental concern. Next I discuss how religion and
science influence environmental concern.
Religion, Scientific Knowledge and Environmental Concern
Most studies investigating the relationship between religion and environmental concern use
data obtained from a majority Christian, U.S.-based population and therefore consider religious
characteristics related to Christian affiliation. Many studies provide evidence that Christian
religious affiliation, beliefs, and behaviors are negatively related to environmental concern
(Clements, McCright and Xiao 2013; Eckberg and Blocker 1989, 1996; Hand and Van Liere
1984; Kanagy and Nelson 1995; Wolkomir, Futreal, Woodrum, and Hoban 1997a, 1997b). A
few studies report simultaneous positive and negative relationships between Christian affiliation
and environmental concern (e.g., Boyd 1999; Guth, Green, Kellstedt, and Schmidt 1995; Kanagy
and Willits 1993). Other studies find no relationship between religion and environmental
concern (e.g., Greeley 1993; Hayes and Marangudakis 2000; Woodrum and Hoban 1994). In
addition to religious affiliation, investigators also study the influence of religiosity on
environmental concern. In general, church attendance, the most widely used measure of
religiosity, is not related to environmental concern (e.g., Boyd 1999; Eckberg and Blocker 1996;
Greeley 1993; Guth et al. 1995; Hayes and Marangudakis 2000; Woodrum and Hoban 1994).
However, Sherkat and Ellison (2007) report a positive relationship, while Kanagy and Nelson
1995 report a negative relationship.
Since the mid-1990s some investigators have described a “greening of Christianity” in the
United States (e.g., Hitzhusen, 2007; Wilkinson, 2010). Advocates of a greener Christianity

34

point to the many individual religious organizations (e.g., Franciscan Sisters of Mary, United
Methodist Church, and Pax Christi) that have formally adopted the Earth Charter and to the rise
of the Evangelical Environmental Network (2013) and Southern Baptist Environment and
Climate Initiative (2013). However, a recent study using nationally representative data from
2010 finds little evidence that Christians in the US general public are green (Clements,
McCright, and Xiao 2013), suggesting that these efforts to evangelize about the environment
have not been widely effective. Key factors that may influence the diffusion of a greener
Christianity include messenger characteristics (e.g., local church leader versus a national leader),
the mode of delivery (e.g., a church bulletin, a sermon, etc.), and the content of the message itself
(e.g., passages from the Bible). This experimental study examines how religious content in a
message about water may influence support for a fictional policy to conserve water.
Several studies report that accurate scientific knowledge of environmental problems is a key
determinant in behavioral intentions to act or participate in developing effective solutions to
environmental problems (Blocker and Eckberg 1997; Bord, O’Connor and Fisher 2000; Steel,
Lach and Satyal 2006). Hamilton, Cutler and Schaefer (2012) find that people who know more
about science in general are more concerned about species loss and rising sea levels. However,
Finger (1994) finds that apart from protest actions, knowledge has very limited effects on
environmental concern, while Iwata (1996) reports that knowledge about the environment and
science does not influence environmental attitudes and behavior. In this study, I also examine
how scientific content in a message about water may influence people’s support for a policy to
conserve water.

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Message Framing
Investigations about the influence of messaging often focus on how information is framed.
Because agreement with, or acceptance of, information is a necessary step to motivate action on
an issue (Dardis 2007), it is important to understand how different message frames influence
opinions and action. Much of the literature on framing environmental messages tests the
influence of positive (e.g., benefits of action) and negative (e.g., losses due to inaction) frames.
Several studies report that positive frames, which emphasize the social benefits of action,
generally produce desirable environmental behaviors and attitudes (Morton et al. 2011; Van de
Velde, Verbeke, Popp, and VanHuylenbroeck 2010). In general, negative frames that emphasize
undesirable environmental consequences because of inaction produce both desirable (Lord 1994)
and undesirable (Gifford and Bernard 2004; Morton et al. 2011) environmental behaviors and
attitudes. In a study of message framing to determine consumers’ likelihood of buying chemical
and pesticide free food, Gifford and Bernard (2004) find that frames which emphasize the
negative consequences of non-organic agriculture, lead to a boomerang effect that results in
lower intention to purchase organic food by people who generally trust food safety procedures.
In addition to positive and negative frames, Gifford and Comeau (2011) report that
motivational frames describing the benefits of a specific strategy are more effective at engaging
people in climate change issues than sacrificial frames. Counterclaims are effective tools in
weakening the influence of original claims about climate change (McCright and Dunlap 2000)
and clean energy (Aklin and Urpelainen 2013). Dardis (2007) reports that when subjects are
primed with information about sources that are potentially to blame for environmental problems,
they are more likely to support a fictional environmental policy.

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Chaiken and Maheswaran (1994) report that receiving information from a credible source has
a positive impact on the acceptance of the information. These credible sources may be religious
leaders for people for whom religion is salient and secular sources for non-religious people. The
point is not whether the information is factual; instead according to the elite cues hypothesis,
people seek, and act on, information from sources they already trust, including the media and
political elites (McCright and Dunlap 2011). This suggests that environmental messages using
religious terms may be effective in enhancing environmental concern in people who are
religious. However for the non-religious, these messages may fall on deaf ears because of the
boomerang effect observed by Gifford and Bernard (2004).
Water Conservation
This study uses an experimental manipulation to test the influence of messages using
religious and scientific framing to determine support for a fictional water use restriction policy.
The group of studies described earlier emphasizes concern about general environmental
problems, whereas this study focuses on water conservation as a more specific subset of
environmental concern. A few studies focus on factors that influence attitudes about water
conservation and some findings are consistent with those reported in the wider environmental
concern literature. Education (Cooper and Crase 2009) and liberal political ideology (Gilg and
Barr 2006) relate positively to acceptance of water use restrictions. However, contrary to the
general environmental concern literature, at least one study reports that age is positively related
to acceptance of water use restrictions (Gilg and Barr 2006). Home ownership is also used as a
predictor in studies about attitudes about water conservation, and here the evidence is equivocal.
Randolph and Troy (2008) report no difference in attitudes about water restrictions between

37

home owners and renters, while Gilg and Barr (2006) report that home owners are among the
most committed to conserving water.
Other studies consider the influence of information seeking on water conservation attitudes
(Trumbo and O’Keefe 2001, 2005). People who actively seek out information about water
conservation, and then pay attention to that information, are more likely to report intention to
conserve water, although the effects are weak (Trumbo and O’Keefe 2001). The effects may be
weak because the information is presented using framing techniques that do not motivate people
to action. However, the effects are stronger in people with pro-environmental values and who
have a history of pro-environmental behaviors (Trumbo and O’Keefe 2005), pointing to the
possibility that environmental values moderate the relationship between seeking information and
behavioral intentions to conserve water. In fact, Trumbo and O’Keefe (2005) suggest that proenvironmental messages might be most effective when they align with preexisting values and
behaviors. In addition, people may readily process and act on messages from sources that they
already trust, such as religious and scientific leaders (i.e., the elite cues hypothesis) (Brulle,
Carmichael and Jenkins 2012; Krosnick et al. 2000; Lewkowicz 2006; McCright and Dunlap
2011). I use religious and scientific messages about water conservation to test the following
hypotheses suggested by the preceding discussion.
Following previous studies that report a negative relationship between Christian religious
affiliation and environmental concern (see e.g., Clements, McCright and Xiao 2013; Eckberg and
Blocker 1989, 1996), I expect that Christian affiliation will negatively predict agreement with a
proposed water use restriction policy (Hypothesis 1). In addition, because of the negative
influence of Christianity, I expect that a religiously framed message will decrease support for a
proposed water use restriction policy compared to a scientific message (H2). However, for those

38

who report a Christian religious affiliation, the elite cues hypothesis suggests that a religious
message about water conservation will increase support for a proposed water use restriction
policy (H3). In the next section, I discuss the experimental methodology, that nature of the data I
collected, and the statistical techniques I used to analyze the data.
METHODS
Experimental Design
The study is a simple, online messaging experiment with a single manipulation and two
conditions. The message emphasizes the importance of water conservation; one condition uses a
religious framing, and the other uses a scientific framing. After providing their consent to
participate, subjects answered a series of questions about their level of worry about six
environmental problems. Subjects then answered three questions about their willingness to
change their lifestyle or pay higher taxes or prices to protect the environment. Next, subjects
read one of two randomized messages about water conservation and then two paragraphs
describing a fictional water use restriction policy. Subjects then answered one question about
their level of agreement with the policy. Finally, subjects answered some basic sociodemographic and political identity questions.
Sample
I recruited subjects for this study via Amazon Mechanical Turk, which allows “requesters”
(such as myself) to solicit “workers” to complete “Human Intelligence Tasks,” (HIT) such as this
experiment. Traditionally, experimental studies are conducted with convenience samples of
university students or people who live in close proximity to a campus, which makes results not
widely generalizable. Some studies report that the demographics of Amazon Mechanical Turk
samples are closer to the U.S. general public than are typical university samples, with

39

significantly lower response error (Mason and Suri 2012; Paolacci, Chandler, and Ipeirotis
2010). In addition, samples from Amazon Mechanical Turk tend to be more diverse than typical
Internet samples (Buhrmester, Kwang and Gosling 2011). Data collected using Mechanical Turk
provides a sample with greater diversity of people in the general public than most other
experiments that have been done. Thus, Amazon Mechanical Turk provides a quick, inexpensive
method to collect experimental data from a wide cross-section of the general public.
I recruited subjects in May 2013 using a HIT on Amazon Mechanical Turk that advertised
for subjects to answer multiple choice questions about environmental issues in the United States.
I set the characteristics to allow the HIT to only be seen by US residents. The sample consists of
608 subjects. I paid each subject $0.25 to complete the survey, which took an average of 3
minutes and 32 seconds. Additional information about the sample is contained in Table 5.
Dependent Variable
See Table 5 for detailed coding information for all variables. To measure agreement with a
proposed water use restriction policy, I included one dependent variable which provided a
scenario about water conservation. Two short paragraphs, which described the fictional policy,
read:
Whether or not your city has a water use policy, imagine that the legislature in
your state is proposing to enact a policy to regulate outdoor use of water on
personal property during times of water scarcity, such as we have seen in the
United States during the summer of 2012. This policy would require that
municipalities reduce water use by 50% during times of drought.
The policy described above could mean mandatory prohibitions on outdoor
uses, such as washing cars, watering lawns and gardens, and filling swimming

40

pools so that municipalities can insure safe and reliable water for the entire
population. What is your level of agreement with this proposed policy?
Subjects’ answers to this question were coded as follows: “strongly disagree”=1, “moderately
disagree”=2, “neither”=3, “moderately agree”=4, and “strongly agree”=5. Eighty-percent of
subjects strongly agreed or moderately agreed with the proposed policy.
Experimental Conditions
Prior to reading the text above about the proposed water use restriction policy, subjects read a
brief experimental message about water conservation. Subjects were randomly assigned to one
of two experimental conditions: religiously framed message (first below) and scientifically
framed message (second below):
1. Many people are concerned with water as a natural resource. Some people
argue that water is a gift from God. We should be concerned about rivers,
lakes, oceans, and ground water. We are a part of God’s creation and by
working to protect the environment we can continue to create life. It is the
duty of Christians to protect water.
2. Many people are concerned with water as a natural resource. Some people
argue that 80% of the United States is facing abnormally dry conditions.
Much of the southern half of the country is experiencing drought, which
will not likely change soon. We can effectively reduce drought problems
by creating solutions to conserve water in drought-affected areas.
Religion Predictors
To examine if Christian affiliation negatively predicts agreement with the proposed water
policy, I created religious affiliation dummy variables to identify those who self-identify as

41

Christians (“Christian”), non-Christians (“non-Christian”), and those not belonging to a religion
(“reference category”). I also included a measure of religious service attendance (“never”=1 to
“greater than once per week”=9) as the most widely used measure of religiosity (Boyd 1999;
Eckberg and Blocker 1996; Hayes and Marangudakis 2000).
Political, Socio-Demographic and Biophysical Predictors
I also account for a range of political, socio-demographic, and biophysical characteristics that
might also influence support for the proposed water use restriction policy. I measured political
ideology as “extremely conservative”=1 to “extremely liberal”=7 (see e.g., Dunlap, Xiao, and
McCright 2001). I included gender (“female”=1), race (white=1), age (actual age in years),
educational attainment (“less than high school”=1 to “more than a 4 year degree”=5), and annual
household income (“$0-$24,999”=1 to “$100,000 and up”=5) as previous studies report their
influence on environmental concern (e.g., Dunlap and Jones 2002; Dunlap, Xiao, and McCright
2001). I also included home ownership (“owned or being bought”=1), as suggested by findings
from Randolph and Troy (2008) and Gilg and Barr (2006). Finally, although the findings about
the effect of proximity to environmental hazards on environmental concern are equivocal
(Spence, Poortinga, Butler, and Pidgeon 2011; Zahran, Brody, Grover, and Vedlitz 2006), I
recoded subjects’ zip codes into a dummy variable to reflect whether or not they lived in a
drought location during the time of the survey (U.S. Drought Monitor 2013).
Environmental Concern Indicators
I used confirmatory factor analysis (CFA) to construct two composite measures of
environmental concern. In each case, items loaded onto one factor. Prior to conducting the CFA
and constructing measures, I used the maximum likelihood estimation option in AMOS 22.0 to
replace missing values for each observed measure that predicts their respective latent measure. I

