enrichment for the data and so the data from data sf, comes with latin long, associated with it and latitude and longitude coordinate and so for a contributor, you can see where the contribution was made and that is useful, but we might want to know from a lat long, what state was that lat long from? what sf district was it from. what california county did the money come from? and you use that, you know, enrichment, to show further correlations between things, do we find that certain kinds of activities are associated with certain geographic regions. and you know, to answer that kind of question, requires, some sort of processing. and processing a data set for that geo enrichment can take, hours to days to find the positions within these geographic regions. and so, there is a lot of processing that needs to be done, and there is a lot of sort of intermediate data that needs to be stored, and going forward we are going to be looking at more of that, and seeing if we can make more out of sort of this foundation, that has been provided to us. and so, yeah, we are very excited and one o

more data. could you talk more about how data is used by different organizations, by governments, versus corporations versus how much information individual operating about themselves online? >> so should the onus be on individual or more broadly on of entities and found the use and so it is a very good question. the problem is that legislation and laws are often fall behind the quick advance of technology. we're here at a law school right now. me if you could go into the field and come up with new guidelines and regulations and standards that could guide us in the future, but right now to the situation we have i tried to encourage the consumer to empower themselves. but certainly there could be more provisions in law or standards that would help out in that regard. you think of issues such as use of medical data, our current standard sufficient to protect our medical data given that there's such a wide sale of medical data that is unseen even if is on a anonymous basic or you could protected na

that data is in, i mean, that level of detail is in my data set. i don't have exact numbers in my head, but i can tell you that the overwhelming majority of immigration crimes are of illegal entry and illegal re-entry. i can't remember if that's on the order of 85%, 90%, 95%, but it's somewhere in that range. are illegal entry, illegal re-entry. and the other -- you know the other crimes that are included in the immigration crime category are document fraud and there's a smuggling offense in there. an alien smuggling offense in there. but the great majority of them are entry and re-entry. crossing the border. being apprehended while crossing the border. >> i saw a hand in the back. yes. >> i am from the south east asia research action center, serac. the majority of people deported in serac's communities are originally refugees, cambodia, laos and vietnam and are green card holders. usually who get in trouble with the law when they're teenagers or young adults. i'm wondering in any of the data sets that you're looking at including from this foia req

so, do we have a motion to continue this item until we get the data? >> i move to continue. >> i second. >> roll call? >> all right. commissioner, we have a motion to continue the item until the data is gathered. so, president adams? >> aye. >> kathleen dooley? >> aye. >> commissioner dwight? >> aye. >> commissioner ortiz-cartagena? >> yes. >> commissioner tour-sarkissian? >> yes. >> commissioner white? >> yes. >> and commissioner irene yee riley? >> yes. >> all right, so, commissioner, we have 7 votes to continue to hear the item once the advisory board has put together its recommendation. >> great. thank you. next item. >> next item is discussion and possible action to make recommendations to the board of supervisors on bos file no. 141006 [administrative code - legacy business registry, rebate program, and establishing fees]. ordinance amending the administrative code to direct the small business he commission to establish a legacy business registry, authorize an administrative fee for the registry not to exceed $50, and, for the next five years, pr

in data. there is the kind of data we gather that is not so bad he did have the nutrition facts bear with the abbreviated version of and as i mentioned credit cards and financial statements have simplified some aspects these their models to help. and honesty should be rewarded those that were of frustrated by what the companies are doing so calling all for something simple so with your city is an example of that. >> but just to say i did agree because whenever you need to do to buy something on the internet first of all, you know, you do not understand it. and then the purpose is to make it understandable. maybe anger cynical. but also of to recognize. >> you are right. it doesn't have to me that way. will hold data aggregation advancements that have made our lives better and did those things were happening with industrialization so there is some progress that we need to look at. so what they do with the data to allow for good marketing and targeting but the impact potential of this mass segre

