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 result. Folks are better off in terms of economic power and healthy birth and academic achievement and better off in terms of family justice. And then theres the performance measures, measures of wellbeing, the land and programs. San francisco has been good at spending money and allocating resources, but the question is are we better off in term office longer term indicators. As an example focusing on economic power. This slide is difficult to see. In the slide deck commissioners, you have a sense of whats happening to the wealth in the city and county of San Francisco. We know theres a 50 black white employment gap and we know it takes about 80,000 a year for a family of four to survive in the city, yet our households get by on about 16,000 a year and the Poverty Level is about 22,000 a year. This is an economic power indicator we want to track. This is another slide here that just shows the Racial Disparities across income in terms of our rise and tides, listing all that has not been the case in San Francisco. Im going to focus the next few slides on the visualization. Its sort of tricky to see with the captions here on the slide deck, but this will just give you a sense of why place is to important to focus on. This gives a sense of the unemployment rates by census track. The redder, the more unemployment, its closely located around the southeast sector of the city. The next few slides, im going to talk about the African American population of the children in the city. It looks somewhat spread out, western addition, parts of the tenderloin and youll start to see the displacement of folks, focusing on the measure of place as a key indicator. So again, in 2011 you wonder what happened, where all the folks, African American children in the city. Moving to issues of family justice, again, underscoring the point that not all data is created equally. For family justice its often the case we focus on an indicator like Violent Crime. In this slide deck you see the Violent Crime rates across the four communities. You see a sdra dramatic decline over Violent Crime in the past six and seven years. We have great partners from the das office and Police Department to help make the violence go down. Is this the only indicator we should look at. If you look at the shootings we continue to have in many of our communities, that indicator may be insufficient. And so the next few slides are a representation. I took it straight from one of our young people, a young person who lives in west point. The number one issue he was focused on was gang violence. Even though he lives in a community that seemingly has a reduction in Violent Crime, violence and safety is still a key issue for him. We focus on not just the Violent Crime rate but another indicator, a perceived feeling of safety. We know households and families dont feel as safe in our neighborhoods as some other folks do across the city. Lastly, ill talk about the academic proficiency indicators that we look at as a city, again, not all data is created equally. We believe in focusing on race, family and place. This slide gives you a sense of the net change from 1990 to 2010 in the educational composition. You dont have to be a Rocket Science to understand we have lost vast majority of folks who have less degree. The focus on place is so important. What we have learned from hope sf, you have to look at this visually. Im going to go to a few slides on the map to dramatize this even more. This is San Francisco in 1990, this is the population with a bachelors degree or more. Its somewhat evenly distributed across the city but the see the lower income areas on the east side and avenue is higher population of education. As i go through the slides watch how much darker San Francisco gets in the areas that dont have the bachelor degree or more. In this last slide deck, as you get your 4 latte, theyre being served by folks with bachelors degree, and the lower end are in the southeast part of the city. So weve made progress in terms of sharing data, theres a shared youth data base some of my colleagues may speak to that shares across juvenile probation. Our chief of juvenile probation is here but were not where we need to be to realize on a shared metric. We believe at hope sf that the vision is that is vision is indeed for realizing and repairing what Public Policies have broken. Youll see across the wellbeing statistics, this is Child Mental Health clients, in the southeast part of the city largely. Juvenile probation clients, largely in the southeast part of the city. And in the shared juvenile probation and Mental Health cases, largely in the southeast part of the city. Im going to close with this in the interest of time just to say that our challenge is to build an Enduring Partnership about families. I didnt mention as much, if you focus only at the individual level, youll miss a lot of life course impacts. I know you have an extensive slide deck from me there. We think about three key factors around data. Number one, the perception, there are structural factors tied to race, the blocked access to social and economic wellbeing. The federal climate that is largening the pressures. We have pathways where displacement is largely used to deal with the labor inequalities. Consider hope sf a partner of yours. We believe strongly race, place and family should be key components we focus on. Thank you. applause thank you mr. Miller. Before we move on with the speakers, i want to acknowledge the fact that June Williams is here as a represent from senator