42

used factor score weights to create two latent measures of environmental concern. In each case, I
accepted factor score weights greater than 0.70 as a cutoff to retain any item as part of the
relevant factor. In addition, I considered several fit measures to evaluate the model fit for each
CFA: chi square, adjusted goodness of fit index (AGFI), root mean square of approximation
(RMSEA), and incremental fit index (IFI).
First, chi square tests the overall model fit by testing the null hypothesis that there is no
difference between the proposed model and the data structure. A good fitting model will retain
the null hypothesis (i.e., the chi square statistic should not be significant). However, one caveat
regarding the chi square test is important. Because it is a test of statistical significance, it is
sensitive to sample size and most large samples (>200) make it very difficult to retain the null
hypothesis (Blunch 2013). The results described below for my CFAs (and later for my structural
equation models) fit this situation. Therefore, I also report other fit indices. The AGFI is an
absolute fit index that tests the ability of the proposed model to reproduce the variance matrix of
the data compared to the ability of no model at all. Generally, .90 is an appropriate cutoff for
determining model fit (Bollen and Long 1993; Joreskog and Sorbom 1984). RMSEA is less
affected by sample size than chi-square, and is a more reliable measure of fit across a range of
sample sizes. Generally values of zero indicate a perfect fit, while anything less than .05 is
regarded as a close fit, with up to .08 evaluated as a fair fit. Values over .10 indicate a poor
model fit. Like the chi square test, the RMSEA can be used to evaluate the null hypothesis that
there is no difference between the proposed model and the data structure. The null hypothesis
will be retained with RMSEA values less than .08 (Blunch 2013; Byrne 2013). Finally, IFI is a
relative fit index that places the proposed model in a continuum between a saturated model with

43

maximum fit (IFI=1) and an independence model with a maximum number of constraints on the
model (IFI=0). The closer the IFI is to one, the better the model fit (Blunch 2013; Byrne 2013).
Six items create a “personal worry” measure (CFA factor loadings between .69 and .82),
which taps into how much respondents worry about the following environmental problems: air
pollution (item to which the CFA is scaled), contamination of soil and water by toxic waste,
extinction of plant and animal species, loss of tropical rain forests, pollution of drinking water,
and pollution of rivers, lakes and reservoirs. Notably, two items (extinction and loss of tropical
rain forests) had factor weights slightly below .70, and I retained these items as part of the single
factor for two reasons. First, the factor loading for each was .69 and while factor loadings are an
important consideration, factor loadings should also be considered in light of theory. In this
case, both items measured worry about an environmental problem, and so on the face, it makes
sense to include these items in the personal worry indicator. Although the chi-square test
suggests poor model fit (210.93, p<.001), the large sample size indicates that other fit indices
should be considered. In this case RMSEA=.04, p=.145, AGFI=.91, and IFI=.87, indicating
good model fit.
Three items form a “willingness to pay or sacrifice” measure (CFA factor loadings between
.70 and .93), which indicates how willing respondents are to pay much higher prices to protect
the environment, pay much higher taxes to protect the environment (item to which the CFA is
scaled), and accept cuts in their standard of living to protect the environment. Again, the chisquare test suggests poor model fit (193.50, p<.001), but the other fit indices suggest good model
fit (RMSEA=.04, p=.07, AGFI=.90, and IFI=.89).

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Statistical Analysis
I used structural equation modeling (SEM) to analyze the structural relationships among the
predictors, mediators, and outcome variables in the model displayed in Figure 1. All but two
variables in the model are observed; “personal worry” and “willingness to pay or sacrifice” are
latent measures. I modeled the willingness to pay or sacrifice latent measure as a mediator
between the religion, political, socio-demographic, biophysical, and environmental worry
variables and agreement with the proposed water use restriction policy. Because the dependent
variable measures agreement with a policy that requires changes in lifestyle (e.g., use less water
for outdoor use, showering, laundry, etc.), the general willingness to pay or sacrifice latent
measure likely intervenes between those variables that influence environmental concern (e.g.,
age, gender, race, religious affiliation) and agreement with the proposed policy. As designed, the
experimental condition is also modeled as mediator between the water policy agreement variable
and the others in the model.
To test H1 and H2 (which expect Christian affiliation and the religiously framed message to
influence agreement with the proposed water use restriction policy, respectively), I ran one SEM
with data from the entire sample (N=680). To test H3 (which expects the religiously framed
message to influence agreement with the proposed water use restriction policy among
Christians), I ran one additional SEM with data from the Christian subsample (N=206). This
SEM is otherwise identical to the structural model used to test H1 and H2, with one exception. I
removed the two religious affiliation dummy variables. As discussed above, while the chi square
test for each SEM suggests poor model fit, the effect of sample size suggests that RMSEA,
AGFI, and IFI should also be considered as indicators of model fit. In each case, these model fit
statistics indicate acceptable model fit. Next I discuss the results of my hypothesis tests.

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RESULTS
Table 6 presents the results of the SEM for the entire sample. The first hypothesis (H1)
expects that Christian religious affiliation is negatively related to agreement with the water use
restriction policy which states that municipalities would be required to reduce water use by 50%
in times of drought. The results in Table 6 do not support H1. Christian affiliation does not
influence agreement with the proposed water use restriction policy. In other words, selfidentified Christians and non-religious subjects have the same level of agreement with the policy.
These results are similar to other studies which report no relationship between religion and
environmental concern (e.g., Greeley 1993; Hayes and Marangudakis 2000; Woodrum and
Hoban 1994). Finally, non-Christians do not differ in their level of agreement from nonreligious people.
The second hypothesis (H2) expects that the religiously framed message will decrease
support overall for the proposed water use restriction policy. The results in Table 6 support H2.
Subjects exposed to the religiously framed message reported lesser agreement with the proposed
water restriction policy than their counterparts exposed to the scientifically framed message.
This does not bode well for the promise of a greener Christianity discussed earlier. Although
green Christian activism such as the Evangelical Environmental Network (2013) and Southern
Baptist Environment and Climate Initiative (2013) are notable, there is little evidence that
Christians in the US general public have embraced environmentalism (Clements, McCright, and
Xiao 2013). The fact that a religiously framed message here reduced support for the water
conservation policy is further evidence that many in the general public still see Christianity and
environmentalism as less than complementary.

46

Before discussing the results that pertain to the third hypothesis, I report the performance of
the remaining variables in Table 6. Consistent with most environmental concern research,
liberals, younger adults, and the highly educated report greater willingness to pay or sacrifice for
the environment compared to their respective counterparts (e.g., Dunlap and Jones 2002; Dunlap,
Xiao, and McCright 2001). As expected, personal worry about environmental problems is the
strongest predictor to willingness to pay or sacrifice for the environment. As subjects’ worry
about environmental problems increases, so too does their willingness to pay or sacrifice to
protect the environment. No other predictors in the model explain subjects’ willingness to pay or
sacrifice. The middle section of Table 6, which presents the effect of predictors on the
experimental message to which subjects were randomly assigned, indicates that no variables
have a statistically significant effect—as expected. Briefly, this confirms that the subjects were
properly assigned to the two experimental conditions via randomization.
The final column in Table 6 reports the total effects of the predictors on agreement with the
proposed water use restriction policy. The two environmental concern indicators (personal
worry and willingness to pay or sacrifice) are the strongest predictors of agreement with the
proposed water use restriction policy. Personal worry and willingness to pay or sacrifice for the
environment positively predict agreement with the proposed water use restriction policy. Also,
liberals, whites, and older adults report greater agreement with the proposed water use restriction
policy than their respective counterparts. The positive effects of liberal ideology and age are
similar to those found by Gilg and Barr (2006).
No other predictors in the model explain subjects’ agreement with the policy, including
living in a drought affected area. This finding is similar to one other study that reports no
relationship between flood experiences and climate change concern (Whitmarsh 2008). Several

47

studies (e.g., Brody, Zahran, Vedlitz and Grover 2008; Spence, Poortinga, Butler, and Pidgeon
2011; Whitmarsh 2008; Zahran, Brody, Grover, and Vedlitz 2006) report equivocal results for
the association between proximity to local environmental hazards (generally flood events) and
environmental concern, but none study proximity to, or experience with, drought.
Finally, the results in Table 7 allow for a test of the third hypothesis (H3). Since past
research finds that people are more likely to accept information from trusted and credible sources
who share similar values (e.g., Chaiken and Maheswaran 1994; McCright and Dunlap 2011;
Trumbo and O’Keefe 2005), I expected that Christians would find the religiously framed
message (grounded in Christianity) to be more credible and persuasive than the scientifically
framed message. Thus, H3 expects that the religiously framed message about water conservation
would increase support for the proposed water use restriction policy among Christians.
Similar to the result for the entire sample, Christians exposed to the religiously framed
message reported lesser agreement with the proposed policy than did Christians exposed to the
scientifically framed message. A few caveats are in order. First, I did not measure how credible
or trustworthy respondents viewed the two experimental messages. Second, I did not measure
how much respondents thought these messages aligned with their values. Regardless, it seems
reasonable to assume that Christians would be more likely to view the religiously framed
message as credible, trustworthy, and embodying their values. Thus, these results do not seem to
support the findings of past research that people are more likely to accept information from
sources they trust and find credible (e.g., Chaiken and Maheswaran 1994; McCright and Dunlap
2011).

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CONCLUSION
With the prevalence of drought throughout the United States in the summers of 2012 and
2013, water policy issues have increased in salience. Municipal water suppliers, the media,
government agencies, farm groups, and environmental nonprofit organizations, among others,
use scientific language to convince the public of the importance of water conservation. At the
same time, approximately 80% of US citizens report some religious affiliation, with the vast
majority being Christians. With an emerging green Christian movement in the US, it is
important to determine how effective environmental messages are from religious sources. This
study uses a convenience sample of subjects recruited on Amazon Mechanical Turk to compare
the influence of religiously framed and scientifically framed messages on agreement with a
fictional proposed water use restriction policy. If religious messages are effective at increasing
concern about environmental problems, they may be an important tool for Christian leaders to
enhance support for addressing environmental problems in the US.
I found that self-reported Christian affiliation does not influence agreement with the
proposed water use restriction policy. In other words, Christians were no more or less likely to
agree with a policy calling for water use restrictions than non-Christians and non-religious
people. However, a Christian religious message negatively influenced agreement with water use
restrictions in the entire sample—and in the Christian subsample. These results suggest that
religiously framed messages may not significantly increase environmental concern. I close with
suggestions for future experimental research in this area.
First, future experiments should continue to examine the influence of scientific and religious
messages on various aspects of environmental concern, but these messages should be designed
using different framing techniques. While the messages used in this study are easily accessible

49

to the general public and therefore have high external validity, they do not use any specific
framing technique generally reported in the messaging literature (e.g., positive/negative frames
or motivational and sacrificial frames). It is possible that some of these framing techniques are
more effective in religious people than in non-religious people. If pro-environmental Christian
leaders want to effectively increase environmental concern, they need to understand techniques
that enhance support to address environmental problems.
Second, future experiments could vary the information that is presented as part of the
dependent variable. The proposed policy in this experiment required a 50% reduction in water
use. Future studies might vary the reduction amount to determine how support for, or opposition
to, the policy differs based on the required reductions. I also provided a range of activities that
would be restricted under a proposed policy. Future studies might vary the number and types of
restricted activities to determine if specific activities (e.g., filling the swimming pool or washing
the car) are more or less important to subjects.

50

CHAPTER 4
ACTUAL PAYMENTS FOR BIODIVERSITY PROTECTION: THE INFLUENCE OF
RELIGIOUSLY AND SCIENTIFICALLY FRAMED MESSAGES

INTRODUCTION
According to the Millennium Ecosystem Assessment (2005), approximately 25% of
mammals and 12% of birds are currently threatened with extinction, mostly due to ecosystems
loss. Also, human activities have increased extinction rates by 100 to 1,000 times the normal
background rate. Further, over the last 100 years, there have been over 100 well-documented
extinctions of birds, mammals and amphibians. Ecosystem loss and change in the United States
leads to hundreds of millions of dollars per year in costs to control invasive species and respond
to floods and fires that are becoming more extreme as ecosystem changes increase (Millennium
Ecosystems Assessment 2005). Above, I employ the concepts of extinction, extinction rates,
species loss, ecosystem loss, ecosystem change to highlight the issue of biodiversity loss as this
is the type of information that is used to bring attention to the issue of biodiversity and is the type
of information that captures the public’s attention. However, it is important to note that these
concepts do not all mean the same thing; nor can they always be used to define the problem of
biodiversity loss. Without the work of communities (Berkes 2007), nongovernmental
organizations (e.g., The Nature Conservancy 2013; World Wide Fund for Nature 2013), and
governments (e.g., U.S. Fish and Wildlife Service) even less biodiversity would exist today.
These organizations frequently use scientifically based arguments to call for greater action to
prevent biodiversity loss.

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Apart from science-based arguments to promote work to prevent biodiversity loss, arguments
based on religious teachings may also be effective to promote action to prevent biodiversity loss
(e.g., Bhagwat 2007; Negi 2005). Approximately 80% of the U.S. public reports some religious
affiliation (mostly Christian). However, some studies provide evidence that Christian religious
people have negative attitudes about science (Campbell and Curtis 1996; Evans and Evans 2008)
and are less influenced by scientific arguments than scientific communicators expect (Brossard et
al. 2009; Ho, Brossard and Scheufele 2007). This becomes relevant when problems such as
biodiversity loss require some understanding of scientific principles and acceptance of sciencebased arguments that promote action to address this problem. It is important that religions
address problems that require scientific solutions, because arguments grounded in religious
morality may be a more effective way to promote action to address environmental problems in
religious individuals, compared to scientific arguments. In this study, I report the results of an
experiment that examines how religiously and scientifically framed messages influence the
choice to make donations to protect against biodiversity loss.
RELIGION, SCIENCE, AND ENVIRONMENTAL CONCERN
Environmental concern is “the degree to which people are aware of problems regarding the
environment and support efforts to solve them and/or indicate a willingness to contribute
personally to their solution (Dunlap and Jones 2002:485).” People demonstrate environmental
concern by, among other things, using less water or driving less, volunteering with an
environmental nongovernmental organization, supporting policies to protect the environment, or
donating money to environmental organizations that work to solve environmental problems.
Many studies investigating the influence of social, demographic, and political characteristics on
environmental concern find that people who report high levels of environmental concern are

52

more likely to be female, younger, highly educated, and identify as liberals and/or Democrats
(e.g., Dunlap, Xiao, and McCright 2001; Xiao and McCright 2012). However, sociodemographic and political factors only explain a small amount of variation in environmental
concern, while value orientations explain much more. The values research suggests that selftranscendent values (e.g., benevolence, pro-environmental values) (Dietz, Fitzgerald, and
Shwom 2005; Stern, Dietz, Abel, Guagnano, and Kalof 1999), empathy (Berenguer 2007), and
especially altruism (Dietz, Fitzgerald, and Shwom 2005; Stern, Dietz, Abel, Guagnano, and
Kalof 1999; Stern, Dietz, Kalof, and Guagnano 1995) are important predictors of environmental
concern. While socio-demographic factors and values do explain some variation in
environmental concern, it is important to investigate the influence of other characteristics, such
as scientific knowledge about environmental problems and religious affiliation and belief
patterns, which likely predict environmental concern.
Scientific Knowledge and Religion
Several studies report that accurate scientific knowledge of environmental problems is a key
determinant in deciding to participate in developing effective solutions to environmental
problems (Blocker and Eckberg 1997; Bord, O’Connor and Fisher 2000; Steel, Lach and Satyal
2006). Additionally, people who know more about science in general are more concerned about
species loss and rising sea levels (Hamilton, Cutler and Schaefer 2012). However, Finger (1994)
reports that knowledge has very limited influence on environmental concern, while Iwata (1996)
finds that knowledge about the environment and science does not influence environmental
attitudes and behavior. In this study, I examine how a scientifically framed message about
biodiversity loss influences people to make a donation to protect against biodiversity loss.

