TY - JOUR
AU - Gibbons, Alyssa, M
AB - Abstract Using theories of intergroup relations, the current research examined whether personal experiences and perceptions of employment hardship (e.g., unemployment, underemployment, perceived job insecurity, and career optimism) were associated with ageist and sexist attitudes among younger workers and male workers toward older workers and female workers, respectively. In Study 1, a survey of working adults found that, among those under 35, underemployment and job insecurity predicted perceived threat from older workers, which was associated with ageist attitudes. In Study 2, in a survey of college students under age 35, career optimism was associated with the perceived threat from older workers, which was correlated with ageist attitudes. Among men, perceived job insecurity predicted threat from women, which was associated with sexist attitudes. These results suggest that groups traditionally viewed as noncompetitive or nonthreatening may be viewed more negatively (in ageist or sexist terms) under conditions of individual-level actual and perceived resource scarcity and competition. The beginning of the 21st century was largely characterized by a major worldwide economic downturn. As a means to weather the economic drought, many organizations cut costs by downsizing workforces, hiring fewer employees, offering fewer promotions, and instituting furloughs. These practices shifted the burden of economic hardship onto workers, making secure employment a scarce commodity. Although the economy has improved (Brenan, 2018; Reinhart, 2017), subsequent research has documented the recession’s long-term effects upon workers (Basbug & Sharone, 2017; Farber, 2015; Hollingsworth, Ruhm, & Simon, 2017; O’Connor, 2017). One potential outcome of the recession is that hostile attitudes toward certain groups of people may increase; a large body of prior work has found that economic scarcity is associated with prejudicial attitudes resulting from perceived competition over resources (e.g., Esses, Jackson, & Armstrong, 1998; King, Knight, & Hebl, 2010; LeVine & Campbell, 1972). In the present research, we examine how workers’ personal experiences with and perceptions of employment scarcity may be associated with ageist and sexist attitudes. Since the late 2000s, workers endured a major recession followed by a slow recovery. This resulted in many workers losing their jobs or finding themselves with work below their skill or education levels (Bureau of Labor Statistics, 2013; McKee-Ryan & Harvey, 2011). During this same period, older adults and women became increasingly salient in the workplace due to their greater presence and prominence. Generally, stereotypes of these two groups have traditionally represented them as relatively noncompetitive or nonthreatening (Cuddy & Fiske, 2004; Fiske, Cuddy, Glick, & Xu, 2002). However, when employment opportunities are perceived to be scarce, younger and male workers may be more likely to perceive older adults and women as threats to their own economic well-being. Further, two intergroup relations theories, realistic group conflict theory (RGCT; Sherif, 1966) and social identity theory (SIT; Brown, Condor, Mathew, Wade, & William, 1986; RGCT: Sherif, 1966; SIT: Tajfel, 1978; Tajfel & Turner, 1979; Turner, 1975; Tajfel & Turner, 1986) suggest that perceived threats of this type may be linked to greater prejudicial attitudes toward older adults and women. In two studies, we investigated how younger workers’ and male workers’ experiences with and perceptions of employment hardship were related to competition-driven prejudicial attitudes toward older adults and women, using intergroup relations theories as a general framework. The principal aims of this research were to establish whether older adults and women are perceived as economic threats and to understand how personal experiences of employment scarcity influence prejudicial attitudes. The current research makes several important contributions to the literatures on ageism and sexism. First, this work advances our understanding of how ageist and sexist attitudes can be associated with the perceived economic threat in times of scarcity. Second, by focusing on actual personal experiences and perceptions of employment hardship, the current research identifies individual-level factors that may be associated with a person’s endorsement of prejudicial attitudes. Third, this work sheds more light on the negative consequences of hard economic times by highlighting their association with intergroup dynamics. In the following sections, we discuss how perceptions of scarcity of job opportunities can be associated with hardships on workers. Further, we use both RGCT and SIT to understand why workers’ experiences of employment hardship may be associated with increased perception of threat toward older adults and women, and other facets of ageist and sexist attitudes. HOW EMPLOYMENT SCARCITY INFLUENCES WORKER PERCEPTIONS Organizations often respond to economic uncertainty by eliminating nonessential programs, personnel, and benefits. Such actions reduce not only the number of employment opportunities available to workers but also the quality of these opportunities in terms of lower pay, benefits, and hours as well as increases in workload. During times of economic uncertainty, work opportunities, especially enriching opportunities, become scarce. This scarcity may negatively affect workers in a variety of ways. For example, some workers may lose their jobs and face prolonged unemployment. For other job seekers, the lack of available work opportunities can lead to underemployment, where skills and experience are underutilized. Underemployed workers receive lower pay and benefits than they would in higher level or higher skilled jobs for which they are qualified (McKee-Ryan & Harvey, 2011). A poor job market also frequently increases job insecurity among workers, a feeling that reflects anxiety based on fears of losing one’s job (De Witte, 2005). The two theories we draw upon (RGCT and SIT) suggest that both objective assessments (e.g., education or skill level relative to job requirements) and subjective perceptions can contribute to work insecurity. For example, perceived underemployment can occur when a worker believes he or she is overqualified for the job or that the job is lacking in some way (Maynard, Joseph, & Maynard, 2006; McKee-Ryan, Virick, Prussia, Harvey, & Lilly, 2009). Perceived job insecurity can be stressful even when there exists no or minimal risk of job loss (De Witte, 2005). Although these experiences are distinct, together they represent related ways in which a poor job market with scarce work opportunities can impose hardships on workers. In this article, we refer to this general negative impact on workers as “experienced employment hardship.” Experiences of objective employment hardship were prevalent during the 2008 recession. For example, the U.S. unemployment rate more than doubled from 3.9% before the recession in 2000 to 10% at its peak in 2009 (Bureau of Labor Statistics, 2013). Estimates of underemployment during the recession were comparably high, ranging from 17% (Bureau of Labor Statistics, 2010) to more than 30% (Green & McIntosh, 2007). Similarly, job insecurity more than doubled from 15% in 2008 to about 31% in 2009, and remained high for several years (Saad, 2013). As the economy recovered, workers experienced less employment hardship and were more optimistic about the labor market (Brenan, 2018; Reinhart, 2018). However, it was not until late 2017 that the national unemployment rate returned to prerecession levels (Bureau of Labor Statistics, 2018) and many workers continue to struggle economically. Further, the economic recovery has been uneven across states, with some regions experiencing little to virtually no economic growth (Economic Innovation Group, 2017). In the places most affected by the recession, the poor job markets led many workers to exit the labor force entirely (Yagan, 2017). The persistence of employment hardship and its negative consequences for workers (see De Witte, 2005; McKee-Ryan & Harvey, 2011; and McKee-Ryan, Song, Wanberg, & Kinicki, 2005 for reviews) have created an impetus for the current research to help understand its lasting impact. Researchers have sought to understand the consequences that employment hardships have upon workers (e.g., Basbug & Sharone, 2017; Hollingsworth et al., 2017; O’Connor, 2017). However, little research has examined the relationships between perceived and actual employment hardship and age- and gender-based prejudicial attitudes. Labor statistics data show that younger workers and male workers were disproportionately affected by employment hardship in the past recession (Bureau of Labor Statistics, 2013, 2014), creating conditions conducive to the emergence of outgroup hostility. Moreover, these types of employment hardships reflect personal experiences and, in the case of underemployment and job insecurity, subjective experiences. Endorsement of prejudicial attitudes is an individual-level phenomenon. Consistent with SIT and more recent research on RGCT, we expect that these individual, subjective experiences may be more useful predictors of prejudiced attitudes than more objective macroeconomic trends because endorsement of prejudicial attitudes is an individual-level phenomenon. EMPLOYMENT HARDSHIP AND PERCEIVED COMPETITION: PRELUDE TO PREJUDICIAL ATTITUDES There are numerous social psychological approaches to understanding intergroup relations and conflict. One such theory, RGCT, posits that prejudicial attitudes arise from realistic threats (i.e., competition over scarce resources; LeVine & Campbell, 1972). Specifically, when the actions, beliefs, or characteristics of an outgroup (e.g., older people or women) pose an obstacle to the goal attainment or well-being of the ingroup (e.g., younger people or men), they are considered a threat and arouse hostility (Riek, Mania, & Gaertner, 2006). These threats reflect the anticipated actual loss of valued resources, such as safety, political power, social status, or economic interests (Jackson, 1993). The resulting outgroup hostility has been attributed to endorsement of zero-sum beliefs, where individuals view gains made by an outgroup as coming at the expense of their ingroup (Bobo & Hutchings, 1996). Early conceptualizations of RGCT assumed a close or one-to-one correspondence between the objective and the perceived interdependence of ingroup losses and outgroup gains (Sherif, 1966). That is, intergroup conflict from competition for valued resources resulted mostly or solely from objective or instrumental factors. On the other hand, research on RGCT has demonstrated that intergroup conflict may occur even when there are few objective resource differences between groups. Specifically, the mere perception or forecast of competition can be sufficient to engender hostility (Bobo, 1983; Esses et al., 1998). This is consistent with SIT, an alternative theory of intergroup relations. SIT can complement RGCT by explaining group relations and outgroup hostilities even when there are few objective conflicting interests by recognizing the role of perceived or subjective conflicting group interests (Tajfel, 1978). For example, younger and male employees may objectively have greater access to occupations that have the best pay, benefits, and prospects for upward mobility. Under these conditions, RGCT would suggest that younger and male employees should not perceive threat from older or female workers. However, if either younger workers or male workers believe that they are more entitled to have access to such positions relative to other groups of workers, they may perceive threats to their identity by outgroup members (e.g., older and female workers) if such access is limited. That is, consistent with SIT, even when younger or male workers disproportionality occupy higher-status jobs, any perceived encroachment by older or female workers among those who identify strongly with their ingroup may be sufficient to engender hostile attitudes and behaviors. Esses and colleagues (1998) proposed that two factors precipitate such threat-based competition: (a) resource stress and (b) outgroup relevance. “Resource stress” refers to the belief that access to resources is limited, while “outgroup relevance” refers to the salience of an outgroup in society and how likely it is to be viewed as a legitimate competitor for resources. This perspective suggests that, although threats are more likely to be perceived when resources are scarce, not all outgroups are equally likely to be viewed as threats. Outgroups that are salient and distinct from the ingroup, yet perceived as capable enough to compete for resources, are more viable as threats. Prior research has established a link between scarcity and prejudicial attitudes toward salient, competitive outgroups with regard to macroeconomic threats. For example, realistic threats involving actual job loss and social assistance redirection were found to predict negative attitudes toward immigrants in the United States (Stephan, Ybarra, & Bachman, 1999) and in Spain (Stephan, Ybarra, Martinez, Schwarzwald, & Tur-Kaspa, 1998). Additionally, the degree of opposition to immigration in Canada increased and decreased in parallel with the unemployment rate (Palmer, 1996). Within the United States, concerns about immigration are highest among individuals lower in socioeconomic status and with lower education levels (Pew Research Center, 2006). Individuals who are closest in socioeconomic status to African Americans hold the most negative prejudicial attitudes toward this group (Greeley & Sheatsley, 1978; Pettigrew, 1978). Finally, using a controlled experiment, King and colleagues (2010) found that participants who were presented with a negative economic forecast (i.e., objectively manipulated resource scarcity) evaluated minority female job candidates more negatively than Caucasian male candidates and were less supportive of diversity programs. OLDER WORKERS AND FEMALE WORKERS AS THREATENING OUTGROUPS RGCT and SIT both describe general processes by which prejudiced attitudes may arise between any social groups, so long as one group perceives the other to be a threat to its own best interests. Recent developments suggest that Esses and colleagues’ (1998) two conditions for prejudicial attitudes—resource stress and outgroup relevance—have been met for older adults and women. First, as discussed above, recent economic downturns helped to turn employment opportunities into scarce commodities. The scarcity created a sense of resource stress with respect to jobs. Second, the recent recession was harder on younger workers and male workers than it was for their older and female counterparts (Bureau of Labor Statistics, 2013, 2014), and younger and male groups may have viewed this relative hardship as coming as a result of competition with these groups. This, along