Harris Office and ellen nance is with us tonight. Youre welcome to be with us as well. I want to invite dr. Bennett may we adjust the presentation schedule just a little bit, miss deberry has a time crunch. Welcoming Christine Deberry. I appreciate the indulgence. Apparently everything is scheduled on this date. Christine sotodeberry. Pleased to be here before all of you and to present on this very important topic. Can you hear me . Sorry. Im not tall enough. Its good. Latino, im short but in heels. But powerful. Im going to be as brief as i can. I know there are many presenters with a lot of interesting information. I want to extend that im happy to have conversations away from this Commission Meeting with you the public or commissioners to fill you in on the work we do. We have a lot of passion around data and equity issues it imindicates. I wont cover everything here tonight but we want to be a partner with you in this effort. So traditionally District Attorney offices are not big for data, concerns over what it may reveal, for our good fortunate, our office has incentive to collect data and react to it in positive ways to lead in important areas people expect us to work on. To speak directly to an issue that this commission has asked, we actually just today at the reentree council released a Racial Disparity sample. The reason it took so long, the data in San Francisco and criminal Justice System is deplorable. And if james bell did not speak to that, he was being very polite. Hes worked with our data and knows how terrible it is. We worked very early on with a researcher to address Racial Disparity in our process and we were told our data was so dirty and incomplete they couldnt do the analysis. We had to spend several years until we could find researchers in Higher Education to put students to work to create complicated algorithms to pull the information out of our Case Management systems. Its an ongoing struggle and i hope part of the work this group will take up is the investment in justice and trying to give it adequate resources to be able to complete the onboarding of our all Case Management systems and the sharing of the data across the systems so important projects like this dont become six year endeavors but closer to a reasonable timeline to answer important questions about how we do our work in a more timely way. The study we just completed is at sfdistrictattorney. Org, you can see all the results there. We asked professor stephen rafael to evaluate all of our decision points, Racial Disparity, who we decide to charge, what types of dispositions we offer. There are disparities. The vast majority are explained by appropriate criminal justice factors that preexist such as the arrest charge or the individuals criminal history, nonetheless theres work remaining to do and were engaged with both those researchers and others to make sure we continue to challenge ourselves, our policies and our practices to be equitable in the work we do every day in our courtrooms. One interesting thing that did come from the study that was conducted was the value of proposition 47 for reducing Racial Disparity. I raise it here today, its one of the rare policies we see working on reducing incarceration and gives the greatest benefit to African American men, above anybody else. Thats a pleasant outcome that warrants evaluation and is the type of policy we want to prioritize across criminal justice if were going to look for areas to reduce mass incarceration and we can simultaneously impact the communitys most impacted by the policies. I think we have come to a good policy to be replicated. So this graph shows the impacts we have around prop 47 and dramatic arrests in relation to other population groups. So as i mention, the data systems within San Francisco for the das office, we have a Case Management system called damien. We input the information about the cases were processing, that system does not contain race information. The information we have on race comes from the courts Management System, which unfortunately has very outdated categories that dont even account for ethnicity. Latinos and other asian populations are not even categorized in the court Management System making it difficult to do a Racial Disparity study or anything else related to race and equity. This is hopefully an issue with justice to the resources to help facilitate the court moving over to a new system and other agencies on boarding can be improved. The places we keep race data of our own that we have confidence in, victims around the city and the services we provide to them and to build on a statement from theo earlier, it is an important area of the Public Safety conversation that we often dont incorporate in the conversation. We know very well overrepresentations of individuals accused or suspected of crime but we dont spend a lot of time talking the victims of the crimes and the sense of safety in the community they reside. Okay. Sorry. Can you go back one . So this will just that is very hard to read. Its in the handout, easier to read. It will show you for example African Americans accounting for about 6 of the population in the city but 19 of the victims. And for latinos about 14 of the population and about 30 of the victims of crime. Those may be numbers that the Commission Wants to consider further. This data we review along with all the other crime data in our monthly da stat, please stand by. Third largest proportion of latino prosecutors at 10. 