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Age stratification at work: Trends in occupational age segregation in the United States, 1950–2000
Research in Social Stratification and Mobility 24 (2006) 299–310
Age stratification at work: Trends in occupational age segregation in the United States, 1950–2000 Alair MacLean Washington State University Vancouver, 14204 NE Salmon Creek Avenue, Vancouver, WA 98686, United States Received 22 November 2004; received in revised form 3 June 2005; accepted 20 August 2005
Abstract This paper adjudicates between competing accounts of recent trends in the amount and patterning of occupational age segregation. These accounts rely on narratives about: (1) the decline of age-graded mobility, (2) the rise of occupational volatility, and (3) the existence of dual labor markets, in particular increasingly bimodal age distributions in low-skill occupations. Using new logmultiplicative models and related methods, the findings show that overall age segregation declined between 1950 and 1990, which is consistent with the decline of age-graded mobility. Among women, though not among men, the findings show increasingly bimodal age distributions in particular low-skill occupations, which is consistent with a dual labor market. Starting in 1990, age segregation increased among men and may have increased among women, which is consistent with the occupational volatility narrative. © 2006 Elsevier Ltd. All rights reserved. Keywords: Age stratification; Age-graded mobility; Occupational segregation
1. Introduction Age, gender, and race/ethnicity have long been regarded as the holy trinity of status distinctions that intersect with, reinforce, and sometimes undercut class-based distinctions (Gurin, Miller, & Gurin, 1980; Parsons, 1942; Wright & Perrone, 1977). However, the vast majority of stratification research has focused on gender or race, and ignored the role of age. This is surprising given that age-based cleavages are seemingly strengthening, that collective action by age-based groupings is on the rise, and that age appears to be an increasingly important determinant of attitudes, lifestyles, and consumption practices (Firey, 2001; Hagestad, 1988; Riley, 1986; Thau & Heflin, 1997). The rise of age consciousness and age-based collective action is especially striking. Age consciousness is
E-mail address: Alair [email protected]. 0276-5624/$ – see front matter © 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.rssm.2005.08.001
hardly new, with young activists warning us, as early as the 1960s, not to trust anyone over 30 years. These activists promoted an overturning of the political status quo, advocating for civil and women’s rights and opposing the war in Vietnam (Smead, 2000). These causes did not, however, explicitly help or hurt the members of any particular age group. In contrast, younger activists born after the sixties have opposed political programs that directly benefit their elders, such as social security and medicare (Thau & Heflin, 1997). Their opposition to these programs implies not just an awareness of the opposing attitudes of people of different ages, but a focus on age itself. Indeed, Americans are increasingly represented by organizations that explicitly advocate for the interests of different age groups. Older Americans are represented by the 35 million-member AARP, which lobbies on issues that affect senior citizens (AARP, 2002). The AARP is opposed by the Third Millennium, a think tank founded in the early 1990s to advance the interests of younger Americans (Firey,
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2001; Freyman & McGoldrick, 2000; Thau & Hildreth, 2001). What accounts for the rise of age-based groupings and collective action? Americans may have become more conscious of age because they spend more time at the beginning and end of life in explicitly age-graded institutions. Younger Americans today spend more time in school (Mare, 1995), where they move from one grade to another based primarily on age. Americans also live longer, spending more years in retirement than in the past. Retirement is also age-graded, commonly beginning when a worker reaches 65 years, though workers increasingly choose “early retirement” (Siegel, 1993). Age stratification theory and research have examined the impact of this age grading (Lawrence, 1996; Riley & Riley, 2000; Riley, 1987; Riley, Johnson, & Foner, 1972; Siegel, 1993). Although there is increasing age segregation at the beginning and end of life, we do not know whether age segregation has increased during the working years. There is, however, a narrative that could account for increases in such segregation. This narrative opens up the possibility that increases in age consciousness and collective action may be attributable, in part, to increases in the importance of age in the workplace. At the same time, a competing narrative suggests possible declines in age segregation. A third, alternative narrative suggests more complicated, multidimensional changes in the structure of age stratification. In the following paper, I adjudicate between these competing narratives. This paper extends research that has examined changes in how age affects work roles, specifically occupations. These previous analyses have been limited to examining trends over 5 years or less (Kaufman & Spilerman, 1982; Smith, 1969, 1973). In contrast, I take a longer-term view, examining changes in occupational age segregation over a 50-year period. I begin by outlining three theories of how larger social forces might affect patterns and trends in occupational age segregation. I then turn to a discussion of new models and methods that can be deployed to test these accounts. Finally, I conclude by presenting and interpreting the results obtained with these models. 2. Occupational volatility The dominant story suggesting that age segregation has increased rests on growing volatility in the occupational structure. If new occupations are constantly emerging and replacing declining ones, different cohorts of labor force entrants will confront dramatically different demand structures, leading in turn to extreme occupa-
tional specialization by cohort (Blossfeld, 1987; DiPrete, 1997; DiPrete, de Graaf, Luijkx, Tahlin, & Blossfeld, 1997; DiPrete & Forristal, 1995). Consequently, when the occupational distribution changes quickly, occupational age segregation will increase. The driving force behind this argument is rapid social and technological change, which brings about structural change in the economy and associated change in the occupational distribution. As the economy evolves, employers recruit workers for different occupations, leading to change in the occupational distribution (Blossfeld, 1987; Hauser, Koffel, Travis, & Dickinson, 1975; Sobek, 1996). Some occupations that did not exist 50 years ago have become important components of the economy. Growing occupations, such as that of computer programmer, are more likely to draw new entrants into the labor force and therefore to be performed by younger workers. Other occupations, such as telegraph operators, have become less important, declining in size. Declining occupations are less likely to attract new, younger workers; and the workers in these occupations will become increasingly older (DiPrete & Forristal, 1995). In both growing and declining occupations, workers therefore should be segregated from each other by age. When there are many changing occupations, workers will tend to be more segregated from each other by age than when there are few changes in the occupational distribution. The ironic conclusion is that a changing economy produces more extreme segregation in the labor force, at least with respect to age. 3. Credentialization By contrast, the story of declining age segregation rests on an account of the growth of the “credential society” (Collins, 1979). In this society, occupational mobility over the life course has declined because: (a) credentials are increasingly required to move into an occupation, and (b) those credentials are not easily secured by workers after their initial entry into the labor force (Blossfeld, 1987; Halaby, 1980, 1994; Hunter, 1988; Lipset & Ray, 1996). There are, of course, multiple routes by which a worker may reach a particular occupation (Blossfeld, 1987; Rosenfeld, 1992; Spilerman, 1977). However, the core argument here is that there is a basic shift in the extent to which employers use worker experience relative to worker education as criteria for hiring and promotion into different occupations. A shift toward education and away from experience should decrease occupational age segregation. This story begins with an ideal–typical representation of the intragenerational mobility process prior to the
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emergence of credentializing forces. In this ideal–typical system, employers promote workers who have gained experience or on-the-job training (Rosenbaum, 1979). For example, an employer with a supervisory opening in a warehouse may promote an employee currently working as a stock clerk. An employer with a junior managerial opening may promote an employee who has completed an on-the-job training program. If mobility between occupations is age-graded in this fashion, some occupations will tend to be performed by middle-aged and older workers who have been promoted into them. Other entry-level occupations will tend to be performed by younger workers. Therefore, occupations will also tend to be characterized by the ages of their incumbents, or age-graded (Kaufman & Spilerman, 1982; Lashbrook, 1996; Smith, 1969, 1973; Spilerman, 1977). This type of age-grading has been especially prominent in Japan (Brinton & Ngo, 1993), but will presumably characterize all stratification systems in which onthe-job training provides the principal route to upward mobility. How would the increasing importance of credentials affect such an ideal-type? As personnel systems become increasingly bureaucratic and formal, with explicit credentials listed as prerequisites for entry into particular occupational lines, the possibility of age-graded mobility declines. For whatever reason, employers come to increasingly value the skills that potential employees learn in school, or they may view schooling as a signal that employees can be trained (Rosenbaum, 1979). This valuing of education leads less educated workers to remain confined to particular occupations regardless of age. More educated workers of all ages will hold other occupations for which an educational credential or other form of certification is required (Hunter, 1988). Occupations allocated in this way will tend to be characterized by their incumbents’ educational levels, rather than age-graded. Consequently, these occupations will tend to be relatively integrated by age. Even when occupations are relatively age integrated, workers of different ages do not necessarily work together. They may still be age segregated into different jobs within an occupational category. For instance, occupational gender segregation has been shown to understate the extent to which men and women are segregated from each other in the workplace (Bielby & Baron, 1986). The core claim, then, is that over the course of the twentieth century, employers came to value experience less and education more (Blossfeld, 1987; DiPrete, 1988; Halaby, 1980, 1994; Hunter, 1988; Lipset & Ray, 1996). Experience continues to affect intra-occupational pro-
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motions and wage mobility, but it no longer enables workers to achieve long-range mobility. This change should, in turn, reduce occupational age segregation. 4. Dual labor markets The rise of the low-skill service sector and of other secondary sector occupations suggests a third possibility regarding trends in age segregation. Dual labor market theory suggests that there are two labor markets: a primary and a secondary one (D’Amico & Brown, 1982; Dickens & Lang, 1985; Doeringer & Piore, 1971; Stolzenberg, 1975; Tigges, 1988). Age segregation should follow two patterns, one for the primary and another for the secondary labor market. In the primary labor market, employers reward more educated workers, yielding a highly credentialized labor market (as described above). Workers are slotted into particular occupational tracks on the basis of their initial educational and vocational credentials. There are, of course, promotion trajectories within the primary sector, but these typically entail changes within, rather than between occupational categories. In this labor market, workers of all ages therefore are employed in the same occupation, as their initial educational levels or qualifications slot them into a particular occupational category. Further mobility merely entails changes in rank or level within that category. The key development within the secondary labor market is the rise of various service sector jobs that recruit simultaneously very young and very old workers (D’Amico & Brown, 1982; Dickens & Lang, 1985; Doeringer & Piore, 1971; Quinn, 1994; Rosenbaum, Kariya, Settersten, & Maier, 1990; Siegel, 1993). These jobs draw upon marginal workers who have not yet completed their schooling, have retired from their main jobs, or are reentering the labor force after protracted absences (because of, for example, childrearing). These marginal workers, who tend to be either old or young, are increasingly clustered in secondary service jobs, such as food service or childcare. The primary sector of the dual labor market has a nearly uniform age distribution, while the secondary sector has an increasingly bimodal age distribution. Though the dual labor market should affect the entire economy, the key changes will occur in the secondary market. These three narratives concerning change in occupational age segregation have not previously been tested. In the following paper, I examine how occupational age segregation has changed, and assess how these changes correspond with the predictions of the narratives.
