Alexander Fishkov, Ph.D. student Computer Science
The Num-Powers-Boyd score measures occupational status based on median education levels and median incomes of individuals. An intuitive interpretation of the score of an occupation is the percentage of the population having an occupation with education and income levels below that occupation. This score weights education and income contribution equally. Although the use of such indices is still a topic of discussion among professional sociologists, this simple and clear interpretation can be understood by everyone.
In a previous post, we used this measure to examine occupation rankings through time. Today we will look at the scores of different demographic groups. This time we also used data provided by the Minnesota Population Center and IPUMS.
About 7.7 percent of men reside in the 90-100 rating interval, while this value is only 4.1 percent for women. However, larger proportions of women fall in the 40-50 and 70-90 bands compared to men. If we define middle-class to be scores between 50 and 90, then 38.3 percent of working women fall in this category. The corresponding value for men is 36.9 percent.
If we look at score distributions among age groups, we see a surprising homogeneity. The shape of the distribution is very similar for different age groups, except for young adults 16 to 24 years old (who only enter higher education or the labor force).
If we divide workers by place of birth, immigrants in the U.S. clearly are more likely to be on the edges of the spectrum — they are either low-paid workers or skilled professionals with high salaries. Among them, 7.3 percent have an occupation standing score above 90, while this ratio among US-born workers is 5.7 percent.
Among different states, the highest mean Num-Powers-Boyd occupation score is found in Washington, D.C.: 60.4. Next are Maryland with 53.5 and Massachusetts with 53.1.
Mean scores are higher on average for workers who live in metropolitan areas, going above 49, compared to those living outside, who have a mean score of 44. The highest-scoring metropolitan areas are San Jose-Sunnyvale-Santa Clara, CA (57.8); San Francisco-Oakland-Hayward, CA (55.7) and Ann Arbor, MI (55.5).
About Alexander Fishkov
Alexander Fishkov, Ph.D. student Computer Science
Alexander is a Ph.D. student in Computer Science. He currently holds B.S. and M.S. degrees in Applied Math. He has experience working for industry major companies performing research in the fields of machine learning, data mining and natural language processing. In his free time, Alexander enjoys hiking, Nordic skiing and traveling.
Other posts by Alexander Fishkov:
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