This article was downloaded by: [Tulane University] On: 19 August 2013, At: 03:20 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Sociological Spectrum: Mid- South Sociological Association Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/usls20 Gender, Race, and Perceived Environmental Risk: The “White Male” Effect in Cancer Alley, LA Brent K. Published online: 12 Aug 2010. To cite this article: Brent K. (2004) Gender, Race, and Perceived Environmental Risk: The “White Male” Effect in Cancer Alley, LA, Sociological Spectrum: Mid-South Sociological Association, 24:4, 453-478, DOI: 10.1080/02732170490459485 To link to this article: http://dx.doi.org/10.1080/02732170490459485 PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan,
Transcript
This article was downloaded by: [Tulane University]On: 19 August 2013, At: 03:20Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH,UK
Sociological Spectrum: Mid-South Sociological AssociationPublication details, including instructions forauthors and subscription information:http://www.tandfonline.com/loi/usls20
Gender, Race, and PerceivedEnvironmental Risk: The“White Male” Effect in CancerAlley, LABrent K.Published online: 12 Aug 2010.
To cite this article: Brent K. (2004) Gender, Race, and Perceived EnvironmentalRisk: The “White Male” Effect in Cancer Alley, LA, Sociological Spectrum: Mid-SouthSociological Association, 24:4, 453-478, DOI: 10.1080/02732170490459485
To link to this article: http://dx.doi.org/10.1080/02732170490459485
PLEASE SCROLL DOWN FOR ARTICLE
Taylor & Francis makes every effort to ensure the accuracy of all theinformation (the “Content”) contained in the publications on our platform.However, Taylor & Francis, our agents, and our licensors make norepresentations or warranties whatsoever as to the accuracy, completeness,or suitability for any purpose of the Content. Any opinions and viewsexpressed in this publication are the opinions and views of the authors, andare not the views of or endorsed by Taylor & Francis. The accuracy of theContent should not be relied upon and should be independently verified withprimary sources of information. Taylor and Francis shall not be liable for anylosses, actions, claims, proceedings, demands, costs, expenses, damages,and other liabilities whatsoever or howsoever caused arising directly orindirectly in connection with, in relation to or arising out of the use of theContent.
This article may be used for research, teaching, and private study purposes.Any substantial or systematic reproduction, redistribution, reselling, loan,
sub-licensing, systematic supply, or distribution in any form to anyone isexpressly forbidden. Terms & Conditions of access and use can be found athttp://www.tandfonline.com/page/terms-and-conditions
BRENTK.MARSHALLDepartment of Sociology and Anthropology, University of Central
Florida, Orlando, Florida, USA
Research on risk perceptions are replete with race- and gender-specific hypotheses attempting to account for attitudinal variation.However, race and gender differences may mask more notablepatterns across subgroups, patterns that lie at the intersection ofrace and gender. Recent national studies suggest that being aWhite male leads to lower risk perceptions and greater willingnessto accept risks. This article extends this research by examining the‘‘White male’’ effect in a chronically polluted context, an areawhere industrial pollution is palpable and well-documented. Dataare drawn from a survey of a population living in ‘‘Cancer Alley,’’a stretch of the Mississippi River from Baton Rouge to NewOrleans. We find that women more than men and Blacks morethan Whites perceive environmental risks as serious. Further, evi-dence suggests that these differences are mostly due to the rela-tively extreme perceptions of risk accepting White males and riskadverse Black females. After controlling for select variables inhierarchical multiple regression analyses, being a White male orBlack female still has a statistically significant impact on risk per-ceptions.
People in the United States have become more concernedabout risk over the last 20 years partially due to the belief that
Received 23 July 2002; accepted 12 June 2003.Address correspondence to Brent K. Marshall, Department of Sociology and Anthropol-
ogy, University of Central Florida, Orlando, FL 32816-1360. E-mail: [email protected]
Sociological Spectrum, 24: 453–478, 2004
Copyright # Taylor & Francis Inc.
ISSN: 0273-2173 print/1521-0707 online
DOI: 10.1080/02732170490459485
453
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
we are increasingly vulnerable to polluted land, air, andwater. Over the same period, risk assessment and manage-ment have become much more contentious, often embroiledin conflict and controversy (Slovic 1993). In the mid-1980s,risk experts began to focus on risk communication as amethod of moving beyond risk conflict, a method that largelyhas failed (Slovic 1993). Given the ineffectiveness of riskcommunication, much research has attempted to understandwhy risk estimates by experts are often at odds with how thepublic perceives risk (for a collection of reprints, see Slovic2000a).
Traditional risk assessment is based on a number of esti-mates, including the measure of the chemical in theenvironment, assumptions regarding the movement ofthe chemical through a specific medium, the way in whichthe chemical is introduced into the body, and the degree andway in which the chemical impacts the body (MacGregor,Slovic, and Malmfors 1999). These estimates rest on scien-tific and technical considerations based on the biophysicalsciences and applied mathematics (Dietz, Frey, and Rosa2002; Kasperson et al. 1988; Rayner and Cantor 1987). Acritical assumption made by experts is that the probabilitiesand consequences of particular threats can be objectivelymeasured and quantified through traditional risk assessment(Slovic 2000b). Social scientists have challenged thisassumption, arguing that assessments of risk by expertsare inherently subjective (Funtowicz and Ravetz 1992;Krimsky and Golding 1992) and, what is more, that ‘‘humanbeings have invented the concept of risk to help them un-derstand the [real] dangers and uncertainties of life’’ (Slovic2000b:392).
In contrast to traditional risk assessment, ‘‘much of thepublics’ reactions to [perceived] risk can be attributed to asensitivity to technical, social, and psychological qualities ofhazards that are not well-modeled in technical risk assess-ments’’ (Slovic 1997:22). In addition, because traditional riskassessments are typically based on aggregate data, the dis-tributional impacts of perceived risks on different segmentsof the population are ignored (Dietz et al. 2002). Simply put,the technical concept of risk is too narrow. The incongruenceof expert assessment and lay risk perceptions, the subjec-tiveness of traditional risk assessment, and the neglect of
454 B. K. Marshall
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
distributional impacts of perceived risk have increasinglychallenged social scientists to inform debates about tech-nological risk assessment and lay risk perception (Dietz et al.2002; Freudenberg 1988; Kasperson et al. 1988; Short 1984).
The purpose of this research is to examine risk perceptionvariation by highlighting hypotheses recently raised in theliterature and testing these hypotheses in a chronicallypolluted context, an area where industrial pollution is palp-able and well-documented. The first hypothesis, derivedfrom the findings of Flynn, Slovic, and Mertz (1994), is thatWhite males perceive risks to be less threatening than wo-men and non-White males. The ‘‘White male’’ hypothesisimplies that there is something unique about being a Whitemale in the United States that leads to lower risk perceptionsand greater willingness to accept risks. To date, the Whitemale hypothesis has not been tested in a high risk, chroni-cally polluted environment. The second hypothesis, articu-lated by Greenberg and Schneider (1995), is that ‘‘genderdifferences in risk perception do not exist among males andfemales who actually live in stressed neighborhoods withmultiple hazards’’ (p. 503). This second perspective, one wewill call the ‘‘context matters’’ hypothesis, suggests thatgender differences in risk perception are, in part, a functionof the existence and number of ‘‘real’’ hazards people face intheir communities.