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Because the majority of US citizens self-identify as Christian, most studies investigating the
relationship between religion and environmental concern consider religious characteristics
related to Christian affiliation. Many studies report that Christian religious affiliation, beliefs,
and behaviors are negatively related to environmental concern (Clements, McCright and Xiao
2013; Eckberg and Blocker 1989, 1996; Wolkomir, Futreal, Woodrum, and Hoban 1997a,
1997b). Boyd (1999) and Guth, Green, Kellstedt, and Schmidt (1995) find simultaneous positive
and negative relationships between Christian affiliation and different facets of environmental
concern. Other studies find no relationship between religion and environmental concern (e.g.,
Hayes and Marangudakis 2000; Woodrum and Hoban 1994). Investigators also study the
influence of religiosity on environmental concern. Church attendance is the most widely used
measure of religiosity, and most studies find that it is not related to environmental concern (e.g.,
Boyd 1999; Eckberg and Blocker 1996; Greeley 1993; Guth et al. 1995; Hayes and
Marangudakis 2000; Woodrum and Hoban 1994). However, Sherkat and Ellison (2007) report a
positive relationship, while Kanagy and Nelson (1995) report a negative relationship.
Some observers have described a “greening of Christianity” in the United States since the
mid-1990s (e.g., Hitzhusen, 2007; Wilkinson, 2010). As evidence of a greener Christianity,
some advocates point to the rise of the Southern Baptist Environment and Climate Initiative
(2013) and the Evangelical Environmental Network (2013), as well as some Catholic
organizations (e.g., Franciscan Sisters of Mary, United Methodist Church, and Pax Christi) that
have formally adopted the Earth Charter. However, a recent study using nationally
representative data from 2010 finds little evidence of a greener Christianity (Clements,
McCright, and Xiao 2013), suggesting that efforts to evangelize about the environment have not
been widely effective. Key factors that may influence the acceptance of a greener Christianity

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include the content of green religious messages (e.g., passages from the Bible or other religious
texts), the mode of delivery (e.g., a homily, church bulletin, or sermon), and messenger
characteristics (e.g., a local church leader versus a national leader). In this study, I examine how
religious content in a message about biodiversity loss influences respondents to make a donation
to protect against biodiversity loss.
Message Framing
Messaging studies often investigate how different framing techniques influence acceptance
or agreement with information. Agreement with, or acceptance of, information is a necessary
step to motivate action on an issue (Dardis 2007); therefore, it is important to understand how
different message frames influence opinions and action. Much of the environmental messaging
literature tests the influence of positive (e.g., benefits of action) versus negative (e.g., losses due
to inaction) frames. In general, compared to negative frames, positive frames which emphasize
the social benefits of action are more likely to produce desirable environmental behaviors and
attitudes (Morton et al. 2011; Van de Velde, Verbeke, Popp, and VanHuylenbroeck 2010).
However, negative frames that emphasize undesirable environmental consequences because of
inaction may produce both undesirable (Gifford and Bernard 2004; Morton et al. 2011) and
desirable (Lord 1994) environmental behaviors and attitudes. Apart from positive and negative
frames, counterclaims are effective tools in weakening the influence of original claims about
clean energy (Aklin and Urpelainen 2013) and climate change (McCright and Dunlap 2000).
Additionally, motivational frames describing the benefits of a specific strategy are more effective
at engaging people in climate change issues than sacrificial frames (Gifford and Comeau 2011).
Chaiken and Maheswaran (1994) find that receiving messages from credible sources has a
positive impact on acceptance of information. The point is not whether the information from a

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credible source is necessary correct or complete, but that people receiving the message are more
likely to accept information from a source that they already find to be credible. To people for
whom religion is salient, credible sources may be religious leaders, while non-religious people
may find secular sources to be more credible. In addition, according to the elite cues hypothesis
(Brulle, Carmichael and Jenkins 2012; Krosnick et al. 2000; Lewkowicz 2006; McCright and
Dunlap 2011), people seek out, and act on, information from sources they already trust who
frame information that aligns with pre-existing beliefs about an issue (McCright and Dunlap
2011). In other words, trust in, and perceived credibility of, information sources influence
acceptance of information apart from the actual message. This is especially true for
controversial issues where opposing viewpoints provide conflicting information (Krosnick et al.
2000). Much of the research about the elite cues hypothesis studies the influence of partisan
leadership and political orientation on attitudes about controversial issues (e.g., Brulle,
Carmichael and Jenkins 2012; Krosnick et al. 2000; Lewkowicz 2006; McCright and Dunlap
2011). With respect to messaging about environmental problems, the elite cues hypothesis
suggests that religiously framed messages about environmental problems may be effective in
increasing environmental concern in religious people.
Biodiversity Loss
This study uses an experimental manipulation to test the influence of messages using
religious and scientific framing on choosing to make a donation to protect against biodiversity
loss. The group of studies described earlier emphasizes environmental concern about general
environmental problems. This study focuses on biodiversity loss as a specific environmental
problem. Hunter and Brehm (2003) suggest that protecting biodiversity is an environmental
problem about which the public is somewhat concerned. At the same time, the public possesses

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little knowledge about the ecological principles and complex forces behind biodiversity loss
(Hunter and Brehm 2003).
The few existing studies of attitudes about biodiversity loss find that women report greater
concern about species loss (Hunter and Rinner 2004) and prioritize species conservation over
property rights (Czech, Devers, and Krausman 2001) compared to men. Hunter and Rinner
(2004) also report that older individuals and those with higher incomes are less concerned about
species loss than their respective counterparts. Finally, people with ecocentric values are more
concerned about species loss than people with anthropocentric values, even when controlling for
knowledge about specific species (Hunter and Rinner 2004). The result about ecocentric values
is similar to other findings about pro-environmental values and general environmental concern
(e.g., Dietz, Fitzgerald, and Shwom 2005), suggesting that value orientations influence general
environmental concern, as well as concern about specific environmental problems, including
biodiversity loss.
No existing studies have investigated the influence of messaging on attitudes about
biodiversity loss. In this study, I use religiously and scientifically framed messages about
biodiversity loss to test the following hypotheses suggested by the preceding discussion.
Following previous studies that report a negative relationship between Christian religious
affiliation and environmental concern (see e.g., Clements, McCright and Xiao 2013; Eckberg and
Blocker 1989, 1996), I expect that Christians are less likely to make a donation to protect against
biodiversity loss compared to non-Christians and non-religious respondents (Hypothesis 1). I
also expect that for subjects who make a donation, Christians will donate less than nonChristians and non-religious people (H2). In addition, because of the negative influence of
Christianity on environmental concern, I expect that people who receive a religiously framed

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message will be less likely to make a donation to protect against biodiversity loss than people
who receive a control message or scientifically framed message (H3). Further, a religiously
framed message will decrease the donation amount compared to the control message and
scientifically framed message (H4). The elite cues hypothesis suggests that, among Christians, a
religiously framed message about biodiversity loss will increase the likelihood of making a
donation compared to a control or scientifically framed message (H5). Finally, the elite cues
hypothesis also suggests that, among Christians, receiving a religious message will increase
donation amounts compared to receiving a control or scientifically framed message (H6).
METHODS
Experimental Design
The study is an online messaging experiment with a single manipulation: one control and two
experimental conditions. The message presents information about biodiversity loss. In addition
to the control text, one condition uses religious framing, and the other uses scientific framing.
After providing their consent to participate, subjects answered a series of questions designed to
measure altruistic values, beliefs about human-environment relations, worry about environmental
problems, and willingness to pay or sacrifice to protect the environment. Then subjects read one
of three randomized messages about biodiversity loss and answered two questions to measure
their understanding about the message. Subjects then answered some basic socio-demographic
and political identity questions. Finally, subjects were notified that they were awarded a $0.50
bonus for completing the survey, which is described in depth below.
Sample
I recruited subjects for this experiment using Amazon Mechanical Turk, which allows
“requesters” (such as myself) to solicit “workers” to complete “Human Intelligence Tasks,”

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(HIT) such as this experiment. Many traditional experimental studies use convenience samples
of university students or people who live close to a campus, limiting the generalizability of
results. Mason and Suri (2012) and Paolacci, Chandler, and Ipeirotis (2010) report that the
demographics of Amazon Mechanical Turk samples are closer to the U.S. general public than are
typical university samples, with significantly lower response error. In addition, samples
recruited from Amazon Mechanical Turk are also more diverse than other Internet samples
(Buhrmester, Kwang and Gosling 2011). Therefore, Amazon Mechanical Turk provides an
inexpensive, quick method to collect experimental data from a cross-section of the general
public.
I recruited subjects in September 2013 using a HIT on Amazon Mechanical Turk that
advertised for subjects to answer multiple choice questions about social issues in the United
States for a payment of $0.25. 836 adult residents of the United States completed the survey.
Unbeknownst to the subjects during the recruitment, I offered an additional $0.50 bonus at the
end of the survey that subjects could choose to donate. On average, subjects completed the
survey in 4 minutes and 26 seconds. Additional information about the sample is contained in
Table 8.
Dependent Variable
See Table 8 for detailed coding information for all variables. As stated above, at the very
end of the survey, subjects read a prompt stating that they were receiving a bonus for completing
the survey. The prompt read:
For completing this survey you have earned a bonus of $0.50! This bonus is
in addition to $0.25 you have already earned.

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You have an option to donate some of your bonus to the World Wide Fund for
Nature, an international conservation organization founded in 1961.
This donation will be used to support efforts in conserving nature and
preventing further loss of biodiversity.
I will deduct the amount you select from your bonus and donate it to the
World Wide Fund for Nature.
Considering the information about nature and biodiversity you read earlier,
how much of this bonus would you like to donate to the World Wide Fund for
Nature?
Subjects then selected any amount ranging from $0.00 to $0.50. Thus, the dependent
variable in this study is a measure of actual behavior (a real donation) rather than merely a selfreported behavior or behavioral intention.
In one previous experiment, Carlsson and Martinsson (2001) had respondents choose
between an amount of money they could receive and an amount of money they could donate to
support one of three environmental projects. However the respondent did not have to make a
choice to donate his or her own money; instead they chose from different amounts of money that
the investigators would then donate (Carlsson and Martinsson 2001:182). My experiment
improves on this design by awarding respondents with a bonus for completing a survey, and then
asking them to donate some of this bonus to a program to protect against biodiversity loss.
Therefore, I am able to measure actual behavior to pay for an environmental public good using a
respondent’s own money. Fifty-percent of subjects made a donation, and the average donation
amount was $0.15 (30% of the bonus).

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Experimental Conditions
Prior to reading the text above about the donation option, subjects read one of three brief
messages about biodiversity loss. Subjects were randomly assigned to a control message (first
below) or one of two experimental conditions: a religiously framed message (second below,
presented in addition to the control text) and a scientifically framed message (third below,
presented in addition to the control text):
1. Many animal and plant species have declined in numbers, and many
are also found in fewer places where they were once abundant. For
instance, 25% of mammal species is currently threatened by
extinction. The overall rate of species extinction has increased.
Human activity—such as land development and increased pollution—
has caused between 50 and 1000 times more extinctions in the last 100
years than would have happened due to natural processes.
2. Christian religious leaders agree with the Book of Genesis account in
the Bible that God created the heavens and the earth and all the
animals and plants. These leaders say because the world is a gift from
God, we should do our best to be good stewards of the earth and our
natural environment.
3. Scientists agree that our natural environment is critical to our
wellbeing. For example, different species of insects are necessary to
pollinate important food crops. Also, some plant species may hold the
key to developing new treatments for various illnesses. Because the

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natural environment is critical to our wellbeing, these scientists believe
that we need to protect our natural environment.
Manipulation Checks
After reading the control or one of the experimental messages, subjects answered two
questions to measure their understanding with the information in the message. The first question
asked subjects to identify the percent of mammal species that is threatened with extinction. The
second question asked subjects to identify the primary reason to conserve nature, according to
the message they read. Subjects who did not answer both questions correctly were excluded
from the study. No control message subjects, one religious message subject, and two science
message subjects were excluded, which resulted in a final sample size of 836 subjects.
Religion Predictors
To examine if Christian affiliation negatively predicts donation, I created religious affiliation
dummy variables to categorize those who self-identify as Christians (“reference category”), nonChristians (“non-Christian”), and those not belonging to a religion (“non-religious”). I also
included a measure of religious service attendance (“never”=1 to “greater than once per
week”=9), since it is the most widely used measure of religiosity in studies of religion and
environmental concern (Boyd 1999; Eckberg and Blocker 1996; Hayes and Marangudakis 2000).
Values Orientation and Environmental Concern Indicators
I used the results of exploratory factor analyses to justify constructing one altruism value
composite measure, and three composite measures of environmental concern. In each case, the
items loaded onto one factor, justifying the creation of summative indices. Much of the research
on how values influence environmental concern suggests that altruism is one of the strongest
predictors of environmental concern (Dietz, Fitzgerald, and Shwom 2005; Stern, Dietz, Abel,