insure that the data that is being stored is being protected? and i know that you can download and it manipulate it, and what are we doing to make sure that it does not get compromised. >> nobody on the commission staff actually has the rights to modify the data. and we can assist, and buyers with completing the forms, but, once they submit it, it goes over to the net file system and it is locked. and every city, in california, at this point that is doing electronic filing with the exception of los angeles is going through the same process. and so, they will not actually do anything to their systems unless they received the written requests from us. >> and so, is net file, responsible for maintaining the entegty of the data? >> yes. >> do you know what they do to insure that it is not hacked or compromised? >> well, first of all they keep an enormous number of back ups. and so, i am not particularly concerned about the integrity of the data in that we have so many snapshots of it, on top of that, where so many different component to it and there

we combined the lights data with the population data as well as a few other data sets, to make sure that we can confirm each light is actually a population place. narrator: using a combination of various population and geographic data sets balk is able to determine how many people live in low-elevation coastal zones. balk: this is southern vietnam. so, we see the white areas are administrative boundaries. the red areas indicate the nighttime lights -- the urban areas. and this blue data set is the elevation zone that we've constructed from the srtm data -- shuttle radar topography mission elevation data set. so, we have ho chi minh city here. that's the big red area. and we'll now add the elevation buffer. the areas that remain bright red are above 10 meters, and all other areas right here where the blue has overtaken it is below 10 meters and it's evident that the entire city is not below 10 meters, but much of it is. this notion of combining these different types of data at these fine resolution is an innovation and it's an important one for effecting policy because without data of thi

as the source data and then whenever the data updates the software will update as well. if you are not a programmer and just at the spread sheet level, which is fine you can actually do quite a bit and using the website you can aggregate the data and filter and some of the dash boards use that functionality to build the charts and graphs and the powerful thing about using this tool is that when the new contributions come in, for instance, and let's say that you build a graph that was analyzing the contributions your graph will update automatically and you will not need to build a new graph every time that new financial data comes in and the last thing that you can do is that you can mash up the data so you can take the data and even if the data source is from another department and if, for instance, the city's geographic team posts a zip code map and we have data that aggregates to the zip code level. in this is a that is right ha the staff presented on the information technology that shows that each department's contributions to the open data effort and despite the fact

it is a data storage device.ou have to move to the other twomms. -- two m, you have to get the credit report and check them out. sign up for transitional monitoring programs, which are free, offered by financial services companies telling you of activity in your accounts, and buy more sophisticated monitoring. and the third m. manage the damage, you need a damage control programme. some think it's prohibitively effective. there are many institutions like insurance companies, smaller banks and enp programs, where they'll help you through situations like this, and it may be free, it may be a perk of your relationship with the institution. >> ed, i was listening to adam run down the steps i should take to protect myself and it sounded like all the convenience i earnt through the new world is going away, because all that swipy, easy commerce is now outweighed by the need to check whether someone is robbing me or not. >> i think it's really about being alert. and you can go ahead and use a lot of the convenient servic

that data? >> the ids from the obama campaign inform all the basic models. of the dnc vote builder which is a combination of our product van and the voter file and additional information -- that has a number of set models and all those models use the obama ids. that is important because there were more ids made by the obama campaign than any other campaign. there is an ability to look of peopleive swath and have information on them. available toare everybody whether you are running for city council, congress, senate, governor. they are having a big impact on races because these models introduce a lot of efficiency. rly, it is revolutionary for the smaller campaigns. chuck was at the rnc in 2004. back in the day, it was $150,000 for a model or something like that. >> we were doing models to were three times in a cycle as opposed to continually recycling them. campaign, to be able to use a model, to determine who they should be modeling is amazing. >> this may sound like an obvious question, but w

data. so what some have talked about is using the method of regression adjustment to level the playing field in terms of assessing institutional performance of minority-serving institutions and non-minority-serving institutions. >> is it something like what deborah santiago was talking about? >> exactly what deborah santiago was talking about. and so in regression adjustment, the idea is to predict a graduation rate based on what we would expect given the student and institutional, financial characteristics, perhaps policies to promote college completion, admissions policies, and compare it with the actual graduation rate. and so if the expected graduation rate was higher than the actual graduation rate of an institution, that institution might be seen as underperforming, but if the graduation rate that was expected was below what we saw to be the actual graduate of that institution, it might be interpreted as overperforming. one of the takeaways that's sort of been coming up is that msis a