with older workers and women’s increased prominence in the workforce (discussed at length in the following sections), positions older adults and women as relevant outgroups viable as economic threats. As a result, both RGCT and SIT predict that ageism and sexism are likely to arise when perceptions of threat and competition exist. Unlike other groups commonly examined as targets of competition-based prejudicial attitudes such as immigrants and racial minorities, older adults and women are often subject to paternalistic prejudicial attitudes that reflect perceptions of low competence and capability to care for themselves independently (Fiske et al., 2002; Glick & Fiske, 1996; Whitton, 1997). Given such stereotypes, it might seem unlikely for younger workers and male workers to view older workers and women as threats to their employment. However, outgroups not historically viewed as threatening in economic contexts may be subject to competition-based prejudicial attitudes when economic scarcity is made salient (King et al., 2010). Thus, older adults and women may also be perceived as realistic threats to economic well-being under similar circumstances. For example, increasing attention to older workers and to women in the workforce in the media makes them more salient. The perception that there is more competition for employment opportunities is likely to make them seem more threatening. Although the conditions of resource stress and outgroup relevance appear to have been met for older adults and women, it is unclear whether younger workers and male workers actually perceive older adults and women as threatening, and if so, whether these threat perceptions will increase the prevalence or intensity of ageist and sexist attitudes. The current research addresses this issue by examining the extent to which such competition-based ageism and sexism occurs. We also seek to identify personal factors associated with increased perceptions of threat. Although previous research has examined the relationship between economic threat and prejudicial attitudes using macroeconomic factors (e.g., general economic outlook, national unemployment rate; Esses et al., 1998; Goldstein & Peters, 2014; King et al., 2010; Quillian, 1995; Ybarra, Sanchez, & Sanchez, 2016), the present research focuses on how personal economic factors (experienced employment hardship) influence prejudicial attitudes. Understanding the relationship between experienced and perceived employment hardship and ageism and sexism is important to understanding individual variance in perceptions of threat and competition. In the following sections, we identify recent developments that may contribute to the increased salience of older workers and women as possible resource-competitive groups. As a result, older workers and women may be viewed as “taking jobs away” from younger workers and male workers, who may believe they are more entitled to such employment and thus feel the greater perceived threat. Outgroup Relevance and Resource Stress With Regard to Older Workers Over the last decade, older workers have become an increasingly salient group in the United States due to their large numbers and continued participation in the workforce. As the large Baby Boomer age cohorts reached retirement age, adults aged 55 and older made up nearly 25% of the overall population in 2011 (U.S. Census Bureau, 2012a), and are projected to remain at this level for several decades (U.S. Census Bureau, 2012b). Increasingly, older adults are choosing to remain active in the workforce up to and beyond traditional retirement age, as evidenced by high labor force participation rates for both men and women aged 55 and older (Fullerton, 1999; Mermin, Johnson, & Murphy, 2007). This trend has been attributed to several factors, including higher life expectancy, changes to Social Security and pension plans that deincentivize early retirement, and the effect of economic downturns on individuals’ savings (Toossi, 2009). Thus, for the first time in U.S. history, there is a large and highly visible older population active in the workforce. The presence of so many older people and workers has not escaped media scrutiny. Government spending on welfare programs for older adults, such as Social Security, has been heavily criticized for being financially unsustainable (Bingham, 2011; Johnston, 2012; Kessler, 2012) and national opinion polls have also been unfavorable toward this spending (CNN/ORC International, 2011a, 2011b). Some pundits have blamed government aid to older adults for the poor economy and accused lobbies for older persons’ interests of “stealing from the young” and leaving nothing for future generations (e.g., Friedman, 2013; Jaffe, 2013). Such arguments suggest that older workers may be viewed, at least by some, as threatening to the interests of younger workers. During this same period, younger workers found themselves disproportionately affected by the recession. Unemployment was highest among younger workers, averaging to 18.4% for those ages 16–24 and 10.9% for ages 25–29 in 2010, while unemployment among workers aged 45 and older was at just 7.4% (Bureau of Labor Statistics, 2013). Younger persons generally experience higher unemployment during difficult economic times (Elsby, Hobijn, & Sahin, 2010; Freeman & Wise, 1982). Additionally, some studies have found that younger workers are more likely to experience underemployment (Tam, 2010) and perceived job insecurity (Roskies & Louis-Guerin, 1990) than other age groups. Higher unemployment among similarly aged young peers may lead to worries about one’s own job security, and becoming unemployed can lead one to settle for lower status jobs in order to get by. Thus, it is reasonable to expect that many younger workers have experienced or continue to experience employment hardship. The combination of the large and economically salient older worker population and the relatively economically disadvantaged younger population may contribute to intergroup or intergenerational conflict. Consistent with RGCT and SIT, younger workers may perceive older persons as direct competitors for work. This perception may be exacerbated by older workers’ continued employment beyond retirement age, which can both (a) delay younger job seekers from entering the workforce or (b) prohibit younger current employees from advancing up the organizational ladder. Research suggests ageist attitudes are influenced by prescriptive age stereotypes, which describe how older workers should or “ought to” behave (North & Fiske, 2012, 2013). These stereotypes indicate that older adults should cede valued resources to younger generations and minimize their consumption of shared resources. Older workers may be perceived by their younger counterparts as already having had their turn with valued job opportunities and are thus expected to relinquish them to younger generations. Older adults’ continued employment in the workplace may be viewed as a violation of this “norm of succession” that may arouse feelings of contempt and threat. Even when older workers retire from paid work, they may continue to be seen as a burden on society by depleting shared societal resources like Social Security. Thus, older persons’ increased presence in the workforce and eligibility for welfare programs may be seen as a competition of resources by younger workers and thereby as a viable threat during a time of economic scarcity. Outgroup Relevance and Resource Stress With Regard to Women Similarly, scarcity of employment opportunities may accentuate ongoing tensions or resource competition between men and women. In the United States, the proportion of women in the labor force steadily increased across much of the 20th century, although it has stabilized since 2000 at approximately 47% (Bureau of Labor Statistics, 2014). Women currently make up a substantial part of the workforce, though it is only recently that they have made inroads into jobs that have the most favorable work conditions, pay, and benefits. Since 2003, the proportion of college graduates in the labor market has been higher among women than men (Bureau of Labor Statistics, 2014). With greater skill and education, women have achieved increasing representation in higher-paying leadership positions in what have been traditionally male-dominated organizational levels. Consistent with SIT and RGCT, traditional incumbents in these highly sought after and prestigious positions, generally males, may view women’s gains as their losses. Further, within the United States and globally (e.g., Germany, United Kingdom), women have been successfully nominated as candidates and have secured positions as heads of state or nations in recent elections. Additionally, media attention has highlighted the expanded and prominent roles that women occupy both in the military and in men’s professional sports (Associated Press, 2014; Chappell, 2014; Harris, 2013; Londoño, 2013; Price, 2015; Sanchez & Smith-Spark, 2015; Stelloh & Johnson, 2015; Wesseling, 2015). Such press and national news attention has increased public awareness of the presence of women in the workplace, especially in increasingly powerful and traditionally male-dominated roles. Although unemployment rates increased for both men and women following the 2007 recession, men’s unemployment rates were consistently higher and had a higher peak (10.5% in 2010 compared with 8.6% for women in the same year; Bureau of Labor Statistics, 2014). Thus, similar to older workers, women constitute an increasing proportion of the workforce, while men were disproportionately disadvantaged economically as a result of the recession. Men also increasingly occupy traditionally female roles. For example, some men choose to remain at home as primary child care providers, forgoing work to be stay-at-home fathers (Morin, 2013), while other fathers request and utilize paid paternity leave despite a stigma surrounding it (Harrington, Van Deusen, Fraone, Eddy, & Haas, 2014). On the other hand, other men may find themselves out of desired paid employment not by choice but rather due to a poor job market. All of this points to multiple societal role-shifts and circumstances among men, women, and paid and unpaid employment, all of which may be viewed as economically threatening. Women’s gains in the workforce may be perceived as coming at the expense of men. Many Americans, including women, continue to endorse traditional gender roles that stress men should be the primary wage earners (Tinsley, Howell, & Amanatullah, 2015). Further, women who work in stereotypically masculine or male-dominated jobs are more likely to report experiencing gender-based and sexual harassment (Willness, Steel, & Lee, 2007), particularly when they display more masculine attributes such as self-reliance and aggression (Leskinen, Rabelo, & Cortina, 2015). These trends suggest that women are more likely to experience negative consequences when they compete directly with men in the workforce. There has also been considerable public debate regarding pay disparities between men and women, prompting the creation in 2010 of a presidential task force to examine the issue and propose legislative remedies (National Equal Pay Task Force, 2013). Although no legislation has been enacted (Pew Research Center, 2013), the media-driven attention may contribute to increased salience of female workers as a competitive outgroup. Consistent with the RGCT and SIT perspectives, the actual and perceived competition over economic resources and opportunities may contribute to intergroup conflict between men and women and enhanced perceptions of threat and stereotypical attitudes. THE PRESENT RESEARCH Our primary research goal was to examine the extent to which personal economic experiences and perceptions are associated with negative attitudes toward older adults and women. We predict, based upon theory (RGCT and SIT) and research on resource scarcity, that a worker’s experienced employment hardship (operationalized as unemployment, perceived underemployment, and perceived job insecurity) will be associated with greater perceived threat from older workers as well as more negative perceptions of older workers. A conceptual model is presented in Figure 1A, and the following relationships are hypothesized: Hypothesis 1a–1c: Among younger persons, experience with unemployment, underemployment, and job insecurity are positively related to perceived threat from older persons. Hypothesis 2: Among younger persons, perceived threat from older persons is positively related to endorsement of ageist attitudes. Hypothesis 3a–3c: Among younger persons, experience with unemployment, underemployment, and job insecurity are positively related to endorsement of ageist attitudes, mediated by perceived threat from older persons. Figure 1. Open in new tabDownload slide (A) A proposed conceptual model for the relationships of unemployment, underemployment, and job insecurity with ageism, mediated by perceived threat felt from older workers. (B) A proposed conceptual model for the relationships of unemployment, underemployment, and job insecurity with sexism, mediated by perceived threat felt from women. Figure 1. Open in new tabDownload slide (A) A proposed conceptual model for the relationships of unemployment, underemployment, and job insecurity with ageism, mediated by perceived threat felt from older workers. (B) A proposed conceptual model for the relationships of unemployment, underemployment, and job insecurity with sexism, mediated by perceived threat felt from women. We further propose that experienced employment hardship will also be associated with increased sexism and perceived threat from women, consistent with the model described above for age. This conceptual model is presented in Figure 1B and hypothesize the following specific relationships: Hypothesis 4a–4c: Among men, experience with unemployment, underemployment, and job insecurity are positively related to perceived threat from women. Hypothesis 5: Among men, perceived threat from women is positively related to endorsement of sexist attitudes. Hypothesis 6a–6c: Among men, experience with unemployment, underemployment, and job insecurity are positively related to endorsement of sexist attitudes, mediated by perceived threat from women. We tested these hypotheses using two separate samples. In Study 1, we used a cross-sectional survey via Amazon’s Mechanical Turk to establish that experienced employment hardship, perceived threat, and prejudicial attitudes were related. In Study 2, we used a time-lagged survey with a university student sample to test whether the results from Study 1 would replicate in a different population, to better establish threat and prejudicial attitudes as distinct constructs, and to reduce the potential impact of monomethod bias on our results. STUDY 1: CROSS-SECTIONAL MTURK SAMPLE The objective of Study 1 was to test whether meaningful relationships existed among the key variables (experienced employment hardship, perceived threat, and prejudicial attitudes) in our conceptual model. Another goal of Study 1 was to determine whether perceived threat was a plausible underlying mechanism to explain the relationship between experienced employment hardship and endorsement of ageism and sexism. Study 1 utilized a cross-sectional survey of participants’ work experiences and attitudes. Method Participants We recruited participants for Study 1 through Amazon’s Mechanical Turk (MTurk; www.mturk.com) website. MTurk facilitates the recruitment of “workers” by “requesters” to complete brief tasks for monetary compensation. We utilized MTurk as a data collection platform for several reasons. First, though concerns have been raised about its viability as a data source (see Landers & Behrend, 2015 for a discussion of common criticisms), research has found that its quality is consistent with other samples commonly used by published studies (e.g., university students, online panels, general population surveys; Buhrmester, Kwang, & Gosling, 2011; Casler, Bickel, & Hackett, 2013; Roulin, 2015). Second, this participant pool is diverse in terms of age, gender, race, ethnicity, education, and work experience (Buhrmester et al., 2011; Casler et al., 2013; Roulin, 2015). Of these, diversity in age, gender, and work experience are all critical for understanding the effect of employment hardship on perceptions of age and gender among working adults. Third, because of the sample’s diversity, it may be a better representation of society as a whole than other samples and may not be subject to biases resulting from collecting data from a single geographical region or organization (Landers & Behrend, 2015). For example, some regions in the United States were affected by the recession much worse than others, making single-site data collection problematic, and large U.S. organizations are subject to employment discrimination regulatory laws that may discourage participants from truthfully responding to items about age- or gender-bias. Fourth, MTurk can be a good mechanism for assessing difficult-to-access populations (Smith, Sabat, Martinez, Weaver, & Xu, 2015). This makes MTurk especially useful for recruiting workers that are unemployed (impossible with an organizational sample) and underemployed (who may be reluctant to report feelings of underemployment if they are concerned managers have access to data). For all of these reasons, we found MTurk to be particularly well suited for the current study. Sample for ageism analyses. A total of 426 participants completed the overall survey, though 26 were discarded after screening for data quality (described in detail below). Of the remaining 400 participants, 219 participants (95 male, 124 female) reported their age as 35 or younger. These participants formed the sample we used for the ageism analyses. We set 35 years of age as the cutoff age for “younger” workers to include workers in the Millennial age cohort and younger. More specifically, participants’ ages ranged from 19 to 35 (M = 28.44, SD = 4.45). The majority of this sample (75%) self-identified as White/Caucasian, with 10% identifying as African American, 5% as Asian, 5% as Hispanic/Latino, 1% as Pacific Islander, and 3% as multiracial. Most (68%) reported having full-time employment; 11% reported no current employment, 18% reported part-time employment, and the remainder reported some other form of employment (e.g., commission, seasonal, etc.) or did not report their employment status. Sample for sexism analyses. For the sexism analyses, we used data from 172 participants who self-identified as male. These participants ranged in age from 19 to 65 (M = 36.52, SD = 11.0). The majority (81%) of male participants described their race as White/Caucasian, with 8% identifying as African-American, 3% as Asian, 6% as Hispanic/Latino, 1% as Pacific Islander, and 1% as multiracial. As before, most (64%) reported having full-time employment; 13% reported no current employment, 17% reported part-time employment, and the remainder reported some other form of employment or did not report their employment status. Procedure We posted a description of the task on the MTurk website and explained that workers would be compensated $1.50 for completing a 25-min survey. Participation was restricted to those 18 or older, who lived in the United States, and who maintained a 95% approval rating across at least 50 tasks. We included a screening survey before the actual survey to prevent workers from participating multiple times solely for the financial incentive. This checked workers’ unique Amazon IDs against a log of those that had already participated and redirected those with matching IDs away from the survey. Participants were then presented with this study’s measures and demographic items, which were part of a larger survey. Measures involving perceived threat and prejudicial attitudes were presented at the end of the survey. Measures Unemployment. Current employment status was measured using three items adapted from the Bureau of Labor Statistics’ (2009) definition of unemployment. These items included: “Do you currently hold any full-time, part-time, temporary, or seasonal employment?” “Are you currently available for work?” and “Have you, over the last four weeks, actively looked for a job?” If the participant answered “no” to the first question and “yes” to the second and third questions then he or she was considered unemployed. This ensured that participants who reported not having jobs were actually available and willing to work (e.g., not on maternity leave or full-time students). In Study 1, the mean of unemployment for the under 35 sample was .09 and was .12 for the male sample. Underemployment. Underemployment was measured using nine items from the unidimensional Scale of Perceived Overqualification (Study 1 α = .87, Study 2 α = .84; Maynard et al., 2006). This scale measures perceived overqualification, which is a more subjective form of underemployment compared with other operationalizations (McKee-Ryan & Harvey, 2011). Items were rated on a 5-point Likert scale (1 = strongly disagree; 5 = strongly agree). Job insecurity. Job insecurity was assessed using the five-item, unidimensional Job Insecurity Scale (Study 1 α = .90, Study 2 α = .83; Hellgren, Chirumbolo, De Witte, Goslinga, Näswall, & Sverke, 2001). Items were rated on a 5-point Likert scale (1 = strongly disagree; 5 = strongly agree). Perceived threat from older adults. Realistic threat felt from older adults was measured using a six-item scale adapted from one used to assess realistic threat felt from Asian Americans (Study 1 α = .87, Study 2 α = .83; Maddux, Galinsky, Cuddy, & Polifroni, 2008). These items assessed threat in a variety of domains (e.g., economic, political) and were modified to be relevant for older persons. Items were rated on a 5-point Likert scale (1 = strongly disagree; 5 = strongly agree). Items are presented in Appendix Table 1A. Perceived threat from women. The same measure by Maddux and colleagues (2008) was also adapted to assess perceived realistic threat from women (Study 1 α = .90, Study 2 α = .90). This version of the scale included seven items, which were rated on a 5-point Likert scale (1 = strongly disagree; 5 = strongly agree). Items are presented in Appendix Table 2A. Ageism. Ageism toward older adults was measured by adapting the revised version of the Fraboni Scale of Ageism (Rupp, Vodanovich, & Crede, 2005). The initial scale included 23 items loading on three factors: stereotypes, separation, and attitudes. We changed the referent for each item from “old person” to “older person” so the content would focus less on attitudes toward the very elderly and more on older adults that are active in the workforce. Because this scale was designed to measure ageism toward the elderly, we omitted five items for which the item content was less applicable to older workers (e.g., “Teenage suicide is more tragic than suicide among the old.”). We also generated six new items that focused specifically on older worker stereotypes. Because these items were all specific to the work domain, these were treated as a separate dimension, resulting in a four-dimensional scale with 19 items. Items were rated on a 5-point Likert scale (1 = strongly disagree; 5 = strongly agree). Reliabilities are presented in Tables 1 and 5. Items are presented in Appendix Table 3A. Table 1. Study 1 Summary of Descriptive Statistics: Participants Under Age 35 Variable . N . M . SD . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 . 10 . 11 . 12 . 1. Age 219 28.44 4.45 — 2. Gender 219 0.57 0.50 −.05 — 3. Unemployment status 219 0.09 0.29 −.15 −.07 — 4. Underemployment 219 3.44 0.84 −.19 .01 .08 .87 5. Job insecurity 219 2.18 0.91 .00 −.01 .28 .23 .90 6. Threat—older persons 219 2.60 0.83 −.21 −.15 .15 .24 .28 .87 7. Threat—women 219 2.23 0.71 −.17 −.19 .14 .10 .13 .48 .90 8. Ageism—stereotypes 219 2.87 0.70 −.23 −.16 .05 .26 .21 .64 .50 .67 9. Ageism—work stereotypes 219 2.96 0.74 −.18 −.06 .02 .20 .19 .43 .33 .61 .74 10. Ageism—separation 219 2.07 0.57 −.23 −.17 .02 .16 .30 .55 .55 .51 .31 .77 11. Ageism—attitudes 219 2.22 0.58 −.07 −.15 .02 .06 .18 .34 .36 .34 .28 .53 .63 12. Sexism 219 2.46 0.85 .04 −.27 −.06 −.05 −.10 −.03 .41 .11 .05 .15 .19 .90 Variable . N . M . SD . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 . 10 . 11 . 12 . 1. Age 219 28.44 4.45 — 2. Gender 219 0.57 0.50 −.05 — 3. Unemployment status 219 0.09 0.29 −.15 −.07 — 4. Underemployment 219 3.44 0.84 −.19 .01 .08 .87 5. Job insecurity 219 2.18 0.91 .00 −.01 .28 .23 .90 6. Threat—older persons 219 2.60 0.83 −.21 −.15 .15 .24 .28 .87 7. Threat—women 219 2.23 0.71 −.17 −.19 .14 .10 .13 .48 .90 8. Ageism—stereotypes 219 2.87 0.70 −.23 −.16 .05 .26 .21 .64 .50 .67 9. Ageism—work stereotypes 219 2.96 0.74 −.18 −.06 .02 .20 .19 .43 .33 .61 .74 10. Ageism—separation 219 2.07 0.57 −.23 −.17 .02 .16 .30 .55 .55 .51 .31 .77 11. Ageism—attitudes 219 2.22 0.58 −.07 −.15 .02 .06 .18 .34 .36 .34 .28 .53 .63 12. Sexism 219 2.46 0.85 .04 −.27 −.06 −.05 −.10 −.03 .41 .11 .05 .15 .19 .90 Note. Correlations in bold text meet statistical significance criteria at α = .05. Cronbach’s alphas for measures are presented in italics on the diagonal. Unemployment, gender, and age are observed variables and do not have alphas. As the underemployment and job insecurity measures refer to one’s present job, these scales were presented only to those participants who indicated that they had a job at the time of the survey. Gender was coded 1 = male, 2 = female. T1 = Time 1, T2 = Time 2. Open in new tab Table 1. Study 1 Summary of Descriptive Statistics: Participants Under Age 35 Variable . N . M . SD . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 . 10 . 11 . 12 . 1. Age 219 28.44 4.45 — 2. Gender 219 0.57 0.50 −.05 — 3. Unemployment status 219 0.09 0.29 −.15 −.07 — 4. Underemployment 219 3.44 0.84 −.19 .01 .08 .87 5. Job insecurity 219 2.18 0.91 .00 −.01 .28 .23 .90 6. Threat—older persons 219 2.60 0.83 −.21 −.15 .15 .24 .28 .87 7. Threat—women 219 2.23 0.71 −.17 −.19 .14 .10 .13 .48 .90 8. Ageism—stereotypes 219 2.87 0.70 −.23 −.16 .05 .26 .21 .64 .50 .67 9. Ageism—work stereotypes 219 2.96 0.74 −.18 −.06 .02 .20 .19 .43 .33 .61 .74 10. Ageism—separation 219 2.07 0.57 −.23 −.17 .02 .16 .30 .55 .55 .51 .31 .77 11. Ageism—attitudes 219 2.22 0.58 −.07 −.15 .02 .06 .18 .34 .36 .34 .28 .53 .63 12. Sexism 219 2.46 0.85 .04 −.27 −.06 −.05 −.10 −.03 .41 .11 .05 .15 .19 .90 Variable . N . M . SD . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 . 10 . 11 . 12 . 1. Age 219 28.44 4.45 — 2. Gender 219 0.57 0.50 −.05 — 3. Unemployment status 219 0.09 0.29 −.15 −.07 — 4. Underemployment 219 3.44 0.84 −.19 .01 .08 .87 5. Job insecurity 219 2.18 0.91 .00 −.01 .28 .23 .90 6. Threat—older persons 219 2.60 0.83 −.21 −.15 .15 .24 .28 .87 7. Threat—women 219 2.23 0.71 −.17 −.19 .14 .10 .13 .48 .90 8. Ageism—stereotypes 219 2.87 0.70 −.23 −.16 .05 .26 .21 .64 .50 .67 9. Ageism—work stereotypes 219 2.96 0.74 −.18 −.06 .02 .20 .19 .43 .33 .61 .74 10. Ageism—separation 219 2.07 0.57 −.23 −.17 .02 .16 .30 .55 .55 .51 .31 .77 11. Ageism—attitudes 219 2.22 0.58 −.07 −.15 .02 .06 .18 .34 .36 .34 .28 .53 .63 12. Sexism 219 2.46 0.85 .04 −.27 −.06 −.05 −.10 −.03 .41 .11 .05 .15 .19 .90 Note. Correlations in bold text meet statistical significance criteria at α = .05. Cronbach’s alphas for measures are presented in italics on the diagonal. Unemployment, gender, and age are observed variables and do not have alphas. As the underemployment and job insecurity measures refer to one’s present job, these scales were presented only to those participants who indicated that they had a job at the time of the survey. Gender was coded 1 = male, 2 = female. T1 = Time 1, T2 = Time 2. Open in new tab Sexism. Sexism was measured using eight items from the unidimensional Modern Sexism Scale (Study 1 α = .90, Study 2 α = .88; Swim, Aikin, Hall, & Hunter, 1995). This scale operationalizes sexism as the denial of gender-based discrimination, antagonism toward the demands of women, and lack of support for policies designed to help women. These items were also rated on a 5-point Likert scale (1 = strongly disagree; 5 = strongly agree). Data cleaning Although MTurk samples are increasingly being used for data collection, it is still a relatively novel source and there is ongoing discussion regarding how to ensure quality data (Long, 2012; Paolacci & Warglien, 2009). Response quality was a concern in this study because participants were offered monetary compensation and were allowed to complete the survey in an unproctored setting. To address this issue, several screening procedures were implemented in a stepwise fashion in line with recommendations from Huang, Curran, Keeney, Poposki, and DeShon (2012). As a result, we excluded a total of 26 participants based on the following criteria: failure to respond correctly to attentional items (e.g., “Please select ‘disagree’ for this item.”; 17 participants), completing less than 90% of the items (2 participants), completion time less than 7.5 min (half the time taken by the fastest pilot tester; 6 participants); and a standard deviation less than 0.50 across all items before reverse coding (1 participant). Results Descriptive statistics and zero-order correlations among all study variables appear in Table 1 (for the ageism analysis) and Table 2 (for the sexism analysis). We tested the hypotheses using structural equation modeling in Mplus (Version 7; Muthén & Muthén, 2012). Table 2. Study 1 Summary of Descriptive Statistics: Men Variable . N . M . SD . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 . 10 . 11 . 