15:08:35 . >> Recording in 15:08:41 progress. >> NIKI: Thank you, everybody. Welcome 15:08:44 to the October fair housing advocacy meeting. 15:08:48 I appreciate everybody 15:08:52 making time. If you're joining us from the public, I do know 15:08:55 we have a few folks, we really appreciate your attendance 15:08:58 today. Please reserve the chat function for 15:09:01 committee members. And you're welcome to participate in 15:09:04 the public comment period. I have it scheduled 15:09:08 for 4:15 to 4:30. We can make more time if need 15:09:11 be. I'll call on those who registered in 15:09:14 advance, but if you did not register, you can still 15:09:17 let us know at the public testimony time that you would like to 15:09:21 provide comments. Okay. I will go 15:09:26 ahead and do the roll call. For the record, when I call your name 15:09:29 if you could please unmute and indicate that you are 15:09:33 here. Ashley 15:09:36 Miller. >> ASHLEY: Present. >> NIKI: Rachel 15:09:40 Nehse. >> RACHEL: Present. >> NIKI: Hi, 15:09:42 Rachel. Taylor Smiley Wolfe. >> TAYLOR: Here. 15:09:45 >> NIKI: Thank you, Taylor. 15:09:47 Allan Lazo. >> ALLAN: Hello, present. 15:09:51 >> NIKI: Hi, Allan. Barbara 15:09:55 Geyer. >> BARBARA: Here. >> NIKI: Thank you, 15:09:59 Barbara. Dung 15:10:04 Ho. >> DUNG: Present. >> NIKI: 15:10:08 Holly Stephens P. >> HOLLY: Sorry, had trouble finding my 15:10:11 mute button. 15:10:15 I'm present 15:10:21 . Thank 15:10:26 you. >> NIKI: Mara 15:10:30 Romero. >> MARA: Present. >> NIKI: And 15:10:32 Fanny Adams. >> FANNY: Present. >> NIKI: Thank you. 15:10:35 The meeting is officially called to order. I have 15:10:38 a few staff updates, mostly housekeeping 15:10:41 items. I will actually start with 15:10:44 reappointments and recruitments 15:10:48 together, specifically around quorum. So if 15:10:51 you got a message from me last minute, we 15:10:54 do have a lot of vacancies currently on the 15:10:58 committee, as we wait for reappointments to go through the full 15:11:01 process. Excuse me, recruitments to go through the full 15:11:04 15:11:09 process. So if you're unable to attend the 15:11:12 meetings, please let us know. Quorum is 15:11:15 nine, and current members is ten. We don't have a 15:11:18 lot of room for absences until we get our 15:11:22 recruitments appointed. Those five 15:11:25 vacancies have candidates identified. They in process 15:11:28 for final selection and appointments. I will follow up with more information 15:11:31 including appointment date, if new folks are finalized before our next 15:11:35 meeting in January. So I will keep you posted 15:11:38 as more information becomes available there. But keep in 15:11:41 mind that quorum is tight in the 15:11:44 meantime. For reappointments, everybody should be 15:11:49 aware that City Council reappointed everyone for their 15:11:53 second terms on September 28th. I appreciate 15:11:57 everyone's patience with the case around that, 15:12:00 but we did get everyone officially 15:12:08 reappointed so thank you for signing up for another two 15:12:11 years of service on this committee. Finally, an update 15:12:14 regarding the executive positions. On 15:12:18 the committee we have the chair 15:12:21 and the vice chair 15:12:24 positions. Marreesa was our former chair and she has 15:12:27 resigned from the committee and did not opt for reappointment. So we 15:12:31 do have availability on the executive 15:12:34 positions. I am going to wait until 15:12:37 our new appointments, new recruits are 15:12:41 appointed to the committee before I open that up. 15:12:44 Just so that anybody who does want to express interest in that 15:12:47 has an opportunity to do so. If you're 15:12:50 interested in serving on the Executive Committee with 15:12:53 Jamila, I will be asking for statements of interest 15:12:57 in early 2023. And 15:13:00 finally, a reminder that our meetings are now 15:13:03 hybrid and you're welcome to attend in person if you'd like. 15:13:06 You can see we are down here at the Portland Housing Bureau 15:13:10 offices. Uma is next to me, Matthew is 15:13:13 on my right, and Ryan our admin is 