1 . This does not count our support staff or investigative staff within the office, which would certainly take those numbers even higher. And in addition to diversity, we spend a fair amount of time on our Office Working on implicit and explicit virus we also brought in kimberly papion to work with us on exercises and put that out to the office to make sure its front of mind for staff. Because of the importance of the work we do and the implications that we have. That was a whirlwind. I apologize. I dont want to take up anybody elses time but im happy to answer anybodys questions or be here after. Thank you for being here. You, like the speakers we have, its an introduction to what you are doing in your departments or jurisdictions so we can begin our conversation about what we believe our city should be doing and bringing in the city agencies. So well be happy to have you back and look forward to take a deeper dive into the justice with you and the Public Defenders Office. Thank you for your leadership and for the presentation. Since our administration is antimuslims, antidaca, antiimmigration, what are some of the things that you are doing to safeguard data thats being collected. And probably the most concerning area for us is probably around immigrants, in terms of the fear that people have about coming forward and working with us and we have done as much work fair amount of work telling people we have no plan to work with i. C. E. We have a policy where people who are victims of Violent Crime they can apply for a uvisa. And we file more of those than anybody at least in the state the vast majority are not granted, unfortunately, even under prior administrations, but we have a robust policy of making sure that people are aware of that right and facilitating the application the other effort weve taken is training all of our staff on the potential for i. C. E. Showing up in the court houses, as has happened in the country, both texas and pasadena, california, to make sure that were aware what we can and cannot do should i. C. E. Show up looking for victims, witnesses or defendants, to make sure were a good partner in the city family. So weve trained our victim advocates to be that support for anybody that comes to the courthouse, expressing fears or concerns about immigration consequences within the building, but we offer an escort to that individual throughout the Court Process to make sure that theyre protected and our advocates have the hotline information so they can call immediately to get immigration counsel for anybody confronted by i. C. E. In the courthouses. Thank you. Any other comments or questions . Thank you. Thank you. Next, i would like to invite up, dr. Bennett, with the department of public health. Thank you for being here. Im dr. Bennett, director of interdivisional initiatives, which means that i do work that crosses from environMental Health and Health Education and those things and the San Francisco health network, which has our hospitals and clinics and Behavioral Health come poep component, so i deal with the data on both sides, which is how i get to be here. So the department uses data pretty extensively. We have very little choice about having the data. Most of the time large amounts of data are required almost us for state, federal or grantrelated reporting. And the medical records that are used for clinical care. So we have lots of data. And we also use data for program planning, for billing, for services, but most importantly, we use data to improve Program Quality and Service Delivery and health quality. So we do that by tracking outcomes. We do it for directing programming to populations most at need or patients most at need. And for evaluating and setting policy. So im going to give just a few examples, because i was told to keep it short. Before i even do that, i will direct people most of the data not most, but a large amount of the data the Health Department collects, at least that that is not specific to patients, is publicly available. Probably the easiest and most userfriendly source is sfhip. Com, the collaborative of all the hospitals in San Francisco, which is overseen by the Health Department and gathers data from across the city and we consider things like Educational Attainment and unemployment and Economic Health data. So thats number of strokes and visits and things you think of. So sfhip. Org. So the example of how we track outcomes, i will take from the San Francisco health network, primary care clinics that include castro, mission, and places you are familiar with. So these slides are hard to read. I think its the screen. What we see on the slide is the clinics and this is hypertension control rate for black African American patients in each clinic. Of all the people, they know who has hypertension in the clinic who are africanamerican, which of them have that hypertension under control under that medical standard and have set goals for themselves about what level all the patients should be at and the goal next to that is that there should not be a disparity between groups. The largest disparity is between black africanamerican patients and the average and thats what all the clinics are focused on right now. Some are quite small. So we know our Patient Population is really concentrated. In some clinics, it may be just a few people, which is why that line looks so busy. Month to month, the clinic judges themselves to get an idea of how you patients are. Next slide. For directing programming, i will use our getting to zero program thats care of h. I. V. , and prevention for people at risk for h. I. V. , very heavily focused on in our clinic sites. The main thrust is out of the research and