The data used in this research are drawn from a survey of apopulation living in a chronically polluted environmentknown as ‘‘Cancer Alley,’’ a stretch of the Mississippi Riverfrom Baton Rouge to New Orleans. The biophysical contextof the study and the survey sampling techniques used affordan opportunity to test the hypotheses discussed above.
GENDER AND PERCEPTIONS OF RISK
Many studies have examined the relationship betweengender and environmental risk perceptions, with evidenceindicating that women are more concerned than men aboutenvironmental risks and tend to judge these risks as moreproblematic (Blocker and Eckberg 1989; Bord and O’Connor1997; Brody 1984; Davidson and Freudenberg 1996;Finucane, Slovic et al. 2000; Flynn et al. 1994; Gutteling and
Risk Perceptions in Cancer Alley, LA 455
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
Wiegman 1993; Gwartney-Gibbs and Lach 1991; Klineberg,NcKeever, and Rothenbach 1998; McStay and Dunlap 1983;Mohai 1992; O’Connor, Bord, and Fisher 1999; Pilisuk andAcredolo 1988; Riechard and McGarrity 1994; Savage 1993;Spigner, Hawkins, and Loren 1993; Steger and Witte 1989;Stern, Dietz, and Kalof 1993). Given this preponderance ofevidence, the question is why do risk perceptions differ bygender? One explanation, from an ecofeminist perspective,is that gender-based risk perception differences are a func-tion of biological differences, manifested in the woman’s roleas reproducers and primary caregivers. For this reason,women are presumed to be inherently more nurturing ofpeople and the environment than men. Recent studiescontend that evidence of the ‘‘White male effect’’ (Finucane,Slovic et al. 2000; Flynn et al. 1994; Slovic 1997, 2000b)attenuates this purely biological explanation, since genderperception differences should (but do not) transcend racialboundaries (Finucane, Slovic et al. 2000; Slovic 2000b).
A second set of explanations focuses on sociologicalfactors, specifically the gendered processes of socializationand the reification of socially constructed gender differ-ences within occupational structures (Blocker and Eckberg1997). Women have been dissuaded from studying sciencein school (Alper 1993) and denied ‘‘access to the market-place and to scientific and technological realms whileassigning them the role of caregiver’’ (Blocker and Eckberg1997:842). Although some evidence indicates that womenare less knowledgeable and familiar with science andtechnology than men, the empirical relationship betweenknowledge and risk perceptions has not been established(Arcury, Scollay, and Johnson 1987; George and Southwell1986; Hoban, Woodrum, and Czaja 1992; Schahn andHolzer 1990; Solomon, Tomaskovic-Devy, and Risman1989). Furthermore, even among physical scientists withpresumably similar levels of scientific knowledge, studiesstill find evidence of women being more concerned thanmen about societal risks (Slovic et al. 1997) and risks fromnuclear technologies (Barke, Jenkins-Smith, and Slovic1997). That women have faced barriers to science-basededucation and careers is unfortunate, but this fact does notexplain why risk perception differences between womenand men exist.
456 B. K. Marshall
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
Other explanations attribute risk perception differences togender roles in society (Crawford and Unger 1996; Eagly1987; Howard and Hollander 1996; Wilkinson and Kitzinger1996; Zelezny, Chua, and Aldrich 2000). On one hand,women are socialized to ‘‘be more expressive, to have astronger ‘ethic of care,’ and to be more interdependent,compassionate, nurturing, cooperative, and helpful incaregiving roles’’ (Zelezny et al. 2000:445; also Beutel andMarini 1995; Gilligan 1982). On the other hand, men aresocialized to provide economically for the family (Blockerand Eckberg 1997; Gilligan 1982; McStay and Dunlap 1983;Mohai 1992) and be independent and competitive (Beuteland Marini 1995; Zelezny et al. 2000). Thus, socialized asnurturing caregivers, women are more concerned than menabout health and safety issues, especially those thoughtto stem from nuclear technologies and chemical waste(Blocker and Eckberg 1997; Brody 1984; Nelkin 1981;Solomon et al. 1989; Steger and Witte 1989; Stout-Wiegandand Trent 1983).
Strong evidence of gender differences regarding risksrelated to health and safety issues are presented in anexhaustive literature review by Davidson and Freudenburg(1996). The authors analyze 85 studies on gender andenvironmental risk concerns, assessing 5 hypotheses thatseek to explain the gender gap in environmental risk per-ceptions regarding technological hazards. Gender variationin risk perceptions may be a function of women, comparedto men, having 1) less knowledge about science and theenvironment, 2) less trust in institutions, 3) less concernabout the economy, 4) more concern about children, and 5)more concern about health and safety issues.
The last hypothesis suggests that women have heightenedrisk perceptions because they are more concerned about thehealth and safety of both family and community. The authorsconclude that the ‘‘health and safety’’ hypothesis ’’ . . .receives the clearest and most consistent support of all thefive hypotheses considered . . . in fact, [this hypothesis] hasreceived support in literally all of the available studies thathave considered it’’ (Davidson and Freudenburg 1996:323).Based on Davidson and Freudenburg’s findings, Bord andO’Connor (1997) contend that ‘‘for women, once risks tohealth and personal well-being become linked to
Risk Perceptions in Cancer Alley, LA 457
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
environmental issues, their levels of concern tend to surpassthose of men.’’ Accordingly, ‘‘if a survey measures environ-mental attitudes in ways that trigger risk perceptions, womenwill score higher in concern than men’’ (p. 832). Studies onrisk are replete with race- and gender-specific hypothesesattempting to account for attitudinal variation. However, raceand gender differences may mask more notable patternsacross sociodemographic groups, patterns that lie at theintersection of race and gender.
WHITEMALE EFFECT
To date, two studies have found evidence of the ‘‘Whitemale effect’’ (Finucane et al. 2000b; Flynn et al. 1994). Thefirst study presented the results of a national survey of riskperceptions associated with 25 hazards that tap a diversearray of specific risks related to technology, lifestyle, andenvironmental conditions. The authors find that Whitemales are significantly more accepting than women andnon-Wite males of specific risks associated with 20 of the 25hazards included in the survey (Flynn et al. 1994).