15:13:16 also attending in person. If you would like to attend in 15:13:19 person, our office is downtown on 4th avenue and the address 15:13:22 is always listed in the top right corner of the 15:13:25 agendas as I send them out. You don't have to let us 15:13:28 know advance, but it is always nice if you 15:13:32 do. So before moving on, does anybody have 15:13:35 any questions about our staff 15:13:39 15:13:43 updates? I see some chats here. 15:13:49 Holly has a hard stop at 15:13:54 4:30. Okay. 15:13:58 >> MARA: I was just going to comment that I appreciated chatting with 15:14:02 commissioner Ryan. >> NIKI: Thank you, Mara. >> MARA: Once 15:14:05 I got him on the line it was all trouble from there, but it 15:14:09 was good. He approved my reappointment, 15:14:12 so it's good. [Laughter] >> NIKI: I know the 15:14:15 commissioner's office did all reach out to you. Thank you all for 15:14:18 making important time there to meet and finalize the 15:14:21 reappointments. It's very much 15:14:24 appreciated. Okay. And with that, I'll move to 15:14:28 the presentation and the primary material for 15:14:31 our meeting today. You have myself 15:14:34 and Uma is joining us and she's going to share screen 15:14:37 here for this second part of our demographic 15:14:48 summary. 15:14:57 If you want to back up one. P 15:15:00 >> UMA: Yeah. >> NIKI: There we go. All right. 15:15:02 Okay. So we are working on those beginning 15:15:06 parts of our Portland Fair Housing Plan and setting 15:15:09 the context as we move forward with 15:15:14 more pieces of analysis. This is 15:15:17 examining demographic and socioeconomic factors and how they impact 15:15:20 housing opportunities. This is 15:15:24 part 2 of the sum relationship covering disability status, 15:15:27 poverty, and income. You have 15:15:31 myself, Niki Luneclair, 15:15:38 Bimal RajBhandary also worked on this although he is not with us 15:15:41 today. He's an analyst with PHB. We have 15:15:44 Dr. 15:15:50 Uma krish Nan next to me presenting. So a quick 15:15:53 review and recap of the demographic summaries from our last 15:15:57 meeting. We met in August, and Uma took us over a 15:16:01 wonderful presentation covering population growth, the difference between 15:16:05 growth for annexation versus increased net 15:16:08 migration, which is what we've seen more recently. We've looked 15:16:11 at statistics for race and ethnicity, 15:16:14 median income, poverty rates, and 15:16:18 housing tenure. 15:16:22 You can see there's some asterisks heerl on race 15:16:26 and ethnicity down to housing tenure. From 15:16:29 our August 2022 meeting till today there's been a 15:16:33 more recent release of datasets. They released the 2016 15:16:36 to 2020 five-year ACS estimate. 15:16:39 And so today on the part 2 we'll be making use 15:16:42 of that dataset, and we just wanted to let you know there is 15:16:46 a change there in the dataset that we are using for this 15:16:49 from our last meeting. So there may be some 15:16:52 slight changes. If you have any questions about 15:16:55 that, Uma is in the best position to answer them 15:16:59 for us. Another thing I wanted to 15:17:03 point out is that the dataset is 2016 to 2020. Obviously 15:17:06 we know that Covid had major impacts in 15:17:10 housing and economic realities of folks in our community, and 15:17:13 that may not be reflected in what we're 15:17:16 seeing here. Data always is going to have 15:17:20 a lag and I know that the last few years have been very intense and 15:17:23 so that's just something to kind of keep in mind is that 15:17:26 this data goes up to 15:17:30 2020, those most recent realities that we see in our communities may 15:17:34 not be accurately reflected in the data as 15:17:39 of yet. For today's presentation, Uma 15:17:42 is going to cover a 15:17:45 variety of factors and the impact 15:17:48 and influence of disability status, 15:17:51 poverty, and measures of income inequities. And this 15:17:55 will be our final part for demographic 15:17:59 summaries today. >> UMA: 15:18:02 Thank you. Good afternoon. Can you guys hear 15:18:07 me? Oh, that's great. We are