This Indicator is measured by the percent of employed individuals who are not employed in industries with a mean annual wage of at least $80,000. In 2016, these industries included management occupations; legal occupations; healthcare practitioners and technical occupations; computer and mathematical occupations; architecture and engineering occupations; life, physical, and social science occupations; and business and financial operations occupations. (Source: Occupational Employment Statistics, CA Employment Development Department https://data.edd.ca.gov/Wages/Occupational-Employment- Statistics-OES-/pwxn-y2g5)

This Indicator measures the percent of the unemployed population (ages 16 and up) in Oakland by race/ethnicity who did not participate in the City of Oakland’s Workforce Development program between 7/1/2016 and 6/30/2017. The percent that did participate for each race/ethnicity is calculated by dividing number of participants of that race/ethnicity by the number of unemployed people in the labor force in Oakland of that race/ethnicity. Percent that did not participate is 100% minus the percent that did participate. NOTE: Participation is not the most meaningful metric, but was the data available. In the future, we hope to replace this with a measurement of exit outcomes for participants by race/ethnicity (i.e., did participants successfully find jobs?).

This Indicator measures the hourly wage for all workers ages 16 and older and compares it to the 2016 Oakland living wage ($14.86 per hour). Hourly wages are calculated by dividing the total person’s earnings by the product of the weeks worked and the usual hours worked per week during the past 12 months. The weeks worked variable was set to the midpoint of the interval included in the ACS data. Only workers with non-zero earnings, who were not self- employed or unpaid family workers, and who were at work or had a job but were not at work last week were included in the analysis. (Source for methodology: http://laborcenter.berkeley.edu/pdf/2014/chartbook-data-and-methods.pdf)