- API data.oaklandnet.com | Last Updated 2018-08-07T15:35:28.000Z
- API data.oaklandnet.com | Last Updated 2018-08-07T15:35:50.000Z
- API data.oaklandnet.com | Last Updated 2018-10-01T22:14:37.000Z
The equal access accommodations Indicator is measured by comparing the percent of public contact position (PCP) employees who speak Spanish to the percent of Spanish speakers who have limited English proficiency (LEP) citywide. The Equal Access to Services Ordinance includes a requirement for City departments to offer bilingual services based on citywide demographics. In FY2016-2017, the two languages required by the ordinance were Spanish and Chinese. We chose to measure Spanish-speaking PCP employees for this Indicator because Spanish speakers comprise a larger proportion of the population.
- API data.oaklandnet.com | Last Updated 2018-10-01T22:14:52.000Z
The measurement is percent of students by race/ethnicity who scored “Standard Not Met” on their SBAC ELA test in 3rd grade. The SBAC is California's state-mandated test for all students starting in 3rd grade. Scores only include students enrolled in OUSD schools, not charters or private schools.
- API data.oaklandnet.com | Last Updated 2018-09-04T15:51:59.210Z
Wellness, physical activity, and nutrition are essential for children as they prepare for a healthy lifestyle and positive health outcomes as adults. The Child Health Topic includes three Indicators that measure different aspects of child health and wellness: childhood asthma emergency department visits, physical fitness, and SNAP recipiency. The first Indicator measures asthma-related emergency department visits and is related to the environmental and housing conditions that affect children’s health. The second Indicator, physical fitness, a measure of student fitness levels assessed in schools, tracks physical aptitude and activity. The third Indicator, SNAP recipiency, shows whether families have adequate income to provide healthy food for their children.
- API data.oaklandnet.com | Last Updated 2018-10-01T22:14:31.000Z
The measurement is percent of teachers who turned over between the 2016-17 and 2017-18 school years at OUSD schools (data from charters and private schools were not available). Turnover percents are calculated at a school level out of the total number of teachers at that school. Schools are placed into groups based on the racial and ethnic breakdown of their student population (see note below data table for full explanation of grouping). Average teacher turnover percent is then calculated for each group of schools.
- API data.oaklandnet.com | Last Updated 2018-10-01T22:14:12.000Z
This Indicator measures the percent of homeowners who have a mortgage or loan on their homes. Outstanding debt distinguishes these homeowners from those who own their homes free and clear and no longer need to make mortgage or loan payments.
- API data.oaklandnet.com | Last Updated 2018-10-01T22:14:27.000Z
This Indicator measures the rate of new HIV diagnoses per 100,000 population for each racial and ethnic group from 2014-2016 in Alameda County. The Alameda County Public Health Department’s HIV Epidemiology and Surveillance Unit is required to report new HIV diagnoses, which is a proxy for new HIV transmissions which are difficult to capture.
- API data.oaklandnet.com | Last Updated 2018-10-01T22:14:13.000Z
The measurement is percent of children within OUSD who are chronically absent. Chronic absence is defined as an attendance rate of 90% or less (missing 18 or more days in a 180 day school year), regardless of whether the absences are excused or unexcused. It is not the same as Truancy. Alternative Education schools are not included in the data.
- API data.oaklandnet.com | Last Updated 2018-08-07T15:35:31.000Z
The Indicators chosen represent the best proxies we could find for the complex disparity themes we set out to measure. The following criteria were used to determining the indicators included in each of the topics in the final framework: 1. Data is available, high quality, and from a reliable source. 2. We will be able to calculate change over time (i.e., data is updated and accessible on an annual basis and changes from year to year can be meaningfully interpreted). 3. There is a strong causal model for why this Indicator matters (i.e., we understand the context behind the Indicator and how disparities affect people). 4. The data accurately represents the impact of inequity on people’s lives (e.g., not measuring quantity when what matters is quality).