1. Age 172 36.52 11.00 — 2. Unemployment status 172 0.12 0.33 .02 — 3. Underemployment 172 3.50 0.77 .09 .13 .86 4. Job insecurity 172 2.22 0.87 −.03 .34 .24 .91 5. Threat—older persons 172 2.61 0.83 −.26 .15 .21 .21 .87 6. Threat—women 172 2.35 0.76 −.10 .03 .16 .12 .65 .91 7. Ageism—stereotypes 172 2.99 0.69 −.06 .07 .23 .22 .54 .47 .67 8. Ageism—work stereotypes 172 2.91 0.69 −.14 .06 .16 .20 .48 .37 .63 .68 9. Ageism—separation 172 2.11 0.56 −.21 .13 .09 .24 .56 .51 .47 .40 .74 10. Ageism—attitudes 172 2.29 0.58 −.14 .10 .05 .18 .38 .37 .40 .34 .55 .62 11. Sexism 172 2.67 0.87 −.04 −.20 .00 −.05 .00 .29 .17 .03 .04 .09 .89 Variable . N . M . SD . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 . 10 . 11 . 1. Age 172 36.52 11.00 — 2. Unemployment status 172 0.12 0.33 .02 — 3. Underemployment 172 3.50 0.77 .09 .13 .86 4. Job insecurity 172 2.22 0.87 −.03 .34 .24 .91 5. Threat—older persons 172 2.61 0.83 −.26 .15 .21 .21 .87 6. Threat—women 172 2.35 0.76 −.10 .03 .16 .12 .65 .91 7. Ageism—stereotypes 172 2.99 0.69 −.06 .07 .23 .22 .54 .47 .67 8. Ageism—work stereotypes 172 2.91 0.69 −.14 .06 .16 .20 .48 .37 .63 .68 9. Ageism—separation 172 2.11 0.56 −.21 .13 .09 .24 .56 .51 .47 .40 .74 10. Ageism—attitudes 172 2.29 0.58 −.14 .10 .05 .18 .38 .37 .40 .34 .55 .62 11. Sexism 172 2.67 0.87 −.04 −.20 .00 −.05 .00 .29 .17 .03 .04 .09 .89 Note. All correlations with an absolute value greater than .09 meet statistical significance criteria at p < .05. Cronbach’s alpha values are presented on the diagonal (where appropriate). Open in new tab Table 2. Study 1 Summary of Descriptive Statistics: Men Variable . N . M . SD . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 . 10 . 11 . 1. Age 172 36.52 11.00 — 2. Unemployment status 172 0.12 0.33 .02 — 3. Underemployment 172 3.50 0.77 .09 .13 .86 4. Job insecurity 172 2.22 0.87 −.03 .34 .24 .91 5. Threat—older persons 172 2.61 0.83 −.26 .15 .21 .21 .87 6. Threat—women 172 2.35 0.76 −.10 .03 .16 .12 .65 .91 7. Ageism—stereotypes 172 2.99 0.69 −.06 .07 .23 .22 .54 .47 .67 8. Ageism—work stereotypes 172 2.91 0.69 −.14 .06 .16 .20 .48 .37 .63 .68 9. Ageism—separation 172 2.11 0.56 −.21 .13 .09 .24 .56 .51 .47 .40 .74 10. Ageism—attitudes 172 2.29 0.58 −.14 .10 .05 .18 .38 .37 .40 .34 .55 .62 11. Sexism 172 2.67 0.87 −.04 −.20 .00 −.05 .00 .29 .17 .03 .04 .09 .89 Variable . N . M . SD . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 . 10 . 11 . 1. Age 172 36.52 11.00 — 2. Unemployment status 172 0.12 0.33 .02 — 3. Underemployment 172 3.50 0.77 .09 .13 .86 4. Job insecurity 172 2.22 0.87 −.03 .34 .24 .91 5. Threat—older persons 172 2.61 0.83 −.26 .15 .21 .21 .87 6. Threat—women 172 2.35 0.76 −.10 .03 .16 .12 .65 .91 7. Ageism—stereotypes 172 2.99 0.69 −.06 .07 .23 .22 .54 .47 .67 8. Ageism—work stereotypes 172 2.91 0.69 −.14 .06 .16 .20 .48 .37 .63 .68 9. Ageism—separation 172 2.11 0.56 −.21 .13 .09 .24 .56 .51 .47 .40 .74 10. Ageism—attitudes 172 2.29 0.58 −.14 .10 .05 .18 .38 .37 .40 .34 .55 .62 11. Sexism 172 2.67 0.87 −.04 −.20 .00 −.05 .00 .29 .17 .03 .04 .09 .89 Note. All correlations with an absolute value greater than .09 meet statistical significance criteria at p < .05. Cronbach’s alpha values are presented on the diagonal (where appropriate). Open in new tab Ageism In the analysis for ageism, we restricted the sample to respondents who indicated their age as 35 or younger. As described above, these are the individuals for whom we expect employment hardships to be associated with greater perceptions of threat from older persons in the workforce and, also, to greater endorsement of ageist attitudes. We measured underemployment, perceived job insecurity, perceived threat from older persons, and ageism as latent variables. As described above in the Measures section, ageism was measured as a multidimensional construct comprising four factors (stereotypes, work-specific stereotypes, separation, and attitudes). [A series of confirmatory factor analyses supported a four-factor solution as preferable to a hierarchical solution in which all four factors loaded onto a second-order general ageism factor. Although the first two factors (stereotypes and work-specific stereotypes) were highly correlated (φ = .85), a model collapsing them into one factor did not fit as well as the four-factor solution. Details are available from the authors upon request.] The measurement model for the latent variables fit acceptably (⁠ χ6382 = 962.33, p < .01, CFI = .90, RMSEA = .05, SRMR = .06). Unemployment status was included in the structural model as an observed variable. The hypothesized structural model (Figure 2) showed acceptable fit to the data (⁠ χ6522 = 994.84, p < .01, CFI = .90, RMSEA = .05, SRMR = .06). There were significant positive paths from job insecurity (β = .24, p < .01) and from underemployment (β = .21, p < .01) to perceptions of threat from older persons, supporting Hypotheses 1b and 1c. However, the path between unemployment status and perceived threat was small and nonsignificant (β = .07, p = .30), so Hypothesis 1a was not supported. Hypothesis 2 was supported, as there were significant positive paths from perceived threat to each of the four ageism dimensions (stereotypes: β = .79, p < .01; work-related stereotypes: β = .48, p < .01; separation: β = .64, p < .01; attitudes: β = .47, p < .01). The indirect effects from underemployment and job insecurity on all four dimensions of ageism were significant (Table 3), supporting Hypotheses 3b and 3c, but once again, there were no significant indirect effects for unemployment. Table 3. Study 1 Indirect Effects for Model Predicting Endorsement of Ageism Among Participants Under 35 Predictor . Ageism Dimension . Indirect Effect (SE) . Standardized Indirect Effect . 95% CI for Standard Indirect Effect . p . Unemployment Stereotypes .11 (.10) .06 −0.09, 0.31 .29 Work stereotypes .06 (.06) .04 −0.06, 0.18 .30 Separation .09 (.09) .05 −0.08, 0.26 .30 Attitudes .07 (.07) .04 −0.07, 0.21 .30 Underemployment Stereotypes .10 (.04) .17 0.02, 0.17 < .01 Work stereotypes .06 (.02) .10 0.01, 0.11 < .01 Separation .08 (.03) .14 0.02, 0.15 < .01 Attitudes .07 (.03) .10 0.01, 0.12 < .01 Job insecurity Stereotypes .11 (.04) .19 0.04, 0.18 < .01 Work stereotypes .07 (.02) .12 0.02, 0.11 < .01 Separation .09 (.03) .16 0.03, 0.15 < .01 Attitudes .07 (.03) .12 0.02, 0.13 < .01 Predictor . Ageism Dimension . Indirect Effect (SE) . Standardized Indirect Effect . 95% CI for Standard Indirect Effect . p . Unemployment Stereotypes .11 (.10) .06 −0.09, 0.31 .29 Work stereotypes .06 (.06) .04 −0.06, 0.18 .30 Separation .09 (.09) .05 −0.08, 0.26 .30 Attitudes .07 (.07) .04 −0.07, 0.21 .30 Underemployment Stereotypes .10 (.04) .17 0.02, 0.17 < .01 Work stereotypes .06 (.02) .10 0.01, 0.11 < .01 Separation .08 (.03) .14 0.02, 0.15 < .01 Attitudes .07 (.03) .10 0.01, 0.12 < .01 Job insecurity Stereotypes .11 (.04) .19 0.04, 0.18 < .01 Work stereotypes .07 (.02) .12 0.02, 0.11 < .01 Separation .09 (.03) .16 0.03, 0.15 < .01 Attitudes .07 (.03) .12 0.02, 0.13 < .01 Open in new tab Table 3. Study 1 Indirect Effects for Model Predicting Endorsement of Ageism Among Participants Under 35 Predictor . Ageism Dimension . Indirect Effect (SE) . Standardized Indirect Effect . 95% CI for Standard Indirect Effect . p . Unemployment Stereotypes .11 (.10) .06 −0.09, 0.31 .29 Work stereotypes .06 (.06) .04 −0.06, 0.18 .30 Separation .09 (.09) .05 −0.08, 0.26 .30 Attitudes .07 (.07) .04 −0.07, 0.21 .30 Underemployment Stereotypes .10 (.04) .17 0.02, 0.17 < .01 Work stereotypes .06 (.02) .10 0.01, 0.11 < .01 Separation .08 (.03) .14 0.02, 0.15 < .01 Attitudes .07 (.03) .10 0.01, 0.12 < .01 Job insecurity Stereotypes .11 (.04) .19 0.04, 0.18 < .01 Work stereotypes .07 (.02) .12 0.02, 0.11 < .01 Separation .09 (.03) .16 0.03, 0.15 < .01 Attitudes .07 (.03) .12 0.02, 0.13 < .01 Predictor . Ageism Dimension . Indirect Effect (SE) . Standardized Indirect Effect . 95% CI for Standard Indirect Effect . p . Unemployment Stereotypes .11 (.10) .06 −0.09, 0.31 .29 Work stereotypes .06 (.06) .04 −0.06, 0.18 .30 Separation .09 (.09) .05 −0.08, 0.26 .30 Attitudes .07 (.07) .04 −0.07, 0.21 .30 Underemployment Stereotypes .10 (.04) .17 0.02, 0.17 < .01 Work stereotypes .06 (.02) .10 0.01, 0.11 < .01 Separation .08 (.03) .14 0.02, 0.15 < .01 Attitudes .07 (.03) .10 0.01, 0.12 < .01 Job insecurity Stereotypes .11 (.04) .19 0.04, 0.18 < .01 Work stereotypes .07 (.02) .12 0.02, 0.11 < .01 Separation .09 (.03) .16 0.03, 0.15 < .01 Attitudes .07 (.03) .12 0.02, 0.13 < .01 Open in new tab Figure 2. Open in new tabDownload slide A structural model predicting endorsement of ageism among participants under 35 (N = 219) in Study 1. Standardized coefficients are presented here, with standard errors in parentheses. *p < .05. Indirect effects are presented in Table 2. For simplicity, latent variable indicators are not depicted here. Figure 2. Open in new tabDownload slide A structural model predicting endorsement of ageism among participants under 35 (N = 219) in Study 1. Standardized coefficients are presented here, with standard errors in parentheses. *p < .05. Indirect effects are presented in Table 2. For simplicity, latent variable indicators are not depicted here. Sexism The analysis for sexism paralleled the analysis for ageism, with underemployment, job insecurity, perceived threat from women, and sexism as latent variables. However, for this analysis, we used the responses from the 172 men (of any age) who responded to the survey. The measurement model again showed acceptable fit to the data (⁠ χ2932 = 562.29, p < .01, CFI = .90, RMSEA = .07, SRMR = .07). Experience with unemployment was included in the structural model as an observed variable. The structural model (Figure 3) showed a slight decrease in fit from the measurement model (⁠ χ3202 = 637.07, p < .01, CFI = .88, RMSEA = .08, SRMR = .08). The paths from job insecurity (β = .07, p = .47, 95% CI = −.11 to .24) and unemployment (β = −.07, p = .75, 95% CI = −.19 to .14) to perceived threat from women were not significant, so Hypotheses 4a and 4c were not supported. The path from underemployment to perceived threat (β = .16, p = .07, 95% CI = −.01 to .33) was only marginally significant, though the 95% confidence interval very nearly excluded zero, so although Hypothesis 4b was not supported, the data do suggest a possible trend. The path from perceived threat to sexism was significant, (β = .35, p < .01, 95% CI = .14 to .44) supporting Hypothesis 5. Table 4 summarizes the indirect effects for the three experienced employment hardship variables on sexism as mediated by perceived threat. None were significant, though consistent with the findings above, the 95% confidence interval for the indirect effect of underemployment nearly excluded zero. Thus, we did not find support for Hypotheses 6a, 6b, or 6c. Table 4. Study 1 Indirect Effects for Model Predicting Endorsement of Sexism Among Men Predictor . Indirect Effect (SE) . Standardized Indirect Effect . 95% CI for Standard Indirect Effect . P . Unemployment − .02 (.08) −.01 −0.05, 0.04 .75 Underemployment .05 (.03) .05 −0.01, 0.10 .10 Job insecurity .02 (.03) .02 −0.03, 0.07 .48 Predictor . Indirect Effect (SE) . Standardized Indirect Effect . 95% CI for Standard Indirect Effect . P . Unemployment − .02 (.08) −.01 −0.05, 0.04 .75 Underemployment .05 (.03) .05 −0.01, 0.10 .10 Job insecurity .02 (.03) .02 −0.03, 0.07 .48 Open in new tab Table 4. Study 1 Indirect Effects for Model Predicting Endorsement of Sexism Among Men Predictor . Indirect Effect (SE) . Standardized Indirect Effect . 95% CI for Standard Indirect Effect . P . Unemployment − .02 (.08) −.01 −0.05, 0.04 .75 Underemployment .05 (.03) .05 −0.01, 0.10 .10 Job insecurity .02 (.03) .02 −0.03, 0.07 .48 Predictor . Indirect Effect (SE) . Standardized Indirect Effect . 95% CI for Standard Indirect Effect . P . Unemployment − .02 (.08) −.01 −0.05, 0.04 .75 Underemployment .05 (.03) .05 −0.01, 0.10 .10 Job insecurity .02 (.03) .02 −0.03, 0.07 .48 Open in new tab Figure 3. Open in new tabDownload slide A structural model predicting endorsement of sexism among men (N = 172) in Study 1. Standardized coefficients are presented here, with standard errors in parentheses. *p < .05, †p <.10. Indirect effects are presented in Table 2. Figure 3. Open in new tabDownload slide A structural model predicting endorsement of sexism among men (N = 172) in Study 1. Standardized coefficients are presented here, with standard errors in parentheses. *p < .05, †p <.10. Indirect effects are presented in Table 2. STUDY 2—TIME-LAGGED STUDENT SAMPLE The objective of Study 2 was to replicate and extend the results from Study 1 using a different population and to address some of the limitations posed by testing a mediational model with a single, cross-sectional sample. Although results from Study 1 demonstrated a pattern of relationships consistent with mediation, all variables were measured at the same point in time. Such cross-sectional measurement raised the possibility of monomethod bias and precluded confidence in the temporal precedence of variables. In Study 2, participants completed two surveys across a 5-day lag, which allowed us to temporally separate the measurement of perceived threat from the measurement of ageist and sexist attitudes. Further, in Study 2, we measured an additional subjective indicator of employment hardship, career optimism, which is the belief that one’s future employment opportunities will be good (De Hauw & De Vos, 2010). The rationale for including this measure was to extend the overall nomological net of subjective employment hardship beyond the three constructs measured in Study 1. Each of the measures in Study 1 included more conceptually negatively constructs: unemployment, perceived underemployment, and perceived job insecurity. We wanted to ensure we captured the correlates of employment hardship more fully by including a positively worded yet highly relevant construct. Career optimism reflects a positive construct and focuses on expectations about the future rather than past or current experiences or beliefs about the present. This construct is consistent with emerging age-related constructs such as occupational future time perspective (Rudolph, Kooij, Rauvola, & Zacher, 2018; Zacher & Frese 2009). Importantly, the measure of career optimism was written specifically by De Hauw and DeVos (2010) for college students similar to our Study 2 participants. Constructs such as perceived underemployment and perceived job insecurity may be viewed as less relevant (and not experienced yet) by students given that many students work in temporary jobs while in school that are often unrelated to their intended careers. However, career optimism nevertheless reflects beliefs about one’s personal economic circumstances and the availability (scarcity) of job opportunities. Career optimism should, therefore, be negatively associated with perceptions of threat from other social groups, consistent with RGCT and SIT. Accordingly, we expanded hypotheses from Study 1 to include the following: Hypothesis 7a: Among younger persons, career optimism is negatively related to perceived threat from older persons. Hypothesis 7b: Among younger persons, career optimism is negatively related to endorsement of ageist attitudes, mediated by