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5. Materials and methods 5.1. Data The data used in the following analyses are drawn from the 1950 to 2000 censuses. I use the one percent samples, accessed through the Integrated Public Use Microdata Series (IPUMS) (Ruggles et al., 2004). The sample is limited to whites to avoid confusing race with age segregation, as it is well-known that workers of different races are segregated into different occupational categories (Fossett, 1984). Research has also extensively documented occupational sex segregation (Jacobs, 1989; Reskin, 1993; Weeden, 1998). Therefore, I conduct the analyses separately for men and for women. The sample is restricted, finally, to individuals currently employed at the time of the census. Age is divided into categories. In the preferred categorization, employed workers are grouped into five groups: 20-year olds (20–29 years); 30-year olds (30–39 years); 40-year olds (40–49 years); 50-year olds (50–59 years); 60-year olds (60–69 years). Parameter estimates from the best-fitting model using these categories are reported. However, several of the log-multiplicative models fail to converge using the five-category age categorization, as some sectors of the table are quite sparse Therefore, the comparison of fit statistics reported below is based on models using a less refined categorization, one with four categories: younger than 30 years; 30–39 years; 40–49 years; and 50 years or older. Occupations for all census years are recoded into the categories from 1950. This strategy allows a test of the hypothesis that occupational age segregation did not change. In addition, it avoids overestimating increases in age segregation that are due to increases in precision. In several years, the Census Bureau introduced occupational definitions that were different and more precise than those used in previous years. In 1950, the census contained 269 detailed occupational categories. By 2000 this number had grown to 539. In 1950, census bureau coders classified many workers as performing unclassified professional and technical occupations. By 2000, they might classify such workers in more detailed occupations, such as human resources managers or human resources specialists. On an average, human resources managers are one and a half years older than human resources specialists. Therefore, workers would look more age segregated from each other in the 2000 than in the 1950 census if the occupational categorizations from each year were used. The observed increase would stem solely from the increased precision of the census categories. In addition, the use of a constant
coding scheme should be more likely to lead to the conclusion that segregation patterns have not changed. Therefore, patterns that do appear are less likely to result from idiosyncratic features of the different coding schemes. For the assessment of long-term trends, then, a scheme using constant occupational categories is superior to one that allows the occupational categories to vary by year. The disadvantage of using the 1950 categories is that they do not capture increases in age segregation due to the rise and fall of particular occupations. Some of the new occupations in 2000 represent not just increasing precision on the part of the census, but the addition of new kinds of work. As mentioned above, new or growing occupations will tend to be performed by younger workers. For instance, the 1950 census included neither the computer systems analysts and scientists nor the computer programmers categories. By 2000, slightly more than 1% of workers were in these occupations. Using the 1950 classification scheme, the bulk of these computer workers would be classified as working as either accountants and auditors or unclassified professional and technical workers. These categories therefore would look more age integrated than if the computer categories were included. Models using the 1950 occupational categories therefore may understate the extent of age segregation in later years. In order to test whether the results are driven by the use of the 1950 categorization, I also estimate models that allow more limited comparisons between adjacent census years. I compare the 1950 and 1960 census years to one another using the 1950 occupational categorization. I compare the 1960 and 1970 censuses to each other using the detailed 1960 categorization. I compare the 1970, 1980 and 1990 censuses using the detailed 1980 occupational categorization. Finally, I compare the 1990–2000 censuses using an intermediate classification based on the occupation codes from the 2000 census. This allows me to compare the trends assessed with the single 1950 categorization to those with more nearly contemporaneous classification schemes. Within the 1950 occupational classification scheme, I use a series of intermediate categories, developed by the Census and based on the most detailed categorization (U.S. Bureau of the Census, 1953). Because of occupational sex segregation, these intermediate schemes differ by gender. The male intermediate occupational classification has 95 occupational categories, and the female intermediate occupational classification has 48 categories. (Translation of detailed into intermediate occupational classifications available on request.)
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5.2. Methods To test the hypotheses regarding change in occupational segregation, I estimate a series of logmultiplicative models (Agresti, 1990). These models expand on those used to measure occupational sex and race segregation (Charles & Grusky, 1995; Grusky & Pager, 1999; Weeden, 1998). The most unconstrained model describes age segregation in two dimensions, thus allowing a test of the hypothesis that the structure of age segregation differs across two labor markets. This model (Model D) is based on the following equation: mijk = αk βik γjk e(φk μik υjk )+(θk ωik ηjk )
(1)
In this model, mijk is the expected frequency in the ijkth cell, the value in the cell for the ith age group in the jth occupation at the kth time period. The subscript i indexes the five age groups (20–29 years; 30–39 years; 40–49 years; 50–59 years; 60–69 years), and j indexes the J occupations. The total number of occupations, as described above, is different for men and for women. Finally, k indexes the six time periods (1950–2000). Within the model, αk represents the main effect in the kth time period, βik is the time-specific marginal effect for the ith age group, and γ jk is the time-specific marginal effect in the jth occupation. The model also provides estimates of the following association parameters: φk , θ k , μik , ωik , υjk , and ηjk . The main parameters of interest are φk and θ k , as these describe the extent of overall age segregation in each of two, orthogonal dimensions for each of the k = 6 time periods. The parameters take on lower values when workers are not highly age segregated. Therefore, the values decrease from one period to the next when age segregation decreases. When the different occupational categorizations described above are used, the values of the global age segregation parameters differ depending on the number of occupational categories. Therefore, to construct a trend that covers the whole period, I calculate segregation index values for years after 1950 by calculating each year’s segregation parameter as a percent of the previous year’s value. For instance, I calculate the value of the 1970 parameter as a percent of the 1960 parameter when both are based on the 1960 coding scheme. Likewise, I compare the 1960 parameter to the 1950 parameter when both are calculated using categories from 1950. The 1970 parameter can then be compared to the 1950 parameter. The occupation scale parameters, υjk , and ηjk , reveal the extent and direction of segregation within each occupation (and with respect to each dimension). These parameters take on a different value for each of the
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j occupations and each of the six time periods and are orthogonal to one another. They are constrained to have a variance of one and a mean of zero within each time period. If an occupation scale parameter is large, it implies that the occupation is strongly segregated in terms of the age scale values pertaining to that dimension. We might therefore refer to a “stretching out” of that dimension. At the other extreme, a value of zero implies that there is no segregation with respect to that dimension, and segregation will instead be governed by the patterning of age scale values in the other dimension. These parameters are allowed to vary across the five time periods. The age scale parameters, μik and ωik , characterize the particular combination of age groups that prevail in each dimension. If, for example, a linear age scale emerges in a given dimension, then workers’ representation increases or diminishes with age within particular occupations. The sign of the corresponding occupation scale value determines which age groups are represented in that occupation. By contrast, a U-shaped scaling implies a bimodal distribution, with young and old workers either over- or under-represented. Again, the sign of the corresponding occupation scale value determines whether that particular occupation comprises mainly young and old workers or, alternatively, mainly middle-aged workers. Like the occupation scale parameters, these parameters are constrained to have a variance of one and a mean of zero within each time period and are orthogonal to each other. I estimate three other models using a variety of constraints. The most constrained model contains one dimension and does not allow any of the parameters to change over time. This model (Model A) may be represented as follows: mijk = αk βik γjk e(φμi υj )
(2)
Under this formulation, there is only one dimension governing age segregation, and the parameters pertaining to that dimension are all constant over time. Subsequent models relax these constraints. Model B allows a test of change in overall age segregation with φ varying over time. Model C allows the scaling of age categories, μi , and the segregation particular to occupations, υj , to vary over time. I use standard Chi-square comparisons and BIC statistics to choose the best-fitting model (Raftery, 1995). The following section examines what the three preceding narratives imply about the type of model that will be preferred. The predictions of the three narratives are summarized in Table 1.
