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Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles (1980)

Chapter: 7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information

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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Suggested Citation:"7 An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information." National Research Council. 1980. Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles. Washington, DC: The National Academies Press. doi: 10.17226/92.
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Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

7 INTRODUCTION An Assessment of the Dictionary of Occupational Titles as a Source of Occupational Information In the preceding chapter, procedures used to compile the most recent edition of the Dictionary of Occupational Titles are described, and several concerns are raised about the quality and characteristics of the fourth edition in light of the way it was produced. To fulfill the committee's charge to make recommendations about whether future editions of the DOT should be produced and what kinds of occupational research should be conducted to produce them, an evaluation of the quality and characteristics of the DOT is presented in this chapter. The results of this assessment, coupled with knowledge about use, have helped to inform us as to how well the data contained in the DOT meet the purposes for which they are intended and/or used. This assessment is also a basis for the committee's recommendations about whether data collection and analysis activities used in compiling future editions of the DOT should differ substantially from what has been done in the past. Establishing the quality and characteristics of data contained in the DOT is not a straightforward task. First, as already mentioned, data collection procedures were not well documented. As a result the possibilities are Pamela S. Cain had primary responsibility for the preparation of this chapter. 148

An Assessment of DOT as a Source of Occupational Information 149 limited for systematic secondary analysis of the procedures themselves or of their implications for the resulting data. Second, most of the data contained in the DOT are unique, so no readily available bench marks exist against which to compare and assess them. In fact, a great deal of occupational research takes the DOT as the bench mark or standard of comparison, a fact that makes the assessment of DOT data even more important. In this chapter we present the results of several analyses that were designed to explore in detail and systematically the nature of the process by which the DOT was produced and the quality and characteris- tics of the resulting data. SAMPLING PROCEDURES As described in chapter 6, the industry designations developed by the occupational analysis program provide the "sampling frames" from which establishments are selected for on-site visits. The underlying assumptions of the procedure are that jobs vary by industry, by region, and by size (i.e., number of employees) and that these criteria provide the soundest basis for achieving reasonable coverage of all jobs and for discovering significant variations among jobs within occupations. Within the establishments chosen, emphasis is put on analyzing those jobs that appear to be unique to the work performed in establishments of the type that the selected one represents. No bench mark data on the "population" of jobs exist, and the procedures by which specific choices were made about which jobs to study are not well documented. Consequently, it is not possible to establish whether the DOT provides comprehensive and representative information about jobs in the U.S. economy. Nevertheless, certain aspects of the procedures and their outcomes raise serious questions about the success in attaining representative coverage. A total of 232 industry designations are used to delineate the "universes" from which sample establishments are chosen. As we have noted in chapter 2, several of these, notably the designation clerical and kindred workers, are not in fact industries, and their use carries the implicit assumption that such occupations do not vary significantly in content among establishments of different types. As a consequence of this treatment of a number of nonproduction occupations the majority of the 232 industry designations that provide the universes from which establish- ments are selected are in the manufacturing sector. In contrast, the current version of the Standard Industrial Classification denotes 1,005 industries at its most detailed level, and less than half are in manufacturing. Viewed in this context then, the DOT cannot be said to be based on job analyses

lso WORK, JOBS, AND OCCUPATIONS conducted in establishments representing the entire spectrum of U.S. industry types. Comparable establishment-level data for the DOT and the U.S. economy can be used to yield a crude indicator of the direction in which the job analysis efforts for the fourth edition DOT were channeled. In themselves these data do not constitute an evaluation of the DOT'S coverage, since the critical issue, under the assumptions of the procedure currently used, is the variety of types of establishments rather than the number of establishments (or the number of employees). Nevertheless, comparison of the two distributions reinforces the impression of a disproportionate emphasis on manufacturing. Data for DOT establishments were obtained from a set of staffing schedules that were recently computerized and made available to us by the national office of the Division of Occupational Analysis. As noted in chapter 6, in the course of fourth edition production, staffing schedules were not prepared for all establishments entered or for all jobs analyzed. Furthermore, computerization of the schedules had not yet been com- pleted at the time of the committee's study. Thus the data employed in our analysis cover only 2,063 establishments; schedules for an estimated 1,100 to 1,200 establishments are still outstanding.) The characteristics of establishments in which staffing schedules were not completed or of establishments whose schedules had not yet been computerized cannot be determined. As far as we can ascertain, there is no reason to believe that there are marked differences between the characteris- tics of establishments for which data are and are not available, especially since analysts were supposed to complete staffing schedules for every establishment in which they analyzed a significant number of jobs. Given the procedures by which staffing schedules were filled out and their purpose, however, we conjecture that analysts may have been more likely to complete the schedules in larger, more bureaucratic establishments, especially those with personnel offices. Data on the national population of establishments were obtained from tables in County Business Patterns, 1974 (U.S. Bureau of the Census, 1977~. This publication is compiled by the Census Bureau using data from the administrative records of the Internal Revenue Service and the Social Security Administration. Information is available on establishments, payroll, and employment by industrial classification, size class, and county for all types of employment covered by the Federal Insurance Contribu- tions Act. In 1974 these data covered approximately 90 percent of U.S. This information was obtained through personal communication with staff at the national office and the North Carolina field center.

An Assessment of DOT as a Source of Occupational Information 151 establishments and 75 percent of the employed population. Not covered were some government employees; self-employed persons; and certain types of farm, domestic service, and railroad workers. In order to compare the DOT data with the published data on the national population of establishments, the staffing schedules were recoded to the categories used in County Business Patterns. The DOT establishments in public administration (N = 59) were excluded from tabulations, as were establishments for which data were missing. These exclusions resulted in the loss of 113 establishments and a final total of 1,950 establishments in the DOT sample. Table 7-1 presents a comparison of the percentage distribution of DOT and U.S. establishments by sac major industry division. The two distributions exhibit marked dissimilarities. The largest discrepancy occurs in the manufacturing category: 67 percent of the DOT establishments are in manufacturing industries, although this category accounts for only 8 percent of all U.S. establishments and for 32 percent of total employment. Underrepresentation is most pronounced in the retail trade and services divisions. Retail trade accounts for a mere 4 percent of the DOT establishments, although nationally, it includes 29 percent of establish- ments and employs 20 percent of the labor force. Only 7 percent of the DOT establishments are in the services division, an industry division that accounts for 27 percent of all U.S. establishments and for 20 percent of U.S. employment. Both retail trade and services include establishments engaged in a great variety of activities. It seems highly improbable that the disparity in coverage between these major industry divisions and the manufacturing division reflects a real difference in the heterogeneity of occupations. As previously noted, the wide disparity between the two distributions cannot be interpreted as conclusive evidence; but it does suggest that the procedures used to select establishments for the fourth edition DOT resulted in an overrepresentation of establishments in manufacturing industries. This overrepresentation occurred primarily at the expense of the retail trade and service industries, which include 40 percent of all workers. Moreover, the comments and observations of field center personnel lend additional support to the general impression that job analysis activities have tended to place emphasis on manufacturing industries. Size was another important criterion of establishment selection accord- ing to the occupational analysts, one for which national data are also available from County Business Patterns, 1974 (U.S. Bureau of the Census, 1977~. In Table 7-2 the percentage distribution of establishments by size class (number of employees) is presented for the DOT and for the U.S.

152 WORK, JOBS, AND OCCUPATIONS TABLE 7-1 Percentage Distribution of Establishments by SIC Industry Division: Comparison of DOT Sample a and U.S. Labor Force b Establishments U.S. Labor DOT,U.s.,Force, c sac DivisionDOT, Npercentagepercentagepercentage Agricultural services, forestry, fisheries1618.30.90.3 Mining271.40.61.1 Contract construction522.49.16.2 Manufacturing1,30967.27.632.1 Transportation and utilities954.93.56.4 Wholesale trade402.18.77.0 Retail trade824.229.019.6 . . . . finance, insurance, real estate442.39.06.8 Services1407.226.819.6 Nonclassifiable ~00.04.80.9 TOTAL1,950100.0100.0100.0 a DOT data taken from establishment staffing schedules. For purposes of comparison with U.S. data, establishments in public administration were eliminated from tabulation. bSOURCE: Coun~BusinessPatterns,1974(U.S.BureauoftheCensus,1977:TablelB). C Workers employed in the establishments covered, not the employed civilian labor force. Included in this category are establishments that could not be classified because of insufficient information. Typically, these were new businesses. population of establishments. This comparison also reveals discrepancies between the DOT sample and the national population; the discrepancy is particularly large in the smallest size class. Establishments employing one to four workers made up 59 percent of all U.S. establishments but only 6 percent of the DOT establishments. Generally, small establishments with fewer than 20 employees were underrepresented in the DOT sample, while intermediate (20 to 249 employees) and large (250 or more employees) establishments were overrepresented in relation to the U.S. distribution of establishments. There is a rather close correspondence, however, between the DOT distribution of establishments and the distribution of U.S. employment. Once again, we point out that the implications of these results for the