Health Education departments or areas within the Population Health division. Th this slide shows what has happened with h. I. V. Its a national model. If you look at the green line, its dropped dramatically over the last 10 years, as have deaths and new infections. People living with h. I. V. Is a good thing because its mainly because thats where we got that. This is a slide of just women. That blue line that is above everyone else, africanamerican women. So that lets the team know that while they have many reasons to feel good, there is work still to be done and thats allowed them to create new projects around prevention. If i used other slides, i could explain why theyre focused on transwomen and on youth. All of those are groups that are not following that trend that the general population of h. I. V. Positive people or people at risk of h. I. V. Are following. So thats how we use that data to create equity, we look for data that looks positive, you look to see if its positive equally across the population. And setting policy. This is out of the office of inclusion and Work Force Development looks at what the racial and ethnic makeup of our work force is and this compares that to the makeup of our San Francisco population, which is our client base. 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 it is. Make changes. Measure the impact. And then make changes again and repeat and repeat and repeat. So data is meant to be part of an iterative process that says, we looked at the data. We made decisions based on the data and keep going back again and again, so the data is an ongoing endeavor. Not something we do one time it. Has to be something that you can look at in realtime in order to be useful for all of the uses. Questions . Thank you. This is interesting. I know you are giving us snapshots of Different Things going on, different data that you are collecting and analyzing, but tracking outcomes. Do you track them across the board for just about everything or do you choose strategic things to track . There are things about which we have no choice, like hep a outbreak. Other things are mandated but with choice. So we have outcomes around our valuebased payments. So part of the way the system is converting to reward quality work in medicaid and medicare is by paying people based on their outcomes. Which outcomes they pay for is somewhat mandated by the federal government and somewhat up to the institution. We have chosen some like africanameric africanamerican hypertension. We were required to do an equity measure and we chose that one. And others are based on what we see in the population. H. I. V. Is a very salient issue in San Francisco. It might not be something tracked as closely in other jurisdiction, probably to their detriment. And other things are clinicspecific. So every entity within our system is doing a slightly different look at their own data and people have some agency around having their own data and each clinic can look at what they, themselves, are doing and then when have both mandated and centrally decided measures that we use. We do have measures that are used across the department to judge quality of work. Is tracking live births in the city data that you collect . Yes. That is state mandated data that we and every other medical unit in the city send. And mortality data. Hospital admission data. Those things are on sfhip site. Very interesting. Look forward to having you back to go deeper into this. Any questions or comments . Well move open to the next speaker. I will slink away, too, because i have to go parent. Thank you for being here tonight. Next i would like to ask our public defender to join us tonight. Thank you. I think what i heard the District Attorney say is that the system is not racist. I would disagree with that. Everything was explained by other factors. And while i think thats partially true, i think that the data definitely shows that the system is not raceneutral. I dont think there could be any dispute about that. Even though our africanamerican population is 5 , 55 of our clients, public differ ender clients, and folks in the system are africanamerican men and women. If you look at categories of crime starting with traffic tickets, africanamericans are seven times as likely to be stopped for a traffic violation. Why is that, because africanamericans cant drive . More likely to be stopped for a drug offense, even though every study has shown that whites use and abuse and sell drugs more. If you look at the overdose rate, six times the rate for whites than blacks, but the statistic is the opposite when it comes to being arrested for drug offenses. James bell, who spoke earlier, did an amazing, groundbreaking study. It showed clearly that there were disparities. We sought to take that study and work with the university of pennsylvania, which offered to do a twoyear study independently. All we did was provide them with our files. And we opened our files up to them. They came up with a report first slide, please . Second slide. They gave us an economist and a scientist and a law professor for two years, who worked on the study. And we gave them 11,000 cases. When asking the question, what specifically did the disparities result in . They found that africanamericans are held in pretrial custody 62 longer than their white counterparts and on average serve 30 days longer in custody. These are folks that are charged with the same crime, same criminal history and all of the characteristics are exactly the same. So in other words, making an applestoapples comparison. Next slide, please. In terms of cases, the time to resolve a case is 14 longer if you are africanamerican. And on average, it was 90 days to process a case of a black defendant. 