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Table 1 Predicted characteristics of occupational age segregation Credentialization
Occupational volatility
Dual labor market
Number of dimensions
One
Two
Two
Trend in segregation First dimension Second dimension
Weaken –
Strengthen Strengthen
Stable or weaken Strengthen
5.2.1. Occupational volatility Consider, first, the consequences of occupational volatility. Many occupations will have an age profile that reflects the period when they emerged or expanded and hence disproportionately attracted new entrants. This initial cohort representation will be retained as workers age with the occupation. Occupations that recently expanded will be performed by younger workers, while those that expanded long ago will be performed by older workers. These occupations can be adequately characterized by a linear, one-dimensional scaling for the age categories. However, some occupations will have principally middle-aged incumbents because of the timing of their emergence or expansion. They would not be well-characterized by a linear, one-dimensional scaling. It follows that a two-dimensional model will likely be needed under this formulation. Moreover, one would expect overall age segregation to be increasing over time, as growing turnover should create ever-more occupations with a distinctive “age stamp.” This increase will be reflected in the parameters φk and θ k .
in the past emphasized on-the-job training and experience rather than formal credentials. Workers progressed through sequences of occupations as they gained experience, without having to secure formal credentials outside the labor market. Some occupations were points of entry for newcomers, while others were restricted to older workers with the requisite experience. Age segregation should be substantial (that is, a large φ), but could be characterized with a one-dimensional formulation with roughly linear age scale values. If the forces of credentialization then play out, this should be revealed as a decline in age segregation, in other words, a decline in φ. 5.2.3. Dual labor markets This narrative implies that an increasing number of service occupations are filled simultaneously by young and old workers, implying a two-dimensional specification. The second-dimension of this model will presumably show up in the form of U-shaped age parameters. The peripheralized service occupations will have large occupation scale values on the second dimension, implying that recruitment is principally governed by this U-shaped dimension. This narrative implies that such second-dimension segregation is strengthening over time (that is, θ k is increasing).
5.2.2. Credentialization Recall our ideal–typical representation of intragenerational mobility processes prior to the emergence of credentialization. The claim here was that employers Table 2 Fit statistics for models of occupational age segregation, 1950–2000 Men
Women
L2
d.f.
D
BIC
L2
d.f.
D
BIC
One-dimensional models (A) Baseline model (B) A + overall segregation varies (C) B + age and occupation parameters vary
97,298 96,765 57,487
1596 1591 1116
6.31 6.31 4.60
73,487 73,030 40,838
64,818 63,745 26,941
797 792 552
6.64 6.54 3.89
53,285 52,284 18,953
Two-dimensional model (D) All parameters vary
4005
552
1.01
−4230
2441
270
1.02
L2
d.f. 4 475 564
BIC −457 −32,192 −45,068
L2
d.f. 5 240 282
Contrasts Period effects (Model B-A) Age and occupation effects (Model C-B) Effect of two dimensions (Model D-C)
−533 −39,278
Source: Author’s calculations of model fit using census data.
% of 0.01 0.41
L2
−1073 −36,804
% of 0.02 0.58
−1466 L2
BIC −1001 −33,331 −20,419
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6. Findings Table 2 presents fit statistics from models estimated among both men and women. In model A, occupational age segregation is described in one-dimension, with no change in overall segregation, occupation and age scale parameters. In subsequent models, the parameters are allowed to vary over time. The best-fitting model among both men and women is model D, which introduces a second dimension. This model allows changes in both dimensions governing age segregation. As described above, two dimensions of age segregation may be a result of either dual labor markets or of occupational volatility. Below, I look more closely at the occupational changes to determine which narrative is more consistent with the results. 6.1. Trends in overall segregation Fig. 1 shows the trends in occupational age segregation among male and female workers from the bestfitting model. The census year 1950 dimension 1 value for each gender is set as the base value for that gender, and the values of the dimension 2 scale factors and dimension 1 scale factors for subsequent years are shown as a share of that 1950 dimension 1 value. The solid lines trace the trends estimated using the constant 1950 coding scheme. The dashed lines show the trends when the models are estimated using the 1950, 1960, 1980 and 2000 occupational codes (as described above). The overall trend in occupational age segregation is affected somewhat by the choice of coding scheme (described below). According to the results from the best-fitting model (Model D), occupational age segregation in the first dimension declined between 1950 and 1990 among both women and men, as predicted by the credentialization
Fig. 1. Age segregation in two dimensions, 1950–2000.
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narrative. Among women, the direction of the trend after 1990 depends on the occupational categorization used. When the 1950 categorization is used, female workers appear less age segregated at the end of the period than at the beginning. Thus, in the first dimension, workers of each age group were more often employed in occupations performed by workers of other age groups in 1990 (or perhaps 2000) than they were at the beginning. According to the credentialization argument, they were more likely recruited to these positions based not on their experience, but on their initial credentials. Recall that neither the dual labor market nor occupational volatility narratives suggested that age segregation would decline, but rather that it would remain stable or increase. Starting in 1990, however, occupational age segregation among male and perhaps female workers increased. In 2000, male workers were at least as segregated by age as they were in 1950. If the 2000 occupational categorization is used, age segregation also appears to have increased between 1990 and 2000 among women workers. This suggests that occupational volatility may have caused an increase in occupational age segregation in the last decade of the twentieth century. 6.2. Changes in occupational age profiles differ by gender As described above, the best-fitting model describes two dimensions, which is consistent with both the dual labor market and occupational volatility narratives. Both narratives predict that second dimension age segregation would strengthen. However, age segregation in this dimension remained relatively stable. In order to determine which narrative is more consistent with the results, I look more closely at change within particular occupations. The dual labor market narrative suggests service and other low-skill occupations should have increasingly bimodal age distributions. The trends in occupational age profiles correspond with this prediction. Occupational age profiles are determined by a combination of the occupation scale values in both dimensions with reference to the corresponding age scale values. Fig. 2 shows the age segregation patterns among women and men at the beginning and end of the period in the first dimension. The patterns of the age scale values are consistent across time. This dimension was characterized by a linear age scale. According to this scale, workers of each age group were less occupationally segregated from those closer in age than they were from those more distant in age. For instance, 20-year old workers were less likely to work in occupations performed by 40-year old workers than in those performed by 30-
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Fig. 2. Age segregation in dimension 1, 1950 and 2000.