perceived threat from older persons. Hypothesis 8a: Among men, career optimism is negatively related to perceived threat from women. Hypothesis 8b: Among men, career optimism is negatively related to endorsement of sexist attitudes, mediated by perceived threat from women. All other hypotheses from Study 1 remained the same in Study 2. Method Participants We chose to focus on students in this study because they are well suited to testing our questions about employment scarcity. College students are regularly exposed to messages about the job market and their prospective employability, as well as to the societal messages discussed above about generational and gender conflict in the workplace. Thus, the issues of employment scarcity should be salient to them. We collected data from 296 students participating in the undergraduate psychology research pool at a large public university. The research pool draws from courses that reflect both required (for psychology majors) and optional for a diverse body of students from all majors across the university. Following data cleaning procedures (discussed in detail below), 269 participants (128 male, 141 female) were included in the working sample. Participants’ ages ranged from 17 to 38 (M = 21, SD = 2.37). The majority of participants (67%) reported their ethnicity as White Caucasian (non-Hispanic), with 17% identifying as Hispanic, 9% identifying as Asian, and the remaining 7% reporting other ethnicities. Slightly over half of the participants (53%) reported being employed at least part-time, 3% were employed full time, and 47% were not employed at the time of the study. However, only 18% of the sample met the criteria for “unemployment” as defined by the Bureau of Labor Statistics (2009) that we used in Study 1 (not employed, available for work, and actively looking for work). In Study 2, the mean of unemployment for the under 35 sample was .18 and was .17 for the male sample. Samples for ageism and sexism analyses. As in Study 1, the ageism analyses were focused on participants aged 35 and younger. Only one participant reported being older than 35 years of age. For the sexism analyses, we included only male participants (N = 128). Compared with the overall sample, there was a higher proportion of White participants (73%), though the distributions of the other demographic characteristics were highly similar to the overall sample. Procedure We posted a description of this study on the university research pool’s online portal that stated the survey would ask about participants’ “work experiences and perceptions of various groups in the workplace.” The description informed participants that they would be compensated one research credit for completing two surveys, each to be completed 5 days apart. Participation was open to all students in the research pool; as per university policy, students under 18 are allowed to participate in minimal risk research with parental permission. Because this study was anonymous, we used three unique identifier questions to link responses from Time 1 to those from Time 2. These identifier questions were “What is the mascot of the high school you graduated from?” “In what month was your youngest sibling born (if you have no siblings, write ‘none’)?” and “What are the last two digits of your current phone number?” These questions were utilized in order to create a unique code for each participant while preserving their anonymity. The survey for Time 1 included measures for unemployment, underemployment, job insecurity, career optimism, perceived threat from older adults, perceived threat from women, ageism, and sexism. The survey for Time 2 included measures for perceived threat from older adults, perceived threat from women, ageism, sexism, and demographic items. Scale presentation order was randomized for both surveys to avoid ordering effects. Demographic information was collected at the end of the Time 2 survey. Measures Along with the addition of the more future-oriented measure of career optimism, Study 2 included the same measures used in Study 1 for unemployment, underemployment, job insecurity, perceived threat from older adults, perceived threat from women, ageism, and sexism. Cronbach’s alpha coefficients for all Study 2 measures are presented in the Methods section and in Table 5. Table 5. Study 2 Summary of Descriptive Statistics: Participants Under Age 35 Variable . N . M . SD . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 . 10 . 11 . 12 . 13 . 1. Age 269 20.44 2.12 — 2. Gender 269 1.52 0.50 −.03 — 3. Unemployment (T1) 269 0.18 0.38 −.12 .02 — 4. Underemployment (T1) 174 3.70 0.72 .25 −.01 .00 .84 5. Job insecurity (T1) 174 1.60 0.76 .00 −.02 .10 −.14 .83 6. Threat—older persons (T1) 269 2.80 0.82 −.01 −.03 −.04 .15 .10 .88 7. Threat—women (T1) 269 1.80 0.66 −.06 −.24 .01 −.06 .06 .24 .90 8. Ageism—stereotypes (T2) 269 2.90 0.75 −.20 −.17 .09 .04 .15 .37 .22 .60 9. Ageism—work stereotypes (T2) 269 2.70 0.74 −.13 −.12 −.06 .12 .04 .29 .23 .54 .62 10. Ageism—separation (T2) 269 2.00 0.67 −.18 −.09 −.01 .02 .17 .33 .42 .48 .48 .81 11. Ageism—attitudes (T2) 269 2.10 0.69 −.17 −.07 −.07 −.08 .17 .24 .28 .33 .35 .68 .65 12. Sexism (T2) 269 2.40 0.82 −.11 −.35 .01 .01 −.12 −.15 .48 .09 .09 .22 .10 .88 13. Career optimism (T1) 269 3.40 0.84 .00 −.16 −.06 −.08 −.22 −.18 .07 −.18 −.16 −.16 −.18 .22 .82 Variable . N . M . SD . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 . 10 . 11 . 12 . 13 . 1. Age 269 20.44 2.12 — 2. Gender 269 1.52 0.50 −.03 — 3. Unemployment (T1) 269 0.18 0.38 −.12 .02 — 4. Underemployment (T1) 174 3.70 0.72 .25 −.01 .00 .84 5. Job insecurity (T1) 174 1.60 0.76 .00 −.02 .10 −.14 .83 6. Threat—older persons (T1) 269 2.80 0.82 −.01 −.03 −.04 .15 .10 .88 7. Threat—women (T1) 269 1.80 0.66 −.06 −.24 .01 −.06 .06 .24 .90 8. Ageism—stereotypes (T2) 269 2.90 0.75 −.20 −.17 .09 .04 .15 .37 .22 .60 9. Ageism—work stereotypes (T2) 269 2.70 0.74 −.13 −.12 −.06 .12 .04 .29 .23 .54 .62 10. Ageism—separation (T2) 269 2.00 0.67 −.18 −.09 −.01 .02 .17 .33 .42 .48 .48 .81 11. Ageism—attitudes (T2) 269 2.10 0.69 −.17 −.07 −.07 −.08 .17 .24 .28 .33 .35 .68 .65 12. Sexism (T2) 269 2.40 0.82 −.11 −.35 .01 .01 −.12 −.15 .48 .09 .09 .22 .10 .88 13. Career optimism (T1) 269 3.40 0.84 .00 −.16 −.06 −.08 −.22 −.18 .07 −.18 −.16 −.16 −.18 .22 .82 Note: Cronbach’s alphas for measures are presented in italics on the diagonal. Correlations in bold text meet statistical significance criteria at α = .05. Unemployment, gender, and age are observed variables and do not have alphas. As the underemployment and job insecurity measures refer to one’s present job, these scales were presented only to those participants who indicated that they had a job at the time of the survey. Gender was coded 1 = male, 2 = female. T1 = Time 1, T2 = Time 2. Open in new tab Table 5. Study 2 Summary of Descriptive Statistics: Participants Under Age 35 Variable . N . M . SD . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 . 10 . 11 . 12 . 13 . 1. Age 269 20.44 2.12 — 2. Gender 269 1.52 0.50 −.03 — 3. Unemployment (T1) 269 0.18 0.38 −.12 .02 — 4. Underemployment (T1) 174 3.70 0.72 .25 −.01 .00 .84 5. Job insecurity (T1) 174 1.60 0.76 .00 −.02 .10 −.14 .83 6. Threat—older persons (T1) 269 2.80 0.82 −.01 −.03 −.04 .15 .10 .88 7. Threat—women (T1) 269 1.80 0.66 −.06 −.24 .01 −.06 .06 .24 .90 8. Ageism—stereotypes (T2) 269 2.90 0.75 −.20 −.17 .09 .04 .15 .37 .22 .60 9. Ageism—work stereotypes (T2) 269 2.70 0.74 −.13 −.12 −.06 .12 .04 .29 .23 .54 .62 10. Ageism—separation (T2) 269 2.00 0.67 −.18 −.09 −.01 .02 .17 .33 .42 .48 .48 .81 11. Ageism—attitudes (T2) 269 2.10 0.69 −.17 −.07 −.07 −.08 .17 .24 .28 .33 .35 .68 .65 12. Sexism (T2) 269 2.40 0.82 −.11 −.35 .01 .01 −.12 −.15 .48 .09 .09 .22 .10 .88 13. Career optimism (T1) 269 3.40 0.84 .00 −.16 −.06 −.08 −.22 −.18 .07 −.18 −.16 −.16 −.18 .22 .82 Variable . N . M . SD . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 . 10 . 11 . 12 . 13 . 1. Age 269 20.44 2.12 — 2. Gender 269 1.52 0.50 −.03 — 3. Unemployment (T1) 269 0.18 0.38 −.12 .02 — 4. Underemployment (T1) 174 3.70 0.72 .25 −.01 .00 .84 5. Job insecurity (T1) 174 1.60 0.76 .00 −.02 .10 −.14 .83 6. Threat—older persons (T1) 269 2.80 0.82 −.01 −.03 −.04 .15 .10 .88 7. Threat—women (T1) 269 1.80 0.66 −.06 −.24 .01 −.06 .06 .24 .90 8. Ageism—stereotypes (T2) 269 2.90 0.75 −.20 −.17 .09 .04 .15 .37 .22 .60 9. Ageism—work stereotypes (T2) 269 2.70 0.74 −.13 −.12 −.06 .12 .04 .29 .23 .54 .62 10. Ageism—separation (T2) 269 2.00 0.67 −.18 −.09 −.01 .02 .17 .33 .42 .48 .48 .81 11. Ageism—attitudes (T2) 269 2.10 0.69 −.17 −.07 −.07 −.08 .17 .24 .28 .33 .35 .68 .65 12. Sexism (T2) 269 2.40 0.82 −.11 −.35 .01 .01 −.12 −.15 .48 .09 .09 .22 .10 .88 13. Career optimism (T1) 269 3.40 0.84 .00 −.16 −.06 −.08 −.22 −.18 .07 −.18 −.16 −.16 −.18 .22 .82 Note: Cronbach’s alphas for measures are presented in italics on the diagonal. Correlations in bold text meet statistical significance criteria at α = .05. Unemployment, gender, and age are observed variables and do not have alphas. As the underemployment and job insecurity measures refer to one’s present job, these scales were presented only to those participants who indicated that they had a job at the time of the survey. Gender was coded 1 = male, 2 = female. T1 = Time 1, T2 = Time 2. Open in new tab Career optimism. We used a measure of career optimism that was designed for use with college student participants (De Hauw & De Vos, 2010). The scale consisted of four items that assess the extent to which respondents are optimistic about the opportunities available to them in the labor market upon graduation (α = .82). Items were rated on a 5-point Likert scale (1 = strongly disagree; 5 = strongly agree). Ageism. As in Study 1, we used the revised version of the Fraboni Scale of Ageism (Rupp et al., 2005) with the additional work-specific stereotype items created for Study 1. However, with all items included, the hypothesized four-factor solution did not meet criteria for acceptable fit (⁠ χ2032 = 555.02, p < .01, CFI = .80, RMSEA = .08, SRMR = .09). By dropping six items (of the original 22) based on low factor loadings and large residual correlations among items, we achieved marginally acceptable fit with a model based on the original four factors (⁠ χ982 = 236.86, p < .01, CFI = .89, RMSEA = .07, SRMR = .06). All four factors were positively correlated; in fact, the latent correlation between the separation and affect dimensions was φ = .95. Cronbach’s alpha coefficients for the stereotypes, work-specific stereotypes, and affect factors were below conventionally accepted levels (α = .60–.65; Table 5). However, to ensure Study 2’s results could be compared with those from Study 1 and interpreted in the context of findings from other research using the Fraboni scale, we proceeded with the four-factor model, acknowledging its limitations. Data cleaning We implemented the same data cleaning procedures used in Study 1 for Study 2 to ensure data quality. We excluded a total of 10 participants prior to analysis based on the following criteria: completing less than 90% of the items (1 participant); completion time less than 3 min (half the completion time estimated by the Qualtrics survey software; 7 participants); and completion time over 90 min (2 participants). No participants had a standard deviation less than 0.50 across all items before reverse coding. We also excluded 16 participants who had a lag time of more than 7 days between the Time 1 and Time 2 surveys, and one participant who was over age 35 and female (and thus did not meet the inclusion criteria for either the ageism or sexism analyses). The final sample for Study 2 was comprised of 269 participants with relatively complete data at both Time 1 and Time 2. Results Descriptive statistics and zero-order correlations among study variables for the ageism analyses appear in Table 5. We used the lavaan package (Rosseel, 2012) in R (R Core Team, 2018) to test our hypotheses using structural equation modeling. Stability of threat and prejudice measures To assess whether the measures of threat and prejudicial attitudes were empirically distinct, we measured both threat and prejudice at both Time 1 and Time 2. For the hypotheses tests (below), we used threat measured at Time 1 and prejudicial attitudes (ageism and sexism) measured at Time 2 in order to reduce method bias from measuring both variables at the same point in time. This also allowed us to assess the stability of these constructs across the 5- to 7-day lag between Time 1 and Time 2. The test–retest reliabilities for perceptions of threat felt from older persons (r = .72), perceptions of threat felt from women (r = .74), and sexism (r = .87) all demonstrated high stability. The separation subdimension of the ageism scale also showed a reasonably high level of stability (test–retest r = .70), though the stereotypes (test–retest r = .55), work stereotypes (test–retest r = .56), and affect (test–retest r = .60) subdimensions demonstrated acceptable, albeit more modest, stability over time. As noted above, however, the internal consistency reliability of these three scales was also low, possibly due to the short length (three items) of each measure. Importantly, the correlations between the perceived threat measures and the corresponding prejudice measures (ageism and sexism) are considerably smaller in magnitude (r = .24–.48, Table 5) than the test–retest correlations or internal consistency coefficients. Although perceived threat and prejudicial attitudes are related, these correlations demonstrate that they are empirically distinct constructs. Ageism We restricted the sample for ageism analyses to participants who, similar to, Study 1 reported their age as 35 years or younger. We used structural equations modeling in the lavaan package to test Hypotheses 1–3. We included underemployment, job insecurity, career optimism, perceived threat from older persons (all measured at Time 1), and the four dimensions of the ageism scale (measured at Time 2) as latent variables in the model. Unemployment was included as an observed variable in the structural model. After we removed two items in the underemployment scale due to low factor loadings (“The work experience that I have is not necessary to be successful on this job.”) and high residual correlations with other items (“Someone with less work experience than myself could do my job just as well.”), the measurement model fit acceptably (⁠ χ11742 = 1152.07, p < .01, CFI = .90, RMSEA = .04, SRMR = .06). The hypothesized structural model (Figure 4) fit approximately as well as the measurement model (⁠ χ8002 = 1180.65, p < .01, CFI = .90, RMSEA = .04, SRMR = .07). Figure 4. Open in new tabDownload slide A structural model predicting endorsement of ageism among participants under 35 (N = 269) in Study 2. Standardized coefficients are presented here, with standard errors in parentheses. *p < .05. Indirect effects are presented in Table 7. For simplicity, latent variable indicators are not depicted here. Figure 4. Open in new tabDownload slide A structural model predicting endorsement of ageism among participants under 35 (N = 269) in Study 2. Standardized coefficients are presented here, with standard errors in parentheses. *p < .05. Indirect effects are presented in Table 7. For simplicity, latent variable indicators are not depicted here. In the structural model, the only predictor variable that had a significant positive path to perceptions of threat from older persons was career optimism (β = −.17, p = .02). Consistent with Study 1, employment status did not have a significant path predicting perceptions of threat (β = −.09, p = .17), and in contrast to Study 1, neither underemployment (β = .11, p = .20) nor job insecurity (β = .06, p = .49) predicted perceptions of threat. This supports Hypothesis 7a but fails to support Hypotheses 1a–1c. However, consistent with Study 1 and supporting Hypothesis 2, there were significant positive paths between perceptions of threat from older persons and all four subdimensions of ageism: stereotypes (β = .50, p < .01), work-specific stereotypes (β = .38, p < .01), separation (β = .36, p < .01), and affect (β = .30, p < .01). Consistent with the analyses above, the indirect effect of career optimism on ageism through perceptions of threat was significant but small for all four dimensions of ageism (Table 6). This supports Hypothesis 7b but fails to support Hypotheses 3a–3c. Table 6. Study 2 Summary of Descriptive Statistics: Men Variable . N . M . SD . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 . 10 . 11 . 12 . 1. Age 128 20.52 2.27 — 2. Unemployment (T1) 128 0.17 0.38 −.09 — 3. Underemployment (T1) 82 3.74 0.75 .33 .08 .85 4. Job insecurity (T1) 82 1.66 0.85 −.03 .26 −.19 .92 5. Threat—older persons (T1) 128 2.86 0.84 .07 −.12 .14 .17 .88 6. Threat—women (T1) 128 1.92 0.65 .01 .05 .02 .16 .28 .89 7. Ageism—stereotypes (T2) 128 3.02 0.74 −.14 .08 .00 .13 .36 .20 .58 8. Ageism—work stereotypes (T2) 128 2.82 0.77 −.07 −.11 .05 .13 .36 .23 .56 .71 9. Ageism—separation (T2) 128 2.09 0.65 −.17 −.10 −.06 .26 .30 .41 .41 .45 .75 10. Ageism—attitudes (T2) 128 2.12 0.72 −.15 −.06 −.20 .17 .20 .27 .22 .27 .65 .61 11. Sexism (T2) 128 2.66 0.82 −.08 −.06 .07 −.05 −.21 .34 .06 .00 .19 .07 .84 12. Career optimism (T1) 128 3.54 0.86 −.02 −.10 .11 −.35 −.17 .08 −.15 −.15 −.11 −.14 .28 .83 Variable . N . M . SD . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 . 10 . 11 . 12 . 1. Age 128 20.52 2.27 — 2. Unemployment (T1) 128 0.17 0.38 −.09 — 3. Underemployment (T1) 82 3.74 0.75 .33 .08 .85 4. Job insecurity (T1) 82 1.66 0.85 −.03 .26 −.19 .92 5. Threat—older persons (T1) 128 2.86 0.84 .07 −.12 .14 .17 .88 6. Threat—women (T1) 128 1.92 0.65 .01 .05 .02 .16 .28 .89 7. Ageism—stereotypes (T2) 128 3.02 0.74 −.14 .08 .00 .13 .36 .20 .58 8. Ageism—work stereotypes (T2) 128 2.82 0.77 −.07 −.11 .05 .13 .36 .23 .56 .71 9. Ageism—separation (T2) 128 2.09 0.65 −.17 −.10 −.06 .26 .30 .41 .41 .45 .75 10. Ageism—attitudes (T2) 128 2.12 0.72 −.15 −.06 −.20 .17 .20 .27 .22 .27 .65 .61 11. Sexism (T2) 128 2.66 0.82 −.08 −.06 .07 −.05 −.21 .34 .06 .00 .19 .07 .84 12. Career optimism (T1) 128 3.54 0.86 −.02 −.10 .11 −.35 −.17 .08 −.15 −.15 −.11 −.14 .28 .83 Note. Cronbach’s alphas for measures are presented in italics on the diagonal. Correlations in bold text meet statistical significance criteria at α = .05. Unemployment and age are observed variables and do not have alphas. As the underemployment and job insecurity measures refer to one’s present job, these scales were presented only to those participants who indicated that they had a job at the time of the survey. Gender was coded 1 = male, 2 = female. T1 = Time 1, T2 = Time 2. Open in new tab Table 6. Study 2 Summary of Descriptive Statistics: Men Variable . N . M . SD . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 . 10 . 11 . 12 . 1. Age 128 20.52 2.27 — 2. Unemployment (T1) 128 0.17 0.38 −.09 — 3. Underemployment (T1) 82 3.74 0.75 .33 .08 .85 4. Job insecurity (T1) 82 1.66 0.85 −.03 .26 −.19 .92 5. Threat—older persons (T1) 128 2.86 0.84 .07 −.12 .14 .17 .88 6. Threat—women (T1) 128 1.92 0.65 .01 .05 .02 .16 .28 .89 7. Ageism—stereotypes (T2) 128 3.02 0.74 −.14 .08 .00 .13 .36 .20 .58 8. Ageism—work stereotypes (T2) 128 2.82 0.77 −.07 −.11 .05 .13 .36 .23 .56 .71 9. Ageism—separation (T2) 128 2.09 0.65 −.17 −.10 −.06 .26 .30 .41 .41 .45 .75 10. Ageism—attitudes (T2) 128 2.12 0.72 −.15 −.06 −.20 .17 .20 .27 .22 .27 .65 .61 11. Sexism (T2) 128 2.66 0.82 −.08 −.06 .07 −.05 −.21 .34 .06 .00 .19 .07 .84 12. Career optimism (T1) 128 3.54 0.86 −.02 −.10 .11 −.35 −.17 .08 −.15 −.15 −.11 −.14 .28 .83 Variable . N . M . SD . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 . 10 . 11 . 12 . 1. Age 128 20.52 2.27 — 2. Unemployment (T1) 128 0.17 0.38 −.09 — 3. Underemployment (T1) 82 3.74 0.75 .33 .08 .85 4. Job insecurity (T1) 82 1.66 0.85 −.03 .26 −.19 .92 5. Threat—older persons (T1) 128 2.86 0.84 .07 −.12 .14 .17 .88 6. Threat—women (T1) 128 1.92 0.65 .01 .05 .02 .16 .28 .89 7. Ageism—stereotypes (T2) 128 3.02 0.74 −.14 .08 .00 .13 .36 .20 .58 8. Ageism—work stereotypes (T2) 128 2.82 0.77 −.07 −.11 .05 .13 .36 .23 .56 .71 9. Ageism—separation (T2) 128 2.09 0.65 −.17 −.10 −.06 .26 .30 .41 .41 .45 .75 10. Ageism—attitudes (T2) 128 2.12 0.72 −.15 −.06 −.20 .17 .20 .27 .22 .27 .65 .61 11. Sexism (T2) 128 2.66 0.82 −.08 −.06 .07 −.05 −.21 .34 .06 .00 .19 .07 .84 12. Career optimism (T1) 128 3.54 0.86 −.02 −.10 .11 −.35 −.17 .08 −.15 −.15 −.11 −.14 .28 .83 Note. Cronbach’s alphas for measures are presented in italics on the diagonal. Correlations in bold text meet statistical significance criteria at α = .05. Unemployment and age are observed variables and do not have alphas. As the underemployment and job insecurity measures refer to one’s present job, these scales were presented only to those participants who indicated that they had a job at the time of the survey. Gender was coded 1 = male, 2 = female. T1 = Time 1, T2 = Time 2. Open in new tab Sexism As noted above, we included only male participants in the analyses for sexism (N = 128). We followed the same procedures as above to test the hypotheses. Although the initial measurement model with all items did not fit well (⁠ χ6512 = 1015.90, p < .01, CFI = .84, RMSEA = .07, SRMR = .08), we removed the same two items as above from the underemployment measure, along with one item from the perceived threat from women scale (“Many companies believe women are more qualified than men.”) and one item from the sexism scale (“It is easy to understand why women’s groups are still concerned about societal limitations of women’s opportunities.”) due to low factor loadings. After removing these items, the measurement model fit acceptably (⁠ χ5132 = 712.43, p < .01, CFI = .90, RMSEA = .06, SRMR = .07). The structural model (Figure 5) showed a small diminution in fit compared with the measurement model (⁠ χ5172 = 724.98, p < .01, CFI = .89, RMSEA = .06, SRMR = .08). The only predictor variable with a significant path to perceptions of threat from women was job insecurity (β = .30, p = .02). The paths from unemployment (β = −.04, p = .70) and underemployment (β = −.02, p = .88) to threat from women were not significant. Although not statistically significant, there was a trend toward a path from career optimism to perceptions of threat from women (β = .21, p = .07), suggesting that male participants with higher career optimism were more likely to report perceptions of women as economic threats. The SEM also showed that the path from perceived threat to sexism was significant (β = .40, p < .01). Unlike results from the working adult MTurk sample, the indirect effect of job insecurity on sexism was significant in the student sample (Table 7). Finally, the indirect effects of unemployment and underemployment were not significant, and although there was a trend toward a positive indirect effect of career optimism on sexism, it did not reach significance. Table 7. Study 2 Indirect Effects for Model Predicting Endorsement of Ageism Among Participants Under 35 Predictor . Ageism Dimension . Indirect Effect (SE) . Standardized Indirect Effect . p . Unemployment Stereotypes −.05 (.04) −.04 .19 Work stereotypes −.05 (.04) −.03 .19 Separation −.06 (.05) −.03 .19 Attitudes −.05 (.04) −.03 .20 Underemployment Stereotypes .03 (.02) .05 .22 Work stereotypes .03 (.02) .04 .22 Separation .04 (.03) .04 .22 Attitudes .03 (.02) .03 .23 Job insecurity Stereotypes .02 (.02) .03 .49 Work stereotypes .02 (.03) .02 .49 Separation .02 (.03) .02 .49 Attitudes .02 (.02) .02 .50 Career optimism Stereotypes −.06 (03) −.08 .04 Work stereotypes −.07 (.03) −.07 .04 Separation −.08 (.04) −.06 .03 Attitudes −.06 (.03) −.05 .05 Predictor . Ageism Dimension . Indirect Effect (SE) . Standardized Indirect Effect . p . Unemployment Stereotypes −.05 (.04) −.04 .19 Work stereotypes −.05 (.04) −.03 .19 Separation −.06 (.05) −.03 .19 Attitudes −.05 (.04) −.03 .20 Underemployment Stereotypes .03 (.02) .05 .22 Work stereotypes .03 (.02) .04 .22 Separation .04 (.03) .04 .22 Attitudes .03 (.02) .03 .23 Job insecurity Stereotypes .02 (.02) .03 .49 Work stereotypes .02 (.03) .02 .49 Separation .02 (.03) .02 .49 Attitudes .02 (.02) .02 .50 Career optimism Stereotypes −.06 (03) −.08 .04 Work stereotypes −.07 (.03) −.07 .04 Separation −.08 (.04) −.06 .03 Attitudes −.06 (.03) −.05 .05 Open in new tab Table 7. Study 2 Indirect Effects for Model Predicting Endorsement of Ageism Among Participants Under 35 Predictor . Ageism Dimension . Indirect Effect (SE) . Standardized Indirect Effect . p . Unemployment Stereotypes −.05 (.04) −.04 .19 Work stereotypes −.05 (.04) −.03 .19 Separation −.06 (.05) −.03 .19 Attitudes −.05 (.04) −.03 .20 Underemployment Stereotypes .03 (.02) .05 .22 Work stereotypes .03 (.02) .04 .22 Separation .04 (.03) .04 .22 Attitudes .03 (.02) .03 .23 Job insecurity Stereotypes .02 (.02) .03 .49 Work stereotypes .02 (.03) .02 .49 Separation .02 (.03) .02 .49 Attitudes .02 (.02) .02 .50 Career optimism Stereotypes −.06 (03) −.08 .04 Work stereotypes −.07 (.03) −.07 .04 Separation −.08 (.04) −.06 .03 Attitudes −.06 (.03) −.05 .05 Predictor . Ageism Dimension . Indirect Effect (SE) . Standardized Indirect Effect . p . Unemployment Stereotypes −.05 (.04) −.04 .19 Work stereotypes −.05 (.04) −.03 .19 Separation −.06 (.05) −.03 .19 Attitudes −.05 (.04) −.03 .20 Underemployment Stereotypes .03 (.02) .05 .22 Work stereotypes .03 (.02) .04 .22 Separation .04 (.03) .04 .22 Attitudes .03 (.02) .03 .23 Job insecurity Stereotypes .02 (.02) .03 .49 Work stereotypes .02 (.03) .02 .49 Separation .02 (.03) .02 .49 Attitudes .02 (.02) .02 .50 Career optimism Stereotypes −.06 (03) −.08 .04 Work stereotypes −.07 (.03) −.07 .04 Separation −.08 (.04) −.06 .03 Attitudes −.06 (.03) −.05 .05 Open in new tab Figure 5. Open in new tabDownload slide A structural model predicting endorsement of sexism among male participants (N = 128) in Study 2. Standardized coefficients are presented here, with standard errors in parentheses. *p < .05. †p < .10. Indirect effects are presented in Table 8. For simplicity, latent variable indicators are not depicted here. Figure 5. Open in new tabDownload slide A structural model predicting endorsement of sexism among male participants (N = 128) in Study 2. Standardized coefficients are presented here, with standard errors in parentheses. *p < .05. †p < .10. Indirect effects are presented in Table 8. For simplicity, latent variable indicators are not depicted here. Table 8. Study 2 Indirect Effects for Model Predicting Endorsement of Sexism Among Men Predictor . Indirect Effect (SE) . Standardized Indirect Effect . p . Unemployment −.04 (.10) −.02 .70 Underemployment −.01 (.06) −.01 .88 Job insecurity .13 (.06) .12 .04 Career optimism .12 (.07) .09 .09 Predictor . Indirect Effect (SE) . Standardized Indirect Effect . p . Unemployment −.04 (.10) −.02 .70 Underemployment −.01 (.06) −.01 .88 Job insecurity .13 (.06) .12 .04 Career optimism .12 (.07) .09 .09 Open in new tab Table 8. Study 2 Indirect Effects for Model Predicting Endorsement of Sexism Among Men Predictor . Indirect Effect (SE) . Standardized Indirect Effect . p . Unemployment −.04 (.10) −.02 .70 Underemployment −.01 (.06) −.01 .88 Job insecurity .13 (.06) .12 .04 Career optimism .12 (.07) .09 .09 Predictor . Indirect Effect (SE) . Standardized Indirect Effect . p . Unemployment −.04 (.10) −.02 .70 Underemployment −.01 (.06) −.01 .88 Job insecurity .13 (.06) .12 .04 Career optimism .12 (.07) .09 .09 Open in new tab DISCUSSION Using RGCT and SIT as theoretical frameworks in two studies, we assessed the hypothesized relationships that experienced employment hardship (operationalized as unemployment, perceptions of underemployment, job insecurity, and career optimism) would be associated with ageist and sexist attitudes, and that these relationships would be mediated by perception of threat by older persons and women. Results generally supported these predictions for ageism, yet much less so for sexism across the two samples. Using SEM, the indirect effects model was supported in Studies 1 and 2 though using varying predictors. In the working adult sample, job insecurity and underemployment were associated with greater perceived threat from older adults, and perceived threat from older adults was associated with more ageist attitudes. In Study 2, using SEM and two data collection points with a short time in between, career optimism (a more relevant construct among students than underemployment or job insecurity) was associated with less perceived threat from older adults. Further, greater perceived threat from older adults was associated with more ageist attitudes. In addition, across both studies, the role of experienced unemployment in predicting perceptions of threat or sexist or ageist attitudes was not significant. Overall, results are consistent with SIT in that perceptions of competition over scarce work resources are associated with higher endorsement of ageism and sexism. Importantly, these results also suggest that the specific factors that give rise to perceptions of threat are complex and may vary depending upon the specific social group (e.g., age groups, gender groups). The current two studies meaningfully contribute to the literatures on prejudice and intergroup conflict. First, this study focused on how economic factors at the individual-level predict prejudicial attitudes. This helps ground SIT specifically, and to some degree, more recent interpretations of RGCT, using individuals’ experiences of scarcity and supports a person-centered approach to examining perceptions of threat. Perceived job insecurity, underemployment, and career optimism were each predictive of prejudicial attitudes in at least one sample. Additionally, experienced or actual unemployment was not associated with prejudicial attitudes in either sample. However, caution needs to be observed for the results across the two samples. Actual unemployment