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Journal of Environmental Planning and Management, 46(4), 000–000, July 2003

Diffusion of US Army Chemical Weapons Disposal Technologies: Public Perception of Technology Attributes

BRYAN L. WILLIAMS,* HOI K. SUEN,† SARAH E. RZASA,† TANYA HEIKKILA† & MARIA PENNOCK-ROMAN† *University of Arizona, Arizona Prevention Center (EBR Lab), Campus PO Box 245163 Tucson, AZ 85724, USA. E-mail: [email protected] † The Pennsylvania State University (Received September 2001; revised May 2003)

ABSTRACT This study was conducted to identify factors that influence individuals’ acceptance of environmental management technologies for cleaning up hazardous materials. The study sample consisted of approximately 2600 residents living within emergency response zones surrounding eight US Army’s Chemical Weapons Stockpile sites. The findings suggest that residents perceive clear differences between the desirable characteristics of the two technologies: incineration and neutralization. In a relative comparison, the majority of positive technological attributes were associated with incineration. Positive perceptions toward incineration were associated with individuals who trust the Army, who perceive that the media have made them more trusting of weapons disposal activities, who are ready to participate, and who are male. Unlike incineration, there was insufficient evidence that individual factors influence variations in perceptions toward neutralization. No community factor was related to perceptions toward either incineration or neutralization.

Background As evidenced by recent world events, the American military is confident in its ability to produce and use cutting edge technologies in the battlefield. Yet this confidence seems to wane when it comes to the military’s ability to develop technologies to deal with hazardous byproducts of its cutting edge weaponry. The American military has historically struggled with its inability to gain public acceptance of weaponry disposal technologies. Hence, the relics of past wars remain, posing an increasing threat to public health and the environment. Ironically, the USA is asking other countries to do what it has been unable to do, dispose of its chemical weapons arsenal. In fact, since 1985 the US Army has only destroyed about one-quarter of the agent in its original stockpile (http:// www.pmcd.apgea.army.mil/default.asp). Additionally, only about half of weapons disposal facilities have reached completion (http:// 0964-0568 Print/1360-0559 Online/03/040000-00  2003 University of Newcastle upon Tyne DOI: 10.1080/0964056032000133134

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500 B. L. Williams, H. K. Suen, S. E. Rzasa, T. Heikkila & M. Pennock-Roman www.pmcd.apgea.army.mil/default.asp). This is well behind the projected schedule for the programme and violates international treaty. Public opposition to incineration has been one of the biggest obstacles for the Army programme to overcome. The Chemical Weapons Working Group (CWWG), a non-profit organization based in Kentucky has longed opposed the US Army’s use of incineration to destroy the chemical weapons stockpile (see http://cwwg.org). In March of 2003, CWWG filed a federal lawsuit (1⬊03CV00645) that contends that the US Army has violated the National Environmental Policy Act (NEPA) in its pursuit of the incineration programme (see http://cwwg.org). Public efforts like those of CWWG have thwarted Army efforts to dispose chemical weapons in a timely manner. Despite the programme’s numerous reorganizations and abundant public outreach, the public is simply not willing to take the Army’s word that incineration is the way to go (NRC, 1998). The failure of the disposal programme begs the question, ‘why does the public frequently oppose the Army’s choice of technology’? The answer to this question is elusive. Since technology choices are often swayed by public opinion, it is important to understand why the public either supports or opposes a given technology. The choice of disposal technologies has been divisive issue in communities surrounding the chemical weapons stockpile over the years (NRC, 1998). Dialogue between the military and the public has been further stymied by the looming threat of terrorism. Arguably, the need to protect ‘national security’ has afforded the military with increasing latitude when it comes to keeping the public in the dark. Nonetheless, if the Army expects the public to accept or participate in its technological decisions it must first understand how the public perceives proposed technologies. The purpose of this paper, therefore, is to identify and explain the extent to which residents living near the eight chemical weapons stockpile sites attribute specific characteristics to two types of hazardous waste disposal technologies. Additionally, the authors identify specific individual and community level factors that explained the public’s perceptions toward the two types of hazardous waste disposal technologies. This study not only provides insights into the factors that shape public opinion toward the Army’s Chemical Demilitarization programme; it also contributes to a broader understanding of how environmental management decisions are made more generally by contributing to decision-making theory in environmental management. This study examined how and why people associate specific technological characteristics with actual disposal technologies and wanted to determine how much one’s community influences the perceptions of such characteristics. This study addressed two main questions: do people living near chemical weapons sites believe incineration of weapons is more advantageous, compatible, triable, observable and less complex than is neutralization of chemical weapons? To what extent are residents’ beliefs a function of their individual characteristics (i.e. ethnicity) and/or the community within which they reside? Public Opposition to Environmental Technology Public opposition to hazardous waste disposal technologies, especially incineration is hardly uncommon (Luloff et al., 1998; McAvoy, 1998; Smith & Marquez,

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2000). There is increasing public pressure on government agencies to adopt environmentally friendly technologies and practices (Schwepker & Cornwell, 1991; Arntzen, 1992; Farhar, 1993; Electric Power Research Institute, 1997; Berry, 1999; Norberg-Bohm, 1999) and to be more accountable for environmental practices (Arntzen, 1992; Berry, 1999). The federal government frequently resists such pressure contending that political agendas not scientific facts primarily fuel public opposition to technology (US Congressional Subcommittee on Basic Research, 2000). At best, government agencies and politicians may choose technologies that appease opponents, irrespective of scientific evidence that suggests that the chosen technologies are not optimal. In such case, neither the public’s nor the government’s interests are best served. Diffusion of Innovations theory provides a framework for better understanding the public’s perceptions toward such technologies.

Diffusion of Technology Numerous studies have examined how and why individuals and organizations accept or reject various technological innovations using Diffusion of Innovations theory (Stiff, 1994; Rogers, 1995a; Dearing et al., 1996; Ferrence, 1996; Ganesh et al., 1997; Johnson et al., 1997). Diffusion theory is founded on the idea that the dispersal and subsequent adoption of innovations across populations is a predictable and observable process (Rogers, 1983, 1995a). Diffusion theory is increasingly being used to explain the adoption of environmental technology in varied contexts (Purvis & Outlaw, 1995; Dupuy, 1997; Geiser & Greiner, 2000; Kemp et al., 1999; Norberg-Bohm, 1999; Repplin-Hill, 1999; Rennings, 2000; Siegrist, 2000). To date, most of the literature details the impact of government on the diffusion of environmentally friendly (or ‘green’) technologies in the private sectors (Norberg-Bohm, 1999; Geiser & Greiner, 2000). Thus, it is found that the literature is ripe for helping explore the ways in which citizens and interest groups can shape environmental technology innovations, particularly decisions by public agencies. At the same time, the literature is relatively thin on identifying the particular characteristics of individuals or groups that determine diffusion. A number of key concepts can summarize the basic explanations of decision making provided by this theory. An ‘innovation’ refers to an idea, procedure or object that is perceived as new by an individual (Rogers, 1983, 1995a; Steckler, 1998). ‘Diffusion’ is a process in which members of a social system are able over a period of time to communicate an innovation or a new idea. This communication involves making potential adopters aware of an innovation’s existence, its characteristics, and its significance within the social order (Rogers, 1983, 1995a). ‘Adoption’ refers to the actual utilization or acceptance of a given innovation (Rogers, 1983, 1995a). ‘Technological attributes’ are the perceived and actual characteristics of a technology that influence various aspects of adoption (i.e., speed) (Oldenburg et al., 1997). ‘Change agents’ represent groups or individuals within a social system (e.g. community) that are key players, opinion leaders and agents who can influence peoples’ attitudes toward an innovation (Rogers, 1995a; Johnson et al., 1997). The diffusion and adoption of environmental technologies provides a good illustration of how these concepts can be applied.