Fig. 3. Age segregation in dimension 2, 1950 and 2000.
year old workers. In the second dimension, shown in Fig. 3, workers were segregated according to a U-shaped age scale. In this dimension, young and old workers were more likely to be employed in the same occu-
pations than in occupations performed by middle-aged workers. Based on these age patterns, the sign of an occupation scale value determines the occupation’s age pattern in each dimension. For instance, young workers would be over-represented in the first dimension in an occupation with a negative scale value. Middle-aged workers would be over-represented in an occupation with a negative scale value in the second dimension. In either dimension, occupations with near-zero scale values would be integrated. One can combine the occupation scale values in each dimension to determine that occupation’s overall age profile. For instance, an occupation with a near zero value in the first dimension and a positive value in the second dimension would have a bimodal age distribution, combining young and old workers. To see if the results are consistent with the dual labor market narrative, I examine occupation scale values in the second dimension for those occupations that are integrated in the first dimension. Fig. 4 shows the mean occupational scale values in the second dimension for aggregate occupational categories in both 1950 and 2000. The numerical values are translated into the following categories: middle-aged, integrated, and bimodal. As shown in Fig. 4, among women, the clerical, sales, and service worker occupations were more likely to have bimodal age distributions in 2000 than in 1950. This finding is consistent with the dual labor market narrative. However, among men, the laborer, clerical, and service occupations became slightly less likely to employ a combination of young and old workers. In 1950, occupations in this cat-
Fig. 4. Second dimension occupation scale values in 1950 and 2000.
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egory tended to exhibit bimodal age distributions. By 2000, they were slightly more integrated in the second dimension. Thus, age segregation among men appears not to have been shaped by an increasingly bimodal age distribution in the secondary labor market. 6.3. Effect of the coding scheme Between 1950 and 1990, the choice of occupational coding scheme does not have a large effect on the parameter estimates of the extent of age segregation shown in Fig. 1. However, between 1990 and 2000, the trend in dimension 1 age segregation estimated with the 1950 codes differs from that estimated with the 2000 codes. The 1950 occupational codes may understate the extent of occupational age segregation in 2000. Among men, this understatement affects the strength of the trend in age segregation, while among women, it affects the direction of the trend. Men may have experienced a greater increase in occupational age segregation than revealed by the 1950 codes. Women may have become more, rather than less age segregated. The occupation scale values show that the 1950 occupational codes may understate occupational age segregation because they do not capture the addition of new work. Fig. 5 shows occupation scale values in the first dimension for 1990 and 2000. These values are based on the intermediate occupational categorization derived from the 2000 census. The left panel shows the occu-
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pation scale values for women, ordered based on their values in the 2000 census. The right panel shows the occupations in the same order, but this time with the occupation scale values for men. This provides some evidence that age segregation increased among women in part because younger female workers can now work in occupations that have traditionally been performed by male workers. For instance, the aircraft and architect occupations became increasingly dominated by young women. As would be expected from the growth of the high tech industry in the nineties, the computer and math occupations have increasingly drawn both younger male and female workers. Thus, the 1950 codes with their reliance on the prevailing gender segregation of that era do not capture age segregation that came about as occupations became open to women, drawing in younger workers. Nor do they capture changes in age segregation due to the addition or expansion of occupations such as computer programmers that represent new work. 7. Discussion Age continues to be an important status distinction alongside race and sex, with ramifications for the occupations that individuals perform. After 40 years of decline, occupational age segregation began to rise again at the end of the twentieth century. Between 1950 and 1990, male and female workers became less age segregated. This finding is con-
Fig. 5. First dimension occupation scale values in 1990 and 2000.
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sistent with a decline in age-graded mobility stemming from credentialization. The credentialization narrative described a transition from a system in which individuals advance through a sequence of occupations based on the experience that they accumulate as they age. According to the narrative, this age-graded system was eroded in favor of another system in which individuals enter, and remain in, occupations based on initial credentials. Individuals of one age became more likely to work in occupations alongside individuals of other ages. This was the only one of the initial three narratives that predicted declining occupational age segregation. Indeed, in the best-fitting model, occupational age segregation declined by 20–40% between 1950 and 1990. The credentialization narrative also predicted that there would be only one dimension governing occupational age segregation. However, the preferred model contained two dimensions, suggesting at least partial support for either the dual labor market or occupational volatility narrative. Throughout the last half of the twentieth century, age segregation is best described as having a linear and a bimodal dimension. The decline in linear segregation suggests that changes in the primary sector may reflect declining age-graded mobility. In the second dimension, young and old workers performed the same occupations. The dual labor markets narrative suggested that service occupations, in particular, would increasingly exhibit bimodal age distributions. Women workers did experience increasingly bimodal age distributions in a variety of occupations, including service occupations. In 1950, middle-aged women were more likely to work in these occupations, while in the year 2000, a combination of younger and older women worked in these occupations. However, among men, service occupations were less likely to exhibit such bimodal age distributions in 2000 than in 1950. Starting in 1990, age segregation in the first dimension increased among men and may have increased among women. By 2000, male, and perhaps female, workers were at least as occupationally age segregated as they had been in the year 1950. As mentioned above, individuals are increasingly age segregated at school, and in retirement. Thus, among men and possibly among women, this increased age segregation before and after the work life has been accompanied by relative increases in age segregation at work. The increase in age segregation is consistent with the occupational volatility narrative. This narrative suggested that as employers add new occupations, members of different cohorts confront different occupational choices. New or expanding occupations should be performed by younger workers. However, though the level of occupational age segre-
gation may be the same as in the 1950s, the source is different. In the 1950s, such segregation stemmed from age-graded mobility, which meant that members of different cohorts could anticipate aging in the same way. Today, when age segregation is based on occupational volatility, the members of different cohorts will have different experiences of aging. The possible increase in female occupational age segregation suggests that age segregation may be affected by changes in gender segregation. Women workers may experience a gender-specific form of occupational volatility. Recall that the 1950 occupational categorizations were gender-specific intermediate categorizations based on the distribution of workers in 1950. Thus, these categorizations rely on the assumption that the genderspecific distributions remained roughly similar across the 50-year period. This assumption is more tenable among men than among women. Women may confront a new set of occupational choices when occupations that have traditionally been performed by male workers shift to become less gender segregated. When this shift happens, young women in particular can make different choices than were available to middle-aged and older women. More generally, occupational age segregation may be affected by changes in the occupational segregation of groups defined by other status characteristics, such as race/ethnicity. Exploring the relationship between occupational age segregation and other forms of occupational segregation presents a promising avenue for future research. The increased age structuring of society has important ramifications for the kinds of activities that individuals do at particular points in their lives. Today, the primary membership organization representing older Americans has two times as many members as the all the unions in the United States. Its sphere of influence extends from traditional areas such as the policy debates about social security to less traditional partnerships that encourage businesses to hire older workers. The recent increase in occupational age segregation may stem from and contribute to increases in such age-based advocacy. Acknowledgments Support for this research was provided by the National Institute on Aging (T32-AG00129), the National Science Foundation (SBR-9320660), the Wisconsin Alumni Research Foundation, and the Center for Demography and Ecology at the University of Wisconsin-Madison. I thank Charles N. Halaby, Michael Hout, and Lincoln Quillian for helpful comments on different versions of the paper. I am especially grateful for the advice and
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help of David B. Grusky and Robert M. Hauser. This is a revised version of a paper prepared for presentation at the 2000 Meetings of the American Sociological Association, Washington, DC. The opinions expressed herein are those of the author. Address correspondence to Alair MacLean, Washington State University Vancouver, 14204 NE Salmon Creek Avenue, Vancouver, WA 98686. References AARP (2002). AARP History. http://www.aarp.org/about aarp/aarp overview/a2003-01-13-aarphistory.html. Agresti, A. (1990). Categorical data analysis. New York, NY: John Wiley & Sons. Bielby, W. T., & Baron, J. N. (1986). Men and women at work—sex segregation and statistical discrimination. American Journal of Sociology, 91, 759–799. Blossfeld, H.-P. (1987). Entry into the labor market and occupational career in the Federal Republic: A comparison with American Studies. In W. Teckenberg (Ed.), Comparative studies of social structure: Recent research on France, the United States, and the Federal Republic of Germany (pp. 86–115). Armonck, NY: M.E. Sharpe. Brinton, M. C., & Ngo, H.-Y. (1993). Age and sex in the occupational structure: A United States–Japan comparison. Sociological Forum, 8, 93–111. Charles, M., & Grusky, D. (1995). Models for describing the underlying structure of sex segregation. American Journal of Sociology, 100, 931–971. Collins, R. (1979). The credential society: An historical sociology of education and stratification. New York: Academic Press. D’Amico, R., & Brown, T. (1982). Patterns of labor mobility in a dual economy: The case of semiskilled and unskilled workers. Social Science Research, 11, 153–175. Dickens, W. T., & Lang, K. (1985). A test of dual labor market theory. American Economic Review, 75, 792–805. DiPrete, T. A. (1988). The upgrading and downgrading of occupations: Status redefinition vs. deskilling as alternative theories of change. Social Forces, 66, 725–746. DiPrete, T. A. (1997). Structural change, labor market turbulence, and labor market outcomes. American Sociological Review, 62, 386–404. DiPrete, T. A., de Graaf, P. M., Luijkx, R., Tahlin, M., & Blossfeld, H.-P. (1997). Collectivist versus individualist mobility regimes? Structural change and job mobility in four countries. American Journal of Sociology, 103, 318–358. DiPrete, T. A., & Forristal, J. D. (1995). Socioeconomic change and occupational location for successive cohorts of American male and female workers. Social Science Research, 24, 390–438. Doeringer, P. B., & Piore, M. J. (1971). Internal labor markets and manpower analysis. Lexington, Mass: Heath. Firey, T. A. (2001). Social security’s inequities. Milwaukee Journal Sentinel (p. 9A). Milwaukee. Fossett, M. A. (1984). City differences in racial occupational differentiation: A note on the use of odds ratios. Demography, 21, 655– 671. Freyman, R., & McGoldrick, B. (2000). They pretend to talk to us, we pretend to vote: Candidates and young adults in campaign 2000 and beyond. New York, NY: Third Millennium.