Finucane, Slovic, et al. (2000) replicates the above studyby examining data from a national survey that includedrisk perception questions measuring ‘‘health risk to in-dividuals and families’’ and ‘‘food risks to the public.’’ Theauthors also find strong support for the White male effect onrisk perceptions for both sets of measures. The obviousquestion is why are White males so accepting of risk. Flynnet al. (1994) shed light on the question, finding that theWhite male effect is accounted for by only 30% of the Whitemale sample; the risk perceptions of the other White males(70%) were similar to that of females and blacks. The risk-accepting White males had higher levels of socioeconomicstatus and were more politically conservative compared tothe risk adverse White males and the rest of the sample(Flynn et al. 1994; Slovic 2000b). Slovic (1997) concludes:
Perhaps white males see less risk in the world because theycreate, manage, control and benefit from many of the majortechnologies and activities. Perhaps women and non-whitemen see the world as more dangerous because in many ways
458 B. K. Marshall
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
they are more vulnerable, because they benefit less from manyof its technologies and institutions, and because they have lesspower and control over what happens in their communitiesand their lives. (p. 402)
Previous empirical studies finding evidence of the Whitemale effect used national data. We add to this literature bytesting the White male hypothesis at the local level in achronically polluted environment.
CONTEXTMATTERS: GENERALVERSUS LOCAL RISKS
Greenberg and Schneider (1995) suggest that those studiesthat find gender differences draw on surveys of nationalpopulations or college students who generally do notexperience risks directly, but indirectly through the media orinfrequent trips to high risk environments. The authorshypothesize that the risk perceptions of males and femalesshould not significantly differ in ‘‘stressed’’ neighborhoodswith multiple hazards, since responses to actual risks shouldtranscend gender. This hypothesis is partially based on stu-dies finding that males and females have similar levels ofconcern and stress in the aftermath of conflict and naturaldisasters.1 Greenberg and Schneider (1995) utilized two datasets—the national data from the American Housing Survey(AHS) and mail surveys of 10 neighborhoods in New Jersey,Pennsylvania. The critical variable that distinguishes betweenstressed (high risk) and nonstressed (low risk) environmentsfor both analyses are measures of neighborhood quality. Theauthors find moderate support for their hypothesis; genderdifferences in risk perceptions exist in nonstressed environ-ments, but not in stressed environments. However, thesefindings appear to be anomalous and incongruent withevidence from other studies examining gender and riskperceptions of technological disasters and toxic waste.
1It should be noted that disaster researchers make a distinction between natural and tech-nological disasters, documenting that the latter ’’ . . . create a far more severe and long-lastingpattern of social, economic, cultural and psychological impacts than do natural [disasters]’’(Freudenburg 1997:26). As such, using data on technological disasters to test a hypothesisdrawn from studies on natural disasters is questionable.
Risk Perceptions in Cancer Alley, LA 459
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
In summing up their review of 85 studies, Davidson andFreudenburg (1996) conclude that, on one hand, for studiesfocusing on broad questions of environmental concern, thereis limited variation by gender and when differences do exist,they are quite weak. On the other hand, for studies thatexamine environmental issues framed as localized threats tohealth and safety, there is consistent and significant evidencethat women express higher levels of concern than do men(see also, Blocker and Eckberg 1989, 1997; Mohai 1992,1997). Specifically, research has shown that women aremore concerned than men about local environmental healthand safety risks, such as the contamination of water supply(Hamilton 1985a, 1985b) and the construction of a nuclearpower plant or a waste facility (Brody 1984; George andSouthwell 1986; Nelkin 1981; Solomon et al. 1989).Research on the grassroots environmental movement alsosupports the notion that women are more concerned thanmen about local environmental problems. Case studieshave found that women, not men, tend to emerge asleaders in community efforts to address local environmentalcrises (Krauss 1993). In sum, purely biological and knowl-edge-based explanations have been attenuated by recentresearch, while it is becoming increasingly clear that socialfactors have an impact on risk perceptions.
Hypotheses
We contend that the degree to which risk perceptions varyby gender is contingent on the immediate threat to self andfamily that is conveyed by the environmental referent underquestion. In other words, gender and race risk perceptiondifferences for nonspecific or broad environmental concernquestions should be minimal. If, however, the environmentalhazards are specific and perceived as posing a threat to thehealth and safety of children and the family, then risk per-ceptions will vary by gender and race, with females andBlacks being more concerned. Finally, we argue that genderand race differences in risk perceptions can be largelyaccounted for by the White male effect.
1. People who indicated that there is an industrial plant intheir community will perceive risks as more serious thanthose who did not.
460 B. K. Marshall
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
2. Gender differences in risk perception will not exist incommunities without industrial plants; however, in com-munities with industrial plants, women will perceive risksas more serious than men.
3. Racial differences in risk perception will not exist incommunities without industrial plants; however, in com-munities with industrial plants, Blacks will perceive risks asmore serious than Whites.
4. Risk perception differences by gender and race in com-munities with industrial plants mostly will be due to theWhite male effect.
CANCER ALLEY, LA
Given its history of plantations and slavery and, morerecently, as a refuge for polluting industries, Roberts andToffolon-Weiss (2001:25) refer to Louisiana as the environ-mental justice ‘‘frontline.’’ Cancer Alley, an area along an85-mile stretch of the Mississippi River from Baton Rouge toNew Orleans, is one of the most highly polluted industrialregions in the nation (Bullard 1990). The Mississippi Rivercollects nearly one-half of all the toxic pollutants dumped intothe waters of the United States (Myers 1989). Twenty-fivepercent of the nation’s chemical industries are located inLouisiana and the state dumps more waste into the river thanany other (Adler 1990). Much of this waste, 150,000 tons oftoxic effluent per annum, is generated and dumped by morethan 130 industrial facilities that line the banks of theMississippi River in Cancer Alley (Ellis 1993; LouisianaDepartment of Environmental Quality 1991). The chemicalsreleased into the environment include some of the most toxicused inmanufacturing, some ofwhich are known or suspectedto cause health risks when humans are exposed to them(Louisiana Department of Environmental Quality 1991).
Research on environmental justice have focused on con-taminated communities and the distribution of environ-mental risks in Cancer Alley (Adeola 1995, 2000; Burby andStrong 1997; Roberts and Toffolon-Weiss 2001; Wright1998). Conducting a Geographic Information Systemsanalysis of nine parishes along the Mississippi River,Wright (1998) found that air polluting facilities were
Risk Perceptions in Cancer Alley, LA 461
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
disproportionately located in areas with high concentrationsof African Americans and that cancer mortality rates werehigher in Cancer Alley than average rates in Louisiana. Twolarge metropolitan areas lie at opposite ends of Cancer Alley.In Baton Rouge, Adeola (1995) found that Blacks and maleswere more likely to reside near hazardous waste sites andreport problems with environmental illness than Whites andfemales, respectively. Similarly, Adeola (2000) conducted asurvey of people living in a community with a Superfund site(Agriculture Street Landfill) and people living in threeenvironmentally benign (control) communities. Compared tothe control communities, respondents from the AgriculturalStreet community were more likely to be Black, have lowersocioeconomic status, indicate that their community haschanged for the worse, and link health problems toenvironmental conditions (Adeola 2000). As the abovestudies illustrate, people of color and poor people living inCancer Alley are not only disadvantaged socioeconomicallybut also must bear the burden of living in a contaminatedenvironment.2
METHODS
Survey
We conducted a secondary data analysis of a survey ofresidents living in seven Louisiana parishes (Ascension, WestBaton Rouge, East Baton Rouge, St. Charles, Iberville, St.James, St. John the Baptist) along the Mississippi River withinCancer Alley. Using a Computer-Aided Telephone Inter-viewing (CATI) system and random digit dialing, the SurveyResearch Center at the University of New Orleans conducteda stratified (by seven parishes) random sample survey ofhouseholds located in Cancer Alley in July 1994. At the startof each interview, the interviewer screened the respondents
2Those living in Cancer Alley have been somewhat empowered in the 1990s due, in part,to the environmental justice movement. Two of the four case studies presented by Robertsand Toffolon-Weiss (2001) are in Cancer Alley. In the LES case, a community group blockedthe siting of a uranium-enrichment facility. In the second case, a coalition of residents andoutside groups prevented the siting of a multi-million-dollar chemical plant in Convent,LA by the Shintec Corporation.