data. so what some have talked about is using the method of regression adjustment to level the playing field in terms of assessing institutional performance of minority-serving institutions and non-minority-serving institutions. >> is it something like what deborah santiago was talking about? >> exactly what deborah santiago was talking about. and so in regression adjustment, the idea is to predict a graduation rate based on what we would expect given the student and institutional, financial characteristics, perhaps policies to promote college completion, admissions policies, and compare it with the actual graduation rate. and so if the expected graduation rate was higher than the actual graduation rate of an institution, that institution might be seen as underperforming, but if the graduation rate that was expected was below what we saw to be the actual graduate of that institution, it might be interpreted as overperforming. one of the takeaways that's sort of been coming up is that msis a

we're collecting the data to supplement the data being collected by self report. the self report data from students is one of our chief outcome of interest. so this is just giving you a little bit of an overview of how we select the students. some schools do want to assess all the students. they feel strongly about that. it's nonidentifiable. it's annan mus in that framework. it allows us to capture the data electronically through the on line system and most importantly, it spits it right back out to administrators. they can see the data in real time and be able to sort it and create different types of charts. so we built in a lot of elements around youth involvement and youth voice. in fact, we had youth advisory committee that came up with our tag line that you'll see here. what kind of school do you want your school to be? i would love to say these are real children but they aren't. they're just too perfect and beautiful. we wanted to put together a campaign that we rolled out across the schools and you can see it's really about getting youth voice and youth in

lot of cars have data. what if we collected the data from a car manufacture that was getting a feed about where that car was going? that would, i think, raise similar issues to what we have with the meta data. my guess is that there will be a change in the third party doctrine. it won't be overruled. i think pen registers will continue to be pen registers but i think there might be limits or recasting. largely because these are older doctrines and there's a lot of unattended consequences from simply repealing the doctrine all together. >> i would hope that whatever recalibration of the rule takes place we don't end up in the position where the line is drawn between surveillance that you can do easily and surveillance that's expensive to do. >> right. i agree. >> yes. >> hi, i'm rita from national security council with the constitution project here in d.c. my question i'm happy to hear from other panel lists from oth panelists but for bob in particular. i was hoping you could respond with the government's vi

of voters role data bases that simply we don't know -- we don't have good data. we have problems in which there are errors and mistakes in the data bases we are using to check voters. and the end result is similar to here. there is big news and everybody hears about it. in the end you come down to 85 people. and in the end you come down to 8 5 people out of a hundred thousand, out of, what, 7 million potential voters in florida. the problem isn't new. and so while i think the decision to hold back was the right one, why were we in the decision in 2014? why weren't we fixing this or holding off earlier? >> let me just say something, i'm not an expert in this o area, but obviously the way in which this whole thing was implemented was clumsy. or certainly gave that appearance. it didn't look well. but it is in our best interest to make sure we don't have people on the roles that are not entitled to vote. so if there is someone on the roles here and in two different states, we don't want that. if the person is not qualified in the first place, we don't want that puer

there has been possible data, but more importantly, there is a lot of data coming out today and that's giving a lot of uncertainty. we also get the industrial production as a eurozone as a whole which follows the individual countries we've had over the last few weeks. the ftse 100 is off 0.36%. france off exactly the same amount. italy is flat. let's go on to bonds. we have seen a lot of tightening in the yield surf over the last few weeks as people post to safety. in the u.s., 2.42%. germany, 0.89% below 0.9%. it happened significant lit in the uk. 2.11% in the start of october. as a relative trade within europe, uk seen as a safe haven as growth outlook at got worse and italy the yield at 2.34%. let's look at forex. the u.s. dollar has just come back again after the last day, of course, the last week and the first day of this week. the u.s. dollar weakened off its recent trend. we had that weak italian inflation data out. the u.s. dollar backed against the yen 0.4% up. aussie/dollar, 0.8746. dane yesh shared chipped up a gear after the group reported 8.6 billion euros. investors welc