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Age stratification at work: Trends in occupational age segregation in the United States, 1950–2000 Alair MacLean Washington State University Vancouver, 14204 NE Salmon Creek Avenue, Vancouver, WA 98686, United States Received 22 November 2004; received in revised form 3 June 2005; accepted 20 August 2005
Abstract This paper adjudicates between competing accounts of recent trends in the amount and patterning of occupational age segregation. These accounts rely on narratives about: (1) the decline of age-graded mobility, (2) the rise of occupational volatility, and (3) the existence of dual labor markets, in particular increasingly bimodal age distributions in low-skill occupations. Using new logmultiplicative models and related methods, the findings show that overall age segregation declined between 1950 and 1990, which is consistent with the decline of age-graded mobility. Among women, though not among men, the findings show increasingly bimodal age distributions in particular low-skill occupations, which is consistent with a dual labor market. Starting in 1990, age segregation increased among men and may have increased among women, which is consistent with the occupational volatility narrative. © 2006 Elsevier Ltd. All rights reserved. Keywords: Age stratification; Age-graded mobility; Occupational segregation
1. Introduction Age, gender, and race/ethnicity have long been regarded as the holy trinity of status distinctions that intersect with, reinforce, and sometimes undercut class-based distinctions (Gurin, Miller, & Gurin, 1980; Parsons, 1942; Wright & Perrone, 1977). However, the vast majority of stratification research has focused on gender or race, and ignored the role of age. This is surprising given that age-based cleavages are seemingly strengthening, that collective action by age-based groupings is on the rise, and that age appears to be an increasingly important determinant of attitudes, lifestyles, and consumption practices (Firey, 2001; Hagestad, 1988; Riley, 1986; Thau & Heflin, 1997). The rise of age consciousness and age-based collective action is especially striking. Age consciousness is
E-mail address: Alair [email protected]. 0276-5624/$ – see front matter © 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.rssm.2005.08.001
hardly new, with young activists warning us, as early as the 1960s, not to trust anyone over 30 years. These activists promoted an overturning of the political status quo, advocating for civil and women’s rights and opposing the war in Vietnam (Smead, 2000). These causes did not, however, explicitly help or hurt the members of any particular age group. In contrast, younger activists born after the sixties have opposed political programs that directly benefit their elders, such as social security and medicare (Thau & Heflin, 1997). Their opposition to these programs implies not just an awareness of the opposing attitudes of people of different ages, but a focus on age itself. Indeed, Americans are increasingly represented by organizations that explicitly advocate for the interests of different age groups. Older Americans are represented by the 35 million-member AARP, which lobbies on issues that affect senior citizens (AARP, 2002). The AARP is opposed by the Third Millennium, a think tank founded in the early 1990s to advance the interests of younger Americans (Firey,
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2001; Freyman & McGoldrick, 2000; Thau & Hildreth, 2001). What accounts for the rise of age-based groupings and collective action? Americans may have become more conscious of age because they spend more time at the beginning and end of life in explicitly age-graded institutions. Younger Americans today spend more time in school (Mare, 1995), where they move from one grade to another based primarily on age. Americans also live longer, spending more years in retirement than in the past. Retirement is also age-graded, commonly beginning when a worker reaches 65 years, though workers increasingly choose “early retirement” (Siegel, 1993). Age stratification theory and research have examined the impact of this age grading (Lawrence, 1996; Riley & Riley, 2000; Riley, 1987; Riley, Johnson, & Foner, 1972; Siegel, 1993). Although there is increasing age segregation at the beginning and end of life, we do not know whether age segregation has increased during the working years. There is, however, a narrative that could account for increases in such segregation. This narrative opens up the possibility that increases in age consciousness and collective action may be attributable, in part, to increases in the importance of age in the workplace. At the same time, a competing narrative suggests possible declines in age segregation. A third, alternative narrative suggests more complicated, multidimensional changes in the structure of age stratification. In the following paper, I adjudicate between these competing narratives. This paper extends research that has examined changes in how age affects work roles, specifically occupations. These previous analyses have been limited to examining trends over 5 years or less (Kaufman & Spilerman, 1982; Smith, 1969, 1973). In contrast, I take a longer-term view, examining changes in occupational age segregation over a 50-year period. I begin by outlining three theories of how larger social forces might affect patterns and trends in occupational age segregation. I then turn to a discussion of new models and methods that can be deployed to test these accounts. Finally, I conclude by presenting and interpreting the results obtained with these models. 2. Occupational volatility The dominant story suggesting that age segregation has increased rests on growing volatility in the occupational structure. If new occupations are constantly emerging and replacing declining ones, different cohorts of labor force entrants will confront dramatically different demand structures, leading in turn to extreme occupa-
tional specialization by cohort (Blossfeld, 1987; DiPrete, 1997; DiPrete, de Graaf, Luijkx, Tahlin, & Blossfeld, 1997; DiPrete & Forristal, 1995). Consequently, when the occupational distribution changes quickly, occupational age segregation will increase. The driving force behind this argument is rapid social and technological change, which brings about structural change in the economy and associated change in the occupational distribution. As the economy evolves, employers recruit workers for different occupations, leading to change in the occupational distribution (Blossfeld, 1987; Hauser, Koffel, Travis, & Dickinson, 1975; Sobek, 1996). Some occupations that did not exist 50 years ago have become important components of the economy. Growing occupations, such as that of computer programmer, are more likely to draw new entrants into the labor force and therefore to be performed by younger workers. Other occupations, such as telegraph operators, have become less important, declining in size. Declining occupations are less likely to attract new, younger workers; and the workers in these occupations will become increasingly older (DiPrete & Forristal, 1995). In both growing and declining occupations, workers therefore should be segregated from each other by age. When there are many changing occupations, workers will tend to be more segregated from each other by age than when there are few changes in the occupational distribution. The ironic conclusion is that a changing economy produces more extreme segregation in the labor force, at least with respect to age. 3. Credentialization By contrast, the story of declining age segregation rests on an account of the growth of the “credential society” (Collins, 1979). In this society, occupational mobility over the life course has declined because: (a) credentials are increasingly required to move into an occupation, and (b) those credentials are not easily secured by workers after their initial entry into the labor force (Blossfeld, 1987; Halaby, 1980, 1994; Hunter, 1988; Lipset & Ray, 1996). There are, of course, multiple routes by which a worker may reach a particular occupation (Blossfeld, 1987; Rosenfeld, 1992; Spilerman, 1977). However, the core argument here is that there is a basic shift in the extent to which employers use worker experience relative to worker education as criteria for hiring and promotion into different occupations. A shift toward education and away from experience should decrease occupational age segregation. This story begins with an ideal–typical representation of the intragenerational mobility process prior to the