77 days to process a case for a white defendant. Same charges. Same criminal history. Same background. Defendants of color are convicted of more serious crimes than their white counterparts. 60 more felony charges and 10 fewer misdemeanor charges. Next slide. Defendants of color receive longer sentences than white defendants. Sentences received by blacks are 28 longer than those received by whites. Probation sentences received by latinos are 55 longer than those received by whites. Next slide. People of color receive more serious charges at the initial booking stage and the reason why this was significant, again, you ask the question, why, why do we get different out comes . For a person of color for the same offense, you will be charged with more serious charges and more charges. And thats when the Police Determine what the charges are. And they found that that disparity starts with the police charging and goes throughout the system. In other words, the District Attorneys, defense attorneys, are responding to the charge. So you might have a black defendant that will be charged with more serious charges than a White Department for this same conduct, given the same criminal history. So it has a Ripple Effect that effects subsequent charges and results in a person of color being convicted of more charges than their white counterparts. So that gives you an overview as to what the study found and we have a link to the study, which is quite comprehensive. The question is, what do we do about it . How do we address this . You will also see that theres a chart at the end of the materials that you have and i have them for the audience as well. Thats a breakdown of exactly what we do in our office. Were able to see for every teryn now how many pleas, trials, misdemeanor pleas, dismissals, diversions. And its allowed us to be able to look at exactly what our lawyers are doing. Were interested in the disparities in the way that our lawyers are representing clients. And we did find disparities we found one attorney that pled clients guilty to 30 felonies in a year. Weve had another that only had 5. So we started to look at those and say, which lawyer would you want . Somebody that fled somebody to 30 felony pleas or somebody that pled 5 . We started to look at the practices and we saw differences in outcomes because of the way that cases were being handled. So we have implicit bias training and mandatory coaches and meetings to ensure that were addressing that within our own office. You also see the stats that we published through our annual report and we have an annual report its against the law in San Francisco to use city funds to print an annual report. So i pay for this myself, but we print 5,000 of these and we have all the statistics related to every program in our office. Thats how we track our criminal justice outcomes. To answer what to do, the first thing we have to do is we have to disrupt. And, for example, you see that one of the main culprits is the bail system. When a high bail is set and you cant afford to pay, youre in jail and the only way that you get out of jail is you plead guilty and a lot of poor people do that and people of color do that. It means you are on probation. You give up your right to a jury trial and ultimately, you will be in the system. And so what weve done is we have now filed bail motions in every case. In one weekend, we filed 800 bail motions and it almost shut down the courts. Why did we do that . Court were unconstitutionally setting bails that people cant afford. When a transgender activist was arrested for trumpedup charges for assault, she had a bail of 173,000, no prior record. Fortunately, our Early Release unit was able to work with the d. A. s office, provide them the information that showed she was innocent. 250 people showed up at her arraignment and the case was dismissed. Otherwise, she would have had to post bail. Even if the case was dismissed, she would have been out if she put up 17,300. That happened to a number of our clients. So we filed a lawsuit in federal court and state court and we have, i think, seven lawsuits going on right now. Again, disrupting. As a result of that lawsuit, the city attorney, and others issued statements that the bail system is unconstitutional. Today we filed an appeal in state court and just today, about two hours ago, got a decision from the court of appeal saying that the way that San Francisco courts set bail is unconstitutional. Thats a huge way that were disrupting. Were trying to work to change the law. Sb 210 is working through the legislature. Were concerned about that because we think the judges are trying to hijack it and we wouldnt have real bail reform. So were working on that. And the other thing we have to do is we have to repair. In San Francisco, tens of thousands of people have been convicted of marijuanarelated crimes. Theyre now under prop 64 entitled to relief. Who will make sure they get relief . Weve had in the Public Defenders Office a cleanslate program for 15 years. And we clear about 2,000 records a year. And we make sure that people bring expungements to court and we handle that process for them. Very important to do that. Another huge reform is fines and fees. And were about to introduce a bill that would eliminate all the fines and fees collected by San Francisco superior court. If you plead guilty to a felony, there are no less than 32 separate fines and fees that how of to