and it questions how accurate the data is. >> related to that, talking about accessibility of data. i can say we are very disappointed they didn't mention the clary reporting act process on the website. they listed the 55 schools under investigation, but they're not going to do that again. now you have to request it. and one of the big problems with this issue, and i know law enforcement can speak to it, it's a silent issue. people didn't know there was a complaint on campus, and if they did, they could come forward. and the evidence gets flushed out. i think data is of concern. >> let me ask our police chief. one of the things that i realize is that the clary act uses definitions from both the ucr and the national incident base reporting. and it's my understanding that if someone is taken by force into their car and driven across town and then they break in somebody else's apartment and then there is a rape, are you reporting a kidnapping, a rape and a breaking and entering as three separate incidents, and nobody has any idea that it was the sail, all-in-one crime. is that actually

financial data, marketing data, sale data on the fly. people really want right sized information.don't want weeks and weeks. >> who are some of your customers? large enterprises. we are focused on scale making it easy but at the same time, keeping it scalable. when you talk about accessibility, that's great. on the other side of the coin is security and scalability. they have some large volumes of data and a large number of users. butg able to provide these meeting scalability and manageability needs is sort of a key focus of thoughtspot. >> so much has been made about the potential of big data that we have yet to see it become truly usable. it's difficult to go through all of that information. ig data been overhyped or have we not figured it out yet? >> we are learning how to use it. thoughtspot is a classic way of turning data into insights. you don't actually need to know the full query. it suggests things just like the google search box but on enterprise data and very large amounts of data. applications like thoughtspot make data usable. intos the key to turning reality. >> ho

. >> 5 and 6 a that's the breakdown of that data. >> so it's that's the completed grade 12 without graduation requirements right. >> is that ms. chan. >> is that considered drop out is this completed grade 12 without the graduation are those 50 included in the 80. >> completely left without a diploma they're just gone from our system and we don't have that. >> i would like to say in terms of retained in the fifth year we're working with the counseling office to develop a task force to look at the fifth year seniors and how to better serve them in our district as we well. >> any convicting from the colleagues okay. seeing none oh, commissioner maufas okay. i think that one thing it stands out when we look at the plan one and we look at on page 7 and we looked at it broken down by race i feel there's something i don't know what it is but i feel some of this is missing it would giving me a good at some point whether or not they are offering more or less opportunity through our graduation is the gpa or the grades i feel like we i've seen indicate i gave us that showed us a large number of student

data on the fly.e really want bite-size information. they do not want to wait for weeks and weeks for somebody from i.t. to pull a report for them. our customer base is made to large. -- miod to large. scale, making on it easy, but at the same time, when you talk about accessibility, they have large volumes of data and a large number of users being able to provide ease, but meet the enterprise class needs, security needs, stability means, work.ment needs, that is >> so much as been made about the potential of the data, but we have yet to see us become truly usable. it is difficult to go through all of that information. big data overhyped, or have we not figured it out? >> we are learning how to use it. is a classic example. one of the interesting things is you do not actually need to know the full query. googlejust things like search does but on very large cases of data. makes the data usable. that is the key for turning what is hype into reality. >> how do you turn it into a reality? this over the ne

we're collecting the data to supplement the data being collected by self report. the self report data from students is one of our chief outcome of interest. so this is just giving you a little bit of an overview of how we select the students. some schools do want to assess all the students. they feel strongly about that. it's nonidentifiable. it's annan mus in that framework. it allows us to capture the data electronically through the on line system and most importantly, it spits it right back out to administrators. they can see the data in real time and be able to sort it and create different types of charts. so we built in a lot of elements around youth involvement and youth voice. in fact, we had youth advisory committee that came up with our tag line that you'll see here. what kind of school do you want your school to be? i would love to say these are real children but they aren't. they're just too perfect and beautiful. we wanted to put together a campaign that we rolled out across the schools and you can see it's really about getting youth voice and youth in

and we can share the tools, that we are using to analyze and enrich and structure, the data. and so that we don't have any repetition of work and so that we can all sort of stand on each other's shoulders and make progress with these things. and, yeah, so, those, maybe, we rambled a little bit. but, there are a number of sort of technical, social issues with these different brigades going forward. and we are going to continue working with the ethics commission, and as much as possible. and for, you know, the foreseeable future, continue working on this project, which is really just a sort of start. so, yeah. thank you. >> for the public, can you tell us the name of the website? it is hard to see on the screen. >> yeah, the website is transparent voting.com. this is the url that we have chosen for this particular visualization we have the get hub repo which is the place where we store our code, and we can put a link to it on this page, after we go. >> great, so the people want to go and play with this site, they can go to transparent voting.com? >> correct. >> voting. >> >> qu