462 B. K. Marshall
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
by using three criteria: 1) age 18 or older, 2) family income ofless than $32,000 (the estimated median family income ofresidents in the sampling frame), and 3) household residencewithin one mile of the Mississippi River. As such, only re-spondents from low- and moderate-income households wereinterviewed.3 Furthermore, proximity to the petrochemicalindustries was quasi-controlled, since these industries tend toline the river for easy access to shipping lanes, use of waterfor industrial processes, and to dispose of pollutants. Theresponse rate for this survey was 53%, 774 respondents wereinterviewed, and each interview lasted approximately 15minutes.4
Measures
Environmental Risk: Eleven variables measure the per-ception of environmental risks. The setup statement for thisseries of items is as follows: ‘‘Now I’d like you to think aboutthe environment along the Mississippi River. Some peoplethink there are problems with industry along the river. Otherpeople think there aren’t very many problems. For each itemI read, tell me whether you think it not much of a problem,somewhat of a problem, or a serious problem.’’ The problemsincluded water pollution, noise, disposal of hazardous waste,air pollution, toxic chemical leaks, odors, flames from a
3This survey was funded by the Louisiana Environmental Resource and Education Pro-gram (LEREP) at the University of New Orleans. Dr. Raymond Burby of the College of Urbanand Public Affairs at the University of New Orleans served as the principal investigator. Sam-pling decisions were made based on the mission of the LEREP. The simple random samplewas stratified (in proportion to parish population) to provide information that would be usefulin delivering technical assistance to each Parish. The survey’s focus on low- and moderate-income families reflects LEREP’s mission to assist this population, since they are the most atrisk from the adverse health effects of living in Cancer Alley.
4With a relatively low response rate, an assessment of nonresponse bias is warranted. Themost common method (the other two techniques—intensive postsampling and wave extrapo-lation—must be used during the survey or shortly after its completion) of estimating nonre-sponse bias is through a population comparison, where survey averages are comparedwith known population averages for selected variables. Since the study population (peopleliving within one mile of the Mississippi River) does not correspond with extant politicalboundaries (parishes or Louisiana), I do not have data on the population. Comparing surveyaverages to parish averages is doable and might be interesting, but it would not allow me toaddress the issue of nonresponse bias.
Risk Perceptions in Cancer Alley, LA 463
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
refinery smoke stack, plumes of smoke, pollution of landfrom improper waste disposal, industry too close to people’shomes, and illness caused by industry. Each ordinal variablewas recoded as a dichotomous variable with 1 ¼ ‘‘seriousproblem’’ and 0 ¼ ‘‘not much of a problem,’’ or ‘‘somewhatof a problem.’’
Internal Efficacy: This question uses a 5-point likert scale,asking the respondent their attitudes regarding the fol-lowing statement: ‘‘People like me have a voice in whetherchemical industries are located here.’’ This question is ameasure of internal efficacy, the degree to which people feelthat they can impact the world around them.
Age: Respondent ages ranged from 18 to 88, with a meanage of 47 years.
Household Income: Again, only respondents from low-and moderate-income households were interviewed. Assuch, this variable is coded with 1 ¼ less than $10,000, 2 ¼$10,000 to $19,000, 3 ¼ $20,000 to $29,000, and 4 ¼$30,000 to $32,000.
Education: This question is measured with a five-categoryresponse set (1 ¼ less than ninth grade, 2 ¼ ninth toeleventh grade, 3 ¼ high school degree, 4 ¼ some college,and 5 ¼ college degree).
Employed Full-Time: This variable was computed fromtwo questions regarding employment status (0 ¼ un-employed or employed part-time; 1 ¼ employed full-time).
School-Age Children: This question asks the respondent ifthey have school-age children at home (0 ¼ no; 1 ¼ yes).
Industrial Plants in Community: This question asks therespondent if there is an industrial plant located in theircommunity (0 ¼ communities without plants; 1 ¼ com-munities with plants).
Work in Chemical Plant: This question asks the respondentif they or someone in their family work in one of the che-mical plants (0 ¼ no; 1 ¼ yes).
FINDINGS
Data presented in Table 1 provide a test of the firsthypothesis which contends that perceptions of risk will behigher for people who indicated that there is a plant in their
464 B. K. Marshall
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
community compared to those who did not. SPSS forWindows (version 11.0) was used for the analyses thatfollow. Cell entries in Table 1 are the percentage of re-spondents who indicated the environmental risk was a‘‘serious’’ problem. Cross tabulation procedures were used toidentify statistically significant (p< .05) group differences.The percent difference and the statistical significance of thisdifference are presented in the last column. The positive signof the percent differences indicates strong support for the firsthypothesis. Respondents with plants in their communityperceived each of the 11 risks as more serious than re-spondents without plants in their community. What is more,the percent differences for all 11 risks are statistically sig-nificant at the p< .05 or lower. Differences are largest forindustry too close (þ17.4), illness from industry (þ15.2),flames from smokestacks (þ15.1) and toxic chemical leaks(þ13.4).
In Table 2, the data presented allows for an assessment ofthe second hypothesis, that gender differences are less likelyto exist in communities without plants, but women willperceive risks as more serious than men in communities with
TABLE 1 Percent Reporting Each Risk as Serious by Community
Environmental risksCommunitieswithout plants
Communitieswith plants
%Difference
Water pollution 46.9 54.3 þ7.4a
Air pollution 41.4 53.6 þ12.2c
Hazardous waste disposal 41.5 45.8 þ4.3a
Industry too close 27.9 45.3 þ17.4c
Illness from industry 27.4 42.6 þ15.2c
Odors 27.7 36.8 þ9.1b
Toxic chemical leaks 23.6 37.0 þ13.4c
Pollution from waste 22.1 31.0 þ8.9b
Plumes of smoke 13.4 26.1 þ12.7c
Flames from smokestacks 10.6 25.7 þ15.1c
Noise 4.7 13.9 þ9.2c
n 157–195 474–563
Cell entries are the percent reporting each risk as serious. Pearson’s chi-squarestatistic was used to test significance.
asignificant at p< .05; bSignificant at p< .01; csignificant at p< .001.