in Study 2, among college-aged students whose primary role is education acquisition, is quite different than among non-college participants who are carving out a work life and career. College age employees (as in Study 2), when employed, often take full- or part-time work to support themselves short-term while going to classes and such work may reflect lower skill levels than career occupations. Consistent with this, unemployment and underemployment are slightly higher among Study 2 college students than in the Study 1 MTurk sample. Further, job insecurity is slightly lower among Study 2 college students than Study 1 MTurk participants. One possible explanation for the nonsignificant relationships for unemployment in both samples is that unemployment status is a more objective indicator of employment hardship, whereas the other constructs reflect subjective evaluations of hardship. These findings are more consistent with SIT than the initial conceptualizations of RGCT. RGCT initially posited that objective features of a context influence individuals’ perceptions of threat and competition of resources. We did not find evidence of this in the results of the current two studies. Rather, an individual’s perceptions that his or her economic situation is at risk may be associated with enhanced perceptions about potential threats to their economic well-being. Therefore, workers’ actual economic well-being may be a less important factor in the perception of threat than their subjective economic well-being, which is consistent with SIT. Alternatively, the nonsignificant relationship between the unemployment variable and prejudicial attitudes may be attributable to how unemployment was measured. Although we defined unemployment consistent with the U.S. Bureau of Labor Statistics, our operationalization yielded a dichotomous variable that captured only a respondent’s employment status at a particular moment in time. As a result, this measure may not have been sensitive to variations in respondents’ experience with unemployment, such as whether they had been unemployed in the past, the length of their unemployment or the timing of unemployment in their careers. Unemployment is a complex and personal experience, and a simple “yes or no” response to unemployment status may not adequately tap one’s perceptions of threat from other groups. Finally, the unemployment rates in both samples were fairly low and this range restriction could affect the (lack of) relationships between this variable and other outcomes. Second, another contribution of this study is the application of RGCT and SIT to older adults and women, who may be viewed as less likely groups for competition-based prejudicial attitudes. According to the stereotype content model (Fiske et al., 2002), stereotypes function across two dimensions—warmth and competence—and are driven by the perceived status and competitiveness of the target group. Fiske and her colleagues found that older persons (along with intellectually and physically disabled persons) occupied a warmth/competence cluster that is associated with nonthreatening characteristics (Cuddy & Fiske, 2004; Fiske et al., 2002). As the older population becomes proportionally larger, more prominent at work, and utilizes a greater share of valued resources—including jobs—the stereotype of older adults as a social group increasingly may be viewed as more competitive and threatening. Our findings regarding sexism were equivocal and may reflect a complex and evolving set of stereotypes of female gender roles. As women continue to make inroads to workplace equality and their role as primary income earners becomes more common, the “competitive businesswoman” perception of females which is rated as more competent and less warm (Fiske et al., 2002; Deaux, Winton, Crowley, & Lewis, 1985; Eckes, 1994; Six & Eckes, 1991 for common gender categorizations) may become more salient than that of the “docile housewife” perception. Therefore, working women increasingly may be viewed as a more threatening outgroup and as a competitor for valued resources, such as high-quality jobs. Notably, in the current study through SEM direct effects, underemployment among men was only marginally associated with perceived threat from women. Future research should focus upon investigating men’s perceived threat by competition from women focusing upon women entering high paying, high-status occupations. Theoretical and Empirical Contributions The current research makes a number of theoretical contributions to the literature on age- and sex-based attitudes. First, the two studies advance the body of work focused on how scarcity and competition are associated with ageism and sexism. Using both SIT (Tajfel & Turner, 1979) and RGCT (Sherif, 1966) as guiding theories, our results support prior research findings that outgroups historically less salient as economic threats (i.e., women and older persons) can be linked to competition-based hostility under certain conditions (King et al., 2010). Specifically, a favorable or mixed perception of an outgroup can be rated more negatively when the group is thought to be an economic threat (Dear & Gleeson, 1991). Second, results provide empirical evidence for the age and generation research literature on the possible intergroup conflict between younger workers and older age groups. There has been extensive discussion of purported generational differences in the workplace (Toossi, 2009) as well as arguments that these differences form the basis for intergenerational conflict. However, little evidence has been provided to support these claims of cross-age-group conflicts. Results of the present study provide critical empirical evidence that under specific conditions (e.g., job insecurity and underemployment), younger working age people hold more negative views of older workers when feeling threatened economically, such as in the work context. We urge age and work researchers to more directly examine the conditions under which relations among age diverse workers become strained or conflicted. Finally, the correlates and underlying mechanisms of ageism and sexism may not be the same. Using SEM and correlations, our results suggest that men, especially when perceiving a threat from women at work, report more sexist attitudes. Although men’s perception of their underemployment is marginally correlated with perceived threat from women, it is less clear from the current study what role employment status factors have in predicting men’s perceived threat or sexist attitudes. Clearly, more research is needed to further explicate these relationships. The relationships between men and women at work may need to incorporate greater interactional theory as perceptions of women by men (and vice versa) may differ by one’s age and career stage as well as by occupation (Cleveland, Huebner, & Hanscom, 2017). Practical Implications Work environments have become more diverse in terms of age (Meister & Willyerd, 2010) and gender (Bureau of Labor Statistics, 2014). Understanding how and under what conditions ageism and sexism may emerge has unique implications for the workplace. Prior work on competition-driven prejudicial attitudes shows that macroeconomic trends can set the stage for intergroup hostility, and these trends may persist for several years and can be challenging for individual organizations to address. However, the individual-level factors contributing to prejudicial attitudes identified in this study can lend themselves to organizational intervention, change, and development. Organizations can influence their employees’ perceptions about their job security by clearly communicating expectations regarding what is appropriate and respectful behaviors and interactions among employees (Schweiger & DeNisi, 1991). Further, organizations can directly address underemployment among employees by allowing and encouraging job crafting (Wrzesniewski & Dutton, 2001). Additionally, positive and constructive contact between groups has been found to improve perceptions of outgroups (Pettigrew & Tropp, 2006). Thus, providing opportunities for workers of different age and gender groups to cooperate to achieve jointly valued organizational, group, and individual goals is a worthwhile strategy for mitigating prejudicial attitudes. With regard to age, intergenerational cooperation at work can provide developmental opportunities for younger workers and socio-emotional generativity opportunities for older workers while reducing prejudicial attitudes via positive contact (Henry, Zacher, & Desmette, 2015). Considerable research has established that employment hardship is detrimental to many organizational outcomes, including productivity, work attitudes, and health (De Witte, 2005; McKee-Ryan & Harvey, 2011); the present findings add one more impetus for organizations to do what they can to manage these perceptions. Strengths and Limitations This study is not without limitations. First, although the model we proposed implies a causal sequence, we tested it using a cross-sectional study in Study 1 and only a brief time lag in Study 2. Thus, we do not have evidence that experiences of employment hardship cause the endorsement of prejudicial attitudes. Further, we cannot conclude that changes in perceptions of job insecurity or underemployment would change an individual’s perceptions of threat from outgroups or their level of prejudicial attitudes. Alternative models may suggest, for example, that deeply entrenched prejudices may lead individuals to view the world more negatively or fearfully, thus increasing perceptions of job insecurity and underemployment. As an exploratory analysis, we tested some such models (specifically, predicting job insecurity and underemployment from ageism and threat from older workers, and from sexism and threat from women). The fit of these models was very similar to the fit of our proposed models, but none of the paths from prejudicial attitudes or threat variables to either job insecurity or underemployment were significant. Thus, although the models proposed in the present research are more interpretable, it would be valuable to pursue these alternative models in future research (perhaps including constructs such as negative affectivity). Importantly, although difficult to implement, longitudinal research is warranted to better understand the specific direction of the relationships found in the current set of studies in the development of ageism and sexism among groups. Collecting data from a single source at a single point in time, as we did in Study 1, raises the possibility that common method variance could have inflated the relationships we observed among variables. Conway and Lance (2010) point out, however, that common method measurement does not necessarily or consistently result in inflated correlations, and that post hoc corrections for common method variance are often flawed. We followed several of their recommendations for proactive mitigation of bias. For example, the measures used in Study 1 were separated from one another within the context of a larger survey, and in Study 2, we temporally separated the measurement of our key variables (perceptions of threat and prejudicial attitudes). We chose a short time lag to minimize the possibility that participants’ employment circumstances would change between Time 1 and Time 2 (as is common among college students), even though it is possible that some of the correlations among measures may have been somewhat inflated by participants’ memory of their prior answers. Of greater concern is the similarity between the perceived threat and prejudice measures; it could be argued that perceived threat is merely a particular type of prejudiced attitude, and thus large correlations between threat and prejudice are only to be expected. Conway and Lance (2010) also addressed this issue and the need for researchers to be able to support an argument that their constructs are theoretically and empirically distinct. In our measures, the perceived threat items generally focused on perceptions of societal trends and explicit competition (e.g., “Older people dominate American society more than they should”) and the prejudice items focused on perceptions of personal attributes (“Many older people are not motivated when confronting challenges”). Thus, it seems unlikely that content overlap among items is a major driver of the relationships we observed; although these measures are conceptually related, they are not the same. The measurement models suggested that participants did differentiate among constructs, providing some evidence that the nomological net of the constructs was as we expected. Although our study is not the first to identify a connection between perceived threat and prejudice, our results reaffirm the importance of threat perceptions in understanding other expressions of prejudice. Future Research Directions The results of these studies offer several avenues for future research. Replicating the present findings with behavioral measures of prejudicial attitudes and other individual- and macro-level operationalizations of employment hardship would strengthen confidence in these relationships and help to understand their nuances. The proposed mediational model implies a causal process that could not be established with a cross-sectional survey or even a two-data point survey. Future studies could seek to develop interventions to reduce perceptions of job insecurity and underemployment and investigate the resulting effects on prejudicial attitudes. They could also use longitudinal designs to evaluate whether prejudice changes following positive or negative personal employment events (such as a layoff, promotion, or job change), which might change perceptions of hardship, or group-level events (such as news stories about the gains of one group in the labor market), which might change perceptions of threat. Finally, our results (and much of the relevant theoretical literature) are limited by our use of U.S. samples. Many of the labor trends in the United States are paralleled in other countries, where younger workers and, in particular, males, have been more affected by economic scarcity (Lallement, 2011). However, prejudice occurs in many forms, and gender and age are not the only salient identities for workers. Future research should consider more diverse and multicultural populations to explore how cultural differences and international differences in economic conditions might extend or limit the predictions made here. Additionally, this study focused on the perceptions and attitudes of younger and male workers toward older and female workers. We chose this focus on the grounds that older and female workers are often targets of prejudice in the workplace, and thus understanding how such prejudices arise is important for the success and well-being of these segments of the workforce. The current research is a solid first set of studies on the application of SIT and RGCT to understanding the relationship between economic threats and ageism and sexism. However, we do not mean to imply that only these groups may be perceived as threatening. Indeed, older workers who perceive their work opportunities as scarce may endorse negative stereotypes about younger workers, or the same pattern may hold for female workers about male workers. Future research should explore reciprocal perceptions of competition and hostility across groups and explore whether such perceptions are symmetric or asymmetric. Future research using both older and younger people and men and women is needed to better understand the complete intergroup phenomenon. Further, it would be useful to include both macro-level “objective”’ employment data of own and other groups and more subjective individual level perceptions employment scarcity. For example, despite the advances that older and female workers have made in the workplace, many individuals continue to face unique sets of challenges. Although actual unemployment rates were lower for both groups during the recession, negative stereotypes about their performance and competence may make finding (re)employment more difficult for older or female workers than for younger or male workers, especially when work is scarce. Future research should explore perceptions of competition and hostility toward younger and male workers as well. Furthermore, as a more direct test of RGCT, there could be an explicit measure or benchmark of economic hardship factors of whether participants believe that lower economic positioned members of their ingroup (and themselves) was due to a specific outgroup (e.g., the “fault” of women, older persons, immigrants, and so forth). Finally, recent work has begun to focus on the importance of meta-stereotypes, which are beliefs that an individual holds about the perceptions or stereotypes others may have of him or her (see Finkelstein, King, & Voyles, 2015 for a discussion on age meta-stereotypes). 