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Guagnano, and Kalof 1999; Stern, Dietz, Kalof, and Guagnano 1995). Therefore, I use six items
to form an altruism measure (alpha=.86, factor loadings between .67 and .88), which taps into
how important each of the following is as a guiding principle in subjects’ lives: a world of peace,
free of war and conflict; equality, equal opportunity for all; protecting the environment,
preserving nature; respecting the earth, harmony with other species; social justice, correcting
injustice, care for the weak; and unity with nature, fitting into the nature.
Next, the New Ecological Paradigm (NEP) (Dunlap and Van Liere 1978; Dunlap et al., 2000)
taps into five facets of an ecological worldview including: the possibility of an ecological crisis,
anti-anthropocentrism, the fragility of nature, the reality of limits to growth, and antiexemptionalism. Individuals with ecocentric perspectives, as measured by the NEP tend to
believe that humans have a responsibility to be stewards of the earth, and accept that there are
environmental limits to our activities. Eight items create a revised NEP measure (alpha=.87,
factor loadings between .55 and .83), that taps into level of agreement with the following
statements about the relationship between humans and the environment: we are approaching the
limit of the number of people earth can support, when humans interfere with nature it produces
disastrous consequences, humans are severely abusing the environment, plants and animals have
as much right as humans to exist, despite special abilities, humans are still subject to laws of
nature, earth is like spaceship with very limited room and resources, the balance of nature is very
delicate and easily upset, and if we continue on our present course we will experience an
ecological catastrophe.
Some literature reports that the American public is moderately willing to spend tax money on
environmental problems (Dunlap and Scarce 1991) and that they are willing to make sacrifices in
order to decrease the impacts of global warming (O’Connor et al. 1999). I use three items to

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form a “willingness to pay or sacrifice” measure (alpha=.88, factor loadings between .85 and
.92), which indicates how willing respondents are to pay much higher prices to protect the
environment, pay much higher taxes to protect the environment, and accept cuts in their standard
of living to protect the environment. Finally, because previous studies suggest that concern
about the harmful consequences of environmental problems is positively related to support for
the environmental movement (Stern et al. 1995), I include an indicator of “personal
environmental worry” as a possible influence on donation behavior. Six items create a “personal
environmental worry” measure (alpha=.89, factor loadings between .63 and .85), which taps into
how much respondents worry about the following environmental problems: air pollution,
contamination of soil and water by toxic waste, extinction of plant and animal species, loss of
tropical rain forests, pollution of drinking water, and pollution of rivers, lakes and reservoirs.
Political and Socio-Demographic Predictors
I also account for a range of political and socio-demographic characteristics that might
influence donations. I measured party identification as “strong Republican”=1 to “strong
Democrat”=7 (see e.g., Dunlap, Xiao, and McCright 2001). I included gender (“female”=1),
race (“white”=1), age (“18-19”=1 to “80 or greater”=8), educational attainment (“less than high
school”=1 to “more than a 4 year degree”=5), and annual household income (“$0-$24,999”=1 to
“100,000 and up”=5), since previous studies report their influence on environmental concern
(e.g., Dunlap and Jones 2002; Dunlap, Xiao, and McCright 2001). I also included a measure of
the number of college-level science courses taken (“none”=1 to “21or greater”=5) as a measure
of scientific knowledge (Bord, O’Connor and Fisher 2000; Hamilton, Cutler and Schaefer 2012).

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Statistical Analysis
I used zero-inflated Poisson (ZIP) regression to test my hypotheses using Stata 13. Zeroinflated data have a larger proportion of zeros than might be expected from a pure count
(Poisson) distribution (Lambert 1992). In this experiment, the “zeros” are those who did not
donate. The ZIP technique assumes that people fall into this zero group because of one of two
reasons (Lambert 1992): subjects either chose not to donate, or subjects did not donate because
of some other constraint. The ZIP regression determines membership in the true zero group, and
simultaneously predicts the counts (actual donation) of those not in the true zero group. The ZIP
regression generates two separate models (Long and Freese 2005). First, a logit model predicts
membership in the zero-coded group (i.e., those who did not donate). Then, a Poisson model
predicts the counts (i.e., the donation amount) for those subjects who are not in the zero-coded
group.
To test H1 and H2 (which expect Christian affiliation to influence making a donation and the
donation amount, respectively) and H3 and H4 (which expect the religiously framed message to
influence making a donation and the donation amount, respectively), I ran a ZIP regression with
data from the entire sample (N=836). To test H5 and H6 (which expect the religiously framed
message to influence making a donation and donation amount, respectively, in a Christian
subsample), I ran one additional ZIP regression for the Christian subsample (N=269). The
second model is similar to the first except I removed the unnecessary religious affiliation dummy
variables.
RESULTS
Table 9 presents the results of the ZIP regression for the entire sample. The first column
presents the unstandardized logit regression coefficients, and the second column presents the

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unstandardized Poisson regression coefficients. As a reminder, the logit model predicts the odds
of not making a donation versus making one, while the Poisson model predicts the amount of
donation for those respondents who made one.
The first hypothesis (H1) expects that Christians are less likely than non-Christians and nonreligious respondents to make a donation to protect against biodiversity loss. The results in
Table 9 do not support H1. The coefficients of the logit portion of the zero-inflated Poisson
regression (the first column in Table 9) predict membership in the “zero” group, in this case
those not making a donation. Self-identified Christians are just as likely to make a donation as
are non-Christians and non-religious subjects. These results are similar to other studies which
report no relationship between religion and environmental concern (e.g., Hayes and
Marangudakis 2000; Woodrum and Hoban 1994).
The second hypothesis (H2) expects that Christian affiliation decreases the donation amount
relative to non-Christians and non-religious people among donators. The Poisson regression
results (the second column in Table 9) indicate that, compared to Christians, non-religious
subjects and non-Christians donate more to protect against biodiversity loss. While many
Christians do donate some amount of money, the finding that they donate less than others aligns
with other studies that report a negative relationship between Christian affiliation and
environmental concern (e.g., Clements, McCright and Xiao 2013; Eckberg and Blocker 1989,
1996).
The third hypothesis (H3) expects that subjects who receive a religiously framed message are
less likely to make a donation to protect against biodiversity loss than subjects who receive a
control message or scientifically message. The fourth hypothesis (H4) expects that a religious
message will decrease donation amounts among donators, relative to a control message or

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scientifically message. The results in Table 9 do not support H3 or H4. Subjects exposed to the
religiously framed message are just as likely to make a donation as their counterparts exposed to
a control message or a scientifically framed message about biodiversity loss. In addition,
receiving the religiously framed message does not decrease the donation amount compared to
receiving the control or scientifically framed message. The results for H1 through H4 challenge
general claims of a greener Christianity discussed earlier. While Christian affiliation is
negatively associated with donation amount, there appears to be no relationship between
Christianity and actually making donation. There is also no relationship between a religiously
framed message and making a donation or donation amount. These findings provide additional
evidence that, at best, Christians are indifferent toward the environment, at least with respect to
donating toward this environmental cause.
Before discussing the results that pertain to the last two hypotheses, I discuss the
performance of the remaining variables in Table 9. As expected, the results of the logit portion
of the ZIP regression indicate that willingness to pay or sacrifice for the environment and a proenvironmental worldview (NEP) are the only statistically significant predictors of making a
donation to protect against biodiversity loss (first column in Table 9). Individuals reporting low
willingness to pay and low support for the NEP are significantly more likely to not make a
donation. No other predictors in the model explain whether subjects make a donation.
The third column in Table 9 presents the Poisson portion of the ZIP regression that predicts
donation amount for those subjects identified as donators in the logit portion of the regression.
Willingness to pay or sacrifice for the environment and support for the NEP positively predict
donation amount, consistent with other findings about willingness to pay (Dunlap and Scarce
1991;O’Connor et al. 1999), NEP (Dunlap et al. 2000; Hunter and Rinner 2004) and general

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environmental concern. Also, altruism positively predicts donation amount in agreement with
previous results about values and general environmental concern (e.g., Dietz, Fitzgerald, and
Shwom 2005), and values and biodiversity loss specifically (e.g., Hunter and Rinner 2004).
Consistent with most environmental concern research (e.g., McCright 2010; Xiao and McCright
2012), and research about biodiversity protection (Czech, Devers, and Krausman 2001; Hunter
and Rinner 2004), females donate more than males. Age positively predicts donation amount
which contradicts results for general environmental concern (e.g., Dunlap, Xiao, and McCright
2001; Xiao and McCright 2012) and for biodiversity protection specifically (Hunter and Rinner
2004). In this study, educational attainment, as well as the number of science courses a
respondent has taken, negatively predict donation amount. This result is contrary to other
research that reports that people who know more about science are more concerned about species
loss (Hamilton, Cutler and Schaefer 2012).
The results in Table 10 allow for a test of the fifth and sixth hypotheses (H5 and H6).
Because people are more likely to accept information from credible and trusted sources (e.g.,
Chaiken and Maheswaran 1994; McCright and Dunlap 2011), I expected that Christians would
find the religiously framed message to be more credible and persuasive than the control and
scientifically framed messages. Thus, H5 expects that in a subsample of Christian respondents,
the religiously framed message would increase the likelihood of making a donation compared to
the control message and scientifically framed message. The results in Table 10 do not support
H5. There was not a statistically significant difference in the likelihood of making a donation
between Christians who received the control message and Christians who received the
religiously framed message, The results in Table 10 for Christians who received the religiously
framed message are similar to the results in Table 9 for the entire sample . These results suggest

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that a religious message promoting a greener Christianity does not encourage people to donate to
this environmental cause. However, Christians who received the scientifically framed message
were more likely to make a donation than Christians who received the control message. These
results are not similar to the results in Table 9 for the entire sample. The results for the Christian
subsample are unexpected given the evidence described earlier that indicate some Christian
religious people have negative attitudes about science (Campbell and Curtis 1996; Evans and
Evans 2008) and are less influenced by scientific arguments (Brossard et al. 2009; Ho, Brossard
and Scheufele 2007). Receiving the scientific message is the strongest predictor of making a
donation in this subsample of Christians, providing some evidence that refutes the notion of a
conflict between science and religion.
Finally, H6 expects that Christians receiving the religiously framed message donate more
than Christians receiving the control and scientifically framed messages. The results in Table 10
(second column) partially support this hypothesis. Christians who received the religiously
framed message donated more money to protect against biodiversity loss than subjects who
received the control message. These results provide suggestive evidence that religious messages
may be effective in promoting pro-environmental behaviors among Christians. Thus, these
findings seem to support the results of previous research that people are more likely to accept
information from sources they trust and find credible (e.g., Chaiken and Maheswaran 1994;
McCright and Dunlap 2011). This also suggests that a green Christian message may increase
environmental concern in some Christians. Finally, there is no difference in donation amount
between those who received a religious or scientific message about biodiversity loss.

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CONCLUSION
There have been over 100 well-documented species extinctions over the last 100 years
worldwide. Approximately 25% of the plant and animal species in the U.S. are threatened with
extinction (Millennium Ecosystem Assessment 2005). In light of this, communities,
nongovernmental environmental organizations, and governments are active partners in efforts to
protect against further biodiversity loss, generally using scientific arguments to promote action to
prevent further loss. In addition, some religions promote attention to biodiversity loss. Because
a large proportion of the U.S. public reports some religious affiliation (mostly Christian), it is
important to investigate the performance of religiously and scientifically framed messages for
promoting action about biodiversity loss. An emerging green Christian movement in the US
suggests it is important to determine how effective religiously framed environmental messages
are in increasing environmental concern. This study uses a convenience sample of subjects
recruited on Amazon Mechanical Turk to conduct an experiment that examines how religiously
and scientifically framed messages about biodiversity loss influences a choice to make donations
to protect against biodiversity loss. If religious messages are effective at increasing concern
about environmental problems, this provides an important tool for green Christian leaders to use
to enhance support for addressing environmental problems in the U.S.
I found that self-reported Christian religious affiliation does not influence the likelihood of
making a donation to protect against biodiversity loss. In other words, Christians were no more
or less likely to make a donation than were non-religious subjects and non-Christians. However,
when Christians did make a donation, they donated less than non-religious people and nonChristians. Subjects who received the religiously framed message were just as likely to make a
donation as participants who read a control or scientifically framed message about biodiversity

70

loss. In addition, the religiously message did not decrease the donation amount compared to a
control or scientifically framed message.
These results provide equivocal evidence about a greener Christianity. I found that Christian
affiliation was negatively associated with donation amount. However, there was no relationship
between Christianity and actually making donation, or between a religiously framed message and
making a donation and donation amount. In a subsample of Christians, the religiously framed
message did not influence people to make a donation to protect against biodiversity loss,
compared to a control message. Interestingly, a scientifically framed message increased the
likelihood of making a donation in Christians. Further, when a Christian made a donation, the
control message decreased the donation amount relative to a religiously framed message.
Finally, there was no difference in donation amount between Christians who received the
religiously framed message and the scientifically framed message.
The Millennium Ecosystem Assessment (2005) estimates that the U.S. spends hundreds of
millions of dollars per year to deal with biodiversity losses caused by ecosystem destruction,
changes in biodiversity brought upon by invasive species, and responses to extreme events (fires,
floods, etc.) that are partially attributed to biodiversity losses. Much of this spending comes
from tax dollars and donations from U.S. citizens. Because there is a cost associated with these
changes, additional research like that described here is important to determine how different
message framing techniques promote action to prevent further biodiversity loss. The results of
this study point to other areas of fruitful research.
First, future experiments could vary the information that is included as part of the messages.
I included information from the Millennium Ecosystem Assessment (2005) that detailed the
number and rate of species extinction. However, this was general information related to the

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entire world. Willingness to pay and sacrifice for the environment might be influenced by
proximity to environmental problems, so future studies might include information related to
biodiversity changes and loss in the United States or even in specific regions of the U.S. to
determine if details about a local problem might heighten awareness and willingness to donate.
Second, future experiments should continue to examine the influence of messages on various
aspects of environmental concern, but these messages should be designed using different framing
techniques. While the messages used in this study come from public reports, and therefore have
high external validity, they also do not use positive or negative frames, or motivational and
sacrificial frames, that are generally tested in the messaging literature. Some of these framing
techniques (especially those that call for sacrifice) may be more effective in religious people. As
such, green Christian leaders could use results of future studies to help understand techniques
that allow for a greater diffusion of green Christianity and further enhance support to address
environmental problems.

