of ways the problem of underrepresentation might be addressed. We think these policy proposals must, however, be informed by a clear understanding of the underlying reasons for the limited numbers of women in IT careers.
the Ku Professional Worker career experience Study
To shed light on how men and women make career choices we conducted four in-depth focus groups with IT professionals in the greater Kansas City area, and then collected detailed information from a sample of over 500 IT and non-IT professionals. Participants in the survey were solicited from employees at several large organizations with offices in the central U.S. and from business school and computer science alumni of a large Midwestern university.
We sought to compare the family backgrounds, work histories, educational experiences, and personality characteristics of IT professionals with those of individuals working in equally demanding careers that required roughly comparable levels of education and skills. This quasi-experimental design allowed us to isolate the reasons for gender-based differences in career choice.
The sample consists of 523 working professionals. The non-IT professionals include accountants, auditors, CEOs, CFOs, presidents, consultants, engineers, managers, administrators, management analysts, scientists, technicians, nurses, and teachers. The IT professionals include application developers, programmers, software engineers, database administrators,
systems analysts, Web administrators, and Web developers.
About three-quarters of the sample (73%) are non-IT professionals, with the remainder being IT professionals. The overall sample is almost evenly divided between men (54%) and women (46%), but consistent with broader national patterns the IT workers were mostly male (68%), while the non-IT professionals were nearly evenly divided between men and women. The average age of participants in our survey was 39 years and they averaged 17 years of formal education (92% held four-year college degrees).
Personality matters for career choice
Vocational psychologists have developed a way of quantifying the personality differences between individuals and how those differences affect the choice of occupation. This line of research began in 1927 when E.K. Strong developed the Strong Vocational Interest Bank (SVIB; now the Strong Interest Inventory, SII). By the 1950s, Holland had augmented Strong’s work by introducing six basic occupational interest categories that closely resembled the dimensions found in research on vocational interests using the SVIB.
In 1974, the theories developed by Holland and by Strong were combined to create the Strong Interest Inventory, which is used to measure six general occupational themes (GOT) for both people and jobs, and this approach remains one of the leading tools used by career counselors to match individuals to careers. These six vocational types (RIASEC) are:
˲ Realistic (R) refers to a person’s preference for activities that entail the explicit, ordered, or systematic manipulation of objects, tools, and machines.
˲ Investigative (I) refers to a person’s preference for activities that entail the systematic or creative investigation of physical, biological, and cultural phenomena.
˲ Artistic (A) refers to a person’s preference for activities that are ambiguous, free, non-systematic and that entail the manipulation of materials to create art forms or products.
˲ Social (S) refers to a person’s preference to lead others or for activities that entail the manipulation of others to in-
form, train, develop, cure, or enlighten.
˲ Enterprising (E) refers to a person’s preference for activities that entail the manipulation of others to attain organization goals or economic gain.
˲ Conventional (C) refers to a person’s preference for activities that entail the explicit, ordered, systematic manipulation of data.
Career fields are often chosen when a person finds a career that “matches” his or her personality. For example, accountants typically score very high on the Conventional GOT. Accounting jobs typically involve a systematic approach to credits and debits and financial statements. Similarly, computer programmers typically score highly on the Realistic GOT. Programming requires a focus on concrete problem solving to abstract reasoning.
We know from decades of work by vocational psychologists that the occupational themes measured by the SII are not distributed equally between men and women. Men, for example, score higher on Realistic and Investigative themes, while women score higher in Artistic, Social, Enterprising, and Conventional themes. 1, 2
Our analysis of the survey data we collected indicates that more than two-thirds of the gender difference between IT professions and our control group can be accounted for by differences in the distribution of GOT scores between men and women. 4 Based on these figures we estimate that in the absence of systematic gender differences in the distribution of GOT scores the IT work force today would be close to 40% female, rather than the actual figure of 26%.
IT workers in our study had higher scores on the Realistic and Investigative GOT. As discussed previously, fewer women have these types of occupational personalities, preferring occupations higher in the other four GOTs. Women do not view IT professions as artistic, social, enterprising, or conventional so they choose other occupations they feel will better match their personality.
Another recent study, by David Lubinski and Camilla Persson Benbow3 supports our conclusions. Their work found that among a group of mathematically precocious youths who have been followed for up to 20 years women and men make quite different career choices. They note that mathematically
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