502 B. L. Williams, H. K. Suen, S. E. Rzasa, T. Heikkila & M. Pennock-Roman The Applicability of Diffusion Theory to Environmental Technologies in the Public Sector It might be asserted that the public does not make individual choices about the selection of environmental technologies (i.e. incineration), thus undermining the relevance of diffusion theory in this context. Albeit, selecting an environmental technology is not the equivalent of consumers choosing DVD over VCR players. However, the public is playing an increasingly important role in environmental decision making and the choice of environmental technology (Schwepker & Cornwell, 1991; Farhar, 1993, Electric Power Research Institute, 1997; Goldstein et al., 2000; Siegrist, 2000; Williams et al., 2001). In fact, segments of the public have played a central role in the US Army’s selection and testing of waste disposal technologies (NRC, 1999). Hence, it is reasonable to suggest that the certain sectors of the public (i.e. activist and special interest groups) epitomize Rogers’s concept of a ‘change agent’. These groups fulfill several change agent roles including creating a ‘perceived need for change’ and ‘creating an information exchange network’ within itself (Rogers, 1995a). In support of this literature, an array of policy and management theories have acknowledged the power of interest groups to shape policy agendas and decisions, particularly in the environmental field (e.g. see Sabatier & Jenkins Smith, 1994; Schneider & Ingram 1997). As change agents, the public influences environmental technology decisions. As Burns (1969) stated, “technology transfer is accomplished by agents, not agencies” (p. 12). ‘Citizen’ lobbies (e.g. environmentalists) have grown exponentially in numbers and in power, within the confines of the Beltway (Berry, 1999). ‘Washington’ has taken environmental causes more seriously over the past decade, giving life to a new sort of liberalism (Berry, 1999). Consequently, prominent citizen lobbies (i.e. Environmental Defense Fund, Sierra Club, etc.) do impact selection and regulation of environmental technologies (i.e. incineration), thus affecting the diffusion of various environmental innovations. For example, Berry found that citizen lead ‘environmentalist’ groups prevailed on about 83% of the environmental issues presented before the 104th Congress (Berry, 1999). Current public opinion suggests that government will have to address the public’s growing empathy toward environmental issues. For example, in a recent Gallup Poll, 47% of respondents identified themselves as being ‘environmentalist’ (Gallup, 2000). Samuelson argues that the public opinion dictates the progress and direction of public policy in our nation. Consequently, in the future it appears that increasing numbers of ‘environmentally concerned’ citizens will help shape environmental policy (Samuelson, 1999).

Factors that Affect the Acceptance of Environmental Management Technologies Environmental management technologies are often new or innovative, particularly when the need to respond to environmental contamination is urgent. The general public, however, generally knows very little about existing and emerging environmental technologies (Cross, 1994). Once aware of an environmental technology, individuals or groups may choose to accept, reject, or ignore them. Community opposition to waste disposal technologies is typically stanch (Luloff et al., 1998; McAvoy, 1998; Smith & Marquez, 2000). Some experts contend that this opposition stems from the public’s ignorance and misunderstanding of

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waste disposal technologies, particularly incineration (Johnson-Cartee et al., 1992–93; Cross, 1994; Rogers, 1995b). H. Rogers (1995) states “members of the general public often have little training or experience in analyzing the impacts of technologic events on the environment or their health” (p. 12). The public and the scientific community typically disagree in their perceptions toward and understanding of environmental technologies, especially risk perceptions (Rogers, 1995a; Cross, 1994). This divergence of perception may slow down the diffusion of environmental technologies. For example, widespread public opposition to incineration impedes the placement and use of incinerators, irrespective of scientific support for the device (Cross, 1994; Blackwood, 1999). This divergence in perspective raises an important question, how does the lay public evaluate different types of environmental technologies? The literature tells us a lot about how people use common attributes to evaluate technologies before they decide whether to adopt (Rogers, 1983,1995a). The rate of adoption and extent of diffusion is greatly influenced by an individual’s perceptions of the attributions of a technology (Rogers, 1995a; Oldenburg et al., 1997). This is true even if such perceptions are erroneous. Some of the essential perceived attributes of the technology that have been found to influence the rate of adoption of an innovation include (1) the innovation’s relative advantage over other practices; (2) the innovation’s compatibility with needs and attitudes of adopters; (3) the innovation’s complexity; (4) the innovation’s reversibility; and (5) the observability of the results of the innovation. Overall, innovations that individuals perceive as having the attributes of greater relative advantage, compatibility, trialability, observability and less complexity will be adopted more rapidly than other innovations (Rogers, 1995a). In addition, technologies that have been around for a long time (i.e. telephone) are more readily adopted than new technologies (i.e. e-mail) (Ganesh et al., 1997). In fact, ‘proven’ technologies tend to have an advantage in the adoption process. People typically embrace familiar conventional technologies and reject the unknown (Ganesh et al., 1997). For example, we know that ‘unfamiliarity’ tends to amplify perceptions of personal and environmental risk (Covello, 1995). Hence, people may be less apprehensive toward conventional waste disposal technologies (i.e. incineration, landfill, etc.) than they would be of newer less proven technologies (i.e. plasma thermal waste treatment). There is abundant evidence that individual (i.e. age, sex, ethnicity) and community level factors (i.e. access to media) greatly influence the adoption of technologies in general (Sparkes & Kang, 1986; Reagan, 1991; Michaelson, 1993; Parcel et al., 1995; Paulussen, 1995; Rogers, 1995a; Shaperman & Backer, 1995; Ferrence, 1996; Jeffres & Atkin, 1996; Ganesh et al., 1997; Gruber, 1998). Despite this evidence, it is not known how people perceive disposal technologies in a diffusion context. That is, to what extent do people attribute these characteristics to hazardous waste disposal innovations? This study will examines how people apply the attributes of relative advantage, compatibility, trialability, observability, and complexity to chemical weapons disposal technologies. Diffusion of Technologies Designed to Dispose of the US Army’s Chemical Weapons Stockpile The power of the public to influence environmental technology decisions is clearly evident in the US Army’s chemical demilitarization programme. This