An Assessment of DOT as a Source of Occupational Information 153 TABLE 7-2 Percentage Distribution of Establishments by Employment-Size Class: Comparison of DOT Sample a and U.S. Labor Force b Establishments U.S. Labor DOT,U.S., Force, c Size DOT, Npercentagepercentage percentage 1-4 1256.458.7 7.2 5-9 1497.618.0 8.2 10-19 20010.311.3 10.4 20-49 36718.87.5 15.3 50-99 27714.22.4 11.4 100-249 33817.31.4 13.6 250-499 21611.10.4 9.6 500-999 1206.20.2 8.3 1,000+ 1588.10.1 16.0 TOTAL 1,9501 ~.01 00.0 1 00.0 a DOT data taken from establishment staffing schedules. For purposes of comparison with U.S. data, establishments in public administration were eliminated from tabulation. bSOURCE: Coun~Business Patterns, 1974(U.S. Bureau ofthe Census, 1977: Table 1B). C Workers employed in the establishments covered, not the employed civilian labor force. coverage of jobs are not straightforward. If the assumption that industry type is the proper basis for sampling establishments is correct, then an important first step might be to revise the industry list so that it provides coverage of all unit items in the sac. In this frame of reference the number of establishments in each industry would not be relevant, since the objective would be to obtain adequate minimum coverage for each separate type of establishment. On the other hand, if jobs in manufacturing are more diverse than those in other sectors, then oversampling of manufac- turing enterprises is quite appropriate. The DOT analysts would be expected to devote more of their attention to establishments (and presumably jobs) in these industries. Furthermore, if jobs tend to be similar in large and small establishments, undersampling small establish- ments and oversampling large estabishments would be justified on grounds of cost effectiveness. The difficulty is that there is no evidence at all regarding the relationship between type of establishment and the variability of job content. We do not

154 WORK, JOBS, AND OCCUPATIONS know whether manufacturing jobs are more heterogeneous than other jobs or whether jobs in small establishments differ from ostensibly similar jobs in large establishments or in other small establishments. In addition to considering the types and sizes of establishments providing the base data for the DOT, it is also possible to compare the distribution of occupational units in the DOT with the distribution of workers. This approach also has very obvious limitations, since some occupational units include large numbers of workers and others include relatively few. Nevertheless, the data presented in Table 7-3, in which DOT coverage and labor force employment by major occupational category are shown, reveal very marked discrepancies. Some 60 percent of all base titles fall in the processing, machine trades, and benchwork categories, although these categories include only about 12 percent of the labor force. Taken in conjunction with the finding (documented in Table 7-5 below) that a substantial proportion of occupational titles are supported by one (or no) job analysis schedule, the skewness of the distribution in Table 7-3 raises the conjecture that the choice of jobs for analysis has a major impact on the number of occupations identified and that therefore the concentration of attention on manufacturing establishments has an important impact on the entire classification structure. To state this more explicitly, if there is a strong tendency for each job analysis to result in the identification of a separate occupation (as Table 7-5 seems to imply), the selection of job analysis sites and of the jobs to be analyzed at these sites becomes the crucial decision of the occupational analysis program. As noted above, the procedures for selecting sites for job analysis were not carefully developed. Analysts drew heavily on the third edition DOT to guide their job analysis activities. This practice might well have led them to concentrate more on jobs in established manufacturing industries (which were well represented in earlier editions) and to devote less attention to jobs in newly emerging or rapidly growing sectors of the economy, such as services or retail trade. In addition, it was clear to us in talking with the analysts that many were oriented almost exclusively toward the study of production jobs. Undoubtedly, this orientation is a historical outgrowth of the program, rooted in tradition, but other reasons may be salient, such as the ease of access to manufacturing establishments. Similarly, the emphasis on large establishments may have come about because of the relative efficiency of analyzing many jobs in a few large establishments versus a few jobs each in many small ones. For whatever reasons the concentration on manufacturing and relatively large establishments came about, and whatever its implications are for the coverage of jobs, the results of the foregoing comparisons raise questions about exactly how sampling for the DOT should proceed. Previous practices were relatively unsystematic, virtually uninfonned by empirical

An Assessment of DOT as a Source of Occupational Information 155 TABLE 7-3 Comparison of Percentage Distributions of DOT Titles and Labor Force by DOT Occupational Categories Percentage of Base Titles Percentage of DOT Occupational Category(N = 12,099) Labor Force Professional, technical, and managerial12 25 Clerical and sales8 25 Service4 16 Agriculture, fishing, and forestry2 4 Processing23 2 Machine trades18 6 Benchwork19 4 Structural work7 9 Miscellaneous7 8 TOTAL100 99 SOURCE: Labor force data derived from April 1971, Current Population Survey; sample (N = 60,441) includes currently employed workers and experienced unemployed for whom a census code could be assigned. Excluded are 12 percent of sample for whom WT codes could not be assigned. Data on distribution of DOT titles by category provided by the Department of Labor occupational analysis program. data, and resulted in relative inattention to several sectors that include large proportions of workers. The distributions of workers or of establish- ments that we have had to use as crude indicators are not the basic relevant criteria, of course; a more desirable goal would be the iden- tification of the types of organizations that have unique types of jobs, with at least minimum coverage of these unique types of jobs. A sampling strategy that would ensure adequate coverage of the job content of the American economy will not be easy to develop, but it is essential that work on this problem be initiated immediately if the DOT is to serve the many demands that are made of it. SOURCE DATA Chapter 6 observes that the amount and type of source data supporting DOT titles and definitions vary and that the quality of the data appears to be uneven. These conclusions were based on examination of the source data, on reports from analysts involved in writing definitions, and on findings of the Booz, Allen & Hamilton, Inc. (1979) management review. In this section a more systematic and detailed inquiry into the quality of

156 WORK, JOBS, AND OCCUPATIONS source data is undertaken to determine the extent to which departures from standard procedures occurred and whether such departures vary by period or across certain types of jobs. As is evident from the discussion in chapter 6, there are numerous points at which departures could have occurred. The nature of these departures is important to the extent that they have deleteriously affected the quality and comparability of the data in the DOT. To assess the quality of DOT documentation, we used a set of data collected by Booz, Allen & Hamilton as part of its management review. Because the only information available on the procedures by which the DOT was produced is anecdotal and impressionistic, Booz, Allen & Hamilton conducted a special study of DOT source data in November 1978. Analysts at the North Carolina field center were requested to record information on the documentation available for a sample of 307 DOT base titles. The sample was systematically selected by choosing every fortieth title in the DOT. However, there was an occasional departure from this procedure. If the title selected was not a base title, a substitution was made, but the procedure by which this was done is unclear. Even though the sample is slightly unsytematic, the difficulties of conducting another similar study justify the use of these data to get an idea of the quality of DOT documentation. As a check on the Booz, Allen & Hamilton sample, the percentage distribution of base titles by DOT major occupational categories for the sample was compared with that of the DOT. The comparison, in Table 7-4, reveals that the two distributions are very similar. Hence on this criterion at least, the sample appears to be quite representative of the population from which it was drawn. The distribution of DOT titles by the kind of documentation available for each is shown in Table 7-5. The summary information at the end of the table shows that 11 percent of the DOT titles had no supporting documentation other than the third edition definition, which was based on job analyses conducted prior to 1965. Seventy-one percent of titles were supported by job analysis schedules only, 8 percent by schedules and occupational code requests, and the remaining 10 percent by other combinations of data. Thus job analysis schedules constituted the bulk of the data base for the DOT, other types of information making up a relatively small percentage of the source data. The quality of the definitions for the 11 percent of titles lacking any sort of documentation other than the third edition is particularly questionable, . .. . ~ . . ~ ~ , . since there Is no way ot knowing whether and to what extent changes in the content of these jobs occurred between the third and fourth editions. The quality of definitions based solely (5 percent) or in part (14 percent) on information other than job analysis schedules may also be questionable.

An Assessment of DOT as a Source of Occupational Information ·57 TABLE 7-4 Percentage Distribution of DOT Titles by Major Group: The DOT versus the Booz, Allen & Hamilton Sample Category DOT Booz, Allen & Hamilton Sample 0-11213 289 345 4 52321 61818 71919 878 976 TOTAL1~1~ N(12,099)(307) Occupational code requests, for example, are essentially employers' job orders, which are taken over the phone and may not be verified on site. As a result the job specifications contained in code requests probably reflect hiring requirements rather than the functional requirements of jobs, as would have been determined via on-site analysis. Similarly, information obtained through letters from trade associations (which are, in part, advocacy groups) is perhaps more likely to depict the ideal job than the average or typical one. For both sources of information, skill and other requirements of the job may be inflated or biased upward, in relation to what would have been determined through on-site analysis. If these data continue to be used to support DOT definitions, steps should probably be taken to determine their properties and possible biases and their comparability to data obtained via on-site observations and interviews. Table 7-5 shows the distribution of titles by the number of job analysis schedules available for each. Sixteen percent of DOT occupations are unsupported by job analysis schedules (11 percent of these are completely unsupported, and 4.5 percent are supported by other types of information). Of the total number of occupations an additional 29 percent are supported by only one schedule, 19 percent by two schedules, and the remaining 37 percent by three or more schedules. The small number of jobs analyzed per title raises additional questions about the inclusiveness and accuracy of the occupational information

158 WORK, JOBS, AND OCCUPATIONS TABLE 7-5 Percentage Distribution of DOT Titles by Number and Type of Supporting Documentation Documentation Percentage Number of job analysis schedules (]AS) o 2 4 6 8+ TOTAL Number of occupational code requests (OCR) o 3+ TOTAL Number of othera sources o 1 2 3+ TOTAL All forms of documentation None JAS only OCR only Other only WAS and OCR JAS and other JAS, OCR, and other TOTAL TOTAL N 16 29 19 4 2 13 101 90 6 2 2 100 89 8 2 1 100 1 1 4 8 101 307 a Other includes comments from trade associations, job descriptions from employees, etc. SOURCE: Tabulated using data from Booz, Allen & Hamilton study of DOT documentation.