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emergence of credentializing forces. In this ideal–typical system, employers promote workers who have gained experience or on-the-job training (Rosenbaum, 1979). For example, an employer with a supervisory opening in a warehouse may promote an employee currently working as a stock clerk. An employer with a junior managerial opening may promote an employee who has completed an on-the-job training program. If mobility between occupations is age-graded in this fashion, some occupations will tend to be performed by middle-aged and older workers who have been promoted into them. Other entry-level occupations will tend to be performed by younger workers. Therefore, occupations will also tend to be characterized by the ages of their incumbents, or age-graded (Kaufman & Spilerman, 1982; Lashbrook, 1996; Smith, 1969, 1973; Spilerman, 1977). This type of age-grading has been especially prominent in Japan (Brinton & Ngo, 1993), but will presumably characterize all stratification systems in which onthe-job training provides the principal route to upward mobility. How would the increasing importance of credentials affect such an ideal-type? As personnel systems become increasingly bureaucratic and formal, with explicit credentials listed as prerequisites for entry into particular occupational lines, the possibility of age-graded mobility declines. For whatever reason, employers come to increasingly value the skills that potential employees learn in school, or they may view schooling as a signal that employees can be trained (Rosenbaum, 1979). This valuing of education leads less educated workers to remain confined to particular occupations regardless of age. More educated workers of all ages will hold other occupations for which an educational credential or other form of certification is required (Hunter, 1988). Occupations allocated in this way will tend to be characterized by their incumbents’ educational levels, rather than age-graded. Consequently, these occupations will tend to be relatively integrated by age. Even when occupations are relatively age integrated, workers of different ages do not necessarily work together. They may still be age segregated into different jobs within an occupational category. For instance, occupational gender segregation has been shown to understate the extent to which men and women are segregated from each other in the workplace (Bielby & Baron, 1986). The core claim, then, is that over the course of the twentieth century, employers came to value experience less and education more (Blossfeld, 1987; DiPrete, 1988; Halaby, 1980, 1994; Hunter, 1988; Lipset & Ray, 1996). Experience continues to affect intra-occupational pro-
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motions and wage mobility, but it no longer enables workers to achieve long-range mobility. This change should, in turn, reduce occupational age segregation. 4. Dual labor markets The rise of the low-skill service sector and of other secondary sector occupations suggests a third possibility regarding trends in age segregation. Dual labor market theory suggests that there are two labor markets: a primary and a secondary one (D’Amico & Brown, 1982; Dickens & Lang, 1985; Doeringer & Piore, 1971; Stolzenberg, 1975; Tigges, 1988). Age segregation should follow two patterns, one for the primary and another for the secondary labor market. In the primary labor market, employers reward more educated workers, yielding a highly credentialized labor market (as described above). Workers are slotted into particular occupational tracks on the basis of their initial educational and vocational credentials. There are, of course, promotion trajectories within the primary sector, but these typically entail changes within, rather than between occupational categories. In this labor market, workers of all ages therefore are employed in the same occupation, as their initial educational levels or qualifications slot them into a particular occupational category. Further mobility merely entails changes in rank or level within that category. The key development within the secondary labor market is the rise of various service sector jobs that recruit simultaneously very young and very old workers (D’Amico & Brown, 1982; Dickens & Lang, 1985; Doeringer & Piore, 1971; Quinn, 1994; Rosenbaum, Kariya, Settersten, & Maier, 1990; Siegel, 1993). These jobs draw upon marginal workers who have not yet completed their schooling, have retired from their main jobs, or are reentering the labor force after protracted absences (because of, for example, childrearing). These marginal workers, who tend to be either old or young, are increasingly clustered in secondary service jobs, such as food service or childcare. The primary sector of the dual labor market has a nearly uniform age distribution, while the secondary sector has an increasingly bimodal age distribution. Though the dual labor market should affect the entire economy, the key changes will occur in the secondary market. These three narratives concerning change in occupational age segregation have not previously been tested. In the following paper, I examine how occupational age segregation has changed, and assess how these changes correspond with the predictions of the narratives.
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5. Materials and methods 5.1. Data The data used in the following analyses are drawn from the 1950 to 2000 censuses. I use the one percent samples, accessed through the Integrated Public Use Microdata Series (IPUMS) (Ruggles et al., 2004). The sample is limited to whites to avoid confusing race with age segregation, as it is well-known that workers of different races are segregated into different occupational categories (Fossett, 1984). Research has also extensively documented occupational sex segregation (Jacobs, 1989; Reskin, 1993; Weeden, 1998). Therefore, I conduct the analyses separately for men and for women. The sample is restricted, finally, to individuals currently employed at the time of the census. Age is divided into categories. In the preferred categorization, employed workers are grouped into five groups: 20-year olds (20–29 years); 30-year olds (30–39 years); 40-year olds (40–49 years); 50-year olds (50–59 years); 60-year olds (60–69 years). Parameter estimates from the best-fitting model using these categories are reported. However, several of the log-multiplicative models fail to converge using the five-category age categorization, as some sectors of the table are quite sparse Therefore, the comparison of fit statistics reported below is based on models using a less refined categorization, one with four categories: younger than 30 years; 30–39 years; 40–49 years; and 50 years or older. Occupations for all census years are recoded into the categories from 1950. This strategy allows a test of the hypothesis that occupational age segregation did not change. In addition, it avoids overestimating increases in age segregation that are due to increases in precision. In several years, the Census Bureau introduced occupational definitions that were different and more precise than those used in previous years. In 1950, the census contained 269 detailed occupational categories. By 2000 this number had grown to 539. In 1950, census bureau coders classified many workers as performing unclassified professional and technical occupations. By 2000, they might classify such workers in more detailed occupations, such as human resources managers or human resources specialists. On an average, human resources managers are one and a half years older than human resources specialists. Therefore, workers would look more age segregated from each other in the 2000 than in the 1950 census if the occupational categorizations from each year were used. The observed increase would stem solely from the increased precision of the census categories. In addition, the use of a constant
coding scheme should be more likely to lead to the conclusion that segregation patterns have not changed. Therefore, patterns that do appear are less likely to result from idiosyncratic features of the different coding schemes. For the assessment of long-term trends, then, a scheme using constant occupational categories is superior to one that allows the occupational categories to vary by year. The disadvantage of using the 1950 categories is that they do not capture increases in age segregation due to the rise and fall of particular occupations. Some of the new occupations in 2000 represent not just increasing precision on the part of the census, but the addition of new kinds of work. As mentioned above, new or growing occupations will tend to be performed by younger workers. For instance, the 1950 census included neither the computer systems analysts and scientists nor the computer programmers categories. By 2000, slightly more than 1% of workers were in these occupations. Using the 1950 classification scheme, the bulk of these computer workers would be classified as working as either accountants and auditors or unclassified professional and technical workers. These categories therefore would look more age integrated than if the computer categories were included. Models using the 1950 occupational categories therefore may understate the extent of age segregation in later years. In order to test whether the results are driven by the use of the 1950 categorization, I also estimate models that allow more limited comparisons between adjacent census years. I compare the 1950 and 1960 census years to one another using the 1950 occupational categorization. I compare the 1960 and 1970 censuses to each other using the detailed 1960 categorization. I compare the 1970, 1980 and 1990 censuses using the detailed 1980 occupational categorization. Finally, I compare the 1990–2000 censuses using an intermediate classification based on the occupation codes from the 2000 census. This allows me to compare the trends assessed with the single 1950 categorization to those with more nearly contemporaneous classification schemes. Within the 1950 occupational classification scheme, I use a series of intermediate categories, developed by the Census and based on the most detailed categorization (U.S. Bureau of the Census, 1953). Because of occupational sex segregation, these intermediate schemes differ by gender. The male intermediate occupational classification has 95 occupational categories, and the female intermediate occupational classification has 48 categories. (Translation of detailed into intermediate occupational classifications available on request.)