and it questions how accurate the data is. >> related to that, talking about accessibility of data. i can say we are very disappointed they didn't mention the clary reporting act process on the website. they listed the 55 schools under investigation, but they're not going to do that again. now you have to request it. and one of the big problems with this issue, and i know law enforcement can speak to it, it's a silent issue. people didn't know there was a complaint on campus, and if they did, they could come forward. and the evidence gets flushed out. i think data is of concern. >> let me ask our police chief. one of the things that i realize is that the clary act uses definitions from both the ucr and the national incident base reporting. and it's my understanding that if someone is taken by force into their car and driven across town and then they break in somebody else's apartment and then there is a rape, are you reporting a kidnapping, a rape and a breaking and entering as three separate incidents, and nobody has any idea that it was the sail, all-in-one crime. is that actually

our focus has always been the data. we are using the tools to get the data fast. retreat it fast, be able to alocate the robots, they are bad. hot. most of our projects, if you go to the client sights are not very interesting, mine is in the middle of the desert it is extreme let valuable to where they usually send people on top of them. in terms of our technology, we used to tell investors, in a world where you have no bikes, we basically have photographers that need to go around a construction site, we created a bil to get on it and go around. our focus is not the bike t is the data coming back to us. we mixed, you know, creating the wheels and christ's products r our -- chris's products. >> how safe and reliable the systems are. you look at people and companies who operated these for hundreds of thousands of flight hour, all of that is in the military. a significant portion of their losses are all related to pilot and operator error. as we develop the software to make the aircraft autonomous, and put things in forced work flows in place, there is someone who ca

that it's easy to store the data? >> what a good business would be if you write a blocker app that send it to a fake calendar and fake address book. >> you work on that. thank you for being with us this morning. "press:here" will be back in just a moment. >>> welcome back to "press:here." i thought we'd talk about what's working when it comes to girls and stem careers, science, technology, and sharing and math. 74% of girls now is express interest in stem in schools. that is in thanks part to mentoring going to those classrooms, telling girls about the fun to be had in engineering and programming. case in point, the band of animators who make the pixar films. this is what you're seeing, it's computer science. danielle fineburg, her bio says she was responsible for among other things, the jelly fish in "finding knee moe," that impresses the heck out of me. she's the director of photography. i said 74% of girls are interested in s.t.e.m. in school naps number just drops amazingly when it comes to the number of girls who

in the spring of 2014 this is an update about the interventions and status of the students so the data enlarging validation with the transition. >> i'm sorry mr. koffman can you explain that are you saying this is just of the students that we are that told about previously that didn't graduate? commissioner that is an update of the students that were endorsed in 12 grade last year >> and didn't graduate or still had some missing a g credits i guess i misunderstood i didn't get the meeting sorry. >> based on the 12 graders that were enrolled and this was the plan one of the 5 plans for the first year of a there g dwrauts is so any students enrolled in 12 grade we have this projection that are on track it was 70 percent i'll get that slide then that is the update of interventions banlsz the model we put in place the number of 12 graders that graduate last year. >> okay. i appreciate that you. >> so with the switchful from student information systems last year under the director bill sandy son the superintendent we evaporated an end year the synergy if he were going to have clean day we'l

in any city in california, and then they also took the state's data and included it as well. and so you can actually tap into all of the data state wide and so you could build something like this now and again, this is only, it has developed in the past week, so a lot of stuff is moving at the moment. >> thank you. >> any other questions from the commissioners? >> well, thank you very much for the presentation. we appreciate it, and thank you for your hard volunteer work. it is really great, and i think that the public is going to greatly benefit from it. [ applause ] public comment, on agenda item three? >> i too would like to compliment these volunteers, the website looks terrific. i think journalists larry bush at city report.com would absolutely love this new website. so, keep on encouraging them to work with mr. massey. >> david, pilpal speaks an individual, three comments, it would be nice if the group could explain the light blue and the dark blue, and the difference between the blue and the red and i just saw it quickly. >> and i think that there is an explanation, an

