TPC-Journal-V5-Issue1

The Professional Counselor /Volume 5, Issue 1 11 the Strong Interest Inventory and many other career assessments, the idea of using this schema to analyze occupational information is more novel. For example, thinking of income levels in terms of the RIASEC schema means using an order of IEASRC per the 2010 census data when discussing occupational information with clients. Reardon et al. (2007) reported that examining levels of cognitive complexity associated with occupations may provide an explanation for the income disparity among the six RIASEC areas. G. D. Gottfredson and Holland (1996) created the Complexity Rating (Cx) to estimate the cognitive skill and ability associated with an occupation. In developing the Cx, the authors wanted to make greater use of job analysis ratings obtained by the U.S. BLS and also create a single measure of cognitive or substantive complexity associated with an occupation. They noted that cognitive complexity of work demands (G. D. Gottfredson & Holland, 1996) might be an appropriate term for the Cx. A Cx rating of 65 or higher could be associated with an occupation requiring a college degree and possibly postgraduate work and on-the-job training of 4–10 years, while a Cx level of 50 might characterize an occupation requiring a high school diploma and a year or more of on-the-job training. Reardon et al. (2007) found that Cx levels were highest in the Investigative and Artistic areas and that the Conventional area was associated with the lowest ratings. They found that employment in the Investigative area occurred only at the highest two levels of Cx (i.e., baccalaureate or higher) while the other four areas— Realistic, Social, Enterprising and Conventional—showed employment at all six levels of Cx. Huang and Pearce (2013) reported that higher annual incomes in 2010 were found in occupations associated with greater Investigative and Enterprising traits. In addition, they found that the differentiation of an occupational interest profile positively predicted median annual income and moderated the effect across each of the six RIASEC areas. In other words, the more the occupation was characterized by a single, robust RIASEC code letter, the greater the income level for the occupation. Reardon et al. (2007) examined income by kinds of work and found that the average income profile for six kinds of work ranging from highest to lowest was IESARC. In the current study, the income profile was almost identical—IEASRC. These findings are very similar to those reported by Huang and Pearce (2013). Given that the Investigative area of work requires more education and training than the other five areas, these findings from census data provide evidence that education pays. Reardon et al. (2012) reported that the unemployment rate is clearly related to educational attainment. Those with more education are less frequently unemployed and have higher weekly earnings—more education is connected to more income. Limitations As with earlier studies (Reardon et al., 2007; Reardon et al., 2004), several limitations in the present study should be noted. First, the occupational titles included in the census have changed only slightly over the years. The U.S. BLS conducts extensive research to determine whether a new occupation should be added to its list of detailed occupations. A new occupation is one that includes duties not previously identified, one that has been recognized in small numbers and continues to grow (e.g., now has its own professional association or trade group), or one that is evolving and whose tasks have changed significantly. These new occupations arise from technological advances, new laws or regulations, or changing demographics. However, we believe that this issue has minimal impact on the findings of the present study because changes in occupational codes are unlikely to affect the first letter of a code. First-letter codes of occupations are much more stable over time and across industries than second or third letters. A second limitation of this study is related to the classification of hundreds of thousands of jobs into 350– 500 occupational categories, which requires considerable judgment and skill by occupational analysts. These