An Assessment of DOT as a Source of Occupational Information 159 contained in the DOT. The DOT definitions purport to be composites of the content of jobs that can be grouped together under a single occupational title- not average or representative in the statistical sense, but rather typical. Granted that this claim is a vague one, there is still reason to question it, for 64 percent of fourth edition DOT titles are based either solely on a single third edition definition (which appears not to have been verified for the fourth edition) or on the new analysis of only one or two jobs. If jobs within an occupational composite are very similar (i.e., if the occupation is homogeneous), then a small number of observations per occupation may be sufficient to define it accurately. If, on the other hand, there is a good deal of variation among the jobs making up an occupation (e.g., differences in job tasks or in technologies or materials), then a larger number of observations is probably desirable in order to capture adequately the occupation's core tasks and its significant variations. Unfortunately, for the majority of occupations in the DOT there is insufficient information to determine whether an occupation is homoge- neous (so as to require few job analyses) or heterogeneous (requiring numerous analyses). Assuming that some occupations vary in their constituent jobs, it would seem advisable to explore further this issue of job or occupational heterogeneity in order to determine the optimal number of analyses needed to obtain reliable and adequately representative occupa- tional information. This might be done by analyzing the existing source data for those DOT titles that are based on multiple job analyses or by undertaking intensive new analyses of numerous jobs in the same occupation (see Appendix E for a limited analysis of this kind). An inquiry into the characteristics of job analysis schedules shows that they too vary in several respects that might affect the quality of the DOT'S occupational composites. Table 7-6 gives the distribution of schedules by treatment type, the procedures by which they were produced, and quality. This table and the next one are based on the 1,351 schedules contained in the files of the Booz, Allen & Hamilton sample of 307 DOT occupations. As Table 7-6 shows, the majority of schedules available for the fourth edition (66 percent) are C schedules, in which the job description is abbreviated to include only variations from the third edition definition. A schedules, which were prepared for jobs that could not be converted to a third edition code and thereby contained full job descriptions, constitute 26 percent of all schedules. V schedules, in which the job description is abbreviated to include only variations from descriptions in other schedules, make up 8 percent of the total. In accordance with Handbook procedures (U.S. Department of Labor, 1972), almost all schedules (94 percent) were prepared on the basis of direct observation of jobs. Only 6 percent were prepared using data

160 WORK, JOBS, AND OCCUPATIONS TABLE 7-6 Percentage Distribution of Job Analysis Schedules by Selected Characteristics for Selected Periods 1962-1966-1974 CharacteristicTotal196519731976 Treatment type A (new job analysis)26203413 C (confirmation of occupational definition in previous edition DOT)66676469 V (verification of occupational definition based on previous job analysis)813218 TOTAL100100100100 Direct observation No60116 Yes941009984 TOTAL100100100100 Photocopy No86989470 Yes142630 TOTAL100100100100 Quality Acceptable66537460 Unusual MTEWAa or MPSMS b not described19171822 Job did not convert to 3rd edition code and description inadequate3432 Technical terms not defined0000 Other1226516 TOTAL100100100100 Period produced 3rd edition (1962-1965)10 Regular (1966-1973)57 Verification (1974-1976)33 TOTAL100 TOTAL NC(1,351)(128)(735)(426) a Machine, tools, equipment, or work aids. b Material, products, subject matter, or services. C Totals for period subgroups do not add to 1,351 because cases with missing data were eliminated. SOURCE: Tabulated using data from Booz, Allen & Hamilton study of DOT documenta- tion.

An Assessment of DOT as ~ Source of Occupational Information 161 obtained through other means such as phone calls or letters. Eighty-six percent of all schedules are original write-ups, while 14 percent are photocopies of other schedules a shortcut that is not, strictly speaking, acceptable. Sixty-seven percent of all schedules, whether an original or based on direct observation, are acceptable by Handbook criteria; i.e., terms are defined and all items were completed. For 19 percent of the schedules, machines, tools, equipment, or work aids (MTEWA) or materials, products, subject matter, or services (MPSMS) are not described, while for another 15 percent the job description is inadequate or various items on the schedule have been omitted. Table 7-6 also shows the distribution of schedules by the period in which they were produced. The first period (1962-1965) covers third edition production. The second period (1966-1973) is post-third-edition, during which standard operating procedures were in effect. The third period (197~1976) covers the years immediately prior to publication of the fourth edition, during which abbreviated verification procedures were used. Results indicate that 10 percent of the schedules used in developing the fourth edition were in fact produced for the third edition. The majority, 57 percent, were produced in the 9-year period after publication of the third edition. One third of all schedules were produced in the "verification" period, when abbreviated procedures were implemented in order to speed completion of the fourth edition. In the verification period (197~1976), procedures were reportedly much abbreviated. To investigate whether there was a relative lowering of standards during that time and a concomitant decline in quality, the distribution of procedural and qualitative indicators was broken down by period (see Table 7-6~. As expected, the percentage of verification (V) schedules increased in this period, from 2 percent of all schedules in 1966- 1973 to 18 percent of all schedules in 197~1976. The production of A schedules for new jobs that were not readily coded to the third edition dropped from 34 to 13 percent. The production of C schedules as a proportion of the total, by contrast, remained fairly constant across all periods. The results in Table 7-6 document an increase in the proportional incidence of departures from Handbook procedures during the 3-year verification period. Whereas 99 percent of all schedules produced in the period prior to verification (1966-1973) are based on direct observation, 84 percent of the schedules dating from the verification period were produced in this way. Thus 16 percent of the schedules dated from the period immediately preceding publication result, not from on-site observation interview but from phone calls to employers, mailed questionnaires, talks with professional and trade associations, etc. The practice of duplicating

162 WORK, JOBS, AND OCCUPATIONS TABLE 7-7 Percentage Distribution of Job Analysis Schedules, by Selected Characteristics and Type of Job Characteristic Nonmanufacturing Manufacturing Treatment type A3024 C6566 V510 TOTAL100100 Direct observation No66 Yes9494 TOTAL100100 Photocopy No9084 Yes1016 TOTAL100100 Quality Acceptable7065 Unusual MTEWA or MPSMS not described1422 Job did not convert to 3rd edition code and description inadequate23 Technical terms not defined00 Other1410 TOTAL100100 TOTAL Ha(471)(823) a Total does not add to 1,351 because cases with missing data were eliminated. SOURCE: Tabulated using data from Booz, Allen & Hamilton study of DOT documenta- tion. previous schedules rather than writing up analyses anew also increased proportionally, from 6 percent in the post-third-edition period to 30 percent during the verification period. In interpreting these variations by period it should be borne in mind that the total incidence of departures- from Handbook procedures across all periods is relatively small, as is shown in Table 7-6. Concomitant with the increase in shortcut procedures, the percentage of acceptable schedules dropped from 74 percent of the total in 1966-1973 to 60 percent in 197~1976. Although there is variation by period in the incidence of shortcuts or deviations from accepted procedures, these departures do not appear to

An Assessment of DOT as a Source of Occupational Information 163 have occurred disproportionately for certain types of jobs. Table 7-7 shows the type, procedures, and quality of schedules broken down by two broad categories: manufacturing and nonmanufacturing. The number of cases in the sample did not permit a finer breakdown by job type. The nonmanufac- turing category is composed of occupations in DOT categories ~1 (professional, technical, and managerial), 2 (clerical and sales), 3 (service), 4 (agriculture, fishing, and forestry), and 9 (miscellaneous). The manufac- turing category is made up of occupations in DOT categories 5 (process- ing), 6 (machine trades), 7 (benchwork), and 8 (structural work). The distribution of schedules by treatment type is very similar for both categories, with slightly more verification schedules and fewer schedules for new jobs for manufacturing than for nonmanufacturing. In addition, the distributions on observation are identical: 94 percent of the schedules completed in both categories were based on on-site observation. Schedules for manufacturing jobs, however, are slightly more likely (16 versus 10 percent) than those for nonmanufacturing jobs to have been photocopies of other schedules rather than original write-ups. The quality of manufactur- ing schedules is also somewhat lower than those for nonmanufacturing jobs: 65 percent of schedules in manufacturing were acceptable, compared with 70 percent of nonmanufacturing schedules. The difference is due primarily to the greater incidence of undefined terms (machines, tools, equipment, or work aids and materials, products, subject matter, or services) for schedules in the manufacturing category. Although the consequences of departures from standard procedures or of schedules of poor quality cannot be determined with any certainty, the existence of such departures raises doubts about the quality of the occupational definitions in the DOT. Overall, the incidence of shortcuts or deviations is relatively low. Departures did occur disproportionately, however, in the period just prior to publication. If job analysis for the fourth edition had been better planned and paced, it is likely that these departures could have been avoided altogether. To cut down on the incidence of such last-minute departures, better planning of DOT produc- tion and an ongoing process of quality control are advisable. Another concern arising from these analyses deserves further consider- ation. According to Handbook procedures, full job descriptions are not required for schedules of treatment type C (confirming third edition codes) and V (verifying fourth edition descriptions), which, as Table 7-6 shows, account for 74 percent of all fourth edition schedules. In some cases, analysts provided full job descriptions anyway; in other cases, "same as third edition" is the only job description available on a schedule. The description of job duties is perhaps the most important piece of information contained in the job analysis schedule, serving as the basis for