504 B. L. Williams, H. K. Suen, S. E. Rzasa, T. Heikkila & M. Pennock-Roman programme has spurred a number of public technological debates and scientific investigations (NRC, 1999). Mounting public pressure forced the Army to investigate alternative disposal technologies for at least four of the nine sites (NRC, 1999). The NRC states, “The most significant impetus for seeking alternative technologies to destroy assembled chemical weapons has been public opposition to incineration—and support for alternatives—by national activist groups and some members of the communities near the stockpile sites” (NRC, 1999, p. 4). In 1996, public pressure resulted in action, precluding adoption of the incineration technology at some sites. The US Army was required by Congress under Public Law 102–484 to investigate prospective alternatives to the ‘baseline incineration process’ for possible use at sites storing chemical weapon agent and not munitions (NRC, 1996). Public Law 104–208 required the Army to “identify and demonstrate not less than two alternatives to the baseline incineration process for the demilitarization of assembled chemical munitions” (NRC, 1999, p. 1). Four sites were earmarked for alternative technology testing, Richmond, Kentucky; Edgewood, Maryland; Newport, Indiana; and Pueblo, Colorado. Incineration was deemed appropriate for the remaining four sites, Umatilla, Oregon; Anniston, Alabama; Pine Bluff Arkansas; and Tooele, Utah. Finally, Public Law 104–201 necessitated that the NRC conduct an independent technical review and assessment of the technology packages that passed the Army’s original screening criteria (NRC, 1999). A special dialogue group of various public stakeholders was also formed to participate in the process. This group was established to ensure that the public would play a role in the selection of the alternative technology. Finally these laws lead to the formation of the Assembled Chemical Weapons Assessment (ACWA) and the Alternative Technologies and Approaches Program (ATAP) within the Army. The goal of these programmes was to test alternative technologies for disposing of assembled chemical weapons and unassembled chemical agents in bulk containers respectively. Progress of Existing Disposal Technologies Despite the comprehensive government effort, progress at most of the sites has been slow. As a result of the ‘testing’ process, three of the four sites, Newport and Edgewood have adopted an alternative technology to dispose of their chemical agent in bulk containers (NRC, 1998). These sites will use various forms of a process called ‘neutralization’ a method that “detoxifies the chemical agent but does not completely destroy its potential precursors” and “supercritical water oxidation” (NRC, 1998, p. 7). However, these technologies have not been fully implemented because of varying technical difficulties. Since 1996, the NRC has evaluated numerous alternative technologies and has suggested some viable alternatives to incineration (NRC, 1996, 1998, 2000). Incineration has only been used at two of the Army’s nine stockpile weapons locations, Tooele, Utah and Johnston Atoll. Despite millions of dollars in construction costs, the three remaining incineration sites in Alabama, Oregon, Arkansas have made no progress. The permitting process at these sites has been slowed by a number of factors including but not limited to lawsuits and environmental injustice claims (Associated Press, 2001). The lack of progress demonstrated by the Program Manager for Chemical Demilitarization recently prompted a major reorganization of the programme. The newly formed Chemi-


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cal Materials Agency will take over centralized control of both the Chemical Demilitarization Program (CDP) and the Soldier Biological and Chemical Command (SBCCOM) (US Army Press Release, 2003). As evidenced by the lack of progress, the Army’s adoption of disposal technologies has been less than optimal. As of 1999, the Army had destroyed less than 25% of its original stockpile. The continuing scientific and public debate over the efficacy of various disposal methods has made the 2007 deadline established by the Chemical Weapons Convention international treaty unobtainable (NRC, 1998). Developing a more complete understanding of the public’s perceptions toward the disposal technologies appears to be logical step in curbing this debate and moving forward with the programme.

Public Perceptions Toward Specific Disposal Technologies As seen in the chemical demilitarization programme, the public tends to take strong positions on environmental technologies. Exactly why the public allows the use of some environmental technologies and opposes the use of others is unclear. Heightened risk perception is frequently cited as the reason why the public opposes such technologies (Williams et al., 2001). This seems to ring true with the Army situation as well where citizens’ groups contend that incineration, “presents an imminent threat to public health” (NRC, 1999, p. 4). However, the public’s comprehension of and beliefs toward specific attributes of environmental technology is still not fully understood. Furthermore, the various factors that might influence the adoption of waste disposal technologies have yet to be identified. As shown in the literature, characteristics of technological innovations (e.g. relative advantage, compatibility, trialability, observability and complexity) greatly influence technological acceptance or opposition (Rogers, 1995a). The purpose of this study is to examine to what extent people associate innovation characteristics with actual disposal technologies and to determine how much a person’s community influences their perceptions of such characteristics. To this end, the study tested the following three hypotheses: H1: Residents will attribute a significantly higher number of positive technological characteristics toward incineration than they will with neutralization. H2: Resident attributions toward the two technologies will be significantly related to an individual’s demographic, personal, and psychological characteristics. H3: Resident attributions toward the two technologies will be significantly related to the characteristics of the community within which an individual resides.

Method The answers to the three research questions were sought by analyses of data related to perceptions of attributes, personal characteristics and societal characteristics. Data obtained through the US Army Chemical Weapons Stockpile Community (CWSC) Study conducted at the University of Arizona in 1999 and which was sponsored by the US Army’s Program Manager for Chemical Demilitarization (PMCD) were used in this study.1 The CWSC Study was designed to gather data to help understand possible factors that may be related to public participation in the decision-making process. This study represents a portion of the survey data that was collected in the CWSC study. A more

506 B. L. Williams, H. K. Suen, S. E. Rzasa, T. Heikkila & M. Pennock-Roman Table 1. Descriptions of Likert-type scales Variable Perceptions of emergency preparedness

Variable code EMPRSUM

Interpretation of variable An increase in EMPRSUM means a respondent increasingly believes he or she is prepared in case of a chemical emergency.

Risk perception of site activities

ACTYSUM

An increase in ACTYSUM means a respondent perceives an increasing amount of risk associated with activities related to disposal of chemical weapons.

Perceived awareness of Army public outreach programme

PGMSUM

An increase in PGSUM means that a respondent demonstrates an increased awareness of the Army’s public outreach and education programme.

Trust in the Army

TRUSTSUM

An increase in TRUSTSUM means a respondent is increasingly trustful of the Army to perform various activities.

Perception of incineration

INCINSUM

An in INCINSUM means a respondent has associated an increase number of positive characteristics with incineration technology.

Perception of neutralization

NEUTRSUM

An in NEUTRSUM means a respondent has associated an increase number of positive characteristics with neutralization technology.

Level of participation in the community

PARTSUM

An increase in PARTSUM means a respondent has participated in an increased number of civic activities.