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CHAPTER 5
CONCLUSION
Discussions about conflict, separation, or ambivalence between science and religion are as
old as science itself, with evidence suggesting both negative and positive relationships between
religion and science. Although there is a general lack of understanding of scientific concepts by
the public, correct scientific knowledge of environmental problems is often a key predictor of
intentions to behave pro-environmentally. At the same time, religion plays an important part in
the daily lives of millions of Americans. If religion plays a role in the lives of adherents, even in
the face of increasing secularization, it is important to examine the effects of religion, as well as
religious messages, on matters related to science and the environment. My dissertation used
quantitative methods to explore the intersections of religion, science, and environmental concern
by testing hypothesis related to two main questions: 1) how do religious affiliation, belief, and
commitment characteristics influence attitudes about science in contemporary U.S. society? and
2) how do religiously and scientifically framed messages influence specific facets of
environmental concern?
The first essay (Chapter 2) investigated the relationship between religious affiliation, belief,
and commitment patterns, and attitudes about science. The results of the first essay (Chapter 2)
indicate that while Christians have more negative attitudes about science than non-Christians and
non-religious people, there is very little difference in attitudes across Christian denominations.
In addition, religiosity and fundamentalism have very little influence on attitudes about science.
Although Christians do tend to be more negative about science than non-Christians and nonreligious people, my results suggest that there is very little conflict between religion and science
in the U.S. general public, at least for the attitudes investigated here.

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As most existing research reports results using data sets from the 1980s and early 1990s, this
study provides a necessary update using nationally representative data from 2010. In addition, I
used several survey items to develop composite measures of both religiosity and fundamentalism
in this study. Most of the existing literature reports the influence of single-item measures of
religiosity or fundamentalism on attitudes about science. By creating composite measures of
these concepts, I provide a more comprehensive picture of the influence of religiosity and
fundamentalism. I also modeled the potential mediating effects of religiosity and
fundamentalism on the relationship between religious affiliation and attitudes about science,
directly testing what past studies only suggested or implied.
Because most of the existing research in the US, including that reported here, focuses
narrowly on Christian religious affiliation, there is very little that I can say about the influence of
non-Christian religions on attitudes about science. Future research can address this gap by
oversampling respondents from non-Christian religions, administering surveys to targeted
samples of non-Christians, and conducting field research on non-Christian subjects to allow for
deeper understanding of how adherents to these different faiths perceive and understand science.
In addition, existing measures of religiosity and fundamentalism focus narrowly on Christian
practices. Future work should strive to develop and use measures that also focus on nonChristians traditions. Finally, the measures used in this study only refer to attitudes about
science in general. We do not know if the public makes distinctions between the social and
biophysical sciences, or between the goals of more basic science that adds to a body of
knowledge and more applied science that contributes to economic development. Future
measures of attitudes about science should be developed to distinguish between different types
and goals of science.

74

The second and third essays report the results of experiments that tested the influence of
religiously and scientifically framed messages on two specific types of environmental concern:
support for a water use restriction policy (Chapter 3) and donations to protect against
biodiversity loss (Chapter 4). Results of the second essay indicate that Christian affiliation did
not influence agreement with proposed water restrictions. However, a Christian religiously
framed message reduced agreement with water use restrictions—even among self-identified
Christians. These results suggest that religiously framed messages may not significantly increase
environmental concern among Christians, as suggested by many Green Christian leaders.
Apart from investigating the influence of religious and scientific messaging, the third essay
(Chapter 4) addresses a gap in the willingness to pay or sacrifice literature. In contrast to the
existing literature that asks subjects to self-report their hypothetical willingness to pay or
sacrifice for the environment, the experiment in the third essay asked subjects to make an actual
sacrifice by donating their own earned money to a program that works to solve a specific
environmental problem: biodiversity loss. This experiment had two specific outcomes: (1)
whether a subject made a donation or not and (2) the size of the donation amount.
Regarding making a donation or not, the results of the third essay show that subjects who
received the religiously framed message were just as likely to make a donation as participants
who read a control or scientifically framed message about biodiversity loss. Among Christians,
the religiously framed message did not influence people to make a donation to protect against
biodiversity loss, compared to a control message. However, receiving the scientifically framed
message increased the likelihood of making a donation among Christians, suggesting no apparent
conflict between religion and science in this sample.

75

For the size of the donation, the results for the entire sample show that neither the religiously
framed message nor the scientifically framed message made a difference in donation amount
compared to the control message. However, a religiously framed message increased the
donation amount among Christians, relative to a control message, providing some evidence that a
green Christian message may influence concern about biodiversity loss. Finally, among
Christians, the scientifically framed message did not influence donation amount relative to the
control message.
The research described in the second and third essays adds to the existing literature by
directly comparing the influence of religiously and scientifically framed messages on specific
types of environmental concern. The results of the two experiments may help us understand the
effectiveness of attempts at crafting messages to increase environmental concern in targeted
audiences that might otherwise be reluctant to act pro-environmentally because of religious
characteristics or attitudes about science. Finally, these experiments also add to the growing
body of evidence suggesting that systems that allow easy and affordable data collection are as
reliable as large internet-based, resource intensive options.
Future experiments should continue to examine the influence of a range of religiously and
scientifically framed messages on various types of environmental concern. While the messages
used in this study come from public reports, and therefore have high external validity, they also
do not use positive or negative frames, or motivational and sacrificial frames, that are generally
tested in the messaging literature. Some of these framing techniques may be more effective in
religious people (especially those that call for sacrifice). Future experiments might also vary the
information that is presented as part of the experimental manipulations. For example, the
proposed policy in the second essay (Chapter 3) required a 50% reduction in water use. Future

76

studies might vary the reduction amount, as well as the types of restricted activities (e.g., filling
the swimming pool or washing the car), to determine how support for, or opposition to, the
policy differs based on these variations. Future donation experiments (Chapter 4) could focus on
environmental problems in specific locations to determine if details about a local problem might
heighten awareness and willingness to donate. Green Christian leaders could use results of
future experiments to help understand techniques that allow for a greater diffusion of green
Christianity and further increase environmental concern.
Overall, this dissertation contributed to the literature on religion, science, and environmental
concern in several ways. The results indicate that in spite of the small negative influence of
Christian affiliation on attitudes about science in Chapter 2, there does not appear to be a large
conflict between religious characteristics and attitudes about science in contemporary US
society. In addition, the messaging experiments revealed that a scientifically framed message
increased the likelihood of making a donation to protect against biodiversity loss among
Christians (Chapter 4), providing some evidence that Christians accept and act on scientific
messages. The messaging experiments provide equivocal results about a greening of
Christianity. While the Christian religiously framed message reduced agreement with water use
restrictions (Chapter 3), a religiously framed message increased the donation amount to an
environmental organization among Christians (Chapter 4). These results suggest that religiously
framed messages may not consistently increase environmental concern among Christians.
Clearly additional studies are necessary to determine how religiously framed messages influence
environmental concern.

77

APPENDICES

78

APPENDIX A: TABLES

79

Table 1: General Social Survey Variables Used in the Study
Variable

GSS Item*

Coding

Attitudes about Science Indicators

Mean

SD

3.11

.64

3.61

.99

2.86

1.11

2.52

.76

Mean

SD

Scientific research is necessary and should be supported by the federal government
ADVFRONT
1 “strongly disagree” to 4 “strongly agree”
Modern science does more harm than good
HARMGOOD
1 “strongly agree” to 5 “strongly disagree”
We believe too much in science, not enough in faith
SCIFAITH
1 “strongly agree” to 5 “strongly disagree”
Science makes our way of life change too fast
TOOFAST
1 “strongly agree” to 4 “strongly disagree”
Religious Affiliation Indicators
No religion
Christian
Non-Christian
Catholic
Mainline Protestant
Evangelical Protestant
Black Protestant

RELIG
RELIG
RELIG
RELIG, DENOM, OTHER
RELIG, DENOM, OTHER
RELIG, DENOM, OTHER
RELIG, DENOM, OTHER

0 “any religion” to 1 “no religion”
0 “all others” to 1 “Christian religion”
0 “all others” to 1 “non-Christian religion”
0 “not Catholic” to 1 “Catholic”
0 “not Mainline Protestant” to 1 “Mainline Protestant”
0 “not Evangelical Protestant” to 1 “Evangelical Protestant”
0 “not Black Protestant” to 1 “Black Protestant”

80

.18
.77
.05
.24
.13
.23
.08

.38
.42
.21
.43
.34
.42
.27

Table 1: (cont’d)
Religiosity and Fundamentalism Indicators
Religiosity (Alpha=.85)
Attend services
Belief in God
How often you pray
Religious activities
Strength of belief
Importance of religion
How religious

ATTEND
GOD
PRAY
RELACTIV
RELITEN
RELLIFE
RELPERSN

Fundamentalism (Alpha=.76)
Literalism of bible
BIBLE

How fundamentalist
Been “born again”
Jesus as savior

FUND
REBORN
SAVESOUL

Factor Loading
1 “never” to 9 “more than once a week”
1 “don’t believe” to 6 “know God exists”
1 “never” to 6 “several times a day”
1 “never” to 11 “several times a day”
1 “no religion” to 4 “strong”
1 “strongly disagree” to 5 “strongly agree”
1 “not religious” to 4 “very religious”
1 “Bible is an ancient book of fables, legends, history, and
moral precepts recorded by men” to 3 “Bible is the
actual word of God and is to be taken literally”
1 “respondent’s religion is liberal” to
3 “respondent’s religion is fundamentalist”
1 “no” to 3 “has had a born again experience”
1 “no” to 3 “has tried to convince others to accept Jesus”

Political and Socio-Demographic Controls
Political ideology
Party identification
Female
White
Age
Education
Income

POLVIEWS
PARTYID
SEX
RACE
AGE
EDUC
REALINC

.80
.77
.79
.68
.77
.78
.82

.75
.70
.80
.80
Mean

1 “extremely conservative” to 7 “extremely liberal”
1 “strong Republican” to 7 “strong Democrat”
0 “male” to 1 “female”
0 “non-white” to 1 “white”
actual age in years
number of years of school completed
family income in dollars

*Variable names from Smith, Marsden, Hout, and Kim (2010); data source is 2010 General Social Survey.
81

SD

3.92
1.46
4.35
1.95
.56
.50
.76
.43
47.97
17.68
13.46
3.15
30813.31 29348.29

Table 2: Attitudes about Science among Different Religious Subgroups in 2010
All Respondents in Sample

Self-Identified Christians in Sample

Christian

NonReligious

NonChristian

Attitudes about Science Indicators
Scientific research is
necessary and should be
supported by fed govt
% choosing “agree”
or “strongly agree”
86.9

85.9

87.1

97.5*

86.3

79.6#

91.2

90.3

Modern science does more
harm than good
% choosing “disagree”
or “strongly disagree”

62.3

59.3*

72.6

71.0

72.4#

55.5

47.8

59.3##

We believe too much in science
and not enough in faith
% choosing “disagree”
or “strongly disagree”
30.6

24.1*

52.5

48.4

32.6#

19.6

17.4

24.3##

Science makes our way of life
change too fast
% choosing “disagree”
or “strongly disagree”

48.7

66.4*

43.9

50.4

51.1

41.3

43.2

Total

51.5

Mainline Evangelical Black
Protestant Protestant Protestant Catholic

* Percent of specified subgroup in entire sample is statistically different from other two subgroups in entire sample (α=0.05)
# Percent of specified Christian denomination is statistically different from other three denominations in self-identified Christian
subgroup (α=0.05)
##Percent of Catholics is less than Mainline Protestants but greater than Evangelical and Black Protestants (α=0.05)
82

Table 3: Standardized Coefficients from OLS Regression Models Predicting Attitudes about Science: Entire Sample

Model

Research is Necessary;
Fed Govt Should Support

Science Does More
Harm than Good

Believe in Science;
Not Enough in Faith

Science Makes Life
Change too Fast

Religion Indicators
Non-religious
Non-Christian
Reference: Christian

.02
.09*

.10***
.05*

.23***
.08**

.02
.10***
-.09***
.17***
.04
.17***
.12***

.08**
.07*
-.04
.13***
.00
.16***
.15***

.08*
-.04

Political and Socio-Demographic Controls
Party identification
Political ideology
Female
White
Age
Education
Income

.05
.15**
-.07
-.02
.02
.18***
.04

-.03
.08
-.08
.07
.02
.18****
.12**

Sample Size

611

1270

1289

620

R-Squared

.07

.14

.18

.08

* p<.05 ** p<.01 *** p<.001

83

Table 4: Standardized Coefficients from OLS Regressions Predicting Attitudes about Science: Christian Subsample
Research is Necessary
Fed Govt Should Support
Models

Science Does More
Harm than Good

1

2

3

4

5

6

7

8

Religion Indicators
Evangelical Protestant
-.03
Black Protestant
-.13
Catholic
.01
Reference: Mainline Protestant

-.00
-.12
.01

-.01

.02

-.12**
-.07
-.10*

-.04
-.05
-.10*

.01

-.01

Religiosity
Fundamentalism

-.07
.01

-.07
-.01

-.06
-.01

-.03
-.10

-.04
-.11*

-.04
-.10

Evangelical Protestant x Religiosity

.06

Evangelical Protestant x Fundamentalism
Political and Socio-Demographic
Controls
Party identification
.08
Political ideology
.15**
Female
-.07
White
-.10
Age
-.04
Education
.20**
Income
.05
Sample Size
410
R-Squared
.08
* p<.05 ** p<.01 *** p<.001

.01
.00

.08
.14*
-.06
-.12
-.01
.20**
.07

.10
.13*
-.04
-.07
-.04
.16**
.10

.11
.12
-.05
-.07
-.04
.16**
.11

391
.07

361
.07

361
.07

84

.09

-.01
.09
-.10**
.14**
.01
.16***
.09*
894
.10

-.03
.08*
-.08*
.11*
.02
.16***
.08*
855
.11

-.01
-.01
.06*
.06
-.09*
-.09*
.13*
.13*
.04
.03
.26*** .26***
.02
.01
767
.13

767
.13

Table 4: (cont’d)
Believe in Science
Not Enough in Faith
Models

9

Science Makes Life
Change too Fast

10

11

12

13

14

15

16

Religion Indicators
Evangelical Protestant
-.15**
Black Protestant
-.13*
Catholic
-.04
Reference: Mainline Protestant

