So white, asian, africanamerican, if you go down, you can see the different groups and thats where the wide gaps are. First, more white or caucasian staff than population in the city. So the red bar versus the blue. We have fewer africanamerican staff than we have people in the city. Its looking at that imbalance and helping to set policy about how we oversee hiring panels, what kind of oversight we do in terms of recruitment, hiring a recruiter to improve the racial diversity of our pools for applicants, all of those things were done in response to looking at that data. Next slide. And then just an overview of what our approach to data is. We use two methodologies. One is lean, coming out of industry that looks at how to improve a process. And when is resultsbased accountability thats out of public government, looking at how to improve services. And it basically says, use the data to define the problem, so collect good data, analyze the cause very deeply of why your data looks the way
Points into three key points around availability of data, accuracy of data, and being folks being able to ingest it. A lot of the data that we requested is not available because its not broken down in ways that are meaningful and helpful to identify the communities that are most negatively impacted. A lot of times that means that we cannot actually get answers to some of the most pertinent questions. There was a situation that we were in a meeting and wanted to know the population of special education students that were of africanamerican ethnicity or race. And we were not able to get that information, even though we know its one of the larger groups and most impacted in that. Weve had a lot of issues around accuracy. Weve requested data countless times before they had a good, computerized system and gave us 800 documents to sort and sift through to discuss whether its disproportionate suspensions towards africanamericans, and there was. We till have struggles knowing if its accurate a
Legislation what are the mandates of the legislation on the horizon . Its to collect information on all stops made by officers and import the information to the department of justice. The bill requires that each state and local agency, Police Officers to report to the attorney general data on all stops as defined and conducted by the Police Officers and include that information including time, date, location and reason for the stop. The bill further requires the employees 1,000 or more Police Officers to issue its first report by april, 2019. Why does that bring me to this point . In april, 2018, the state department of justice will roll out training on how to collect this data and submit it to the state for the top eight agencies. Were talking about top agencies that we call wave one, Los Angeles Police department, Los Angeles County sheriffs, california highway patrol, San Francisco Police Officer were number five in the state. Riverside sheriffs office, san bernardino, and San Diego
Contract exclusivity provision issuing a permit for ebikes for the others there. Our signing the agreement did not preclude us from issuing our permits legally. Its just an agreement acknowledging our ability to issue this oneebike permit not specifying who the provider would be without compromising the exclusivity clause. That was the resolution of the dispute resolution process that was invoked i dont remember fit was invoked by motivate or ntc. Throughout the process we were communicating closely with folks in the Mayors Office because the whole contract came about through the Mayors Office and approved by the board of supervisors. We wanted to make sure we were keeping in line with the policy intent of the motivate contact to be the regions bike share provider recognizing the industry had significantly change from 2015 to where we were in 2017. So the time lag from the signing and the authorization of the single permit and the notification to the rest of the providers that that was
Three, family justice and four economic power. These are what i consider longer term outcomes and determinaters. This city has kind of stood behind loose and thin measures while we have seen the outcomes go down the drain. Well explain what it means. We at hope sf as an initiative and many of my colleagues are here in the room, its collective Impact Initiative and we focus on results basic accountability. Were having the robust conversation about data and we want to look at transparent Decision Making, longterm outcomes to make sure the population as a whole is better off. I mean things that land on the longterm in families and households so folks are actually better off. So this slide just gives us a sense of so were speaking the same language. We have results, we have indicators, we have performance measures. And so for us, what we have seen, i get into some of the indicator data, we can measure if were focused and share the information items which help quantify the achievement of a