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5.2. Methods To test the hypotheses regarding change in occupational segregation, I estimate a series of logmultiplicative models (Agresti, 1990). These models expand on those used to measure occupational sex and race segregation (Charles & Grusky, 1995; Grusky & Pager, 1999; Weeden, 1998). The most unconstrained model describes age segregation in two dimensions, thus allowing a test of the hypothesis that the structure of age segregation differs across two labor markets. This model (Model D) is based on the following equation: mijk = αk βik γjk e(φk μik υjk )+(θk ωik ηjk )
(1)
In this model, mijk is the expected frequency in the ijkth cell, the value in the cell for the ith age group in the jth occupation at the kth time period. The subscript i indexes the five age groups (20–29 years; 30–39 years; 40–49 years; 50–59 years; 60–69 years), and j indexes the J occupations. The total number of occupations, as described above, is different for men and for women. Finally, k indexes the six time periods (1950–2000). Within the model, αk represents the main effect in the kth time period, βik is the time-specific marginal effect for the ith age group, and γ jk is the time-specific marginal effect in the jth occupation. The model also provides estimates of the following association parameters: φk , θ k , μik , ωik , υjk , and ηjk . The main parameters of interest are φk and θ k , as these describe the extent of overall age segregation in each of two, orthogonal dimensions for each of the k = 6 time periods. The parameters take on lower values when workers are not highly age segregated. Therefore, the values decrease from one period to the next when age segregation decreases. When the different occupational categorizations described above are used, the values of the global age segregation parameters differ depending on the number of occupational categories. Therefore, to construct a trend that covers the whole period, I calculate segregation index values for years after 1950 by calculating each year’s segregation parameter as a percent of the previous year’s value. For instance, I calculate the value of the 1970 parameter as a percent of the 1960 parameter when both are based on the 1960 coding scheme. Likewise, I compare the 1960 parameter to the 1950 parameter when both are calculated using categories from 1950. The 1970 parameter can then be compared to the 1950 parameter. The occupation scale parameters, υjk , and ηjk , reveal the extent and direction of segregation within each occupation (and with respect to each dimension). These parameters take on a different value for each of the
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j occupations and each of the six time periods and are orthogonal to one another. They are constrained to have a variance of one and a mean of zero within each time period. If an occupation scale parameter is large, it implies that the occupation is strongly segregated in terms of the age scale values pertaining to that dimension. We might therefore refer to a “stretching out” of that dimension. At the other extreme, a value of zero implies that there is no segregation with respect to that dimension, and segregation will instead be governed by the patterning of age scale values in the other dimension. These parameters are allowed to vary across the five time periods. The age scale parameters, μik and ωik , characterize the particular combination of age groups that prevail in each dimension. If, for example, a linear age scale emerges in a given dimension, then workers’ representation increases or diminishes with age within particular occupations. The sign of the corresponding occupation scale value determines which age groups are represented in that occupation. By contrast, a U-shaped scaling implies a bimodal distribution, with young and old workers either over- or under-represented. Again, the sign of the corresponding occupation scale value determines whether that particular occupation comprises mainly young and old workers or, alternatively, mainly middle-aged workers. Like the occupation scale parameters, these parameters are constrained to have a variance of one and a mean of zero within each time period and are orthogonal to each other. I estimate three other models using a variety of constraints. The most constrained model contains one dimension and does not allow any of the parameters to change over time. This model (Model A) may be represented as follows: mijk = αk βik γjk e(φμi υj )
(2)
Under this formulation, there is only one dimension governing age segregation, and the parameters pertaining to that dimension are all constant over time. Subsequent models relax these constraints. Model B allows a test of change in overall age segregation with φ varying over time. Model C allows the scaling of age categories, μi , and the segregation particular to occupations, υj , to vary over time. I use standard Chi-square comparisons and BIC statistics to choose the best-fitting model (Raftery, 1995). The following section examines what the three preceding narratives imply about the type of model that will be preferred. The predictions of the three narratives are summarized in Table 1.
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Table 1 Predicted characteristics of occupational age segregation Credentialization
Occupational volatility
Dual labor market
Number of dimensions
One
Two
Two
Trend in segregation First dimension Second dimension
Weaken –
Strengthen Strengthen
Stable or weaken Strengthen
5.2.1. Occupational volatility Consider, first, the consequences of occupational volatility. Many occupations will have an age profile that reflects the period when they emerged or expanded and hence disproportionately attracted new entrants. This initial cohort representation will be retained as workers age with the occupation. Occupations that recently expanded will be performed by younger workers, while those that expanded long ago will be performed by older workers. These occupations can be adequately characterized by a linear, one-dimensional scaling for the age categories. However, some occupations will have principally middle-aged incumbents because of the timing of their emergence or expansion. They would not be well-characterized by a linear, one-dimensional scaling. It follows that a two-dimensional model will likely be needed under this formulation. Moreover, one would expect overall age segregation to be increasing over time, as growing turnover should create ever-more occupations with a distinctive “age stamp.” This increase will be reflected in the parameters φk and θ k .
in the past emphasized on-the-job training and experience rather than formal credentials. Workers progressed through sequences of occupations as they gained experience, without having to secure formal credentials outside the labor market. Some occupations were points of entry for newcomers, while others were restricted to older workers with the requisite experience. Age segregation should be substantial (that is, a large φ), but could be characterized with a one-dimensional formulation with roughly linear age scale values. If the forces of credentialization then play out, this should be revealed as a decline in age segregation, in other words, a decline in φ. 5.2.3. Dual labor markets This narrative implies that an increasing number of service occupations are filled simultaneously by young and old workers, implying a two-dimensional specification. The second-dimension of this model will presumably show up in the form of U-shaped age parameters. The peripheralized service occupations will have large occupation scale values on the second dimension, implying that recruitment is principally governed by this U-shaped dimension. This narrative implies that such second-dimension segregation is strengthening over time (that is, θ k is increasing).
5.2.2. Credentialization Recall our ideal–typical representation of intragenerational mobility processes prior to the emergence of credentialization. The claim here was that employers Table 2 Fit statistics for models of occupational age segregation, 1950–2000 Men
Women
L2
d.f.
D
BIC
L2
d.f.
D
BIC
One-dimensional models (A) Baseline model (B) A + overall segregation varies (C) B + age and occupation parameters vary
97,298 96,765 57,487
1596 1591 1116
6.31 6.31 4.60
73,487 73,030 40,838
64,818 63,745 26,941
797 792 552
6.64 6.54 3.89
53,285 52,284 18,953
Two-dimensional model (D) All parameters vary
4005
552
1.01
−4230
2441
270
1.02
L2
d.f. 4 475 564
BIC −457 −32,192 −45,068
L2
d.f. 5 240 282
Contrasts Period effects (Model B-A) Age and occupation effects (Model C-B) Effect of two dimensions (Model D-C)
−533 −39,278
Source: Author’s calculations of model fit using census data.
% of 0.01 0.41
L2
−1073 −36,804
% of 0.02 0.58
−1466 L2
BIC −1001 −33,331 −20,419
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6. Findings Table 2 presents fit statistics from models estimated among both men and women. In model A, occupational age segregation is described in one-dimension, with no change in overall segregation, occupation and age scale parameters. In subsequent models, the parameters are allowed to vary over time. The best-fitting model among both men and women is model D, which introduces a second dimension. This model allows changes in both dimensions governing age segregation. As described above, two dimensions of age segregation may be a result of either dual labor markets or of occupational volatility. Below, I look more closely at the occupational changes to determine which narrative is more consistent with the results. 6.1. Trends in overall segregation Fig. 1 shows the trends in occupational age segregation among male and female workers from the bestfitting model. The census year 1950 dimension 1 value for each gender is set as the base value for that gender, and the values of the dimension 2 scale factors and dimension 1 scale factors for subsequent years are shown as a share of that 1950 dimension 1 value. The solid lines trace the trends estimated using the constant 1950 coding scheme. The dashed lines show the trends when the models are estimated using the 1950, 1960, 1980 and 2000 occupational codes (as described above). The overall trend in occupational age segregation is affected somewhat by the choice of coding scheme (described below). According to the results from the best-fitting model (Model D), occupational age segregation in the first dimension declined between 1950 and 1990 among both women and men, as predicted by the credentialization
Fig. 1. Age segregation in two dimensions, 1950–2000.