data. we should be able to use them, and looking at what institutions are doing. if you have a high concentration of latin americans and latinos that don't get through, thats that to be weighted when you're looking for completion. completion is the goal, enrollment is the necessary component. you can't complete if you haven't enrolled but looking at the profile of the students that are enrolling has to be weighted by the concentration of the students that have financial needs whether financial or academic. >> in this paper we did focus on men of color because we did try to focus on three critical areas that the nation is calling on right now. in a previous paper i wrote with valerie lundy wagner at columbia, and is one of my former students, we wrote a paper that looks at the gains of women of color. it's specifically at black colleges. i haven't looked at that across all msis, but at black colleges, if i were to be completely frank, the success of black colleges is due to women of color. i

set that would be the data set assuming it's the data set, same data set that the government currently has. i'm asking, is it your position that that is constitutional or unconstitutional? >> it would be constitutional for the government to issue a targeted demand for a limited set of data as it has always done. what is unconstitutional about this program i think are several things. first is that the government is collecting in bulk everything at the outset in a way that has never been permitted either as a statutory matter or as a constitutional matter. second, once the government has that information in its possession, it runs queries on that data. but our principal complaint is about the government's collection of that information. >> that raises what i said was going to be my second question. that is, there appears throughout this in particularly -- this case was brought -- was begun less than a week after the disclosure of the program, if i'm not mistaken. >> that's right. >> there's been a fair amount of water under the bridge since then. what we refer to as the red brief, which

lot of cars have data.hat if we collected the data from a car manufacture that was getting a feed about where that car was going? that would, i think, raise similar issues to what we have with the meta data. my guess is that there will be a change in the third party doctrine. it won't be overruled. i think pen registers will continue to be pen registers but i think there might be limits or recasting. largely because these are older doctrines and there's a lot of unattended consequences from simply repealing the doctrine all together. >> i would hope that whatever recalibration of the rule takes place we don't end up in the position where the line is drawn between surveillance that you can do easily and surveillance that's expensive to do. >> right. i agree. >> yes. >> hi, i'm rita from national security council with the constitution project here in d.c. my question i'm happy to hear from other panel lists from oth panelists but for bob in particular. i was hoping you could respond with the government's view

i get it that there's a lot of data, but now you actually have a data base that's already built, so it seems like anybody working on any one of these projects would just be putting the information in. if i spend 5 hours on it i'm going to put it right into the data base, on this document, which i presume resides with the staff and it could easily be produced every three months. it didn't seem like there was any additional work because six months seems like a very long time. half a year seems like a long time for us not to have any idea --. >> it was just a suggestion. but you are correct, we have standardized a lot of this so we can just run a report and we may have to tweak a few things just to provide some clarification, but if the commission would like to see this quarterly we're certainly amenable to that. again, we just thought because it's so much data to absorb at one time maybe six months made more sense than 3 or 4 months. >> i think we all absorbed it really quickly. >> that's good. >> when you have a data format it's not that hard to print a report. >> that's true. okay. >>

in most... >> and what about the other data does exist. >> yeah, it does exist. i mean that it could be pulled together rather the same way that this data is pulled together. >> thank you >> commissioners. >> i want to thank commissioner melara for setting the tone on domestic violence and i actually wanted to say that dr. harry edwards who is often a commentator on the media and he is a scholar and he was asked to comment on the issue of police accessive force and he really said, on terms of the racial issues that we can't even talk about racial equality until we prevent violence against women and he was asked specifically to comment on whether or not the violence accessive force was a racial issue, and so that is food for thought as you go to your conference. and i am happy with the steps that we have recognized and being on the board of saint francis hospital and there is a woman's physician dialogue group and so we have had the privilege of having the doctor from ucsf as well as christie from the department of department health as trainers to train the health