.00
-.04
-.03

-.02

.03

.08
.00
-.01

.07
-.00
-.03

.03

.08

Religiosity
Fundamentalism

-.12**
-.18**

-.15***
-.17***

-.04
.00

-.09
.06

-.08
.05

Evangelical Protestant x Religiosity

.03

Evangelical Protestant x Fundamentalism
Political and Socio-Demographic
Controls
Party identification
.11**
Political ideology
.02
Female
-.03
White
.07
Age
-.02
Education
.14***
Income
.16***
Sample Size
905
R-Squared
.10
* p<.05 ** p<.01 *** p<.001

-.15***
-.17***

.05
.00

.08*
-.01
.02
.02
-.00
.14***
.15***
863
.14

.10*
-.02
.02
.01
-.01
.20***
.13***
772
.17

.09*
-.02
.02
.01
.01
.20***
.13***
772
.17

85

-.04

-.06
.14*
-.08
.05
.03
.19***
.10
411
.06

-.06
.14*
-.07
.06
.05
.20***
.09
393
.06

-.07
.12
-.07
.03
.03
.19**
.11

-.01
.11
-.07
.04
.03
.18**
.11*

361
.06

361
.06

Table 5: Description, Coding, Mean, and Standard Deviation of the Variables Used in the Study
Variable

Coding

Mean

SD

3.97

1.16

Mean

SD

.34
.09
2.62

.47
.29
2.37

Mean

SD

4.89
.35
.83
29.01

1.49
.48
.38
8.74

3.52
2.46
.49

.84
1.26
.50

.36

.48

Dependent Variable
Agreement with proposed
water use restriction policy

1 “strongly disagree” to 5 “strongly agree”

Religion Indicators
Christian
Non-Christian
Attendance

0 “all others” to 1 “Christian religion”
0 “all others” to 1 “non-Christian religion”
1 “never” to 9 “greater than once per week”

Political, Socio-Demographic, and Biophysical Indicators
Political ideology
Female
White
Age
Education
Income
Homeowner
Drought location

1 “extremely conservative”
to 7 “extremely liberal”
0 “male” to 1 “female”
0 “non-white” to 1 “white”
actual age in years
1 “less than high school” to
5 “more than 4-year degree”
1 “$0-$24,999” to 5 “$100,000 and up”
0 “renting” to 1 “owned/being bought”
0 “does not live in drought zip code” to
1 “lives in drought zip code”

Variable

Coding

Standardized
Factor Loadings

Environmental Concern Indicators
Personal Worry
air pollution
contamination of soil/water by toxic waste
extinction of plant and animal species
loss of tropical rain forests
pollution of drinking water
pollution of rivers, lakes, and reservoirs

1 “not at all” to 4 “a great deal”
1 “not at all” to 4 “a great deal”
1 “not at all” to 4 “a great deal”
1 “not at all” to 4 “a great deal”
1 “not at all” to 4 “a great deal”
1 “not at all” to 4 “a great deal”

Willingness to Pay or Sacrifice to Protect the Environment
pay much higher taxes
1 “not at all willing” to 5 “very willing”
pay much higher prices
1 “not at all willing” to 5 “very willing”
accept cuts in your standard of living
1 “not at all willing” to 5 “very willing”

86

.72
.82
.69
.69
.75
.80

.85
.93
.70

Table 6: Standardized Coefficients from Structural Equation Model Predicting Agreement with Water Policy, Entire Sample (N=608)
Willingness to Pay or Sacrifice
For the Environment
Direct Indirect
Total

Independent Variables
Religion Indicators
Christian
-.06
Non-Christian
.04
Reference: No Religion
Attendance
.05
Political and Socio-Demographic Controls
Political ideology
.23*
Female
.03
White
.04
Age
-.07*
Education
.07*
Income
-.02
Homeowner
-.04
Drought location
.01
Environmental Concern Indicators
Personal Worry
.55*
Willingness to Pay
-Message
Religious Message
-Reference: Scientific Message

Religious
Message
Direct Indirect

Total

Agreement with
Proposed Water Policy
Direct Indirect
Total

---

-.06
.04

.07
.06

.00
.00

.07
.07

.06
.00

-.02
.00

.04
.00

--

.05

-.02

.00

-.02

.04

.01

.05

---------

.23*
.03
.04
-.07*
.07*
-.02
-.04
.01

-.01
.03
.05
-.03
-.04
-.01
-.00
.03

.01
.00
.00
-.00
.00
.00
-.01
.00

.00
.04
.05
-.03
-.04
-.01
-.01
.03

.11*
.03
.10*
.11*
.05
.01
-.05
.03

.04*
.00
.00
-.01
.02*
.00
-.01
.00

.15*
.03
.10*
.10*
.07
.01
-.05
.03

--

.55*
--

.01
.06

.03
.00

.04
.06

.10
.18*

.09*
-.01*

.19*
.17*

--

--

--

--

--

-.13*

--

-.13*

Chi square
Adjusted Goodness-of-Fit Index (AGFI)
Incremental Fit Index (IFI)
Root Mean Squared Error of Approximation (RMSEA)

308.78, p<.001
.90
.86
.07, p<.001

* p<.05

87

Table 7: Standardized Coefficients from Structural Equation Model Predicting Agreement with Water Policy, Christian Subsample
(N=206)
Willingness to Pay or Sacrifice
Religious
Agreement with
For the Environment
Message
Proposed Water Policy
Independent Variables
Direct Indirect
Total
Direct Indirect
Total
Direct Indirect
Total
Religion Indicators
Attendance
.02
Political and Socio-Demographic Controls
Political ideology
.21*
Female
.03
White
-.02
Age
-.13*
Education
.13*
Income
.03
Homeowner
.00
Drought location
.05
Environmental Concern Indicators
Personal Worry
.59*
Willingness to Pay
-Message
Religious Message
-Reference: Scientific Message

--

.02

.00

.00

.00

.13

.01

.13

---------

.21*
.03
-.02
-.13*
.13*
.03
.00
.05

.04
.13
.02
-.11
-.10
.10
-.09
.09

.01
.00
.00
-.01
.01
.00
.00
.00

.04
.13
.02
-.12
-.10
.10
-.09
.09

-.02
-.08
.09
.21*
-.03
-.05
-.02
.09

.07*
-.01
-.01
-.03
.06*
.00
.01
.00

.05
-.09
.08
.18*
.02
-.06
-.01
.09

--

.59*
--

.01
.04

.02
.00

.03
.04

.11
.34*

.19*
-.01

.30*
.33*

--

--

--

--

--

-.14*

--

-.14*

Chi square
Adjusted Goodness-of-Fit Index (AGFI)
Incremental Fit Index (IFI)
Root Mean Squared Error of Approximation (RMSEA)

209.14, p<.001
.89
.92
.05, p=.264

* p<.05

88

Table 8: Description, Coding, Mean, and Standard Deviation of Variables Used in the Study
Variable
Dependent Variables
Made donation (0 “no donation” to 1 “any donation”)
Donation amount in $ (for 415 respondents who made a donation)

Mean

SD

.50
.18

.50
.15

Value Orientation Indicator
Altruism (Alpha = .86) (standardized factor loading in parentheses)
22.57
Please indicate how important each of these is as a guiding principle in your life:
(1 “not at all important” to 5 “extremely important”)
A world if peace, free of war and conflict (.70)
Equality, equal opportunity for all (.67)
Protecting the environment, preserving nature (.86)
Respecting the earth, harmony with other species (.88)
Social justice, correcting injustice, care for the weak (.69)
Unity with nature, fitting into nature (.78)
Environmental Concern Indicators
Willingness to Pay (Alpha = .88) (standardized factor loading in parentheses)
How willing would you be to: (1 “not at all willing” to 5 “very willing”)
Accept cuts in standard of living to protect environment? (.85)
Pay much higher taxes to protect the environment? (.92)
Pay much higher prices to protect the environment? (.92)
New Ecological Paradigm (Alpha = .87)
(standardized factor loading in parentheses)
Listed below are statements about the relationship between humans and the
environment. Please indicate your level of agreement:
(1 “strongly disagree” to 5 “strongly agree”)
We are approaching limit of number of people earth can support (.68)
Humans interfere with nature, produces disastrous consequences (.79)
Humans are severely abusing environment (.83)
Plants and animals have as much right as humans to exist (.61)
Despite special abilities, humans still subject to laws of nature (.55)
Earth like spaceship with very limited room and resources (.73)
The balance of nature is very delicate and easily upset (.76)
Continue on present course, experience ecological catastrophe (.83)

89

4.75

9.39

3.07

30.89

6.06

Table 8: (cont’d)
Variable

Coding

Mean

SD

22.84

5.46

.56
.33
.11
2.53

.50
.47
.31
2.31

Political and Socio-Demographic Characteristics
Political ideology
1 “extremely conservative” to 7 “extremely liberal” 4.94
Party identification
1 “strong Republican” to 7 “strong Democrat”
4.81
Female
0 “male” to 1 “female”
.38
White
0 “non-white” to 1 “white”
.74
Age
1 “18-19” to 8 “80 or greater”
2.58
Educational attainment
1 “less than high school” to 5 “more than 4-yr degree”3.44
Income
1 “$0-$24,999” to 5 “$100,000 and up”
2.36
College science courses
1 “none” to 5 “21+”
2.24

1.52
1.63
.49
.44
1.10
.89
1.23
.99

Personal Environmental Worry (Alpha = .89)
(standardized factor loading in parentheses)
Please indicate if you personally worry about this problem:
(1 “not at all” to 4 “a great deal”)
Air pollution (.76)
Climate change (.67)
Contamination of soil and water by toxic waste (.78)
Extinction of plant and animal species (.78)
The loss of tropical rain forests (.79)
Pollution of drinking water (.75)
Pollution of rivers, lakes, and reservoirs (.85)
Urban sprawl and loss of open spaces (.63)
Religious Affiliation Indicators
Non-religious
0 “any religion” to 1 “no religion”
Christian
0 “all others” to 1 “Christian religion”
Non-Christian
0 “all others” to 1 “non-Christian religion”
Religious service attendance 1 “never” to 9 “greater than once per week”

90

Table 9: Zero-Inflated Poisson Regression Predicting Donation to Protect against Biodiversity
Loss, Entire Sample
Logit Model Predicting
No Donation
Unstandardized
Coefficients (SE)
Message Effect
Control message
Scientific message
Reference: Religious message

ZIP Model Predicting
Donation Amount
Unstandardized
Coefficients (SE)

.01 (.19)
-.28 (.18)

-.02 (.03)
.01 (.02)

Religion and Science Indicators
Non-Religious
Non-Christian
Reference: Christian
Religious service attendance
College science courses

-.04 (.04)
-.05 (.08)

.00 (.01)
-.03 (.01)*

Altruism and Environmental
Concern Indicators
Altruism
New Ecological Paradigm
Personal environmental worry
Willingness to pay

-.01 (.02)
-.04 (.02)**
-.02 (.02)
-.14 (.03)***

.02 (.00)***
.02 (.00)***
-.01 (.00)
.07 (.01)***

Socio-Demographic and
Political Characteristics
Female
Age
White
Educational attainment
Income
Party identification

-.29 (.16)
-.03 (.07)
-.04 (.17)
.00 (.10)
.04 (.06)
-.01 (.04)

.06 (.03)*
.09 (.01)***
.05 (.03)
-.10 (.02)***
.01 (.01)
.00 (.01)

Constant

3.71 (.64)***

1.30 (.12)***

Sample size

.18 (.21)
.37 (.28)

836

Likelihood ratio Chi-Square = 677.00, p<0.001
Vuong test of ZIP versus Standard Poisson, z=17.09, p<0.001
*p<.05, **p<.01, ***p<.001

91

.14 (.04)***
.22 (.04)***

415

Table 10: Zero-Inflated Poisson Regression Predicting Donation to Protect against Biodiversity
Loss, Christian Subsample
Logit Model Predicting
No Donation
Unstandardized
Coefficients (SE)
Message Effect
Control Message
Scientific Message
Reference: Religious Message

ZIP Model Predicting
Donation Amount
Unstandardized
Coefficients (SE)

.10 (.32)
-.87 (.35)**

-.26 (.06)***
.05 (.04)

Religion and Science Indicators
Religious Service Attendance
College Science Courses

-.02 (.05)
-.16 (.16)

.00 (.01)
.00 (.02)

Altruism and Environmental
Concern Indicators
Altruism
New Ecological Paradigm
Personal environmental worry
Willingness to Pay

-.04 (.04)
-.04 (.03)
-.03 (.03)
-.12 (.06)*

.00 (.01)
.01 (.01)*
.00 (.01)
.10 (.01)***

Socio-Demographic and
Political Controls
Female
Age
White
Educational attainment
Income
Party identification

-.48 (.29)
-.14 (.12)
-.01 (.31)
.00 (.17)
.05 (.12)
-.03 (.07)

.04 (.05)
.05 (.02)**
-.06 (.05)
-.13 (.03)***
-.06 (.02)**
-.02 (.01)

Constant

5.04 (1.17)***

1.98 (.21)***

Sample size

279

Likelihood ratio Chi-Square = 267.30, p<0.001
Vuong test of ZIP versus Standard Poisson, z=8.80, p<0.001
*p<.05, **p<.01, ***p<.001

92

141

APPENDIX B: FIGURE

93

Figure 1: Analytical Model

Religion Indicators
Christian
Non-Christian
Attendance

Political, SocioDemographic, and
Biophysical Indicators
Political ideology
Female
White
Age
Education
Income
Homeowner
Drought location