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narrative. Among women, the direction of the trend after 1990 depends on the occupational categorization used. When the 1950 categorization is used, female workers appear less age segregated at the end of the period than at the beginning. Thus, in the first dimension, workers of each age group were more often employed in occupations performed by workers of other age groups in 1990 (or perhaps 2000) than they were at the beginning. According to the credentialization argument, they were more likely recruited to these positions based not on their experience, but on their initial credentials. Recall that neither the dual labor market nor occupational volatility narratives suggested that age segregation would decline, but rather that it would remain stable or increase. Starting in 1990, however, occupational age segregation among male and perhaps female workers increased. In 2000, male workers were at least as segregated by age as they were in 1950. If the 2000 occupational categorization is used, age segregation also appears to have increased between 1990 and 2000 among women workers. This suggests that occupational volatility may have caused an increase in occupational age segregation in the last decade of the twentieth century. 6.2. Changes in occupational age profiles differ by gender As described above, the best-fitting model describes two dimensions, which is consistent with both the dual labor market and occupational volatility narratives. Both narratives predict that second dimension age segregation would strengthen. However, age segregation in this dimension remained relatively stable. In order to determine which narrative is more consistent with the results, I look more closely at change within particular occupations. The dual labor market narrative suggests service and other low-skill occupations should have increasingly bimodal age distributions. The trends in occupational age profiles correspond with this prediction. Occupational age profiles are determined by a combination of the occupation scale values in both dimensions with reference to the corresponding age scale values. Fig. 2 shows the age segregation patterns among women and men at the beginning and end of the period in the first dimension. The patterns of the age scale values are consistent across time. This dimension was characterized by a linear age scale. According to this scale, workers of each age group were less occupationally segregated from those closer in age than they were from those more distant in age. For instance, 20-year old workers were less likely to work in occupations performed by 40-year old workers than in those performed by 30-
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Fig. 2. Age segregation in dimension 1, 1950 and 2000.
Fig. 3. Age segregation in dimension 2, 1950 and 2000.
year old workers. In the second dimension, shown in Fig. 3, workers were segregated according to a U-shaped age scale. In this dimension, young and old workers were more likely to be employed in the same occu-
pations than in occupations performed by middle-aged workers. Based on these age patterns, the sign of an occupation scale value determines the occupation’s age pattern in each dimension. For instance, young workers would be over-represented in the first dimension in an occupation with a negative scale value. Middle-aged workers would be over-represented in an occupation with a negative scale value in the second dimension. In either dimension, occupations with near-zero scale values would be integrated. One can combine the occupation scale values in each dimension to determine that occupation’s overall age profile. For instance, an occupation with a near zero value in the first dimension and a positive value in the second dimension would have a bimodal age distribution, combining young and old workers. To see if the results are consistent with the dual labor market narrative, I examine occupation scale values in the second dimension for those occupations that are integrated in the first dimension. Fig. 4 shows the mean occupational scale values in the second dimension for aggregate occupational categories in both 1950 and 2000. The numerical values are translated into the following categories: middle-aged, integrated, and bimodal. As shown in Fig. 4, among women, the clerical, sales, and service worker occupations were more likely to have bimodal age distributions in 2000 than in 1950. This finding is consistent with the dual labor market narrative. However, among men, the laborer, clerical, and service occupations became slightly less likely to employ a combination of young and old workers. In 1950, occupations in this cat-
Fig. 4. Second dimension occupation scale values in 1950 and 2000.
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egory tended to exhibit bimodal age distributions. By 2000, they were slightly more integrated in the second dimension. Thus, age segregation among men appears not to have been shaped by an increasingly bimodal age distribution in the secondary labor market. 6.3. Effect of the coding scheme Between 1950 and 1990, the choice of occupational coding scheme does not have a large effect on the parameter estimates of the extent of age segregation shown in Fig. 1. However, between 1990 and 2000, the trend in dimension 1 age segregation estimated with the 1950 codes differs from that estimated with the 2000 codes. The 1950 occupational codes may understate the extent of occupational age segregation in 2000. Among men, this understatement affects the strength of the trend in age segregation, while among women, it affects the direction of the trend. Men may have experienced a greater increase in occupational age segregation than revealed by the 1950 codes. Women may have become more, rather than less age segregated. The occupation scale values show that the 1950 occupational codes may understate occupational age segregation because they do not capture the addition of new work. Fig. 5 shows occupation scale values in the first dimension for 1990 and 2000. These values are based on the intermediate occupational categorization derived from the 2000 census. The left panel shows the occu-
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pation scale values for women, ordered based on their values in the 2000 census. The right panel shows the occupations in the same order, but this time with the occupation scale values for men. This provides some evidence that age segregation increased among women in part because younger female workers can now work in occupations that have traditionally been performed by male workers. For instance, the aircraft and architect occupations became increasingly dominated by young women. As would be expected from the growth of the high tech industry in the nineties, the computer and math occupations have increasingly drawn both younger male and female workers. Thus, the 1950 codes with their reliance on the prevailing gender segregation of that era do not capture age segregation that came about as occupations became open to women, drawing in younger workers. Nor do they capture changes in age segregation due to the addition or expansion of occupations such as computer programmers that represent new work. 7. Discussion Age continues to be an important status distinction alongside race and sex, with ramifications for the occupations that individuals perform. After 40 years of decline, occupational age segregation began to rise again at the end of the twentieth century. Between 1950 and 1990, male and female workers became less age segregated. This finding is con-
Fig. 5. First dimension occupation scale values in 1990 and 2000.
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sistent with a decline in age-graded mobility stemming from credentialization. The credentialization narrative described a transition from a system in which individuals advance through a sequence of occupations based on the experience that they accumulate as they age. According to the narrative, this age-graded system was eroded in favor of another system in which individuals enter, and remain in, occupations based on initial credentials. Individuals of one age became more likely to work in occupations alongside individuals of other ages. This was the only one of the initial three narratives that predicted declining occupational age segregation. Indeed, in the best-fitting model, occupational age segregation declined by 20–40% between 1950 and 1990. The credentialization narrative also predicted that there would be only one dimension governing occupational age segregation. However, the preferred model contained two dimensions, suggesting at least partial support for either the dual labor market or occupational volatility narrative. Throughout the last half of the twentieth century, age segregation is best described as having a linear and a bimodal dimension. The decline in linear segregation suggests that changes in the primary sector may reflect declining age-graded mobility. In the second dimension, young and old workers performed the same occupations. The dual labor markets narrative suggested that service occupations, in particular, would increasingly exhibit bimodal age distributions. Women workers did experience increasingly bimodal age distributions in a variety of occupations, including service occupations. In 1950, middle-aged women were more likely to work in these occupations, while in the year 2000, a combination of younger and older women worked in these occupations. However, among men, service occupations were less likely to exhibit such bimodal age distributions in 2000 than in 1950. Starting in 1990, age segregation in the first dimension increased among men and may have increased among women. By 2000, male, and perhaps female, workers were at least as occupationally age segregated as they had been in the year 1950. As mentioned above, individuals are increasingly age segregated at school, and in retirement. Thus, among men and possibly among women, this increased age segregation before and after the work life has been accompanied by relative increases in age segregation at work. The increase in age segregation is consistent with the occupational volatility narrative. This narrative suggested that as employers add new occupations, members of different cohorts confront different occupational choices. New or expanding occupations should be performed by younger workers. However, though the level of occupational age segre-
gation may be the same as in the 1950s, the source is different. In the 1950s, such segregation stemmed from age-graded mobility, which meant that members of different cohorts could anticipate aging in the same way. Today, when age segregation is based on occupational volatility, the members of different cohorts will have different experiences of aging. The possible increase in female occupational age segregation suggests that age segregation may be affected by changes in gender segregation. Women workers may experience a gender-specific form of occupational volatility. Recall that the 1950 occupational categorizations were gender-specific intermediate categorizations based on the distribution of workers in 1950. Thus, these categorizations rely on the assumption that the genderspecific distributions remained roughly similar across the 50-year period. This assumption is more tenable among men than among women. Women may confront a new set of occupational choices when occupations that have traditionally been performed by male workers shift to become less gender segregated. When this shift happens, young women in particular can make different choices than were available to middle-aged and older women. More generally, occupational age segregation may be affected by changes in the occupational segregation of groups defined by other status characteristics, such as race/ethnicity. Exploring the relationship between occupational age segregation and other forms of occupational segregation presents a promising avenue for future research. The increased age structuring of society has important ramifications for the kinds of activities that individuals do at particular points in their lives. Today, the primary membership organization representing older Americans has two times as many members as the all the unions in the United States. Its sphere of influence extends from traditional areas such as the policy debates about social security to less traditional partnerships that encourage businesses to hire older workers. The recent increase in occupational age segregation may stem from and contribute to increases in such age-based advocacy. Acknowledgments Support for this research was provided by the National Institute on Aging (T32-AG00129), the National Science Foundation (SBR-9320660), the Wisconsin Alumni Research Foundation, and the Center for Demography and Ecology at the University of Wisconsin-Madison. I thank Charles N. Halaby, Michael Hout, and Lincoln Quillian for helpful comments on different versions of the paper. I am especially grateful for the advice and
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