pay. Everything from courtroom maintenance to building new courthouses around the state. They have all these fees and they total 2,000 to 5,000. So we have legislation now, which we hope you will support, which is being supported by the supervisors, thats would eliminate almost half of the fines and fees, including probation fees, which are 30 to 50 a month and automatically charged before a person is placed on probation. Beyond that, i think that we have to do what youre doing. You have to question. You have to study. You have to look at this. I appreciate the presentation by the elected official from minnesota, home of prince. I think that we will, you know, be in a better place to look at those issues if we start from a place of reality. And the problems in the criminal Justice System, as you know, are only a small part. We have it look at all of the factors that you are looking at, and thats why you are talking a bigpicture approach and looking at employment, youth services, family services, foster care, and only by looking at all of these things and ultimately addressing all of these things will we have true equity. Thank you. Thank you. Colleagues, are there any questions now or can we move on to the next speaker . We look forward to having you back. Next, were inviting to the podium, our elected sheriff, vicki hennessy, San Francisco Sheriffs Department. Good evening. I apologize, because i didnt get a chance to email our presentation. I put it on the overhead. There it is. Okay. Thank you. Im here to answer the questions you asked us to answer. The question was why do you collect data. It looked pretty good. [laughter] can we get this on the overhead . Its not working . I am here to answer the questions you asked us to answer. First of all, i want to thank you for having me here and i want to thank james bell and toni carter for their presentations. I jotted down a number of things that im thinking about as well that could help me in operating the jails. As sheriff, one of my Main Responsibilities is managing the county jails. Now im not necessarily the person that puts people in jail, but when people get there, through arrests and stay in my jails, its something that im concerned about and i want it ensure that were doing what we can to help with the Racial Equity issue. What do we do . Why do we collect data . To better understand who is in custody or sentenced in one of our outofcustody, alternative programs. 85 of the people are pretrial. 15 or less, sentenced to county jail. Most of the people are out on pretrial alternatives. We collect name, age, address, booking number, case number, sf number. We have our own jail Management System that somewhat interacts with court Management System and somewhat interacts with the other systems in criminal justice and i will echo what Christine Deberry said. One of the things that i hope will come out of this is that we will gather, identify first, and gather excellent data, so we can make good decisions, and were not there. And i think that was said by a number of the other people before me. Were not there. Im hopeful that the Justice System will be able to come up and get together and there will be more investment in it, so we can get the data we need. And one of the things that im doing in my budget is my jail Management System that collects all this data and more, but also interfaces with other systems, but not as much as we would like. We dont get regular reports that we would like. Its very, very complicated to get a report out of the system. Im asking in my budget for a new system, which will be a lot more flexible and well be able to do a lot that we cant do now. So what for what purpose does the Sheriffs Department use the data . Well, on the big in the big picture, we share the data to better understand and evaluate who is in our custody or in our programs. Last year actually, it was in 2016, we were very involved in the reenvisioning the jail with Many Community members at that and working on that and we were very frustrated at that time by the inability to capture data that we needed for that. We do this and we work with our criminal justice partners as much as possible, so for the reports that the d. A. Talked about and james bell talked about, much of that came from our jail Management System. How does the Sheriffs Department use the data to advance equity . In one way, we use it to identify the different the Racial Disparities at the difference Decision Making point in our jail. One of the things were doing is doing research to gather data to inform future policy decisions about what we learn through our Research Project that involves who gets out on alternative sentencing and who does not. As well as working with the pretrial diversion project, identify wooing gets out on pretrial and who doesnt and why not. And so those are things going on right now. The new pretrial system, Risk Assessment tool, has been going on since may, 2016. And its shown a lot of improvement, but we still dont know how much. And over sustained time, so well look at that as well. So on the next page, i gave you the data collected. Were one of the few agencies, where we do collect race and ethnicity and in a robust fashion. We have it so many of the departments depend upon us and come to us to pull our data, for example, the Police Department asked us to provide data to them for a report they were doing and asked us to provide that because we had that about people who had been arrested. And so, as you can see, theres robust race and ethnicity data. So thats pretty much what i came here to tell