Risk Perceptions in Cancer Alley, LA 465
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
plants. Cell entries are the same as in Table 1. The percentdifferences between men and women in communities with-out plants are inconsistent, ranging from 78.6 to þ11.7.For some risks (notably, hazardous waste disposal and waterpollution), men are more concerned; for others (notably,odors and air pollution), women are more concerned.However, none of these differences are statistically sig-nificant. In communities with plants, the positive sign of thepercent difference for ten of the risks (last column, Table 2)indicate that women perceive risk as more serious than men.The only exception is that men view pollution from wasteas more serious than women. The difference for illness fromindustry (þ13.5), industry too close (þ14.2), odors (þ14.0),and air pollution (þ6.6) is large, in the hypothesized
TABLE 2 Percent Reporting Each Risk as Serious by Community andGender
Cell entries are the percent reporting each risk as serious. Pearson’s chi-squarestatistic was used to test significance.
asignificant at p< .05; bsignificant at p< .01; csignificant at p< .001.
466 B. K. Marshall
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
direction, and statistically significant. Overall, we findmoderate support for the second hypothesis.5
The third hypothesis suggests that race differences will notexist in communities without plants, but Blacks will perceiverisks as more serious than Whites in communities withplants. As presented in Table 3, percent differences existbetween Whites and Blacks in communities without plants,
TABLE 3 Percent Reporting Each Risk as Serious by Community and Race
Cell entries are the percent reporting each risk as serious. Pearson’s chi-squarestatistic was used to test significance.asignificant at p< .05; bsignificant at p< .01; csignificant at p< .001.
5One caveat worth noting is that the number of cases for the ‘‘communities with plants’’subgroup is considerably greater than the ‘‘communities without plants’’ subgroup. Thus, thelack of statistical significance found for mean differences in the latter (e.g., water pollutionand hazardous waste disposal) may be due to small number of cases analyzed.
Risk Perceptions in Cancer Alley, LA 467
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
but are inconsistent and only one of the differences is sta-tistically significant. Specifically, Blacks are more likely thanWhites to perceive odors as serious. In communities withplants, percent differences (last column, Table 3) for 8 of the11 risks are statistically significant and support the third hy-pothesis. For instance, significant differences are largest forodors (þ20.3), industry too close (þ16.5), and illness fromindustry ( þ13.1). Overall, we find moderate to strong sup-port for the third hypothesis.
Following earlier research on the White male effect, wedivided the sample into four subgroups—White males,White females, Black males, and Black females. Table 4provides descriptive statistics for each of the four subgroups.The mean age differences are fairly minor with Black malesas the youngest subgroup (43.8 years old) and White femalesas the oldest subgroup (50.5 years old). Income differences,however, are quite large with only 12.3% of White malesearning less that $10,000 a year compared to 39.3% forBlack females. With nearly one-third (31.6%) having lessthan a high school degree, Black females are less educatedthan the other groups. Approximately one-half of the Whitemales (53.3%) and Black males (49.6%) are employed with afull-time job, while the figures are considerable lower forWhite females (31.6%) and Black females (32.4%). Blackfemales (52.8%) are much more likely to have school-agechildren than Black males (38.9%), White females (29.7%),
TABLE 4 Descriptive Statistics for Selected Variables by Race/GenderSubgroups
Selected variablesWhitemales
Whitefemales
Blackmales
Blackfemales
Age (mean) 45.1 50.5 43.8 46.1Income (%< 10,000 per year) 12.3 23.4 23.4 39.2Education (%<H.S. degree) 13.2 20.1 23.9 31.6Employed (% full-time) 53.3 31.6 49.6 32.4School-age children (% yes) 28.4 29.7 38.9 52.8Industrial plant in thecommunity (% yes)
77.6 74.4 73.2 69.7
Respondent/family workin plant (% yes)
60.3 55.7 61.1 51.1
n 229 256 113 176
468 B. K. Marshall
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
and White males (28.4%). A majority of each subgroup(69.7% to 77.6%) indicated that there is an industrial plant intheir community, but the differences across subgroups areminor. Finally, over one-half of each subgroup indicated thatthey or someone in their family worked in a plant, with thehighest percent for Black males (61.1%) and the lowest Blackfemales (51.1%).
Our fourth hypothesis contends that gender and race riskperception differences in communities with plants are mostlydue to the White male effect. Table 5 presents data on therisk perceptions of each of the subgroups. A general linearmodel (GLM) version of one-way analysis of variance(ANOVA) was used to evaluate this hypothesis because itsupports use of ordinal dependent variables. Six dichot-omous, between-subjects factors (each comparing two sub-groups) were created and used in a series of one-wayANOVAs. From a cursory look at Table 5, two patterns arenotable. First, White males perceive risks to be less seriousthan the other subgroups for 9 of the 11 risks (the exceptionsare hazardous waste disposal and pollution from waste).Second, Black females perceive risks to be as or more seriousthan the other subgroups for 9 of the 11 risks (the exceptionsare water pollution and hazardous waste disposal).6 The riskperception differences between White males and Black fe-males are statistically significant for 7 of the risks. The riskperceptions of White males and Blacks males regarding in-dustry being too close and flames from smokestacks aresignificantly different. Finally, White male and White femaledifferences are significant for the question on illness fromindustry. Based on these differences, we find support for theWhite male hypothesis.
The data in Table 5 suggests that the race- and gender-based risk perception differences (presented in Tables 3 and4) may actually reflect differences between White males andBlack females. In order to provide a more rigorous test of theWhite male effect, we conducted four hierarchical multipleregression models (two-stages). The dependent variable was
6Although risk perceptions vary by subgroup, the internal consistency of the eleven riskquestions is quite high for each subgroup, with a Cronbach’s Alpha of .91 for White males,.90 for White females, .89 for Black males, and .90 for Black females.
Risk Perceptions in Cancer Alley, LA 469
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
created by summing the 11 dichotomous risk perceptionvariables. In the first stage, risk perceptions were regressedon a set of 8 control variables and then, in the second stage,the dichotomous variables (White male, White female, Blackmale, Black female) were added in separate models. Table 6only includes the hierarchical models for White males andBlack females, since the effects of being a White female orBlack male, over and above the control variables, were notstatistically significant.