and a network is just data.efending a network is a matter of interpreting that data, doing it very quickly and responding very quickly. and with the algorithm that context relevant has, we are going to be able to do that. >> steven, big banks have an ability to spend more money than many other companies on these efforts. j.p. morgan alone 600 million on cyber security in a year. but it's surprising to see a small company do something a big company can't. why do you think that is? >> i've spend almost a decade on this. and we have a major leap forward in the technology that allows us to automate what people have cone by hand for years. so there are huge companies like ibm and -- that send in armies of the consultants and we send in a few people and a software box and the advantage of technology is putting us ahead of our competitors at this time. >> can you give us a the practical, a firm example of what you are talking about? >> sure. so practically we can scan through voiceover ip logs and all the data logs tha

collecting the right data is complicated and we want to make sure that the people designing the system have the proper expertise to do this right. for this reason we specify the qualifications necessary for each of the seven members for the advisory board, which will include a person who has worked as a discrimination or employment lawyer with an emphasis on gender equity, a person who works in human resources responsible for diversity, a person who has worked on quantitative gender analysis including statistic, and i want to thank the commission on the status of women, after speaking to the president we also provided a copy of the legislation to their director more than a month before this vote. and i want to thank the commission on the status of women for its feedback, for its expertise which we have incorporated the comments that they gave us. after initial phase-in period of the human rights commission believes that wage discrimination has taken place at a particular business, it can proactively investigate the business to determine whether workers receive equal pay for equal work.

data. we should be able to use them, and looking at what institutions are doing. if you have a high concentration of latin americans and african-americans that don't get through, that's to be weighted when you're looking for completion. completion is the goal, enrollment is the necessary component. you can't complete if you haven't enrolled but looking at the profile of the students that are enrolling is going to be weighted by the concentration mass of students with need, whether it's financial or academic. >> great. so, in this paper we did focus on men of color because we tried to focus on three critical areas that the nation is calling out right now. in a previous paper i wrote with valerie lundy wagner at community college research center at columbia, and one of my former students, we wrote a paper that looks at the gains of women of color. it's specifically at black colleges. i haven't looked at that across all msis, but at black colleges, if i were to be completely frank, the success

use the data. and, in fact, have actually seen that even in our control schools that only got access to the survey, they're actually improving just by getting access to the data. but we are seeing greater gains in our schools that got the interventions as well. this is a little bit of an overview of the observational data. we're using two main tools. one we referred to as the assist and has been previously used. we actually go into the classrooms. nobody goes into high school classrooms and provides teachers feedback about the use of praise or punitive statements or who they're providing praise and punitive statements to or much less what the students are doing. and so that data is very eye opening. we go into 25 randomly selected classrooms and provide that feedback to the schools. they're just amazed at how much information they're able to get from that feedback. then we have another measure that's referred to as the safety. this is a little bit more about the built environment. it comes out of a

set that would be the data set assuming it's the data set, same data set that the government currently has. i'm asking, is it your position that that is constitutional or unconstitutional? >> it would be constitutional for the government to issue a targeted demand for a limited set of data as it has always done. what is unconstitutional about this program i think are several things. first is that the government is collecting in bulk everything at the outset in a way that has never been permitted either as a statutory matter or as a constitutional matter. second, once the government has that information in its possession, it runs queries on that data. but our principal complaint is about the government's collection of that information. >> that raises what i said was going to be my second question. that is, there appears throughout this in particularly -- this case was brought -- was begun less than a week after the disclosure of the program, if i'm not mistaken. >> that's right. >> there's been a fair amount of water under the bridge since then. what we refer to as the red brief, which

number of students that passed with a d or better this is the achievement gap and tha that type of data is pretty interesting to find out where we're in the gap if we are doing all this to close the gap and give more opportunity for a there g will give important access but help us to close the gap to fully understand the gap if you're african-american students or latino or chinese students or weather white students if they all graduate with a majority of d that's not giving nor opportunity but closing the door to opportunity because why a there g you won't be able to be joining a larger university so because of the entrance requirements i'm trying to get out of the information is about are we have we narrowed the gap of opportunity for our students like is that racial gap closings and a way to look at it what the students are graduating with we know that organization through g but the graveside it; right? how said that be a greater opportunity to go to a four-year university this was the intention of joining a rigorous graduation requirement. >> thank you president fewer i absolutely ag