164 WORK, JOBS, AND OCCUPATIONS the definition itself and es 'implicit justification for the assignment of a DOT classification code and worker trait ratings. Because of the importance of the description, thought should be given to requiring a full job description on every schedule, regardless of whether the job being analyzed can be converted to a third edition title or is similar to a previously analyzed job. To promote efficiency, some of the items on the schedule or other pieces of information analysts are now required to supply might be eliminated. For example, the narrative report, the process flow chart, and the organization chart, all of which take considerable time to prepare, are apparently almost never used subsequent to their preparation. It would be misguided, however, to abbreviate the most important piece of information on the job schedule: the job descriptions. In addition, the practice of writing full job descriptions only for jobs that cannot be converted to a third edition code may have hindered the effort to identify new jobs adequately or to update old ones by creating a tendency for analysts to force similarities between the job being analyzed and the third edition definition. The use of different treatment types was devised as a way of eliminating needless effort on the part of analysts, but thought should be given to developing other ways of achieving this end that do not carry with them the potential for adversely affecting the data collected. RATINGS OF WORKER FUNCTIONS AND WORKER TRAITS In the course of producing the DOT, analysts assigned scores to jobs (during data collection) and occupations (during definition writing) on a variety of worker functions and worker traits; these procedures are described in chapter 6. Little is known about the validity and reliability of these DOT indicators: what attributes of jobs they actually measure, how accurately they measure them, and how consistent the measurements are. A description of the variables and their scoring is shown in Table 7-8. VALIDITY Concern about the validity of the DOT'S ratings of worker functions and worker traits arises for a number of reasons. First, the factors represented by this set of variables are vague and ambiguously defined. It is not readily apparent what the variables are intended to measure. Worker functions, for example, are said to "express the total level of complexity of the job- worker situation" (Handbook, p. 5), but "complexity" is never defined or further specified. Sidney Fine, who was instrumental in developing the worker functions, has written that they reflect estimates of skill (Fine,

An Assessment of DOT as a Source of Occupational Information 165 TABLE 7-S The DOT Occupational Characteristics, Fourth Edition Variable Label Description a Scoring Worker functions DATA complexity of function in relation to data O to 6 b PEOPLE complexity of function in relation to people O to 8 b THINGS complexity of function in relation to things O to 7 b Training times GED general educational development 1 to 6 svP specific vocational preparation 1 to 9 Aptitudes INTELL VERBAL NUMER SPATIAL FORM CLERICAL MOTOR FINGDEX MANDEX EYEHAND COLORDIS Temperaments intelligence verbal aptitude numerical aptitude spatial perception form perception clerical perception motor coordination finger dexterity manual dexterity eye-hand-foot coordination color discrimination direction, control, and planning feelings, ideas, or facts influencing people sensory or judgmental criteria measurable or verifiable criteria dealing with people repetitive or continuous processes performing under stress set limits, tolerances, or standards variety and change 0/1 0/1 0/1 0/1 0/1 0/1 0/1 0/1 0/1 0/1 1 to4b 1 to5b 1 to5b 1 to5b 1 to5b 1 to5b 1 to5b 1 to5b 1 to5b 1 to5b 1 toSb pop FIF INFLU SJC MVC DEPL REPCON PUS STS VARCH Interests DATACOM communication of data versus activities with things scientific and technical activities versus business contact abstract and creative versus routine, concrete activities activities involving processes, machines, or techniques versus social welfare activities resulting in tangible, productive satisfaction versus prestige, esteem -1 to 1 d SCIENCE ABSTRACT MACHINE TANGIBLE -1 to Id -1 to 1d -1 to 1d -1 to 1d Physical demands STRENGTH lifting, carrying, pulling, pushing 1 to 5 CLIMB climbing, balancing 0/1 Continued overleaf

166 TABLE 7-8 (continued) WORK, JOBS, AND OCCUPATIONS Variable Label Description a Scoring STOOP stooping, kneeling, crouching, crawling 0/1 REACH reaching, handling, fingering, feeling 0/1 TALK talking, hearing 0/1 SEE seeing 0/1 Working conditions L=ATION outside working conditions 1 to 3 COLD extreme cold 0/1 HEAT extreme heat 0/1 WET wet, humid 0/1 NOISE noise, vibration 0/1 HAZARDS hazardous conditions 0/1 ATMOSPHR fumes, odors, dust gases, poor ventilation 0/1 a Descriptions are taken from the [handbook for Analyzing Jobs (U.S. Department of Labor, 1972). b High scores correspond to low values. c Level 5 is not assigned on this aptitude because it is assumed that every job requires at least a '4.' (Source: Handbook for Analyzing Jobs ( 1972: 294).) Interest variables are sets of bipolar contrasts: O corresponds to presence of neither interest in pair; - 1 corresponds to presence of second interest in pair; 1 corresponds to presence of first interest in pair. 1968a:374) and worker autonomy, i.e., the extent to which workers are engaged in "prescribed versus discretionary duties" (Fine, 1968b:7~. Complexity, skill, and autonomy are probably interrelated attributes of jobs, but presumably they are not identical. The precise meaning of the "training times" variables is equally unclear. The validity of these variables general educational development (GED) and specific vocational preparation (svP) has been called into question by the extremely high correlations (of the order of .7-.9) between them and measures of the social status or prestige of occupations. Several researchers have suggested that correlations of this magnitude raise doubts about whether these factors accurately measure the functional requirements of jobs or whether they simply measure an occupation's social standing (Duncan et al., 1972; Siegel, 1971~. Alternatively, it could be argued that since status or prestige are based on functional requirements (Treiman, 1977: chap. 1), high correlations are an indication of the validity of these variables. That such alternative interpretations are possible is an indication of the lack of precision in the definition of these variables.

An Assessment of DOT as a Source of Occupational Information . 167 The "aptitudes," "interests," and "temperaments" traits reflect a theory of vocational preference for which the empirical support is weak. The idea that the adequate performance of particular jobs requires workers with certain traits may seem reasonable enough, but the constancy of such traits as attributes of individual personality has not been adequately established in general and, in particular, with respect to the traits included in the DOT. For a more extended discussion of this point, see chapter 8.) Finally, the working condition and physical demand variables obviously were designed with unskilled factory and physical laboring jobs mainly in mind. As a consequence, they appear not to capture adequately the full range of variability in the working conditions and physical demands of jobs, omitting, for example, distinctions between machine-paced and worker-paced jobs, routine versus nonroutine jobs, etc. One wonders whether the same indicators would be used in devising new scales to measure the working conditions and physical demands of the range of jobs performed today. These factors and the scales used to rate them were developed in the 1950s on a sample of occupations that were found predominantly in manufacturing industries. The indicators represent a combination of measures taken from several sources, and the details of their development for use in the DOT are not well documented. The worker functions, for example, are an extension and refinement of a classification scheme developed in Great Britain after World War II to facilitate demobilization (International Labour Office, 1952~. The aptitude items were chosen to correspond to those available from the General Aptitude Test Battery used by the U.S. Employment Service to screen and profile applicants (Dvorak, 1947~. The interest items were adapted from work by Cattle (1950) in an extension of earlier work by Strong (1943) and others. The GED was designed in house by the staff of the Division of Occupational Analysis in recognition of the need to measure training requirements independently of educational credentials or certification. Although the GED scale was validated in the 1960s against school curriculum content, no attempt was made to validate it against any external criterion related to occupational performance. Changes in the occupational structure and related institu- tions since the development of these scales, e.g., a shift from a predominantly manufacturing to a service economy and changes in school curricula, may have undermined the capacity of these scales to measure the content and requirements of jobs accurately, especially jobs that have recently emerged or changed. Moreover, substantial advances in psychometric scaling techniques (Nunnally, 1967) and also in the theory of vocational preference (see

168 WORK, JOBS, AND OCCUPATIONS chapter 8) are not reflected in the DOT worker traits and worker functions. Rather, they are frozen in a now outmoded mold. Scales that more or less adequately reflected the state of the art of vocational trait measurement at midcentury are now outdated. This condition serves to underscore the urgency of adopting a new strategy in producing the DOT that includes as an intrinsic aspect continuous research and technical improvement of the document as a whole and of each of its components. RELIABILITY These same considerations undercut the reliability of the worker trait and worker function ratings. As noted in chapter 6, these variables were scored for each occupation on the basis of the subjective ratings made by one or several job analysts. Analysts themselves reported difficulty in assigning scores on certain factors, especially svP and aptitudes. The reasons cited for this were the ambiguity of the factors and the inadequacy of the instructions contained in the Handbook for Analyzing Jobs (U.S. Depart- ment of Labor, 1972~. Furthermore, production of the fourth edition DOT was highly decentralized. Analysts were spread across 10 field centers and 1 special project, and there was reportedly little communication or coordination of effort among them, nor were their activities closely supervised by the national office. In developing new scales or adapting existing scales for use in the third edition DOT, the occupational analysis staff made various checks of the reliability of analysts' ratings of these traits; to a lesser extent, checks of the validity of the ratings were made as well. Most of these studies were conducted using small samples of jobs and raters, and the results were not published, even for internal distribution within the Division of Occupa- tional Analysis. Prior to publication of the third edition, however, a major study of ratings of 4,000 of the most frequently occurring jobs was conducted. For the study, eight highly trained analysts at the national office of the occupational analysis program rated occupations on a variety of character- istics, using DOT definitions and job descriptions written by analysts in the field on the basis of on-site observations. These ratings, based on descriptions only, were compared with ratings made by eight analysts who observed and rated similar jobs on site. Results for ratings of aptitudes show that the median correlation between the average ratings of the two groups across all 10 aptitudes was .90. In addition, interrater reliabilities ranging from .74 to .96 were obtained for the national office analysts (Trattner et al., 1955~. Although