The base model (column 1) presented in Table 6 is statis-tically significant and the linear combination of theindependent variables accounts for 9% of the variance(R3¼ .10, F (8, 390)¼ 5.13, p< .001). Four of the controlvariables are statistically significant (p< .05 or lower) pre-dictors of risk perceptions. Specifically, people with lowerhousehold incomes, younger people, people with plants intheir community, and people with low efficacy are more
TABLE 5 GLM One-Way ANOVA of Risk Perceptions by Race/GenderSubgroups in Communities with Plants
Environmental risksFa
valueWhitemales
Whitefemales
Blackmales
Blackfemales
Water pollution .72 48.8 58.7 60.5 51.3Air pollutionb 2.91a 44.8 55.2 61.0 58.8Hazardous waste disposal 1.21 44.3 51.0 39.7 45.0Illness from industryb, c, d, f 17.46a 32.7 42.6 40.5 58.3Industry too closeb, c, e 6.68a 32.9 45.4 47.4 61.5Odorsb, c, d 10.47a 25.0 34.0 38.3 58.3Toxic chemical leaksb, c 2.67a 31.3 36.4 35.5 48.1Pollution from waste .92 32.5 26.3 34.7 33.0Plumes of smokeb, e 2.60a 21.4 23.7 34.6 30.8Flames from stacksb, c, e 3.60a 18.4 24.6 32.9 33.3Noise 1.68 10.7 13.0 17.1 17.5n 177 189 82 122
Main cell entries are percentages of each subgroup responding that the problemis ‘‘serious.’’
aF value significant at the p< .05 level.GLM One-Way ANOVA (two level between subjects factor) significant (p< .05)
differences between: bBlack females and White males; cBlack females and Whitefemales; dBlack females and Black males; eBlack males and White males; fWhitemales and White females.
470 B. K. Marshall
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
likely to view environmental risks as serious. Notably, thecontrol variables education, whether the respondent orsomeone in their household works in a chemical plant, full-time employment, and having children were not statisticallysignificant (omitted from Table 6). We can see from the datain column two that, even after controlling for the othervariables in the model, White males are less likely toperceive environmental risks as serious (R2 change¼ .03,Fchange (1, 389)¼11.95, p< .001). In contrast, Black fe-males (column three) are more likely to perceive environ-mental risks as serious than their counterparts (R2
change¼ .01,F change (1, 389)¼ 4.39, p< .05). Althoughthe effect size of being a White male or a Black female onrisk perceptions is quite small (explaining 3% and 1% ofthe variance, respectively), we find support for hypothesisfour in the multiple regression models. We also find supportfor hypothesis one, since people who indicated they have aplant their community is a significant predictor of riskperceptions.
White male — 71.25 (7.17)c —Black female — — .88 (.11)a
R2 .095c .122c .105c
R2 change — .027c .010a
F change 5.13 11.95 4.39n 398 398 398
Main cell entries are unstandardized regression coefficients; parenthetical cellentries are standardized regression coefficients.
asignificant at p< .05; bsignificant at p< .01; csignificant at p< .001.
Risk Perceptions in Cancer Alley, LA 471
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
DISCUSSION
The main purpose of this research is to test the White malehypothesis and context matters hypothesis in a chronicallypolluted environment. In support of the context mattershypothesis, we found that environmental risks were morelikely perceived as a serious problem by people whoindicated that there is an industrial plant in their communitythan by those who did not. We also found support for thishypothesis in the multiple regression analyses. In addition,few significant race and gender risk perception differencesexisted in communities without plants, but more Blacks thanWhites and more women than men perceived environmentalrisks as a serious problem in communities with plants. Wealso found support for the White male hypothesis. Race andgender risk perception differences in communities with in-dustrial plants are mostly due to the relatively extreme per-ceptions of risk accepting white males and risk adverse Blackfemales. White females and Black males had somewhat si-milar risk perceptions and there were no significant differ-ences between the two subgroups. After controlling forincome, education, age, having a plant in your community,working in a chemical plant, and efficacy, being a Whitemale or Black female still has a significant impact on riskperceptions.
One of the studies found that the White male effect wasmostly due to a subset (30%) of White males with higherhousehold incomes and more education than the rest of thepopulation (Flynn et al. 1994). Due to sampling criteria(determined by the principal investigator, not the author), norespondents with household incomes of more than $32,000were interviewed in this study. The subset of White maleswith high socioeconomic status (SES) who tend to be themost risk accepting were excluded from our analyses. Thus,the strength of the White male effect on risk perceptions inCancer Alley may be attenuated due to the sampling criteria.Compared to the other subgroups, Black females have lowerSES and are more likely responsible for school-age children.
The question is why do White males and Black females inCancer Alley view risks from industrial plants so differently?If the social structural advantages of being White and malecreate what other researchers are calling a White male effect,
472 B. K. Marshall
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
then it follows that the social structural disadvantages ofbeing Black and female would generate a Black femaleeffect. Past studies have used sociodemographic character-istics as surrogates for an individual’s social structural posi-tion in society (e.g., Umberson, 1993). Furthermore, differentexperiences associated with structural position shapeindividuals’ perceptions of self, society (Gecas and Schwalbe1983) and the environment. Following earlier research, wespeculate that race/gender subgroups are crude measures ofone’s social structural position in society and, relatedly, theirlevels of perceived vulnerability (Finucane, Slovic et al.2000; Flynn et al. 1994). Internal efficacy is the strongestpredictor of risk perceptions in the multiple regression ana-lyses and arguably is a measure of vulnerability. After con-trolling for income, education, and efficacy (and three othervariables), being a White male or a Black female still has asignificant effect on risk perceptions.
What can we conclude from this finding? First, it should beremembered that race/gender subgroups are viewed only ascrude measures of social structural position and vulner-ability. Second, even though the sampling criteria used mayserve as a quasi-experimental control of proximity to thepetrochemical industries, proximity may still be a function ofrace. Of those people living within one mile of theMississippi River in Cancer Alley, 60% are White and 38%are Black. Some evidence suggests that Blacks are morelikely than Whites to live literally right next to the petro-chemical industries (Roberts and Toffolon-Weiss 2001).7 Assuch, Black females may be the most risk adverse because afence may be the only barrier separating their home from thepetrochemical plant. In addition, as primary caregivers andmost likely the head of the household, Black females aremore likely to view risks as a threat to the health and safety ofthe family.
7One reason for this pattern is that with few options after slavery was abolished, formerslaves continued to work on the plantations as wage laborers or sharecroppers. Nearly a cen-tury later, these plantations, as large tracts of inexpensive land next to the Mississippi River,became ideal locations for petrochemical industries. In many cases, descendants of formerslaves continue to live around the perimeter of the petrochemical plants (Roberts andToffolon-Weiss 2001).
Risk Perceptions in Cancer Alley, LA 473
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
CONCLUSION
At the risk of oversimplification, we suggest that Whitemales feel less vulnerable because they tend to occupy thehigher social structural positions in society, whereas Blackfemales feel more vulnerable because they tend to occupy thelower social structural positions in society. Furthermore, wecontend that one’s level of vulnerability has an impact on theperceived risk of an event or activity and perhaps on the per-ceived benefits. Some suggest that perceptions of risks andbenefits are inversely related; that is, in response to a particularhazard, ‘‘the greater the perceived benefit, the lower the per-ceived risk, and vice versa’’ (Finucane, Alhakami et al.2000:415). Perhaps less vulnerable White males perceive in-dustrial production as a source of economic benefits with fewrisks, while the more vulnerable Black females perceive in-dustrial production as a threat to the health and safety of familywith few economic benefits.