Religious
Message
Willingness to
Pay or Sacrifice

Agreement with
Proposed Water
Use Restriction
Policy

Environmental Concern
Indicator
Personal Worry

94

REFERENCES

95

REFERENCES

Aklin, Michael and Johannes Urpelainen. 2013. “Debating Clean Energy: Frames, Counter
Frames and Audiences.” Global Environmental Change
http://dx.doi.org/10.1016/j.gloenvcha.2013.03.007
Allum, Nick, Patrick Sturgis, Dimitra Tabourazi and Ian Brunton-Smith. 2008. “Science
Knowledge and Attitudes across Cultures: A Meta-Analysis.” Public Understanding of
Science 17:35-54.
Bak, Hee-Je. 2001. “Education and Public Attitudes toward Science: Implications for the
‘Deficit Model’ of Education and Support for Science Technology.” Social Science
Quarterly 82(4):779-795.
Baker, Joseph O. 2012. “Perceptions of Science and American Secularism.” Sociological
Perspectives 55(1):167-188.
Berenguer, Jaime. 2007. “The Effect of Empathy in Proenvironmental Attitudes and
Behaviors.” Environment and Behavior 39(2):269-283.
Berger, Peter L. 1967. “A Sociological View of the Secularization of Theology.” Journal for
the Scientific Study of Religion 6(1):3-14.
Berger, Peter L. 2008. “Secularization Falsified” First Things February:23-27.
Berkes, Fikret. 2007. “Community-based Conservation in a Globalized World.” Proceedings of
the National Academy of Sciences 104(39):15188-15193.
Bhaduri, Sumit. 2003. “Science, Society, and Technology: Three Cultures and Multiple
Visions.” Journal of Science Education and Technology 12(3):303-308.
Bhagwat, Shonil, Nigel Dudley, and Stuart Harrop. 2011. “Religious Following in Biodiversity
Hotspots: Challenges and Opportunities for Conservation and Development.” Conservation
Letters 4(3):234–240
Binder, A. 2007. “Gathering Intelligence on Intelligent Design: Where did it Come From,
Where is it Going, and How should Progressives Manage it?” American Journal of
Education 113:549-576.
Blocker, T. Jean, and Douglas Lee Eckberg. 1997. “Gender and Environmentalism: Results
from the 1993 General Social Survey.” Social Science Quarterly 78(4):841-858.
Blunch, Niels J. 2013. Introduction to Structural Equation Modeling using IBM SPSS Statistics
and AMOS. London: Sage Publications, Inc.

96

Bollen, Kenneth A., and J. Scott Long (eds.). 1993. Introduction. Testing Structural Equation
Models. Newbury Park, CA: Sage Publications, Inc.
Bord, Richard J., Robert E. O’Connor, and Ann Fisher. 2000. “In What Sense Does the Public
Need to Understand Global Climate Change?” Public Understanding of Science 9:205-218.

Boyd, Heather Hartwig. 1999. “Christianity and the Environment in the American Public.”
Journal for the Scientific Study of Religion 38(1):36-44.
Brody, Samueal D., Sammy Zahran, Arnold Vedlitz and Himanshu Grover. 2008. “Examining
the Relationship Between Physical Vulnerability and Public Perceptions of Global Climate
Change in the United States.” Environment and Behavior 40(1):72-95.
Brossard, Dominique, Dietram A. Scheufele, Eunkyung Kim, and Bruce V. Lewenstein. 2009.
“Religiosity as a Perceptual Filter: Examining Processes of Opinion Formation about
Nanotechnology.” Public Understanding of Science 18(5):546-558.
Brulle, Robert J., Jason Carmichael, and J. Craig Jenkins. 2012. “Shifting Public Opinion on
Climate Change: An Empirical Assessment of Factors Influencing Concern Over Climate
Change in the U.S., 2002-2010.” Climatic Change 114:169-188.
Buckser, Andrew. 1996. “Religion, Science, and Secularization Theory on a Danish Island.”
Journal for the Scientific Study of Religion 35(4):432-441.
Buhrmester, Michael, Tracy Kwang, and Samuel D. Gosling. 2011. “Amazon's Mechanical
Turk: A New Source of Inexpensive, Yet High-Quality, Data? Perspectives on
Psychological Science 6(1) 3-5.
Byrne, Barbara M. 1998. Structural Equation Modeling with AMOS: Basic Concepts, Applications,
and Programming. Mahwah, NJ: Erlbaum.

California Academy of Sciences. 2009. “American Adults Flunk Basic Science.” Science
Daily, Retrieved April 13, 2013, from
http://www.sciencedaily.com/releases/2009/03/090312115133.htm.
Campbell, Robert A. and James E. Curtis. 1996. “The Public’s View on the Future of Religion
and Science: Cross-National Survey Results.” Review of Religious Research 37(3):260-267.
Carlsson, Frederick and Peter Martinsson. 2001. “Do Hypothetical and Actual Marginal
Willingness to Pay Differ in Choice Experiments?” Journal of Environmental Economics
and Management. 41:179-192.
Carlton, Jim. 2013. “California Farm Belt Shrivels--Dry Winters, Water Rationing Force
Output Cuts, Test Fragile Regional Economy,” The Wall Street Journal, June 27, p-A3.

97

Chaiken, Shelly and Durairaj Maheswaran. 1994. “Heuristic Processing Can Bias Systematic
Processing: Effects of Source Credibility, Argument Ambiguity, and Task Importance on
Attitude Judgment.” Journal of Personality and Social Psychology 66(3):460-73.
Chamberlain, Gary L. 2008. Troubled Waters: Religion, Ethics, and the Global Water Crisis.
New York: Rowman & Littlefield.
Chaves, Mark. 1994. “Secularization and Declining Religious Authority.” Social Forces
72(3):749-774.
Christiano, Kevin J, William H Swatos and Peter Kivisto. 2008. “The ‘Religion’ of
Secularization and the History of Religions” in Sociology of Religion, 2nd ed. New York:
Rowman and Littlefield.
Chuvieco, Emilio. 2012. “Religious Approaches to Water Management and Environmental
Conservation.” Water Policy 14:9-20.
Clements, John M., Aaron M. McCright, and Chenyang Xiao. 2013. “Green Christians? An
Empirical Examination of Environmental Concern within the U.S. General Public.”
Organization and Environment doi: 10.1177/1086026613495475
Clements, John M., Aaron M. McCright, and Chenyang Xiao. 2014. “An Examination of the
‘Greening of Christianity’ Thesis within the U.S. General Public, 1993-2010.” Journal for
the Scientific Study of Religion Accepted for Publication.
Critchley, Christine R. 2008. “Public Opinion and Trust in Scientists: The Role of the Research
Context, and the Perceived Motivation of Stem Cell Researchers.” Public Understanding of
Science 17:309-327.
Czech, Brian, Patrick K Devers, and Paul R Krausman. 2001. “The Relationship of Gender to
Species Conservation Attitudes.” Wildlife Society Bulletin 29(1):187-194.
Dardis, Frank E. 2007. “The Role of Issue-Framing Functions in Affecting Beliefs and opinions
about a Sociopolitical Issue.” Communication Quarterly 55(2):247-265.
Dein S. 2005. “Spirituality, Psychiatry, and Participation: A Cultural Analysis.” Transcultural
Psychiatry 42:526:544.
Dietz, Thomas, Amy Fitzgerald, and Rachael Shwom. 2005. “Environmental Values.” Annual
Review of Environmental Resources 30:335-372.
Dunlap, Riley E. 1998. “Lay Perceptions of Global Risk: Public Views of Global warming in
Cross-National Context.” International Sociology 13(4):473-498.

98

Dunlap, Riley E. and Kent D. Van Liere. 1978. “The ‘New Environmental Paradigm:’ A
Proposed Measuring Instrument and Preliminary Results.” Journal of Environmental
Education 9(4):10-19.
Dunlap, Riley E. and Rik Scarce. 1991. “The Polls—Poll Trends: Environment Problems and
Protection.” Public Opinion Quarterly 55(4):651–672.
Dunlap, Riley E. and Robert Emmet Jones. 2002. “Environmental Concern: Conceptual and
Measurement Issues.” Pp. 482-514 in Handbook of Environmental Sociology, edited by R. E.
Dunlap and W. Michelson. Westport, CT: Greenwood Press.
Dunlap, Riley E., Chenyang Xiao, and Aaron M. McCright. 2001. “Politics and Environment in
America: Partisan and Ideological Cleavages in Public Support for Environmentalism.”
Environmental Politics 10(4):23-48.
Dunlap, Riley E., Kent D. Van Liere, Angela G. Mertig and Robert Emmet Jones. 2000.
“Measuring Endorsement of the New Ecological Paradigm: A Revised NEP Scale.” Journal
of Social Issues 56(4):425-442.
Eckberg, Douglas L. and T. Jean Blocker. 1989. “Varieties of Religious Involvement and
Environmental Concerns: Testing the Lynn White Thesis.” Journal for the Scientific Study
of Religion 28: 509-517.
Eckberg, Douglas L. and T. Jean Blocker. 1996. “Christianity, Environmentalism, and the
Theoretical Problem of Fundamentalism.” Journal for the Scientific Study of Religion
35:343-355.
Eister, Allan W. 1978. “Religion and Science in AD 1977…” Journal for the Scientific Study
of Religion 17(4): 347-358.
Ellison, Christopher G. and Marc A. Musick. 1995. “Conservative Protestantism and Public
Opinion toward Science.” Review of Religious Research 36(3): 245-262.
Evangelical Environmental Network. 2013. Home Page. Retrieved October 16, 2013
(www.creationcare.org).
Evans, John H. 2002. “Religion and Human Cloning: An Exploratory Analysis of the First
Available Opinion Data.” Journal for the Scientific Study of Religion 41(4):747-758.
Evans, John H. 2013. “The Growing Social and Moral Conflict between Conservative
Protestantism and Science.” Journal for the Scientific Study of Religion 52(2): 368-385.
Evans, John H. and Michael S. Evans. 2008. “Religion and Science: Beyond the
Epistemological Conflict Narrative.” Annual Review of Sociology 34: 87-105.

99

Evans, Michael S. 2012. “Supporting science: Reasons, Restrictions, and the Role of Religion.”
Science Communication 34(3):334-362.
Finger, Matthias. 1994. "From Knowledge to Action? Exploring the Relationships between
Environmental Experiences, Learning, and Behavior. Journal of Social Issues 50(3):141-60.
Freeman, Patricia K. and David J. Houston. 2011. “Rejecting Darwin and Support for Science
Funding.” Social Science Quarterly 92(5):1151-1168.
Gauchat, Gordon. 2008. A Test of Three Theories of Anti-Science Attitudes. Sociological
Focus 41(4):337-357.
Gauchat, Gordon. 2011. “The Cultural Authority of Science: Public Trust and Acceptance of
Organized Science.” Public Understanding of Science 20:1-20.
Gauchat, Gordon. 2012. “Politicization of Science in the Public Sphere: A Study of Public
Trust in the United States.” American Sociological Review 77(2):167-187.
Genia, Vicky. 1997. “The Spiritual Experience Index: Revision and Reformulation.” Review of
Religious Research 38:344-61.
Gifford, Katie and John C. Bernard. 2004. “The Impact of Message Framing on Organic Food
Purchase Likelihood.” Journal of Food Distribution Research 35(3):19-28.
Gifford, Katie and Louise A. Comeau. 2011. “Message Framing Influences Perceived Climate
Change Competence, Engagement, and Behavioral Intentions.” Global Environmental
Change 21:1301-1307.
Gilg, Andrew and Stewart Barr. 2006. “Behavioural Attitudes Toward Water Saving? Evidence
from a Study of Environmental Actions.” Ecological Economics 57:400–414.
Goidel, Robert K. and Matthew C. Nisbet. 2006. “Exploring the Roots of Public Participation in
the Controversy over Stem Cell Research and Cloning. Political Behavior 28(2):175–192.
Greeley, Andrew M. 1993. “Religion and Attitudes toward the Environment”. Journal for the
Scientific Study of Religion, 32:19-28.
Guth, James L., John C. Green, Lyman A. Kellstedt, and Corwin E. Schmidt. 1995. “Faith and
Environment: Religious Beliefs and Attitudes on Environmental Policy.” American Journal
of Political Science 39:364-382.
Hamilton, Lawrence, Matthew J. Cutler and Andrew Schaefer. 2012. “Public Knowledge about
Polar Regions Increases while Concern Remains Unchanged.” Carsey Institute Issue Brief
42:1-8

100

Hand, Carl M. Kent D. Van Liere. 1984. “Religion, Mastery-Over-Nature, and Environmental
Concern.” Social Forces 63:555-570.
Harke, Jerry. 2008. Water Conservation Today Key to Agriculture’s Water Tomorrow.
Retrieved September 7, 2013
(http://www.fb.org/index.php?action=newsroom.focus&year=2008&file=fo0519.html).
Hayes, Bernadette C and Manussos Marangudakis. 2000. “Religion and Environmental Issues
with Anglo-American democracies.” Review of Religious Research 432(2):159-174.
Hayes, Bernadette C and Vicki N. Tariq. 2000. “Gender Differences in Scientific Knowledge
and Attitudes toward Science: A Comparative Study of Four Anglo-American Nations.”
Public Understanding of Science 9(4)433-447.
Hitzhusen, Gregory E. 2007. “Judeo-Christian Theology and the Environment: Moving Beyond
Skepticism to New Sources for Environmental Education in the United States.”
Environmental Education Research 13:55-74.
Ho Shirley S., Dominique Brossard, and Dietram A. Scheufele. 2008. “Effects of Value
Predispositions, Mass Media Use, and Knowledge on Public Attitudes toward Embryonic
Stem Cell Research.” International Journal of Public Opinion Research 20(2):171–192.
Ho, Shirley S., Dietram A. Scheufele and Elizabeth A. Corley. 2012. “Making Sense of Policy
Choices: Understanding the Roles of Value Predispositions, Mass Media, and Cognitive
Processing in Public Attitudes toward Nanotechnology. Journal of Nanoparticle Research
12:2703–2715.
Hochschild, Jennifer, Alex Crabill and Maya Sen. 2012. “Technology Optimism or Pessimism:
How Trust in Science Shapes Policy Attitudes toward Genomic Science” in Issues in
Technology Innovation Series Number 21 of 23.
Hunter, Lori M., and Joan Brehm. 2003. “Qualitative Insight into Public Knowledge of, and
Concern with, Biodiversity.” Human Ecology 31(2):309-320.
Hunter, Lori M., and Lesley Rinner. 2004. “The Association between Environmental
Perspective and Knowledge and Concern with Species Diversity.” Society and Natural
Resources 17:517-532.
Iwata, Osamu. 1996. "Some Attitudinal and Literacy Correlates of Proenvironmentalism."
Social Behavior and Personality 24(4):335-342.
Jenkins, Edgar W. 2003. “Environmental Education and the Public Understanding of Science.”
Frontiers in Ecology and the Environment 1(8):437-443.
Joreskog, Karl G. and Dag Sorbom. 1989. LISREL 7: A Guide to the Program and Applications
(2nd ed.). Chicago: SPSS.

