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 difference in denial rate of Home Mortgage Disclosure Act (HMDA) loans by race/ethnicity. The HMDA requires that any loan secured by a lien on a
dwelling made for the purpose of purchasing a home is reportable on an annual basis to the Federal Financial Institutions Examination Council (FFIEC), which is the federal reporting agency of the Federal Reserve Board.

This Indicator measures the percent of householders who do not own their homes. The percent of householders living in owner-occupied units does not consider other properties that may be owned by individuals within the household. This Indicator measures whether the householder owns the unit in which s/he lives.

Jail incarceration rates are measured by the number of incarcerated individuals in jail per 100,000 population aged 18-69. This Indicator is measured for Alameda County, and the most recently available data is from 2015.

This Indicator measures the rate of homicides in Oakland by race/ethnicity. Rate is calculated as the number of homicides per 100,000 people of the same race/ethnicity (of any age).

This Indicator measures the percent of individuals who live in housing units that do not have complete plumbing facilities. Complete plumbing facilities include hot and cold water and a bathtub or shower.

This Indicator measures the rate of use of force on subjects per 100,000 people in Oakland by race/ethnicity. Note: There were 10 incidents of use of force that were on a crowd. For these incidents, the number and race/ethnicity of subjects were not available. Therefore, each was counted as one incident in the Citywide total. This will somewhat undercount the true total of people subjected to use of force and will potentially misrepresent the true racial and ethnic breakdown as well.

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 severe mental illness related emergency department visits per 100,000 by race/ethnicity, from 2013 through the third quarter of 2015. Severe mental illness is often defined by its length of duration and the disability it produces. These illnesses include disorders that produce psychotic symptoms, such as schizophrenia and schizoaffective disorder, and severe forms of other disorders, such as major depression and bipolar disorder.

This Indicator measures access to different types of financial institutions by zip code. “Good” institutions include banks, credit unions, and savings institutions. “Bad” institutions include check cashing services, money transfer services, and payday loan institutions. The ratio between the number of bad institutions and the number of good institutions is calculated for each zip code. A higher ratio of bad-to-good institutions means that there are disproportionately more bad institutions in a given zip code. The Indicator then measures the ratio of these ratios, comparing zip codes in which more than 60% of the population is non- White to those in which more than 60% of the population is White. The third category of zip codes is those in which the population is racially and ethnically mixed.