An Assessment of DOT as a Source of Occupational Information 169 the validity of the ratings was found to be rather low when they were compared with test scores for the GATE, this result was ignored by those designing the collection of worker trait data for the third edition DOT. Attention was focused on the reliability exercise, which was more encouraging. The high degree of correspondence between the ratings made on the basis of job descriptions and those based on direct observations was taken as evidence that ratings could be assigned using job descriptions only. Thus for the third edition DOT, ratings were assigned primarily by national headquarters personnel using job descriptions only, with some assistance from the field center staff. The fourth edition saw a change in the procedures used to rate jobs and occupations for the DOT. As noted in chapter 6, field center analysts not only collected job data and wrote descriptions but also rated each job with respect to the worker trait and worker function characteristics. In addition, field analysts were responsible for assigning ratings to the occupational composites contained in the DOT, formerly a task of the national office. Despite changes in the rating procedure, no checks appear to have been made of the validity and reliability of the ratings during the course of fourth edition production. Their validity is a complex issue not easily addressed by us with the means at hand, beyond what we have said above. We were able, however, to assess the reliability of the ratings. A complete description of this exercise appears in Appendix E; here we briefly summarize the exercise and the main results. We asked experienced analysts at 7 field centers to rate 24 job descriptions with respect to DATA, PEOPLE, THINGS, 3 components of GED, svP, 6 physical demand factors, and 7 environmental conditions. Job descriptions were taken verbatim from job analysis schedules prepared for the fourth edition. Thus the rating task closely replicated the procedures used to assign scores for the third edition but was an imperfect simulation of the procedures by which ratings for the fourth edition were actually generated. An exact replication of the fourth edition procedure (comparing ratings made on site) was beyond the scope of our project. Our design enabled us to separate the effect of six potential influences on ratings: the occupation being rated, the GED level of the occupation (four groups), the job type (whether manufacturing or service), the job description used to represent the occupation (each occupation was represented by two descriptions), the field center of the rater (one of seven), and the individual analyst within the field center (one of six). Reliabilities were calculated under three assumptions. The "minimum" estimate treats variance associated with the occupation rated, the GED level, and the job type as legitimate and the variance associated with the

170 WORK, JOBS, AND OCCUPATIONS TABLE 7-9 Reliability Estimates for Selected DOT Variables lob Description Rater Minimum a Medium b Maximum c Effect Effects Variable (1) (2) (3) (2) - (1) (3) - (2) DATA .84 .85 .90 .01 .05 PEOPLE .80 .87 .91 .07 .04 THINGS .25 .46 .65 .21 .19 GED-REASON .75 .82 .88 .07 .06 GED-MATH .58 .61 .85 .03 .24 GED-LANGUAGE .67 .71 .90 .04 .19 svP .76 .80 .92 .W .12 STRENGTH .34 .54 .73 .20 .19 LOCATION .64 .66 .76 .02 .10 Average .63 .70 .83 .07 .13 a Reliability assuming that job type (manufacturing versus service), GED level, and occupation (within GED level by job type) are the only legitimate sources of variation in ratings. b Reliability assuming that in addition to the above, the description rated (one of two per occupation) is a legitimate source of variation in ratings. c Reliability assuming that in addition to the above, variance due to differences among field centers and among analysts within field centers are legitimate sources of variation in ratings. SOURCE: See Appendix E. remaining factors as error. The "medium" estimate treats the job description rated as an additional legitimate source of variation in ratings. The "magnum" estimate treats differences between raters and field centers as additional legitimate sources of variation. The usefulness of this approach is that the difference between the estimates can be interpreted substantively: the difference between the medium and minimum estimates is the error introduced by the fact that one job description rather than another is rated; and the difference between the maximum and medium estimates is the error introduced by the fact that raters differ from one another in the way they assign ratings. Table 7-9 shows the three reliability estimates and the differences between estimates for each of nine variables. First, it can be noted that the estimated reliabilities are not very high. The average minimum estimate is only .63, and the average medium estimate is .70 (it is not sensible to interpret the maximum estimates directly; they are used only to derive rater effects). Second, some variables are much more reliably rated than

An Assessment of DOT as a Source of Occupational Information 171 others. In particular, the THINGS and STRENGTH variables are very unreliably estimated. In large part this is due to the fact that ratings of these factors vary substantially depending on which description is rated, whereas the description has less influence on the ratings of the other factors. It is not clear, however, whether jobs vary more widely in their complexity with respect to things and in their strength requirements than in their other characteristics or whether the descriptions are simply less adequate with respect to these two characteristics than with respect to the other characteristics. These results do suggest, however, the importance of adequately sampling jobs within each occupation. Although the "job description" erect is largest for the THINGS and STRENGTH factors, it is also not trivial for a number of other factors, which means that the ratings of occupations (and presumably occupational descriptions as well) are likely to vary substantially, depending on which particular job is chosen to represent the occupation. One way to overcome this is to average the ratings (and descriptions) of several jobs to form a composite occupational description and set of worker function and worker trait scores. Of course, the optimal solution would be to redesign the classification structure to reduce heterogeneity among the jobs included in each occupational category. Inspecting the last column of Table 7-9, we see that rater effects are even larger on the average than job description effects. Fortunately, we know from the extended analysis in Appendix E that rater effects are almost entirely attributable to differences among individual raters rather than to systematic differences among field centers. This suggests a simple remedy. Each job description should be independently rated for worker traits and worker functions by several analysts. (Appendix E gives estimates of the number of raters needed to achieve specified levels of reliability.) In a second analysis we calculated reliabilities separately for manufac- turing and service occupations. Considering the historical concentration of the DOT on manufacturing jobs, in particular, the emphasis on features of manufacturing jobs in the development of the worker trait variables, we suspected that these variables might be more reliably measured for manufacturing than for service jobs. As Table 7-10 shows, this proved to be the case, with the single exception of the STRENGTH scale. The result for the STRENGTH scale is quite anomalous and suggests that this variable needs to be redesigned or abandoned. More generally, the lower reliablity in the rating of characteristics of service jobs lends credence to the conjecture that the worker function and worker trait scales will become increasingly ill suited to measuring the job content of the American economy as the labor force shifts away from manufacturing jobs, since it is likely that the characteristics of clerical, sales, managerial, and profession

172 WORK, JOBS, AND OCCUPATIONS TABLE 7-10 Estimated Reliabilities, by Type of Occupation a Characteristic b Service Manufacturing DATA r (minimum) .694 .880 r (medium) .727 .889 r (maximum) .798 .918 PEOPLE r (minimum) .666 .908 r (medium) .795 .933 r (maximum) .830 .972 THINGS r (minimum) .107 .186 r (medium) .329 .406 r (maximum) .632 .637 GED-REASON r (minimum) .652 .694 r (medium) .717 .794 r (maximum) .792 .888 GED-MATH r (minimum) .422 .629 r (medium) .431 .682 r (maximum) .771 .878 GED-LANGUAGE r (minimum) .552 .690 r (medium) .609 .739 r (maximum) .853 .862 svP r (minimum) .724 .768 r (medium) .739 .834 r (maximum) .873 .925 STRENGTH r (minimum) .435 .138 r (medium) .594 .495 r (maximum) .724 .705 a Reliabilities are calculated under three different assumptions about sources of error. See Table 7-9. b Reliabilities for the LOCATION scale could not be calculated separately for service and manufacturing occupations because there was no variation on this scale for the manufacturing occupations.

An Assessment of DOT as a Source of Occupational Information 173 al jobs will also be less reliably measured than the characteristics of manufacturing jobs. In addition to the variables discussed above, five physical demands and six environmental conditions were rated. Since these variables are all dichotomous, a different approach was required, described in Appendix E. It is sufficient to note here that the results closely paralleled those we have already reviewed: consistency among raters was only moderate, was much greater for some variables than for others, and was generally lower for service than for manufacturing occupations. In sum, this exercise strongly suggests that the reliability and consisten- cy of the rating of worker functions and worker traits should and can be substantially improved and that this could be quite simply accomplished by adopting standard psychometric procedures involving the rating of multiple job descriptions for each occupation independently by several analysts each. In addition, those variables with particularly low reliability should be reviewed with an eye to improving the reliablity of their measurement. Finally, consideration should be given to the development of multiple-item scales to measure occupational characteristics. We shall have more to say about this below in our discussion of a factor analysis of the worker function and worker trait variables. OCCUPATIONAL CHARACTERISTICS Despite the problems of validity and reliability identified above, the DOT worker functions and worker traits constitute one of the richest sources of occupational data available anywhere. We have already noted (in chapter 4) the wide variety of uses made of these data. As an aid to researchers contemplating further use of these data, we report in this section the results of a number of analyses that investigate the distributional properties of these variables and the interrelationships among them. Data used in the analyses were supplied by the national office of the Division of Occupational Analysis. A DOT summary tape made available to us provided data on DOT codes, worker functions, and worker traits for the 12,099 base title occupations in the DOT. The following analyses are based on a 10-percent random sample of these titles. The definitions and scoring of the worker functions and traits are described in Table 7-8. Table 7-11 presents descriptive statistics for each DOT variable. Note that these statistics pertain to the population of occupations included in the DOT and not to individuals in the labor force. Insofar as the labor force is unevenly distributed over occupational categories, the occupational characteristics of workers would be expected to differ from the characteris- tics of occupations, but we have not systematically investigated the extent