you tonight, but if you have questions, im happy to answer them. Thank you, sheriff hennessy. Its although you didnt present something to us before, what you brought today is very helpful, i think, for us as well as for the people that are here with us at the hearing about these key questions that were presented to you. And this this hearing, this particular hearing, is partially in response to a request that former mayor lee gave to us before he passed away untimely and left us. As a commission, as an agency, weve been looking at the question of disparity on many levels, including and specifically racial levels and he asked us to begin this review of Racial Disparities in that sense and we do have from the Mayors Office a representative. So thank you for that and thank you for putting that together. Okay. Any questions or comments right now for the sheriff . Look forward to having you back to go more deeply into thank you very much for the work youre doing. Thank you for being here tonight. Next we can go to the San Francisco unified school district. Thank you so much. And the superintendent is also with us tonight. Good evening, commissioners, and good evening, members of the audience. Thanks for giving us this opportunity to present our data practices and our data use. So i will begin with the first slide. I want to give you the scope of the data that we collect within San Francisco. It begins at the time of enrollment, where we collect all the demographics. As you can see, it increases to the point where we actually look at college and career, not just graduation, but also through college. So we track longitudinally throughout those years. When theyre in San Francisco, we measure the whole child. So we look at both academic, behavioral, social, emotional and Culture Climate data for our schools and students. We want to use data as a flashlight and not a hammer. So we try to make sure that data is used for Continuous Improvement as, as i said, for a flashlight and not a hammer, but keeping in mind the equity imperative. We use data for evidencebased decisionmaking and definitely for accountability. So when im talking about accountability systems, you know that all accountability systems are designed to measure the district. And similarly we do measure the district. The number one goal is equity. Therefore, data has to measure equity. And the second goal is academic achievement, so you can see evidencebased Decision Making, whether its right from the classroom level to the district level. It looks at evidence and data and lastly, accountability goal in San Francisco. At this point, i will show you lets go a little deeper into the equity imperative. How do we look at equity . The first way we do so is by holding High Expectations or equivalent outcomes for every school within the city. So even though you see variable performance of schools within the city, they all are held to the same standards. So when data is looked at, its all at the same standards that we look at those schools and we look at the disparities that exist. So High Expectations are there for all. We also realize that inequity starts at the input level. San francisco unified is a district of school choice, where parents get to choose their schools. And as a result, right there at the onset of the input variables, you can see differences in student demographics. The segregation, concentration, poverty concentration and race concentration in certain schools versus others. More english language learners, more special ed population. So programs in some schools versus others. Other than that, the other input variable that goes into the school is the teacher factor. So even teacher stability and experience is variable across schools. So equity has to begin right in the beginning. So we begin by actually looking at these input factors and giving more support to the schools that have the higher challenges. Now i will move on to evidencebased Decision Making. In order to really make good decisions, you have it look at data across time. You cant look at it at just one point in time. So in San Francisco, we do look at data across time. Across multiple measures, as i was telling you about the academic, the behavioral, and the Culture Climate measures, and across various groups. You can never look at any data point as one number. Today if i stood here and told you my Graduation Rate for San Francisco unified is 87 , that really says nothing, but the real data lies when i break it down by sub groups. Lastly, more than just presenting the data, the use of the data, is in the dialogue that goes behind the data. So as an example, we have shown you some conversations that we have with school communities, with principals, School Leadership teams around the data. When you ask them, can you determine your School Priorities . What are your outcomes, your targets, but for which groups . Ask which group questions. Going deeper into the dialogue and asking about the practices, linking the practices to the outcomes is, again, the richness of the data, the sensemaking of the data, comes through the dialogue from the data. Yours is a glance or a glimpse at some reports that are available to the public. We do present right from board meetings and parent forums to definitely most of our data for our school community. So we have the multiple measures displayed through time. But what i want it assure you is the aggregation of the data. We also look at it by homelessness, public housing, as well as foster youth. We also disaggregate both as an
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