101

Kanagy, Conrad L. and Fern K. Willits. 1993. “A ‘Greening’ of Religion?: Some Evidence
from a Pennsylvania Sample.” Social Science Quarterly 74:674-683.
Kanagy, Conrad L. and Hart M. Nelsen. 1995. “Religion and Environmental Concern:
Challenging the Dominant Assumptions.” Review of Religious Research 37: 33-45.
Kroll, Jerome and Paul Erikson. 2002. “Religion and Psychiatry.” Current Opinion in
Psychiatry 15:549-554.
Krosnick, Jon A., Allyson L. Holbrook, and Penny S. Visser. 2000. “The Impact of the Fall
1997 Debate about Global Warming on American Public Opinion.” Public Understanding of
Science 9:239–60.
Lach, Denise and Stephanie Sanford. 2010. “Public Understanding of Science and Technology
Embedded in Complex Institutional Settings.” Public Understanding of Science 19(2):130146.
Lambert, Diane. 1992. “Zero-inflated Poisson Regression with an Application to Defects in
Manufacturing.” Technometrics 34(1):1–14.
Lewenstein, Bruce V. 1992. “The Meaning of ‘Public Understanding of Science’ in the United
States after World War II.” Public Understanding of Science 1:45-68.
Lewkowicz, Michael A. 2006. “The Effectiveness of Elite Cues as Heuristics in Proposition
Elections.” American Politics Research 34(1):51-68.
Long, J. Scott, and Jeremy Freese. 2005. Regression Models for Categorical Dependent
Variables Using Stata. Second Edition. College Station, TX: Stata Press.
Lord, Kenneth R. 1994. “Motivating Recycling Behavior: A Quasiexperimental Investigagion
of Message and Source Strategies.” Psychology and Marketing 11(4):341-358.
Maranta, Alessandro, Michael Guggenheim, Priska Gisler, and Christian Pohl. 2003. “The
Reality of Experts and the Imagined Lay Person.” Acta Sociologica 46(2):150-165.
Mason, Winter and Siddharth Suri. 2012. “Conducting Behavioral Research on Amazon’s
Mechanical Turk.” Behavior Research Methods 44(1):1-23.
McCright, Aaron M. 2010. “The Effects of Gender on Climate Change Knowledge and
Concern in the American Public.” Population and Environment 32:66–87.
McCright, Aaron M. and Riley E. Dunlap. 2000. “Challenging Global Warming as a Social
Problem” An Analysis of the Conservative Movement’s Counter-Claims.” Social Problems
47(4):499-522.

102

McCright, Aaron M. and Riley E. Dunlap. 2011. “The Politicization of Climate Change and
Polarization in the American Public’s Views of Global Warming, 2001-2010.” The
Sociological Quarterly 52(2):155-194.
Merton, Robert K. 1938. "Science and the Social Order." Philosophy and Science 5:321-337.
Millennium Ecosystem Assessment, 2005. “Ecosystems and Human Well-being: Biodiversity
Synthesis.” World Resources Institute, Washington, DC.
Miller, Jon D. 2004. “Public Understanding of, and Attitudes Toward, Scientific Research:
What We Know and What We Need to Know.” Public Understanding of Science 13:273294.
Morton, Thomas A., Anna Rabinovich, Dan Marshall and Bret Schneider. 2011. “The Future
that May (Or May Not) Come: How Framing Changes Responses to Uncertainty about
Climate Change Communications.” Global Environmental Change 21:103-109.
National Ground Water Association. 2013. Retrieved September 7, 2013
(http://www.ngwa.org/About/Pages/about.aspx).
Nature Conservancy. 2013. Home Page. Retrieved November 6, 2013
(http://www.nature.org/).
Negi, Chandra Singh. 2005. “Religion and Biodiversity Conservation: Not a Mere Analogy.”
International Journal of Biodiversity Science and Management. 1(2):85-96.
Nicks, Denver. 2013. “Western Black Rhino Declared Extinct.” Retrieved November 6, 2013
(http://science.time.com/2013/11/06/western-black-rhino-declared-extinct/#ixzz2kHpQaFTk)
Nisbet, Matthew C. 2005. “The Competition for Worldviews: Values, Information, and Public
Support for Stem Cell Research.” International Journal of Public Opinion Research 17:90112.
Nisbet, Matthew C., and Robert K. Goidel. 2007. “Understanding Citizen Perceptions of
Science Controversy: Bridging the Ethnographic-Survey Research Divide.” Public
Understanding of Science 16(4):421-440.
O’Connor, Robert E, Richard J Bord, and Ann Fisher. 1999. “Risk Perceptions, General
Environmental Beliefs, and Willingness to Address Climate Change.” Risk Analysis
19(3):461–471.
Palmer, Martin, ed. 2010. Faith in Water. Bath, United Kingdom: Alliance of Religions and
Conservation.
Paolacci, Gabriele, Jesse Chandler and Panagiotis G. Ipeirotis. 2010. “Running Experiments on
Amazon Mechanical Turk.” Judgment and Decision Making 5(5):411-419.

103

Pew Research Center. 2013. Pew Research Religion and Public Life Project: Religious
Landscape Survey. Retrieved November 27, 2013
(http://religions.pewforum.org/affiliations).
Powell, Maria C. and Mathilde Colin. 2008. “Meaningful Citizen Engagement in Science and
Technology, What Would it Really Take?” Science Communication 30(1):126-136.
Randolph, Bill and Patrick Troy. 2008. “Attitudes to Conservation and Water Consumption.”
Environmental Science and Policy 11:441-455.
Scheitle, Christopher P. 2005. “In God We Trust: Religion and Optimism toward
Biotechnology.” Social Science Quarterly 86(4):846-856.
Schultz, P. Wesley. 2001. “The Structure of Environmental Concern, Concern for Self, Concern
for People, and the Biosphere.” Journal of Environmental Psychology 21(4):327-339.
Shapin, Steven. 2007. “Science and the Modern World.” Pp. 433-448 in The Handbook of
Science and Technology Studies 3rd Edition, edited by Edward J. Hackett, Olga
Amsterdamska, Michael Lynch, and Judy Wajcman. Cambridge, MA: The MIT Press.
Sherkat, Darren E. and Christopher G. 2007. “Structuring the Religion-Environment
Connection: Identifying Religious Influences on Environmental Concern and Activism.”
Journal of the Scientific Study of Religion 46:71-85.
Shiklomanav, Igor. 1993. "World Fresh Water Resources" in Water in Crisis: A Guide to the
World’s Fresh Water Resources, edited by Peter H. Gleick. New York: Oxford University
Press.
Simon, Richard M. 2010. “Gender Differences in Knowledge and Attitude towards
Biotechnology. Public Understanding of Science 19(6):642-653.
Smith, Gary Scott. 1985. “The Great Secularization Debate in America.” Reformed Journal
35(7):15-19.
Smith, Tom W., Peter Marsden, Michael Hout, and Jibum Kim. 2013. General Social Surveys,
1972-2012 [machine-readable data file] Principal Investigator: Tom W. Smith. CoInvestigators: Peter V. Marsden and Michael Hout. Sponsored by National Science
Foundation. Chicago: National Opinion Research Center.
Solomon, Joan. 1993. “Reception and Rejection of Scientific Knowledge: Choice, Style and
Home Culture.” Public Understanding of Science 2:111-121.
Southern Baptist Environment & Climate Initiative. 2013. Home Page. Retrieved October 16,
2013 (www.baptistcreationcare.org).

104

Spence, A., W. Poortinga, C. Butler, and N.F. Pidgeon. 2011. “Perceptions of Climate Change
and Willingness to Save Energy Related to Flood Experience.” Nature Climate Change
1:46-49.
Stark, Rodney. 1999. “Secularization R.I.P.” Sociology of Religion 60(3):249-273.
Steel, Brent S, Denise Lach and Vijay A Satyal. 2006. “Ideology and Scientific Credibility:
Environmental Policy in the American Pacific Northwest.” Public Understanding of Science
15:481-495.
Steensland, Brian, Jerry Z. Park, Mark D. Regnerus, Lynn D. Robinson, W. Bradford Wilcox
and Robert D. Woodberry. 2000. “The Measure of American Religion: Toward Improving
the State of the Art.” Social Forces 79(1): 291-318.
Stern, Paul C., Thomas Dietz, Linda Kalof and Gregory A. Guagnano. 1995. “Values, Beliefs,
and Proenvironmental Action: Attitude Formation toward Emergent Attitude Objects.”
Journal of Applied Social Psychology 25:1611-1636.
Stern, Paul C., Thomas Dietz, Troy Abel, Gregory A. Guagnano, and Linda Kalof. 1999. “A
Value-Belief-Norm Theory of Support for Social Movements: The case of
Environmentalism.” Research in Human Ecology 6(2):81-97.
Sturgis, Patrick and Nick Allum. 2004. “Science in Society: Re-evaluating the Deficit Model of
Attitudes.” Public Understanding of Science 13:55-74.
Tate Denise G., and Martin Forchheimer. 2002. “Quality of Life, Life Satisfaction, and
Spirituality: Comparing Outcomes between Rehabilitation and Cancer Patients.” American
Journal of Physical Medicine and Rehabilitation 81:400-410.
Trankina, Michele L. 1993. “Gender Differences in Attitudes toward Science.” Psychological
Reports 73(1):123-130.
Trumbo, Craig W. and Garrett J. O'Keefe. 2001. “Intention to Conserve Water: Environmental
Values, Planned Behavior, and Information Effects. A Comparison of Three Communities
Sharing a Watershed.” Society and Natural Resources: An International Journal 14(10):889899.
Trumbo, Craig W. and Garrett J. O'Keefe. 2005. “Intention to Conserve Water: Environmental
Values, Reasoned Action, and Information Effects Across Time.” Society and Natural
Resources: An International Journal 18(6):573-585.
U.S. Department of the Interior. 2013. Water SMART: A Three-year Progress Report.
Retrieved September 7, 2013 (http://www.usbr.gov/WaterSMART/docs/WaterSMART-theeyear-progress-report.pdf).

105

U.S. Drought Monitor. 2013. Home page. Retrieved October 16, 2013 (http://
droughtmonitor.unl.edu).
U.S. Fish and Wildlife Service. 2013. Conserving the Nature of America. Retrieved November
6, 2013 (http://www.fws.gov/midwest/EcosystemConservation/ecosystem_approach.html)
U.S. Water Alliance. 2013. EPA Launches National Water Conservation Campaign. Retrieved
September 7, 2013 (http://www.uswateralliance.org/2010/08/01/epa-launches-national-waterconservation-campaign/).
VandeVelde, Liesbeth, Wim Verbeke, Michael Popp, and Guido VanHuylenbroeck. 2010. “The
Importance of Message Framing for Providing Information About Sustainability and
Environmental Aspects of Energy.” Energy Policy 38:5541–5549.
Virginia Commonwealth University (VCU) Center for Public Policy. 2010. VCU Life Science
Survey 2010: A National Public Opinion Survey conducted for VCU Life Sciences by the
VCU Center for Public Policy. Richmond. Available at
http://www.vcu.edu/lifesci/images2/survey2010.pdf.
Water.org. 2013. “Water.org Fact Sheet.” Retrieved September 9, 2013
(http://static.water.org/public/pdf/WaterorgFactsheet2012.pdf).
Weber, Max. 1946 [1918]. “Science as a Vocation.” pp. 129-156 in From Max Weber: Essays
in Sociology, edited by H.H. Gerth and C.Wright Mills. New York: Oxford University Press.
Whitmarsh, Lorraine. 2008. “Are Flood Victims More Concerned about Climate Change than
other People? The Role of Direct Experience in Risk Perception and Behavioral Response.”
Journal of Risk Research 11(3):351-374.
Wilkinson, Katherine K. 2010. “Climate’s Salvation?: Why and How American Evangelicals
are Engaging with Climate Change. Environment 52(2):47-57.
Wines, Michael. 2013. “Wells Dry, Fertile Plains Turn to Dust,” The New York Times, May 19,
p. A1.
Wolkomir, Michelle, Michael Futreal, Eric Woodrum, and Thomas Hoban. 1997a.
“Denominational Subcultures of Environmentalism.” Review of Religious Research
38(4):325-343.
Wolkomir, Michelle, Michael Futreal, Eric Woodrum, and Thomas Hoban. 1997b. “Substantive
Religious Belief and Environmentalism.” Social Science Quarterly 78:96-108.
Woodrum, Eric and Thomas Hoban. 1994. “Theology and Religiosity Effects on
Environmentalism.” Review of Religious Research 35:193-206.

106

World Wide Fund for Nature. 2013. Home Page. Retrieved November 6, 2013
(http://worldwildlife.org/about).
Wynne, Brian. 1992. “Misunderstood Understanding: Social Identities and Public Uptake of
Science.” Public Understanding of Science 1:281-304.
Wynne, Brian. 1993. “Public Uptake of Science: A Case for Institutional Reflexivity.” Public
Understanding of Science 2:321-337.
Xiao, Chenyang and Aaron M. McCright. 2012. “Explaining Gender Differences in Concern
about Environmental Problems in the United States.” Society and Natural Resources
25:1067-1084.
Yamane, David. 1997. “Secularization on Trial: In Defense of a Neosecularization Paradigm.”
Journal for the Scientific Study of Religion 36(1):109-122.
Zahran, Sammy, Samuel D. Brody, Himanshu Grover, and Arnold Vedlitz. 2006. “Climate
Change Vulnerability and Policy Support.” Society and Natural Resources 19:771-789.

107