Readiness to participate

DESCSUM

An increase in DESCUM means a respondent is demonstrating a growing intent to participate in decision making related to the programme.

Media influence on trust

INTRUST

Includes only respondents who indicated they had heard or read something in the past year that had influence their trust in the programme. An increase in INTRUST means that a respondent had heard something that had made them trust the programme.

detailed description of the data collection design in the CWSC Study can be found in Williams et al. (2001). Instrument Based on a quasi-Delphi process and focus groups, input from residents, community activists and governmental agency representatives identified a list of important personal and community attributes that might influence the factors related to public participation in chemical stockpile disposal decision making. Based on these results, three versions of a questionnaire, consisting of 45 core items, were created. The overall questionnaire was comprised of several intact Likert-type scales. A description of these scales is provided in Table 1 below. Each individual received a subscale score for each of these constructs. High scores on these subscales can be interpreted as the individual being high on the measured construct. For example, a high INCINSUM score indicates that the individual has a favourable perception and has a high degree of acceptance of


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incineration as a chemical weapons disposal method. A high NEUTRSUM indicates that the individual has a favourable perception and has high degree of acceptance of neutralization as a method of disposal. These scales were fieldtested based on a sample of 771 interviewees. Classical psychometric analyses found that all items had discrimination index values above 0.30. All scale scores had Cronbach alpha values above 0.80 with a mean alpha value of 0.82 (see Williams et al., 1999 and Williams et al., 2001 for a more detailed description of the scales). In addition to the Likert scales, the survey included questions concerning how the individuals learn of site activities and how their opinions of the site are impacted (such as through electronic media, written media, individual contact or group contacts). The individuals were also queried as to their perception of the positive or negative impact that the site has had on the community. Demographics including age, gender, educational and employment background, ethnicity were also asked of the individuals. For a comprehensive list of all personal characteristic (Level 1) variables, see Appendix A. Because of the use of different versions of certain scales, several independent and dependent variables suffered severe problems of missing data primarily due to non-overlapping items. If these variables were included in the overall analysis, following the common listwise deletion method for the treatment of the missing data would have resulted in no usable data at all. To remedy this problem, it was necessary to create subsets of data so that all variables can be investigated. Therefore, several datasets were generated from the overall survey database. In order to include the variable of participation, PARTSUM, along with the incineration and neutralization variables in an analysis simultaneously, only subjects who responded to Version A of the participation Scale were selected. Therefore, the first sub-analysis utilizes this version of the scale, which is termed the Participation Dataset. In order to include the Risk Perception Score (ACTYSUM), Incineration Score, and Neutralization Score in an analysis simultaneously, only subjects who responded to Version B of the Risk Perception Scale were selected. Thus, the second sub-analysis utilizes this version of the scale, which is termed the Risk Dataset. Sample Interviewers made 24 058 telephone contacts from April to July 1999. The authors did not participate as interviewers. Approximately 10 183 residents agreed to participate in the study, and 8315, or 79%, of these residents completed the entire survey, which is comparable to that of other large population surveys (Luevano, 1994; Smith, 1995). Using 1997 projective US Census data for comparison, the demographic characteristics of the sample were similar to demographic characteristics of the eight-state study region for race, age, income and gender. In terms of race, 87% of the respondents identified themselves as Caucasian, 7% as African Americans, 6% as Hispanic and 1% as Native American. In the sample, 41% of respondents identified as male. Although males are typically under-represented in population surveys, the male representation in this sample is comparable to other large population surveys. The sample and study region differed slightly with respect to age distribution. The age distribution comparisons are based upon the population eligible to participate in the study, i.e. those over the age of 18. However, the age intervals for US Census data start at 15

508 B. L. Williams, H. K. Suen, S. E. Rzasa, T. Heikkila & M. Pennock-Roman years of age not 18. Hence, the age distribution data for the study region are likely underestimated to a small degree, which may account for the small disparities between the sample and study region. In terms of age, 30% of the sample respondents were between the ages of 25 and 39, 46% between the ages of 40 and 64, 9% between the ages of 65 and 74, and 7% above the age of 74. In terms of income, 19% of the respondents reported an income between $25 000 and $35 000 per year and 24% reported an income between $35 000 and $50 000 per year. These categories represented the greatest proportion of respondents in the sample. Approximately 16% were identified as having an income below the poverty level. For this study, a total of 5111 individuals were interviewed. As mentioned above, in order to include all variables, two datasets were utilized. A total of 2539 individuals are included in the Participation Dataset, which includes the variable of participation (PARTSUM). A total of 2572 individuals are included in the Risk Dataset, which includes the variable of risk perception (ACTYSUM). Analysis In order to answer the first research question, scores on the level of acceptance of neutralization and incineration subscales were compared using dependent t-tests. The second and third research questions are answered using hierarchical linear modelling (HLM) to predict which characteristics affect technology acceptance. HLM is the most appropriate model in this analysis as data was collected at the personal level and at a larger unit of community (Arnold, 1992, Bryk & Raudenbush, 1992). The data for this study has a hierarchical structure in that the individual is nested within the organizational unit of the community. This common community environment influences each individual within a community. HLM simultaneously estimates the between-community and withincommunity (individual) levels using “linear equations of groups as a function of the groups as well as the characteristics of the members” (Arnold, p. 24). The HLM analysis approach essentially divides the prediction problem into two sets of prediction questions at two different levels: (1) What personal characteristics can predict a person’s acceptance of disposal technology? and (2) How do the prediction models for Question 1 change as a function of the societal characteristics of the site in which the person resides. The dependent variables utilized in the HLM analysis were the Incineration Score (INCINSUM) and the Neutralization Score (NEUTRSUM). The independent Level-1 variables entered into the model included the remaining subscale scores and all other demographic and personal characteristics listed in Appendix A. In addition, the community characteristics that were identified as important in the preliminary focus groups were entered as Level-2 variables into the HLM model. These variables are also listed in Appendix A. When the Level-2 variables (i.e. societal characteristics) were examined, it was found that many of these variables were highly correlated with one another. Because of this multicollinearity problem, W AVG2, W AVG4, POP96, M POP96, MED INC, N COUNTY, and A TEST (see Appendix A) were excluded from further analyses due to statistical redundancy. As there is no strong a priori theory that may suggest specific predictor variables, an exploratory approach was used to conduct the HLM in practice. After careful examination for missing data and skewness, appropriate transformations and imputations were performed to assure the most robust data set for