Beyond the scope of this article, but perhaps an areaworthy of future research, is to assess whether or notvulnerability operates as an affect heuristic that serves as acue in lay risk perceptions. An affect heuristic is based on the‘‘representations of objects and events in people’s minds[that] are tagged to varying degrees with [negative andpositive] affect’’ (Finucane, Alhakami, et al. 2000:414). Therole of affective processes in risk perception has beenunderstudied and deserves more attention (Finucane,Alhakami et al. 2000; Slovic 2000a). Future research alsoneeds to unravel the complex relationship between race/gender subgroups and risk perceptions by identifying andexamining the role of potential mediating factors—such as,vulnerability, social structural position, trust in government,socioeconomic status, and efficacy. Examining these re-lationships across different contexts that vary by spatial scale,region, and the degree and type of environmental degrada-tion may provide information useful for reducing risk con-flict and improving the effectiveness of risk managementand communication. Given that risk management andcommunication go beyond the biophysical sciences andare firmly embedded in the social and political fabric ofour society, social scientists must better understand thecontextual nature of risk perceptions and why certain
474 B. K. Marshall
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
sociodemographic groups tend to be risk adverse whileothers risk accepting.
REFERENCES
Adeola, Francs O. 1995. ‘‘Demographic and Socioeconomic Differentials inResidential Propinquity to Harzardous Waste Sites and Environmental Illness.’’Journal of the Community Development Society 26:15–39.
———. 2000. ‘‘Endangered Community, Enduring People: Toxic Contamination,Health, and Adaptive Responses in a Local Context.’’ Environment andBehavior 32:209–49.
Adler, John. 1990. ‘‘Troubled Waters.’’ Newsweek, April 16, p. 66.Alper, Joe. 1993. ‘‘The Pipeline is Leaking Women All the Way Along.’’ Science
260:409–11.Arcury, Thomas A., Susan Scollay, and Timothy P. Johnson. 1987. ‘‘Sex Differ-
ences in Environmental Concern and Knowledge.’’ Sex Roles 16:463–72.Barke, Richard P., Hank Jenkins-Smith, and Paul Slovic. 1997. ‘‘Risk Perceptions
of Men and Women Scientists.’’ Social Science Quarterly 78:167–76.Beutel, Ann M. and Margaret M. Marini. 1995. ‘‘Gender and Values.’’ American
Sociological Review 60:436–48.Blocker, T. Jean and Douglas L. Eckberg. 1989. ‘‘Environmental Issues as
Women’s Issues: General Concerns and Local Hazards.’’ Social ScienceQuarterly 70:586–93.
———. 1997. ‘‘Gender and Environmentalism: Results from the 1993 GeneralSocial Survey.’’ Social Science Quarterly 78:841–58.
Bord, Richard J. and Robert E. O’Connor. 1997. ‘‘The Gender Gap in Environ-mental Attitudes: The Case of Perceived Vulnerability to Risk.’’ Social ScienceQuarterly 78:830–40.
Brody, Charles. J. 1984. ‘‘Differences by Sex in Support of Nuclear Power.’’ SocialForces 63:209–28.
Bullard, Robert D. 1990. Dumping in Dixie: Race, Class, and EnvironmentalQuality. Boulder, CO: Westview Press.
Burby, Raymond J. and Denise E. Strong. 1997. ‘‘Coping with Chemicals: Blacks,Whites, Planners, and Industrial Pollution.’’ Journal of the American PlanningAssociation 63:469–80.
Crawford, Mary and Rhoda K. Unger. 1996. Women and Gender: A FeministPsychology. New York: McGraw-Hill.
Davidson, Debra and William Freudenberg. 1996. ‘‘Gender and EnvironmentalRisk Concerns: A Review and Analysis of Available Research.’’ Environmentand Behavior 28:302–39.
Dietz, Thomas, R. Scott Frey, and Eugene Rosa. 2002. ‘‘Risk, Technology, andSociety.’’ Pp. 329–69 in Handbook of Environmental Sociology, edited byR. E. Dunlap and W. Michelson. Westport, CT: Greenwood Press.
Eagly, Alice H. 1987. Sex Differences in Social Behavior: A Social Role Inter-pretation. Hillsdale, NJ: Erlbaum Associates.
Risk Perceptions in Cancer Alley, LA 475
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
Ellis, William S. 1993. ‘‘The Mississippi River Under Siege.’’ National Geo-graphic, November, p. 90.
Finucane, Melissa L., Ali Alhakami, Paul Slovic, and Stephen M. Johnson. 2000a.‘‘The Affect Heuristic in Judgments of Risks and Benefits.’’ Pp. 413–29 in ThePerception of Risk, edited by P. Slovic. London: Earthscan Publications.
Finucane, Melissa L., Paul Slovic, C. K. Mertz, James Flynn, and TheresaA. Satterfield. 2000b. ‘‘Gender, Race, and Perceived Risk: The ‘White Male’Effect.’’ Health, Risk & Society 2:159–72.
Flynn, James, Paul Slovic, and C. K. Mertz. 1994. ‘‘Gender, Race, and Perceptionof Environmental Health Risks.’’ Risk Analysis 14:1101–08.
Freudenberg, William R. 1988. ‘‘Perceived Risk, Real Risk: Social Science and theArt of Probabilistic Risk Assessment.’’ Science 242:44–9.
———. 1997. ‘‘Contamination, Corrosion, and the Social Order: An Overview.’’Current Sociology 45(3):19–40.
Funtowics, Silvio O. and Jerome R. Ravetz. 1992. ‘‘Three Types of Risk Assess-ment and Emergence of Post-normal Science.’’ Pp. 251–97 in Social Theoriesof Risk, edited by S. Krimsky and D. Golding. Westport, CT: Praeger.
Gecas, Victor and Michael L. Schwalbe. 1983. ‘‘Beyond the Looking-Glass Self:Social Structure and Efficacy-Based Self-Esteem.’’ Social Psychology Quarterly46:77–88.
George, David L. and Priscilla L. Southwell. 1986. ‘‘Opinion on the DiabloCanyon Nuclear Power Plant: The Effects of Situation and Socialization.’’Social Science Quarterly 67:722–35.
Gilligan, Carol. 1982. In a Different Voice: Psychological Theory and Women’sDevelopment. Cambridge, MA: Harvard University Press.
Greenberg, Michael R. and Dona F. Schneider. 1995. ‘‘Gender Differences in RiskPerception: Effects Differ in Stressed vs. Non-Stressed Environments.’’ RiskAnalysis 15:503–11.
Gutteling, Jan M. and Oene Wiegman. 1993. ‘‘Gender-Specific Reactions toEnvironmental Hazards in the Netherlands.’’ Sex Roles 28:433–47.
Gwartney-Gibbs, Patricia A. and Denise H. Lach. 1991. ‘‘Sex Differences inAttitudes Toward Nuclear War.’’ Journal of Peach Research 28:161–74.