174 WORK, JOBS, AND OCCUPATIONS TABLE 7-1~ Descriptive Statistics for Fourth Edition DOT Occupational Characteristicsa Variable Label bMean SDKurtosisSkew Range Worker functions DATA4.11 2.09-1.40-0.47 6 PEOPLE6.83 1.851.90-1.63 8 THINGS4.32 2.31-1.27-0.28 7 Training times GED3.00 1.09-0.450.12 5 svP4.46 2.06- 1.260.23 8 Aptitudes INTELL3.19 0.720.31-0.65 3 VERBAL3.43 0.780.83-1.17 4 NUMER3.63 0.780.43-0.49 4 SPATIAL3.47 0.710.37-0.77 4 FORM3.36 0.67-0.30-0.53 4 CLERICAL3.89 0.79-0.28-0.36 3 MOTOR3.46 0.56-0.79-0.24 3 FINGDEX3.56 0.610.30-0.88 4 MANDEX3.21 0.530.720.32 4 EYEHAND4.67 0.602.89-1.80 4 COLORDIS4.52 0.701.85-1.42 4 Temperaments c pop0.18 0.38-- 1 FIF0.01 0.10-- 1 INFLU0.04 0.20-- 1 sac0.17 0.38-- 1 MVC0.39 0.49-- 1 DEPL0.23 0.42-- 1 REPCON0.46 0.50-- 1 PUS0.02 0.16-- 1 STS0.60 0.49-- 1 VARCH0.20 0.40-- 1 Interests DATACOM-0.57 0.660.271.23 2 SCIENCE-0.12 0.451.40-0.49 2 ABSTRACT-0.47 0.53-1.250.21 2 MACHINE0.62 0.550.08-1.05 2 TANGIBLE-0.05 0.471.50-0.18 2 Physical demands c STRENGTH2.39 0.91-0.150.42 4 CLIMB0.08 0.27-- 1 STOOP0.20 0.40-- 1 REACH0.89 0.31-- 1 TALK0.29 0.45-- 1 SEE0.57 0.49-- 1

An Assessment of DOT as a Source of Occupational Information 175 TABLE 7-~1 (continued) Variable Label. Mean SD Kurtos~s Skew Range Working conditions c LOCATION 1.22 0.56 4.41 2. ~2 COLD 0.01 0.08 - - 1 HEAT 0.05 0.21 - - 1 WET 0.07 0.25 - - 1 NOISE 0.29 0.45 - - 1 HAZARDS 0.15 0.35 - - 1 ATMO6PHR 0.12 0.33 - - 1 a Based on 10-percent random sample of Dar occupations, N- 1,172. b For variable descriptions and scoring, see Table 7-8. c Kurtos~s and skew coefficients are not presented for dichotomous variables. Of the difference. The average occupation in the DOT involves relatively low levels of complexity: computing data, serving people, and manipulat- ing things. The average occupation requires GED at the level of being able to solve practical problems, perform simple algebra, and read newspapers and novels. Six months to a year of svP is typically needed, as are aptitudes at levels presumed to be possessed by the middle-to-lower third of the population of workers. Adaptability to working with measurable or verifiable criteria, with set limits, tolerances, or standards and with repetitive, continuous processes is a significant requirement of more than a third of the occupations contained in the DOT. Most occupations are also characterized by interest in working with things and machines and in routine activities, and most also involve reaching and seeing. Arduous physical activities or noxious working conditions, however, are present in a relatively small proportion of occupations. An inspection of the means of the dichotomous variables (tempera- ments, physical demands, and working conditions except STRENGTH and LOCATION) indicates that some of the DOT characteristics occur with low frequency (the mean of a dichotomy is the proportion positive). The temperaments involving feelings, ideas, or facts, influencing people, and performing under stress are required in fewer than 10 percent of all occupations, for example, as are the physical demands involving climbing and exposure to cold, heat, and wetness. The aptitude variables have particularly small standard deviations, indicating limited variance on these traits as well. In addition, the range of two of the aptitudes, CLERICAL and MOTOR, iS small: no occupations are scored as requiring the highest

176 WORK, JOBS, AND OCCUPATIONS aptitude level. An inspection of the frequency distributions of the aptitude variables (not shown) reveals that even for those for which the range is not restricted, cases are highly concentrated in one or two of the available five levels. In line with this, data in the third and fourth columns of Table 7-11 indicate that many of the variables exhibit markedly nonnormal distribu- tions. The skewness and kurtosis coefficients presented in these columns are measures of the degree to which a distribution approximates a normal curve. Skewness is a measure of the symmetry of the distribution; kurtosis measures the flatness or peakedness of the curve. Both coefficients equal zero for normal distributions. The distributions of the PEOPLE worker function; the VERBAL, EYEHAND, and COEORDIS aptitudes; the DATACOM and MACHINE interests; and the LOCATION working condition are particularly skewed. On PEOPLE, for example, 63 percent of all occupa- tions are rated at the lowest level, taking instructions-helping, causing the distribution to have a pronounced peak at its extreme tail. The variables DATA, PEOPLE, THINGS, SVP, EYEHAND, ABSTRACT, TANGIBEE, and LOCATION exhibit distributions that are markedly more peaked or flatter than normal, with kurtosis coefficients larger than 1 in absolute value. Among the variables that are not dichotomous, the remaining distribu- tions, notably GED, more closely approximate normality. The distributional characteristics just presented raise several issues worthy of additional consideration. Assuming that the DOT variables accurately reflect the dimensions of an occupation that they are intended to measure, one might ask whether there is a need for analysts to rate occupations for traits that seldom occur or for traits that always occur, i.e., traits that never vary. In some cases, of course, the traits are important attributes of the jobs they characterize, even if such jobs are rare. Working conditions involving extreme cold, heat, or wetness would be of this type. In other cases, such as for many of the temperaments, however, the traits are of little practical interest to job applicants and are useful mainly for research purposes. In such cases the limited variation of highly skewed variables is a matter of considerable importance since it reduces the discriminatory power of these variables. This suggests the need to look into the scaling properties of these measures, which are largely unknown. THE FACTOR STRUCTURE Each of the 44 DOT variables is supposed to reflect a distinct occupational characteristic. Several researchers (Spenner, 1977; Temme, 1975) have noted, however, that many of the variables appear to measure nearly identical phenomena, as evidenced both by the content of the items (Table

An Assessment of DOT as a Source of Occupational Information 177 7-8) and by the high degree of intercorrelation among them (Table 7-12~. In order to determine the underlying dimensions tapped by the full set of DOT variables, we factor-analyzed the 44 DOT variables (using the sPss computer program for principal components with iterations and varimax rotation) for a 10-percent random sample of DOT occupations (N = 1,172~. Six interpretable factors emerged. Factor loadings for the analysis are shown in Table 7-13. Generally, .40 was chosen as the cutoff point for including an item in a factor. By this criterion a number of items did not load on any factor. If on closer inspection these items had factor loadings between .30 and .40 on a given factor and if they corresponded in content to other items on the factor, the decision rule was relaxed, and these items were included in the list of items defining the factor. The six orthogonal factors that emerged account for 95 percent of the common variance in the correlation matrix. The item composition of each of the factors plus factor loadings and the percentage of variance explained by each are given in Table 7-14. The first factor (Table 7-14) accounts for 49 percent of the total shared variance and consists of 17 items with loadings greater than .40. An inspection of the items suggests that this factor reflects the substantive complexity of work, as witnessed by the high loadings of the training variables GED and svP; the worker functions DATA and PEOPLE; and the aptitudes INTELL, NUMER, and VENAL. The loadings of the temperament variables REPCON and VARCH also reinforce the interpretation of this factor as reflecting the complexity of tasks and routines entailed in occupations. The second factor accounts for 23 percent of the shared variance. The high loadings of the variables FINGDEX, MANDEX, REACH, and SEE as well as those of the machine-related THINGS and MACHINE variables clearly indicate that this factor reflects the motor or sensory skills required by occupations. The third factor, which accounts for 10 percent of the shared variance, also taps a dimension of the physical requirements of jobs, but the high positive loadings of the variables LOCATION, STOOP, CLIMB, and STRENGTH coupled with the negative loading of EYEHAND indicate that this factor reflects the arduous physical requirements of occupations, i.e., those characterized more by brawn than by fine motor skills. The fourth factor accounts for only 5 percent of the shared variance, but the items that load strongly on it clearly represent the organizational or administrative components of occupations such as dealing with people (DEPL and PEOPLE) and directing or planning (DCP). It should be noted that factors 1 and 4 share a number of items in common (DATA, PEOPLE, pop, DATACOM, and TALK), a fact that indicates that there is a close

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184 WORK, JOBS, AND OCCUPATIONS TABLE 7-13 Factor Loadings: Varimax Rotated Factor Matrix a Factor Variableb 1 2 3 4 5 6 DATA .81 .06-.02 .44 .17-.05 PEOPLE.47-.05 .02 .70 .17 -.01 THINGS.31.66 .06 -.15 -.16 .13 GED.86.12 -.04 .26 .21 -.01 SVP.86.22 .02 .27 .09 .05 INTEEE.83.07 -.03 .14 .26 -.00 VERBAL.76-.04 -.08 .29 .33 -.11 NUMER.78.09 -.09 .18 .05 -.01 SPATIAL.55.47 .16 -.03 .05 .03 FORM.46.52 -.07 -.07 .07 .01 CLERICAL.64-.04 -.19 .27 .03 -.11 MOTOR.02.68 .07 -.04 -.03 -.08 F! NG DEX. 16.69 -.08 -.10 .08 -.21 MANDEX-.13.67 .13 -.16 -.07 -.00 EYEHAND-.05.17 .52 .03 -.04 -.03 COEORDIS.28.28 -.00 -.04 .17 .06 DATACOM.41-.14 -.12 .49 .37 -.15 SCIENCE-.02.21 .10 - .57 -.08 -.01 ABSTRACT.68.11 .04 .19 .28 -.06 MACHINE-.05.33 .01 -.24 -.37 .26 TANGIBLE-.10.27 .1 2 - .63 .1 3 -.04 pop.43-.09 -.02 .74 .04 .00 FIF.10.06 -.05 .01 .41 .01 INFEU.15-.12 -.08 .17 .41 -.05 S]C.31-.05 .09 .07 .51 -.00 MVC.64.19 .03 -.10 -.27 .03 DEPE. 39-.16 -.06 .78 .18 -.08 REPCON-.81-.04 -.03 -.17 -.08 .03 PUS.03.05 .1 3 .06 .07 .07 STS.13.37 -.12 -.39 -.31 .16 VARCH.42.06 .13 .40 -.05 -.06 STRENGTH-. 30.06 .48 -.16 -.04 .30 CLIMB.08-.02 .49 -.06 -.04 .28 STOOP-.03.05 .53 -.11 .03 .20 REACH-.34.42 .12 -.33 -.21 .11 TALK.44-.11 -.01 .64 .21 -.08 SEE.24.43 .01 -.10 -.06 .08 LOCATION.08-.03 .67 .03 -.03 -.00 COED.04-.02 .01 .00 .02 .15 HEAT-.01-.03 -.03 -.05 -.01 .37 WET-.06-.07 .18 -.03 .02 .22 NOISE-.12.14 .19 .03 -.15 .26 HAZARDS-.03.08 .29 -.04 -.07 .52 ATMOSPHR-.05.05 .14 .02 -.05 .42