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Table 2. Perceived characteristics of technology by Army site

analyses. In order to improve the efficiency of subsequent analyses, the data were first submitted to an ordinary least square regression analysis using only personal characteristics as predictors in order to identify statistically significant Level-1 predictor variables. These significant Level-1 predictor variables were then submitted to HLM along with all Level-2 variables in a one-by-one exploratory process. A final HLM analysis was performed in order to estimate a final set of parameters containing only significant Level-1 and Level-2 variables. In order to facilitate interpretation of the model, all Level-1 independent variables, unless otherwise indicated, were centered around their respective means (Bryk & Raudenbush, 1992). Results Attributions Toward Incineration and Neutralization Table 2 provides a summary of the incineration acceptance and neutralization acceptance scores by site. In five of the eight sites, incineration scores were higher than neutralization score. Results of dependent t-tests indicate that the differences between mean neutralization and incineration scores were statistically significant for all eight sites (p ⱕ 0.05). However, in some cases the differences in mean scores are quite small and lack practical significance (e.g. Richmond). Overall, of the 11 specific innovation attributes investigated, as measured by the items in the subscale, eight were more frequently associated with incineration than with neutralization. The remaining three characteristics were more frequently associated with neutralization than incineration. Specifically, a greater proportion of respondents ascribed the characteristics of flexibility (2.1⬊1), reversibility (3.3⬊1), and potential risk (1.1⬊1) to neutralization than they did to incineration. A greater proportion of respondents attributed eight characteristics as descriptors of incineration rather than neutralization. These characteristics included the following: cost-effective (2.7⬊1), economically beneficial (1.6⬊1), understandable (4.6⬊1), best disposal method (1.2⬊1), better than storage (1.2⬊1), favoured by community (1.2⬊1), process being used at other sites (7.0⬊1), and the fastest disposal method (7.8⬊1). For the hierarchical linear modelling, two separate analyses were performed. Analysis I focuses on the creation of a model using personal (Level 2) and

510 B. L. Williams, H. K. Suen, S. E. Rzasa, T. Heikkila & M. Pennock-Roman Table 3. Prediction of INCINSUM based on PART data Variable Intercept PGMSUM TRUSTSUM IMPACT DESCSUM INCOME

Coefficient

Std. error

t-ratio

p-value

4.543 0.054 0.060 ⫺ 0.132 0.295 0.080

0.190 0.016 0.007 0.046 0.036 0.024

23.935 3.339 8.647 ⫺ 2.898 8.132 3.317

0.000 0.014 0.000 0.024 0.000 0.015

community characteristics (Level 2) to predict the level of acceptance for incineration. Analysis II uses personal and community characteristics to predict the level of acceptance for neutralization. As explained above, each analysis was performed two times on different subsets of the sample. A model was created for each subset consisting of both Level 1 and Level 2 variables, if applicable. Analysis I: Prediction of Incineration Acceptance Analysis I.A: Participation Dataset to Predict INCINSUM When this data subset was analyzed through HLM to predict INCINSUM, five (5) significant Level-1 predictors were found. However, there was no significant Level-2 variable identified. The significant Level-1 predictors were PGMSUM (awareness of Army outreach programmes), TRUSTSUM (trust of Army activities), IMPACT (perceived effect of site on community), DESCSUM (readiness to participate), and INCOME (income level). The regression coefficients and their corresponding standard errors and significance in the final model in which all significant predictors were entered simultaneously are shown in Table 3. The standard error of the predicted INCINSUM score is 2.403. The maximum-likelihood level-1 prediction equation for INCINSUM based on the PART data subset was found to be: Level-1 equation: Predicted INCINSUM ⫽ 4.543 ⫹ 0.054(PGMSUM) ⫹ 0.060(TRUSTSUM) ⫺ 0.132(IMPACT) ⫹ 0.295(DESCSUM) ⫹ 0.080(INCOME)

(*I.1)

The standard error of the predicted INCINSUM scores from Equations (*I.1) is 2.403. This equation was derived based on centring all Level-1 predictor variables. The standard errors and significance of the coefficients for Equation *I.1 are shown in Table *I.T1. The equivalent OLS statistics (e.g. F-ratio, R2) for Equation *I.1 can be found in Appendix B. The final estimation of variance components in this prediction model for PGSUM was significant (䊐2 ⫽ 21.59; p ⫽ 0.003). The variance component for the intercept is significantly different from zero. The conditional intraclass correlation for the intercept is 0.045. These results suggest that individuals with high degrees of outreach awareness, who trust army’s activities, who perceive a ‘negative’ impact of the site on the community, who are ready to participate, and who have a high level of income are more likely to perceive the incineration


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Table 4. Prediction of INCINSUM based on ACTY data Variable Intercept TRUSTSUM INTRUST DESCSUM SEX

Coefficient

Std. error

t-ratio

p-value

4.981 0.047 0.546 0.459 ⫺ 1.218

0.259 0.016 0.207 0.125 0.252

19.201 2.993 2.639 3.661 ⫺ 4.834

0.000 0.021 0.034 0.010 0.001

method of disposal positively. Upon analyzing the variance components, the intercept is shown to have a variance component significantly different from zero. This suggests that some unexplained residual variation of INCINSUM remains that is associated with the intercept from site to site beyond what is predicted in the regression equation. This indicates that the prediction model may be improved by identifying additional site-level variables that have not yet been explored. Further, the conditional intraclass correlation of 0.045 suggests that the residual variance for the intercept is not large but may make a noticeable difference, indicating the need to explore additional new site-level variables in order to predict INCINSUM.

Analysis I.B: Risk Data Subset to Predict INCINSUM When the risk data subset was analyzed through HLM to predict INCINSUM, four (4) significant Level-1 predictors and no significant Level-2 variables were found. The significant Level-1 predictors were PGMSUM (awareness of Army outreach programmes), INTRUST (media influence on trust during past year), DESCSUM (readiness to participate in decision making), and SEX (coded as 1 ⫽ male and 2 ⫽ female). The regression coefficients and their corresponding standard errors and significance in the final model in which all significant predictors were entered simultaneously are shown in Table 4. The standard error of the predicted INCINSUM scores is 2.217. The final estimation of variance components in this prediction model was not significant for any individual variable. However, the variance component for the intercept is significantly different from zero. The conditional intraclass correlation for the intercept is 0.078. The results suggest that individuals who trust army’s activities, who perceive that the media have made him/her more trusting of weapons disposal activities, who is ready to participate, and who are male are more likely to perceive the incineration method of disposal positively. Again, the intercept was shown to have a variance component significantly different from zero, which suggests that there remains some unexplained residual variation of INCINSUM associated with the intercept from site to site beyond what is predicted in our regression equation. The conditional intraclass correlation of 0.078 further suggests that the residual variance for the intercept is not large but may make a noticeable difference, indicating the need to explore additional new site-level variables in order to predict INCINSUM.