Hamilton, Lawrence.C. 1985a. ‘‘Who Cares About Water Pollution? Opinions ina Small-Town Crisis.’’ Sociological Inquiry 55:170–81.
———. 1985b. ‘‘Concerns About Toxic Wastes: Three Demographic Predictors.’’Sociological Perspectives 28:463–86.
Hoban, Thomas, Eric Woodrum, and Ronald Czaja. 1992. ‘‘Public Opposition toGenetic Engineering.’’ Rural Sociology 57:476–93.
Howard, Judith A. and Jocelyn A. Hollander. 1996. Gendered Situations, Gen-dered Selves. Thousand Oaks, CA: Sage.
Kasperson, Roger E., Ortwin W. Renn, Paul Slovic, Halina S. Brown, Jacque Emel,Robert Goble, Jeanne X. Kasperson, and Samuel Ratick. 1988. ‘‘The SocialAmplification of Risk: A Conceptual Framework.’’ Risk Analysis 8:177–87.
Klineberg, Stephen, Matthew McKeever, and Bert Rothenbach. 1998. ‘‘Demo-graphic Predictors of Environmental Concern: It Does Make a Difference HowIt’s Measured.’’ Social Science Quarterly 79:735–53.
476 B. K. Marshall
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
Krauss, Celene. 1993. ‘‘Women and Toxic Waste Protests: Race, Class andGender as Resources of Resistance.’’ Qualitative Sociology 16:247–62.
Krimsky, Sheldon and Dominic Golding, eds. 1992. Social Theories of Risk.Westport, CT: Praeger-Greenwood.
Louisiana Department of Environmental Quality. 1991. Bulletin, 9, 1, 2, 3.MacGregor, Donald G., Paul Slovic, and Torbjoern Malmfors. 1999. ‘‘How
Exposed Is Exposed Enough? Lay Inferences About Chemical Exposure.’’ RiskAnalysis 19:649–61.
McStay, Jan R. andRiley E.Dunlap. 1983. ‘‘Male-FemaleDifferences inConcern forEnvironmental Quality.’’ International Journal of Women’s Studies 6:291–301.
Mohai, Paul. 1992. ‘‘Men, Women, and the Environmental: An Examination ofthe Gender Gap in Environmental Concern and Activism.’’ Society and NaturalResources 4:1–19.
———. 1997. ‘‘Gender Differences in the Perception of Most Important Envir-onmental Problems.’’ Race, Gender, & Class 5:153–69.
Myers, John. 1989. ‘‘Slip Sliding Away: Pollution Along the River.’’ New OrleansTimes-Picayune, November 24, P. A58.
Nelkin, Dorothy. 1981. ‘‘Nuclear Power as a Feminist Issue.’’ Environment23:14–39.
O’Connor, Robert, Richard J. Bord, and Ann Fisher. 1999. ‘‘Risk Perceptions,General Environmental Beliefs, and Willingness to Address Climate Change.’’Risk Analysis 19:461–71.
Pilisuk, Marc and Curt Acredolo. 1988. ‘‘Fear of Technological Hazards: OneConcern or Many?’’ Social Behavior 3:17–24.
Rayner, Steve and Robin Cantor. 1987. ‘‘How Fair is Safe Enough? The CulturalApproach to Societal Technology Choice.’’ Risk Analysis 7:3–9.
Riechard, Donald E. and Jean McGarrity. 1994. ‘‘Early Adolescents’ Perceptionsof Relative Risk from 10 Societal and Environmental Hazards.’’ Journal ofEnvironmental Education 26:16–23.
Roberts, J. Timmons and Melissa M. Toffolon-Weiss. 2001. Chronicles from theEnvironmental Justice Frontline. New York: Cambridge University Press.
Savage, Ian. 1993. ‘‘Demographic Influences on Risk Perceptions.’’ Risk Analysis8:413–20.
Schahn, Ariel K. and Erwin Holzer. 1990. ‘‘Studies of Individual EnvironmentalConcern.’’ Environment and Behavior 22:767–86.
Short, James F. 1984. ‘‘The Social Fabric at Risk: Toward the Social Transforma-tion of Risk Analysis.’’ American Sociological Review 49:711–25.
Slovic, Paul. 1993. ‘‘Perceived Risk, Trust and Democracy.’’ Risk Analysis13:675–82.
———. 1997. ‘‘Public Perception of Risk.’’ Journal of Environmental Health.59:22–25.
———. 2000a. The Perception of Risk. London: Earthscan Publications.———. 2000b. ‘‘Trust, Emotion, Sex, Politics and Science: Surveying the Risk-
Assessment Battlefield.’’ Pp. 390–412 in The Perception of Risk, edited byP. Slovic. London: Earthscan Publications.
Risk Perceptions in Cancer Alley, LA 477
Dow
nloa
ded
by [
Tul
ane
Uni
vers
ity]
at 0
3:20
19
Aug
ust 2
013
Slovic, P., T. Malmfors, C. K. Mertz, N. Neil, and I. F. H Purchase. 1997.‘‘Evaluating Chemical Risks: Results of a Survey of the British ToxicologicalSociety.’’ Human and Experimental Toxicology 16:289–304.
Solomon, Lawrence S., Donald Tomaskovic-Devy, and Barbara J. Risman. 1989.‘‘The Gender Gap and Nuclear Power.’’ Sex Roles 21:401–14.
Spigner, Clarence, Wesley Hawkins, and Wendy Loren. 1993. ‘‘Gender Differ-ences in Perception of Risk Associated with Alcohol and Drug Use AmongCollege Students.’’ Women and Health 20:87–97.
Steger, Mary Ann E. and Stephanie L. Witte. 1989. ‘‘Gender Differences inEnvironmental Orientations: A Comparison of Publics and Activists in Canadaand the U.S.’’ Western Political Quarterly 42:627–49.
Stern, Paul C., Thomas Dietz, and Linda Kalof. 1993. ‘‘ValueOrientations, Gender,and Environmental Concern.’’ Environment and Behavior 25:322–48.
Stout-Wiegand, Nancy and Roger B. Trent. 1983. ‘‘Sex Differences in AttitudesToward New Energy Resource Developments.’’ Rural Sociology 48:637–46.
Umberson, Debra. 1993. ‘‘Sociodemographic Position, World Views, and Psy-chological Distress.’’ Social Science Quarterly 74:575–89.
Wilkinson, Sue and Celia Kitzinger, eds. 1996. Representing the Other: A Feministand Psychology Reader. Thousand Oaks, CA: Sage.
Wright, Beverly. 1998. ‘‘Endangered Communities: The Struggle for Environ-mental Justice in the Louisiana Chemical Corridor.’’ Journal of PublicManagement & Social Policy 4:181–91.
Zelezny, Lynnette, Poh-Pheng Chua, and Christina Aldrich. 2000. ‘‘Elaborating onGender Differences in Environmentalism.’’ Journal of Social Issues 56:443–57.