An Assessment of DOT as a Source of Occupational Information 185 TABLE 7-13 (continued) Factor Variables 1 2 3 4 s 6 Eigenvalue 10.86 4.98 2.18 1.20 1.09 0.63 Percentage variance 49.30 22.60 9.90 5.40 4.90 2.90 Cumulative percentage 49.30 72.00 81.90 87.30 92.20 95.10 a Factor loadings greater than or equal to .4 are in boldface. b Where necessary, scores on variables were reflected so that high scores represent high levels of the trait. relationship in the DOT between the substantive complexity of occupations and their managerial responsibilities. The fifth and sixth factors account for 5 and 3 percent of the shared variance in the matrix, respectively. Factor 5, which is composed of only 4 items, might be labeled "interpersonal skills." An inspection of the items' content reveals that this dimension involves working with feelings and ideas and sensory or judgmental criteria and that it involves influencing people and dealing with their social welfare. The sixth factor, although it accounts for only 3 percent of the variance, is readily interpretable as reflecting undesirable aspects of the working conditions of occupations. By and large, the results of this factor analysis are straightforward. Several variables did load on more than one factor: as noted, there is some overlap between factors 1 and 4; factors 1 and 2 also share two items in common. Only five variables (COLORDIS, PUS, COLD, WET, and NOISE), failed to load significantly on any of the factors. Of these five variables, all but COLORDIS are dichotomous variables with limited variance. The variable COLORDIS (occupations requiring an aptitude for color discrimina- tion) appears to tap a unique occupational dimension. Presumably, many occupations require similar special aptitudes, but since each aptitude is probably required of only a few occupations, it would be preferable to include such information as part of the occupational definition. These results can be interpreted in two ways. The most straightforward interpretation is simply that there is a great deal of redundancy among DOT indicators. Alternatively, the factor patterns just presented could result from the procedures used in making DOT ratings. In rating occupations for these traits, occupational analysts might have forced consistency among them. It is true that many of the functions and traits appear to tap nearly identical phenomena (e.g., GED and INTELL). However, it is also the case that the way in which the ratings were made-

186 WORK, JOBS, AND OCCUPATIONS TABLE 7-14 Factor Analysis of Fourth Edition DOT Occupational Characteristics: Items and Loadings for Six Major Factors Variable Label description Loading Factor 1: substantive complexity, 49.3 percent a GED general educational development svP specific vocational preparation INTELL DATA REPCON NUMER VERBAL ABSTRACT MVC CLERICAL SPATIAL PEOPLE FORM TALK pop VARCH DATACOM intelligence b complexity of functioning with data b repetitive or continuous processes numerical aptitude b verbal aptitude b abstract and creative versus routine, concrete activities measurable or verifiable criteria clerical perception b spatial perception b complexity of functioning with people b form perception b talking direction, control, and planning variety and change communication of data versus activities with things Factor 2: motor skills, 22.6 percent a FINGDEX finger dexterity b MOTOR motor coordination b MANDEX manual dexterity b THINGS FORM SPATIAL SEE REACH STS MACHINE complexity of functioning with things b form perception b spatial perception b seeing reaching set limits, tolerances, or standards activities involving processes, machines versus social welfare Factor 3: physical demands, 9.9 percept a LOCATION outside working conditions STOOP stooping, kneeling, crouching, crawling EYEHAND CLIMB STRENGTH eye-hand-foot coordination b climbing, balancing lifting, carrying, pulling, pushing Factor 4: management, 5.4 percept a DEPL dealing with people pop direction, control, planning PEOPLE complexity of functioning with people b TALK talking .86 .86 .83 .81 .81 .78 .76 .68 .64 .64 .55 .47 .46 .44 .43 .42 .41 .69 .68 .67 .66 .52 .47 .43 .42 .37 .33 .67 .53 .52 .49 .48 .78 .74 .70 .64

An Assessment of DOT as a Source of Occupational Information 187 TABLE 7-14 (continued) Variable Label Description Loading SCIENCE DATA TANGIBLE activities resulting in tangible satisfaction versus prestige scientific, technical activities versus business contact DATACOM communication of data versus activities with things complexity of functioning with data b Factor 5: interpersonal skills, 4.9 percept a sac FIF IN FLU sensory or judgmental criteria feelings, ideas, facts influencing people MACHINE activities involving processes, machines versus social welfare Factor 6: undesirable working conditions, 2.9 percent a HAZARDS hazardous conditions ATMOSPHR fumes, odors, dust, poor ventilation HEAT extreme heat 63 57 .49 .44 .51 .41 .41 37 .52 .42 .37 a Percentage of common variance explained. b Sign reflected on this variable. all ratings assigned at one time by a single analyst-could have inflated the degree of consistency among the scores for each occupation and hence the degree of correlation between variables measured over occupations. This is called a "halo effect," the tendency of one judgment to be affected by another. It is well known that when several ratings are made at a single time by a single judge, they tend to be more consistent than when the ratings are made independently of one another (Selltiz et al., 1959:351- 352~. Evidence that the rating procedure itself is an important source of the high degree of interrelationship among the DOT variables is offered by the results of a similar factor analysis performed by using third edition data (Barker, 1969~. For the third edition, different analysts rated each of the traits: one analyst rated occupations for aptitudes, another for tempera- ments, etc., a procedure that would mitigate the tendency to force consistency among the ratings. In an analysis of third edition ratings, Barker found that 11 factors emerged and that the factor loadings, commonalities, and percentage of common variance explained were all much lower than the estimates presented here. Although other reasons could account for the differences between his findings and ours (e.g., differences in the underlying distribution of occupations), the suspicion is strong that the differences are attributable to the change in the rating

188 WORK, JOBS, AND OCCUPATIONS procedures from the third to fourth edition, that is, that the high covariation among the worker functions and worker traits is an artifact at least in part of the procedures used to rate DOT occupations. If this is so, these findings suggest that a modification of current rating procedures is needed along with a careful examination of the content of the items themselves. These results suggest that the more reliable indicators of the features of occupations tapped by the worker traits and worker functions variables could be created by developing factor-based multiple-item scales to represent the various dimensions revealed by the factor analysis. Such scales would have the advantage of greater internal reliability and consistency than single indicators or scales created by simple summing of items without knowledge of their factor structure. In Appendix F we present scores for scales constructed in this way for the categories of the 1970 U.S. Census detailed occupational classification. SEX BIAS IN THE RATING OF OCCUPATIONS Recently, the DOT has come under attack for alleged sex bias. It has been claimed that in the third edition DOT both the occupational descriptions and the ratings of occupational characteristics undervalued jobs held mainly by women (Wits and Naherny, 1975~. In particular, it has been asserted that third edition ratings of the complexity of work in relation to data, people, and things reflect traditional stereotypes regarding the relative complexity of the kinds of jobs typically held by women and those typically held by men (Wits and Naherny, 1975~. Consideration of a few examples is sufficient to legitimate the charge of sex bias in the third edition. In it the DATA, PEOPLE, and THINGS variables included as the lowest response level a judgment that an occupation had "no significant relationship" to data, people, or things. Typist, a job held mainly by women, was coded as having no significant relationship to things, whereas Typesetting-Machine Tender, a job held mainly by men, was coded at a higher level of complexity. Such jobs as Nursery School Teacher and Practical Nurse were coded as having minimal or no significant relation- ship to data, people, and things, while such jobs as Dog Pound Attendant were rated as functioning at a higher level of complexity. According to informants in the national office the no significant relationship category for the worker functions was dropped in the fourth edition in response to the charge of sex bias in the third edition. Occupations that had been scored at the lowest complexity levels in the third edition were assigned new worker function scores. In addition, in