512 B. L. Williams, H. K. Suen, S. E. Rzasa, T. Heikkila & M. Pennock-Roman Table 5. Prediction of NEUTRSUM based on PART data Variable Intercept DESCSUM AGE COLLEGE

Coefficient

Std. error

t-ratio

p-value

3.720 0.173 ⫺ 0.032 0.030

0.196 0.077 0.005 0.115

18.998 2.255 ⫺ 6.924 2.599

0.000 0.058 0.000 0.036

Summary of Prediction of Incineration Score The two sub-analyses find that several individual characteristics and beliefs may influence whether a person has a positive or negative perception of the incineration method of chemical weapons disposal. The first sub-analysis suggests that individuals who view incineration as a positive method of disposal also trust in the army, are aware of the outreach programmes held by the Army, are ready to participate in the community and also have a high income. Interestingly, they also tend to view the site’s impact on the community as negative. The second sub-analysis agrees with the first in that individuals with a high awareness of the outreach programmes and who are ready to participate also tend to have a positive image of incineration. One variable that did not occur in the first analysis is gender. The second analysis showed that males were more likely to view incineration as positive. Individuals whose trust was positively influenced by the media in the past year also attributed more positive attributes toward incineration than did those whose trust had been negatively influenced by the media. Neither analysis found any significant Level-2 community characteristics. Both analyses suggest that there exists other Level-1 and Level-2 variables that may explain variance that were not addressed in the model. Analysis II: Perception of the Neutralization Disposal Method Analysis II.A: Participation Data Subset to Predict NEUTRSUM When this data subset was analyzed through HLM to predict NEUTRSUM, three (3) significant Level-1 predictors were found. There was no significant Level-2 variable identified. The significant Level-1 predictors were DESCSUM (sum of readiness to participate subscale), AGE (age of respondent), and COLLEGE (whether the respondent has completed a college education, coded as 1 ⫽ completed college and 0 ⫽ has not completed college). The regression coefficients and their corresponding standard errors and significance of the coefficients in the final model in which all significant predictors were entered simultaneously are shown in Table 5. The standard error of the predicted INCINSUM scores is 2.496. This equation was derived based on centering DESCSUM and AGE, but leaving COLLEGE uncentred. The final estimation of variance components in this prediction model was significant for DESCSUM (䊐2 ⫽ 30.699; p ⫽ 0.000 ). The variance component for the intercept is significantly different from zero. The conditional intraclass correlation for the intercept is 0.042. The results suggest that individuals who are ready to participate, who are young and have completed a college education are more likely to perceive the neutralization method of disposal positively. Because


513

Table 6. Final estimates of variance component for the prediction of NEUTRSUM based on ACTY data Residual variations Level-2 Residuals Intercept Level-1 Residuals

Variance component

Degree of freedom

Chi-Square

p-value

0.559 5.378

7

38.631

0.000

COLLEGE was dummy-coded rather than centred around its mean, the intercept of 3.720 represents the expected NEUTRSUM score of the typical respondent who has not completed a college education. The intercept was shown to have a variance component that is significantly different from zero. This suggests that there remains some unexplained residual variation of NEUTRSUM associated with the intercept from site to site beyond what is predicted in the regression equation. The conditional intraclass correlation of 0.042 further suggests that the residual variance for the intercept is not large but may make a noticeable difference, indicating the need to explore additional new site-level variables in order to predict NEUTRSUM. Analysis II.B: Risk Data Subset to Predict NEUTRSUM When the risk data subset was analyzed through HLM to predict NEUTRSUM, no significant Level-1 or Level-2 predictor variable was found. Table 6 shows the final estimation of variance components due to individual and site differences. The results show that the variance component for the intercept (Level-2) is significantly different from zero. The conditional intraclass correlation for the intercept is 0.094. Given the Level-1 and Level-2 variables in the risk data subset for the sub-sample of individuals represented by this subset, it was not possible to predict NEUTRSUM beyond the mean NEUTRSUM score. New and different predictor variables need to be identified and investigated in order to predict NEUTRSUM. The values of the estimated variance components suggest that variation in NEUTRSUM scores is due to both individual (Level-1) difference and site (Level-2) difference. This indicates that future investigations need to look into new predictor variables at both the individual and the site level. The intraclass correlation of 0.094 suggests that about 9% of the variance in NEUTRSUM can be attributed to site difference, rather than individual difference. This is substantial enough to warrant future investigations of site-related Level-2 variables. Summary of Prediction of Neutralization Score The two sub-analyses indicate that more research may need to be done regarding the personal and community characteristics that influence the perception of the neutralization method of chemical weapons disposal. The first sub-analysis suggests that those individuals who tend to be young, educated and ready to participate in the community are more likely to have a positive attitude towards neutralization. Unfortunately, the second analyses failed to identify any personal

514 B. L. Williams, H. K. Suen, S. E. Rzasa, T. Heikkila & M. Pennock-Roman or community characteristics that may influence attitude toward this method. Both analyses suggest that more research regarding possible influences on perception of neutralization may be needed. Discussion This study addressed the following three research questions: (1) To what extent do respondents attribute specific diffusion characteristics with either the incineration or neutralization disposal technology? (2) To what extent do individual factors influence a respondent’s attributions toward the technologies? (3) To what extent do community factors influence a respondent’s attributions toward the technologies? The study findings provide some insight into each of these three questions. To what extent do respondents attribute specific diffusion characteristics with either the incineration or neutralization disposal technology? This study provides an empirical basis for predicting the perceived technological attributes of disposal methods among people living near chemical weapons stockpile sites. The findings suggest that residents appear to perceive clear differences between the desirable characteristics of the two technologies. The majority of positive technological attributes were more commonly associated with incineration. However, it is difficult to determine the extent to which either technology would lend itself more readily to public adoption. The relative perceived weight (i.e. importance) of each of the attributes presented to respondents is not known nor were the respondents presented with an inclusive range of attributes. For example, respondents attributed slightly less potential risk with neutralization than they did with incineration. Consequently, is potential risk more important to residents than the cost or speed of disposal? Site variation in technological attributions was also apparent in this study. As evidenced by these findings, sites differed significantly with respect to individual perceptions of technology attributes. Although statistically significant, some differences between sites were small. The most interesting site variation was demonstrated in Tooele, Utah a site that is currently using incineration. Tooele residents demonstrated the greatest predisposition toward incineration. Tooele residents’ perceptions toward these disposal technologies may stem from the public’s familiarity with the technology. The perceived efficacy of incineration may be enhanced by its actual and prolonged use. As mentioned previously, institutionalized technologies are more readily accepted than newer technologies. That is, the public familiarity with various aspects of a technology is conducive to rapid diffusion. As mentioned previously, less familiar technologies typically diffuse at a slower rate than do better known technologies (Ganesh et al., 1997). In Tooele it appears that familiarity has facilitated the diffusion of incineration among the public. To what extent do individual factors influence a respondent’s attributions toward the technologies? Individual factors were found most predictive of attributions made toward incineration. In one model, perceptions toward incineration were influenced by a person’s perceived awareness and value of outreach, trust in the Army, perceived impact of site on community, intent to participate in the programme and income. In the other model, a person’s sex and perceptions