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Older people hold too many positions of power and responsibility in this country 2. Older people dominate American society more than they should 3. When older people are in positions of authority, they discriminate against younger people when making hiring decisions 4. Older people have more economic power than they deserve in this country 5. Older people make it harder for younger people to get good jobs 6. Many companies believe older people are more qualified than younger people 7. Older people have more political power than they deserve in this country 8. Older people make it harder for younger people to have a good quality of life 9. The legal system lets older people get away with more than younger people 1. Older people hold too many positions of power and responsibility in this country 2. Older people dominate American society more than they should 3. When older people are in positions of authority, they discriminate against younger people when making hiring decisions 4. Older people have more economic power than they deserve in this country 5. Older people make it harder for younger people to get good jobs 6. Many companies believe older people are more qualified than younger people 7. Older people have more political power than they deserve in this country 8. Older people make it harder for younger people to have a good quality of life 9. The legal system lets older people get away with more than younger people Note. Adapted from Maddux and colleagues (2008). Open in new tab Appendix Table 1. Perceived Threat from Older Workers Items 1. Older people hold too many positions of power and responsibility in this country 2. Older people dominate American society more than they should 3. When older people are in positions of authority, they discriminate against younger people when making hiring decisions 4. Older people have more economic power than they deserve in this country 5. Older people make it harder for younger people to get good jobs 6. Many companies believe older people are more qualified than younger people 7. Older people have more political power than they deserve in this country 8. Older people make it harder for younger people to have a good quality of life 9. The legal system lets older people get away with more than younger people 1. Older people hold too many positions of power and responsibility in this country 2. Older people dominate American society more than they should 3. When older people are in positions of authority, they discriminate against younger people when making hiring decisions 4. Older people have more economic power than they deserve in this country 5. Older people make it harder for younger people to get good jobs 6. Many companies believe older people are more qualified than younger people 7. Older people have more political power than they deserve in this country 8. Older people make it harder for younger people to have a good quality of life 9. The legal system lets older people get away with more than younger people Note. Adapted from Maddux and colleagues (2008). Open in new tab Appendix Table 2. Perceived Threat From Women Items 1. Women hold too many positions of power and responsibility in this country 2. Women dominate American society more than they should 3. When women are in positions of authority, they discriminate against younger people when making hiring decisions 4. Women have more economic power than they deserve in this country 5. Women make it harder for younger people to get good jobs 6. Many companies believe women are more qualified than younger people 7. Women have more political power than they deserve in this country 8. Women make it harder for younger people to have a good quality of life 9. The legal system lets women get away with more than younger people 1. Women hold too many positions of power and responsibility in this country 2. Women dominate American society more than they should 3. When women are in positions of authority, they discriminate against younger people when making hiring decisions 4. Women have more economic power than they deserve in this country 5. Women make it harder for younger people to get good jobs 6. Many companies believe women are more qualified than younger people 7. Women have more political power than they deserve in this country 8. Women make it harder for younger people to have a good quality of life 9. The legal system lets women get away with more than younger people Note. Adapted from Maddux and colleagues (2008). Open in new tab Appendix Table 2. Perceived Threat From Women Items 1. Women hold too many positions of power and responsibility in this country 2. Women dominate American society more than they should 3. When women are in positions of authority, they discriminate against younger people when making hiring decisions 4. Women have more economic power than they deserve in this country 5. Women make it harder for younger people to get good jobs 6. Many companies believe women are more qualified than younger people 7. Women have more political power than they deserve in this country 8. Women make it harder for younger people to have a good quality of life 9. The legal system lets women get away with more than younger people 1. Women hold too many positions of power and responsibility in this country 2. Women dominate American society more than they should 3. When women are in positions of authority, they discriminate against younger people when making hiring decisions 4. Women have more economic power than they deserve in this country 5. Women make it harder for younger people to get good jobs 6. Many companies believe women are more qualified than younger people 7. Women have more political power than they deserve in this country 8. Women make it harder for younger people to have a good quality of life 9. The legal system lets women get away with more than younger people Note. Adapted from Maddux and colleagues (2008). Open in new tab Appendix Table 3. Ageism Toward Older Workers Items Stereotype dimension 1. Many older people are not interested in making new friends, preferring instead the circle of friends they have had for years 2. Many older people just live in the past 3. Many older people are happiest when they are with people their own age 4. Older people complain more than other people do Work stereotype dimension 5. Many older people are not motivated when confronting challenges 6. Older people tend to be less productive at work 7. It is difficult to train older people to perform new tasks 8. Older people usually struggle with technology 9. Older people have a hard time learning new things Separation dimension 10. I sometimes avoid eye contact with older people when I see them 11. I don’t like it when older people try to make conversation with me 12. Complex and interesting conversation cannot be expected from most older people 13. Feeling depressed when around older people is probably a common feeling 14. Older people should find friends their own age 15. Older people should feel welcome at the social gatherings of young people. (R) 16. Older people don’t really need to use our community sports facilities 17. It is best that older people live where they won’t bother anyone Affective attitude dimension 18. I personally would not want to spend much time with an older person 19. The company of most older people is quite enjoyable. (R) 20. It is sad to hear about the plight of older people in our society these days. (R) 21. Older people should be encouraged to speak out politically. (R) 22. Most older people are interesting, individualistic people. (R) Stereotype dimension 1. Many older people are not interested in making new friends, preferring instead the circle of friends they have had for years 2. Many older people just live in the past 3. Many older people are happiest when they are with people their own age 4. Older people complain more than other people do Work stereotype dimension 5. Many older people are not motivated when confronting challenges 6. Older people tend to be less productive at work 7. It is difficult to train older people to perform new tasks 8. Older people usually struggle with technology 9. Older people have a hard time learning new things Separation dimension 10. I sometimes avoid eye contact with older people when I see them 11. I don’t like it when older people try to make conversation with me 12. Complex and interesting conversation cannot be expected from most older people 13. Feeling depressed when around older people is probably a common feeling 14. Older people should find friends their own age 15. Older people should feel welcome at the social gatherings of young people. (R) 16. Older people don’t really need to use our community sports facilities 17. It is best that older people live where they won’t bother anyone Affective attitude dimension 18. I personally would not want to spend much time with an older person 19. The company of most older people is quite enjoyable. (R) 20. It is sad to hear about the plight of older people in our society these days. (R) 21. Older people should be encouraged to speak out politically. (R) 22. Most older people are interesting, individualistic people. (R) Note. Adapted from Rupp and colleagues (2005). Open in new tab Appendix Table 3. Ageism Toward Older Workers Items Stereotype dimension 1. Many older people are not interested in making new friends, preferring instead the circle of friends they have had for years 2. Many older people just live in the past 3. Many older people are happiest when they are with people their own age 4. Older people complain more than other people do Work stereotype dimension 5. Many older people are not motivated when confronting challenges 6. Older people tend to be less productive at work 7. It is difficult to train older people to perform new tasks 8. Older people usually struggle with technology 9. Older people have a hard time learning new things Separation dimension 10. I sometimes avoid eye contact with older people when I see them 11. I don’t like it when older people try to make conversation with me 12. Complex and interesting conversation cannot be expected from most older people 13. Feeling depressed when around older people is probably a common feeling 14. Older people should find friends their own age 15. Older people should feel welcome at the social gatherings of young people. (R) 16. Older people don’t really need to use our community sports facilities 17. It is best that older people live where they won’t bother anyone Affective attitude dimension 18. I personally would not want to spend much time with an older person 19. The company of most older people is quite enjoyable. (R) 20. It is sad to hear about the plight of older people in our society these days. (R) 21. Older people should be encouraged to speak out politically. (R) 22. Most older people are interesting, individualistic people. (R) Stereotype dimension 1. Many older people are not interested in making new friends, preferring instead the circle of friends they have had for years 2. Many older people just live in the past 3. Many older people are happiest when they are with people their own age 4. Older people complain more than other people do Work stereotype dimension 5. Many older people are not motivated when confronting challenges 6. Older people tend to be less productive at work 7. It is difficult to train older people to perform new tasks 8. Older people usually struggle with technology 9. Older people have a hard time learning new things Separation dimension 10. I sometimes avoid eye contact with older people when I see them 11. I don’t like it when older people try to make conversation with me 12. Complex and interesting conversation cannot be expected from most older people 13. Feeling depressed when around older people is probably a common feeling 14. Older people should find friends their own age 15. Older people should feel welcome at the social gatherings of young people. (R) 16. Older people don’t really need to use our community sports facilities 17. It is best that older people live where they won’t bother anyone Affective attitude dimension 18. I personally would not want to spend much time with an older person 19. The company of most older people is quite enjoyable. (R) 20. It is sad to hear about the plight of older people in our society these days. (R) 21. Older people should be encouraged to speak out politically. (R) 22. Most older people are interesting, individualistic people. (R) Note. Adapted from Rupp and colleagues (2005). Open in new tab © The Author(s) 2019. 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TI - The Relationship of Employment Scarcity and Perceived Threat With Ageist and Sexist Attitudes
JF - Work, Aging and Retirement
DO - 10.1093/workar/waz003
DA - 2019-07-19
UR - https://www.deepdyve.com/lp/oxford-university-press/the-relationship-of-employment-scarcity-and-perceived-threat-with-xEMMPFuouP
SP - 215
VL - 5
IS - 3
DP - DeepDyve
ER -