An Assessment of DOT as a Source of Occupational Information 189 some instances other scores were changed, presumably to reflect changes in job content or to correct other errors in the third edition. In order to document the changes made between the third and fourth editions and to determine whether the ratings of occupations commonly pursued by women had been upgraded as claimed, we conducted an analysis of third and fourth edition worker function ratings. This was done by utilizing the April 1971 Current Population Survey (cPs) of a representative sample of the labor force. This data set contains, among other variables, both the third and fourth edition DOT codes for the job held at the time of the survey and the sex of each worker. The cPs data set includes data for 60,441 members of the labor force. Third edition DOT codes were assigned to each occupational response by trained occupational analysts in the occupational analysis field centers. Fourth edition codes were subsequently added to the data, using a map prepared by the Division of Occupational Analysis that related fourth edition DOT codes to third edition codes. By comparing third and fourth edition scores on the DATA, PEOPLE, and THINGS variables separately for men and women, we can determine the effect of scoring changes between the third and fourth editions on the relative status of male and female workers. Note that our sample for this analysis is composed of workers, not jobs. However, neither workers nor jobs changed, only the classification of jobs in the DOT scheme and hence the scoring of the worker function variables. An analysis of the nature of these changes permits an indirect inference about the extent of sex bias remaining in the fourth edition DOT. We begin by considering the labor force as a whole (see Table 7-15~. In 1971, about a third of both the male and female labor force were in occupations that were judged in the third edition to have no significant relationship to data. In contrast, a much larger proportion of men than women were in occupations having no significant relationship to people, and a much larger proportion of women than men were in occupations with no significant relationship to things. The second line of the table, which gives the mean fourth edition score for occupations with "no significant relationship" in the third edition, shows what happened to these occupations in the fourth edition. On average, the occupations held by men and those held by women were assigned similar scores on the DATA and PEOPLE variables, but on the THINGS variable the occupations held by women were judged to be more complex than the occupations held by men. In short, the major effect of the abolition of the no significant relationship category was to upgrade substantially the complexity in relation to things of occupations held by women. This conclusion is also evident in the "difference in means" row, which shows the difference in the average score between the third and fourth editions. Since a low score

l9o WORK, JOBS, AND OCCUPATIONS means greater complexity, the fact that all the numbers in the row are negative indicates an average upgrading of complexity levels between the third and fourth editions. The only change of substantive importance, however, is the upgrading of occupations held by women on the THINGS variable. The remaining point to note concerning the total labor force is that except for changes required by the abolition of the no significant relationship codes, there were few changes in ratings between the third and fourth editions. More than 90 percent of the scores remained unchanged between the two editions, as perhaps was to be expected, given the way in which DOT occupational data were generated. Inspection of the second section of Table 7-15 allows us to identify a major source of change in the THINGS ratings: the upgrading of clerical and sales jobs held by women. Most clerical and sales jobs (whether held by men or women) were identified in the third edition as having no significant relationship to things. However, the occupations held by women were coded substantially differently on the THINGS variable in the fourth edition from those held by men; on average, the clerical and sales occupations held by women were judged as having much greater complexity than those held by men. No doubt this reflects the greater propensity of female clerical and sales workers than male clerical and sales workers to operate office machines. Whereas in the third edition the task of typing was rated as not involving a significant relationship to things (level 8), in the fourth edition it was rated as involving the "operating- controlling" of things (level 2~. The same sort of coding change was made for a large number of positions involving the operation of office machines. Hence while both clerical and sales occupations held by women and those held by men tended to be upgraded in the fourth edition, the upgrading was much greater for the jobs held by women. Thus on the basis of fourth edition scores the average female clerical and sales worker is scored as doing more complex work in relation to things than the average male clerical and sales worker. In contrast to the clerical and sales sector the service and benchwork sectors included here because they are also large employers of women do not exhibit radically different patterns of upgrading for jobs held by men and those held by women, although they do show significant differences in the proportion of occupations in the third edition with no significant relationship to data, people, and things. What do these results tell us about sex bias in the fourth edition DoT? Although no definitive judgment is possible in the absence of an external criterion of job complexity against which to assess the DOT ratings, the relative similarity in the mean scores for male and female workers is

An Assessment of DOT as a Source of Occupational Information 191 certainly consistent with an inference that these variables are largely bias free. For the total labor force, the means for the DATA variable vary by only about half a point, and the means for PEOPLE and THINGS by even less. Although the means are lower for men, indicating that they work in occupations with greater complexity than those held by women, the size of the differences is within what would be expected from well-known patterns of occupational segregation by sex. Hence there is no reason to believe that the kink! of work women do is undervalued in the fourth edition DOT, at least with respect to the worker function ratings. Of course, the possibility exists that the work that women do is overvalued and that if unbiased scores were available, the mean difference between male and female workers would be even greater. However, this is unlikely, given otter evidence demonstrating that men and women are equally well educated on the average and hold jobs with similar average prestige (Treiman and Terrell, 1975a, b), that the average GED levels of the jobs held by men and by women are virtually identical (the means are 3.14 and 3.20), and that the average svP levels of the jobs held by men and by women differ by only about a half a point (the means are 4.70 and 4.14~. These results imply that the worker function ratings in the fourth edition-but not the third edition-can be used to assess sex differences in occupational attainment without undue distortion (see chapter 4 for a discussion of such analyses). CONCLUSION This chapter deals with two major issues, the adequacy of the source data used to create the DOT and the adequacy of the data on occupational characteristics created in conjunction with the DOT. These issues are, of course, not unrelated, since the adequacy of the source data determines, in part, the adequacy of the resulting occupational characteristics scales. Still, it is useful to consider them separately. The chapter documents the very uneven coverage of the labor force in the basic data collection process. First, the DOT includes many more production process occupations, relative to the number of individuals in the labor force employed in such occupations, than clerical, sales, and service occupations. While it may be that production process occupations are, in fact, more finely differentiated in the economy than are other occupations, there is no evidence that this is so. An equally plausible explanation is that DOT data collection procedures, which tend to concentrate on manufacturing plants, create a bias toward more detailed coverage of production process occupations than of other types of work. At present, there is no way of resolving this question, since there exist no principles for determining the boundaries of occupations and hence no

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194 WORK, JOBS, AND OCCUPATIONS unambiguous procedures for aggregating jobs into occupations. The development of such principles and of procedures for using them in the data collection process should be given high priority in preparation for future editions of the DOT. Second, some occupations in the fourth edition DOT were analyzed many times, while others were not analyzed at all. Given the heterogeneity of jobs included within a single occupational category (which is confirmed by the substantial "job description" effect on the reliability of worker trait and worker function ratings), procedures need to be developed to ensure a more even sampling of jobs within occupations in order to be certain that each occupational description is based on data froin a sufficient number of job analyses to produce representative data. What constitutes an "occupation" and how much heterogeneity in the content of a set of jobs justifies a single occupational title is a difficult question. Historically, the DOT has tended to define occupations by their titles rather than by their content. Jobs with similar titles have been grouped unless the evidence strongly indicated that they differed in content, and occupations with different titles have been defined as being different, regardless of similarity in content. At the same time, each job analysis tends to produce a new DOT occupation, while jobs with titles similar to titles already existing in the DOT tend not to be analyzed at all, making it impossible to determine their degree of similarity. Occupational titles are also used inconsistently in the DOT to define very specific or very heterogeneous groups of jobs. Branch manager, for example, describes a wide variety of jobs, all of which involve coordination and control functions but vary enormously in terms of the specific tasks performed. Tool and Die Maker, by contrast, describes basically the same job regardless of where tool and die makers are employed. Consideration should be given to developing a clear and unambiguous way of defining occupations. The analysis in this chapter also raises serious questions regarding the adequacy of the worker trait and worker function variables. First, it is unclear whether the 46 variables on which data are collected adequately represent the kind of information needed by users within and outside the Employment Service. Our conjecture is that they do not. Many of the DOT variables, especially the aptitudes, interests, and temperaments, are not heavily used, as we have seen in chapters 3 and 4. Oddly, other information collected on job analysis schedules but never subsequently recorded, i.e., information on promotion ladders and lateral transfer routes, is often mentioned by users outside the Employment Service as a major lack in the DOT. Obviously, consideration should be given to the inclusion of such information in the DOT occupational descriptions. More

An Assessment of DOT as a Source of Occupational Information ·95 generally, a careful conceptual review should be undertaken of the sort of information needed for matching workers with jobs (e.g., data on the transferability of skills), for counseling job applicants about occupational requirements, for assessing the comparability of occupations for the resolution of equal employment opportunity disputes (better data on the responsibilities entailed in occupational performance, for example), and for occupational research of various kinds. Once the major dimensions of occupations on which data are needed are identified, scales measuring these dimensions should be developed following standard psychometric practices. In particular, consideration should be given to the development of factor-based multiple-item scales, the use of which would go a long way toward overcoming the reliability problems identified in Appendix E and summarized in this chapter. Despite the deficiencies in the fourth edition worker trait and worker function variables identified here, they remain the most comprehensive set of occupational characteristics currently available. As such, their use should be encouraged. To facilitate this use, Appendix F provides data on eight DOT variables aggregated to match the categories of the 1970 U.S. Census detailed occupational classification and four factor-based scales derived from the DOT variables. Researchers should find these data a useful supplement to data on the average characteristics of workers that can be derived from census occupational statistics. Moreover, one potential major threat to the usefulness of these data can be discounted on the basis of our analysis: so far as we can tell, the fourth edition worker function variables do not undervalue occupations held mainly by women as the third edition worker function variables apparently did.

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Work, Jobs, and Occupations: A Critical Review of the Dictionary of Occupational Titles Get This Book
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Various editions of the Dictionary of Occupational Titles have served as the Employment Service's basic tool for matching workers and jobs. The Dictionary of Occupational Titles has also played an important role in establishing skill and training requirements and developing Employment Service testing batteries for specific occupations. However, the role of the Dictionary of Occupational Titles has been called into question as a result of planned changes in the operation of the Employment Service.

A plan to automate the operations of Employment Service offices using a descriptive system of occupational keywords rather than occupational titles has led to a claim that a dictionary of occupational titles and the occupational research program that produces it are outmoded. Since the automated keyword system does not rely explicitly on defined occupational titles, it is claimed that the new system would reduce costs by eliminating the need for a research program to supply the occupational definitions.

In light of these considerations, the present volume evaluates the future need for the Dictionary of Occupational Titles.

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