515

toward media effects also influenced perceptions toward incineration. In the first model, perceptions toward the Army and outreach efforts directly affected perceptions toward incineration. As a person’s trust in the Army increases, so do his or her positive attributions toward incineration. As a person’s awareness and perceived value of public outreach efforts increases so does his or her positive attributions toward incineration. Additionally, individuals who perceive a negative impact of the site on the community, who are ready to participate in programme activities, and who have a high level of income are more likely to perceive the incineration method of disposal positively. In the second model, many of the same trends were demonstrated. Positive perceptions toward incineration were associated with individuals who trust the Army, who perceive that the media have made them more trusting of weapons disposal activities, who are ready to participate, and who are male. Past studies have indicated that the technological adoption is greatly affected by the public perceptions of the institutions or individuals responsible for implementing or overseeing the technology (Bradbury, 1994; Frewer & Shepard, 1995; Parcel et al., 1995; Siegrist, 2000). Institutional trust in both the Army and public outreach efforts represent decisive predictors of a population’s perceptions toward disposal technologies. Contrary to popular belief, the public may be willing to accept a given technology so long as it trusts those individuals or groups responsible for designing, implementing and evaluating the technology. The effects of institutional trust on perceptions of environmental risks and policy are well substantiated in the literature (Williams et al., 1999). This study suggests that the Army has had an impact on people’s perceptions toward incineration. Army outreach efforts may have helped people better understand characteristics of incineration technology, thus making the public more comfortable with technical decisions. Overall, these findings imply that the Army may facilitate the diffusion of the incineration technology by increasing public outreach efforts at the site and by further securing public trust. The media represents an area in which the Army plays only a partial role in influencing public opinion. The effects of media on public opinion are widely debated. Many studies have provided evidence that communication sources directly influence the diffusion process (e.g. interpersonal and media-related) (Stiff, 1994; Rogers, 1995b; Ferrence, 1996). This study appears to support the findings of such studies. In this study, perceptions of information sources significantly influenced perceptions toward incineration. Approximately 42% of the respondents indicated that an information source had influenced his or her opinion about the chemical demilitarization programme in general. Of the 42%, 33% indicated the information had them more trusting in the programme, about 48% indicated the information made them less trusting, and about 19% indicated the information had no effect on his or her trust. Respondents who reported that the media or other information sources had made them more trusting of site disposal activities were more likely to associate positive characteristics with incineration than their less trusting counterparts. Newspapers were the most frequently cited source of information, followed by television and personal contacts. The remaining factors influencing incineration perceptions include perceived impact of programme, resident income and participatory intent. Perceiving a negative impact from the site on one’s community tended to increase one’s positive attributions toward incineration. Additionally, wealthier residents re-

516 B. L. Williams, H. K. Suen, S. E. Rzasa, T. Heikkila & M. Pennock-Roman ported significantly more positive attributions toward incineration than did their lower income counterparts. It is feasible to suggest that many site residents perceive the mere presence of chemical agents as inherently negative. Hence, incineration poses a quick solution to the problem. Additionally, higher income residents may have a personal stake in quickly ridding their community of the chemical weapons stockpile. For example, the disposal of these chemicals may be associated with increased property values or increased availability of land. There is also some indication that individuals predisposed toward incineration are ready to actively participate in the programme. Overall, these personal factors may be influential in the adoption of the incineration technology. Other technology diffusion studies support this proposition (Ferrence, 1996). As stated previously, variations in technology adoption may be specifically attributed to variations in personal factors including age, sex, residence, socio-economic status and level of access to communications (Ferrence, 1996). Unlike incineration, there was insufficient proof that individual factors influence variations in perceptions toward neutralization. One model found a statistically significant relationship between such perceptions as level of education, participatory intent and age. However, these relationships were marginal and lack practical significance. The second model substantiates this position. In this model, the variance in neutralization perceptions is not sufficiently explained by the variables analyzed. Consequently, it is not known what would enhance or impede adoption of neutralization. As illustrated by the HLM analysis, there is a definite need to collect additional individual and site level data to explain variations in neutralization perceptions. The observed disparities between perceptions of neutralization and incineration may be due in part to the relative maturity of each technology. Incineration arguably represents a more mature technology in terms of practice or application than does neutralization or variations thereof. Hence, the observed uncertainty and ambivalence toward neutralization may stem from the public’s lack of familiarity with the technology. As a baseline technology, incineration represents a technical standard, whereas other methods of disposal such as neutralization represent conflicting technologies. For conflicting technologies to be readily diffused they must demonstrate a relative advantage over the existing technology. To date, performance assessments of neutralization and alternative technologies have not yielded empirical evidence of such an advantage over incineration. (NRC, 1999) Consequently, it is likely that the diffusion of alternative disposal technologies would be much slower than that of incineration. To what extent is a respondent’s technological attributions influenced by his or her local condition? Sites differed significantly with respect to perceptions toward the disposal technologies. Other studies have found that geographic and economic similarities and dissimilarities are important predictors of technological adoption in a population (Ganesh et al., 1997; Gruber, 1998). This study does nothing to support such findings. Although there are significant differences in technological perceptions across sites, the effects of site level variables on such perceptions remain inconclusive. As indicated in the HLM analyses, there is a lack of statistical evidence that the selected community level factors influenced individual perceptions toward the technologies. However, the variance components for each of the models were significant. This indicates that a significant amount of the variation in such perceptions can be explained by site level


517

factors. However, these factors are yet unknown, and thus were not tested in the current model. There are definite site level differences in perceived attributions, the magnitude of which varied with each model. Conclusion This study suggests that diffusion theory may be a useful way to explain individuals’ acceptance of hazardous waste disposal technologies. Weapons disposal technologies are both complex and foreign to most people. Yet, as shown in this study people still ascribe tangible characteristics to these technologies. People appear to hold preconceived notions about disposal technologies. These ‘notions’ may play a key role in public acceptance of or opposition toward environmental technologies in general. Yet, we do not know if ‘perceptions’ toward the characteristics of this technology are more powerful predictor of adoption than is actual ‘comprehension’ of the technology. Further study is needed to test understanding of these technologies among the general public and to assess the role that such understanding has on public acceptance. Additionally, researchers should examine the actual rate of adoption of specific disposal technologies in varied context. Since adoption is an ongoing process, such an examination will allow us to understand how both perception and comprehension of disposal technologies changes over time. Note 1.

As mandated by international treaty, the primary charge of PMCD is to safely dispose of the US Army’s stockpile of chemical warfare material. Additionally, PMCD is required to engage the public and to integrate public input into the programmatic decision-making process. PMCD has been the target of much criticism concerning public involvement (Shepherd & Bowler, 1997). Critics of the programme argue that public participation opportunities for the programmatic EIS (Environmental Impact Statement) were a “pro forma exercise” (Shepherd & Bowler, 1997, p. 6). They also contend that Army decisions have been “unilateral, unfair, and unsafe” (Shepherd & Bowler, 1997, p. 6).

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Appendix A Table. List of all variables analyzed Personal (Level-1) characteristic Age Sex Income Family size Participated before Years lived Race/ethnicity Black White Hispanic Native American Education background High school College Employment characteristics Full-time Part-time Unemployed Retired Manager Technical Service Labourer Military Relationship to site Current employee Previous employee Family current Family previous Dist Religious background Protest Catholic Latterday Other religion No religion How individuals learn of site activities Electronic media (Electmed) Written media (Written) Individual contacts (Indiv) Group contacts (Group)

Description Age of respondent Male or female Income level Number in household (inclusive) Participated in survey past year Years lived in town Reported Reported Reported Reported

race race race race

as as as as

Black White Hispanic Native American

Highest degree is high school or below Highest degree is college and beyond

Works full-time Works part-time Unemployed including disabled and homemakers Retired Reported occupation as managerial, professional specialty or education Reported occupation as technical, sales or administrative support Reported occupation as service or protective services Reported occupation as farming/fishing/forestry, manufacturing, labourer or transportation Reported occupation as military or governmental Respondent is current site employee Respondent was previous site employee Family member is current site employee Family member was previous site employee Perceived distance from site Individuals Individuals Individuals Individuals Individuals

self-reported self-reported self-reported self-reported self-reported

as as as as as

practicing a Protestant religion practicing Catholicism being Latter Day Saints practicing another religion practicing no religion

Reported that television, radio, or computer is the best way to be kept up to date about chemical weapons disposal activities. Reported that the newspaper or other written media is the best way to be kept up to date about chemical weapons disposal activities Reported that individuals such as personal contacts, professionals, or community spokespersons are the best way to be kept up to date about chemical weapons disposal activities. Reported that employer, government agencies, religious groups, community organizations, the local outreach office, or public meetings are the best way to be kept up to date about chemical weapons disposal activities

522 B. L. Williams, H. K. Suen, S. E. Rzasa, T. Heikkila & M. Pennock-Roman Table. List of all variables analyzed—continued Personal (Level-1) characteristic What influences opinion of site Hear1 Impact by electronic media (Impelect) Impact by written (Impwrit) Impact by individual (Impindiv) Impact by group (Impgroup)

Scores on subscales EMPRSUM PGMSUM TRUSTSUM DESCSUM ACTYSUM INCINSUM NEUTRSUM PARTSUM Other questions: IMPACT INTRUST Societal (Level-2) Characteristics w avg1 w avg2 w avg3 w avg4 w w w w w

avg5 avg6 avg7 avg8 avg9

w avg10 pop96 m pop96 n cnty a popov a tstud a test

Description

Respondent reported that something specific influenced opinion about chemical weapons disposal issues Respondent reported that television or radio influenced opinion about chemical weapons disposal issues Respondent reported that newspaper or other written media influenced opinion about chemical weapons disposal issues Respondent reported that personal contacts, professionals, or community spokespersons influenced opinion about chemical weapons disposal issues Respondent reported that employer, government agencies, religious groups, community organizations, the local outreach office, or public meetings influenced opinion about chemical weapons disposal issues Sum on Emergency Preparedness subscale Sum on Outreach Awareness subscale Sum on Trust of Army Activities subscale Sum on Readiness to Participate subscale Sum on Risk Perception subscale Respondent’s perception of the incineration method of chemical weapons disposal Respondent’s perception of the neutralization method of chemical weapons disposal Sum on Participation subscale Perception of effect of site on the community (positive or negative) “Did this activity make you more or less trusting about chemical weapons disposal related activities?” Description Weighted average of pupil-teacher ratio per site Weighted average of population density Weighted average of percent population change Weighted average of percent population change (over age 65) Weighted average of percent birth rate Weighted average of age adjusted death rate Weighted average of crude death rate Weighted average of violent crime rate Weighted average of percentage of 1990 population level-1 literacy rate Weighted average of percentage of students designated as free lunch eligible Site population in 1996 Mean county population per site in 1996 Number of counties in analysis per site Percent of the population in poverty Percentage of the population who are students in K through 12 Business establishments per population

US Army Chemical Weapons Disposal Technologies Table. List of all variables analyzed—continued Personal (Level-1) characteristic med inc n groups budget fte mission colleges governor senate sthouse voters turnout st act

Description Median Income Number of activist groups ORO FY 1999 budget ORO Full-time employees Site’s mission after Demilitarization (No Longer Operational or Continued Mission) Number of year colleges near site Governor party control Senate party control Statehouse party control Total registered voters General election turnout average Activist groups per population

523

Author Query Sheet Manuscript Information Journal Acronym Volume and issue Author name Manuscript No. (if applicable)

CJEPM 46(4) Williams NA83R

AUTHOR: The following queries have arisen during the editing of your manuscript. Please answer the queries by marking necessary corrections at the appropriate positions on the PROOFS. Do not answer the queries on the query sheet itself. Please also return a copy of the query sheet with your corrected proofs. QUERY NO.

AQ1 AQ2 AQ3 AQ4 AQ5 AQ6 AQ7 AQ8 AQ9 AQ10 AQ11 AQ12 AQ13 AQ14 AQ15 AQ16 AQ17 AQ18 AQ19 AQ20 AQ21 AQ22 AQ23 AQ24 AQ25 AQ26 AQ27 AQ28 AQ29 AQ30 AQ31 AQ32

QUERY DETAILS

Add full addresses for co-authors Sabatier & Jenkins Smith 1994 – not mentioned in references Arnold 1992 – add issue number of journal Bradbury 1994 – add issue number of journal Cohen 1995 – not mentioned in text Covello 1995 – add issue number of journal Dearing et al 1996 – add issue number of journal Dupuy 1997 – add issue number of journal Freeman 1996 – not mentioned in text , and add issue number of journal Ganesh et al 1997 – add issue number of journal Goldstein 2000 – name all authors Green et al 1994 – add initials of all authors Gruber 1998 – add issue number of journal Jeffres et al 1996 – add issue number of journal Johnson et al 1997 – add page numbers Johnson-Cartee et al 1992-3 – add initial of first author Kweit & Kweit 1987- not mentioned in text Lidskog 1997 – not mentioned in text Luloff et al 1998 – name all authors Norberg-Bohm 1999 – add issue number of journal Parcel et al 1995 – add issue number of journal Paulussen et al 1995 – add issue number of journal Purvis & Outlaw 1995 – add issue number of journal Reagan 1991 – add issue number of journal Rennings 2000 – full title of journal needed Repplin-Hill 1999 – add initial of author. Add issue number of journal Rogers 1995b – add issue number of journal Shaperman & Backer 1995 – add issue number of journal Schneider et al 1997 – add initial of first author Slovic 1997 – not mentioned in text. Add issue number of journal Sparkes & Kang 1986 – add issue number of journal USEPA 1992 – not mentioned in text

AQ33 AQ34

USEPA 1998 – not mentioned in text Williams et al 1999 – add issue number of journal