breathing a sigh of 15:18:11 relief here because we've had some issues. Good afternoon to 15:18:14 all of you and some of you may 15:18:17 have been at Part 1, and we really 15:18:22 hope the brief recap that Niki gave, it kind of 15:18:25 communicates that, you know, we are beginning to focus 15:18:28 on the demographic determinants that can have an 15:18:32 impact and we don't 15:18:35 have it in the slide, it's in the backup. But if 15:18:38 you all remember, we talked about the impact -- this is the 15:18:43 analysis of impedestrianimpedestrianments, which is 15:18:46 about policy decisions. But then there are values which are tied 15:18:49 to certain factors of conditions, including but not limited 15:18:52 to demographic and housing 15:18:56 characteristics that have this potential 15:18:59 to act as a barrier and, in 15:19:06 turn, as a 15:19:17 pediment. This means they don't have the same kind of access even if 15:19:20 farp housing wasn't an issue. So that's kind of the reason we start looking 15:19:24 at these demographic variables, and there are 15:19:27 so many different variables we could look at and last 15:19:30 time we were looking at just the growth itself, the 15:19:33 population growth. 15:19:36 And I think we covered housing 15:19:41 tenure and maybe poverty briefly, and I 15:19:44 had talked about race. But these slides 15:19:49 today we focus on disability status, 15:19:52 poverty, and measures of income inequities. And 15:19:55 often we just talk about income 15:19:59 variables, but the census put out three or 15:20:02 four different measures which really captured in the 15:20:08 income inequities. And I have personally I think saved 15:20:11 the best for last because it's so stark. So even if the 15:20:14 front of the presentation gets a little bit 15:20:18 boring and dreary, bear with me 15:20:21 because the last one speaks volumes 15:20:25 to the whole disparity in income inequities 15:20:28 and, in turn, 15:20:31 its impact on fair housing. So before we 15:20:34 go over the number of people living with 15:20:39 disabilities and the race, it's good 15:20:42 to kind of have this Census Bureau definition of 15:20:45 disability. These are slides that we put 15:20:48 together and any gap in knowledge based on your question, that's on 15:20:52 me. He's not here, and he would have definitely been able to 15:20:56 answer. But I will surely note them down and get back 15:20:59 to you. But he had asked 15:21:03 us to mention, you guys don't know about 15:21:07 in, first it's self-reported. So you know, when 15:21:10 they fill out these forms, it's up to a 15:21:13 person to report and not 15:21:16 report. And these -- these have 15:21:20 to be truth against some of the data from 15:21:23 Multnomah County and other better sources that 15:21:26 also capture data on people living 15:21:30 with disabilities probably to 15:21:33 a better extent. But as for a census is 15:21:36 concerned, we look at these -- they have these five 15:21:40 categories of disabilities, which is cognitive, 15:21:44 developmental, intellectual, mental, physical, 15:21:47 sensory, all a combination of these 15:21:53 factors. So if a person reports having one or more of these 15:21:56 issues, then they will be classified as living with 15:22:00 disability. And I wanted to start with the sheer 15:22:03 number of people who have disability. And the 15:22:06 easiest connection to the housing access and situation is, you 15:22:09 know, if we 15:22:14 have close to 15:22:20 75,000, 76,000 of people living with a 15:22:24 disability of one way or 15:22:27 another, we would 15:22:33 have -- accessing -- we 15:22:36 don't have what percent of our housing stock is accessible. Hopefully 15:22:39 we'll get better as it as we move along. But these are 15:22:42 actually the number of people who have -- the 15:22:45 self-reported numbers and you can see overall if 15:22:52 you look at the City of Portland about 15:22:56 12%, 13 sprers been reported living with disabilities. That's the 15:22:59 population living with disabilities. And that clearly 15:23:03 really is the different race groups. And the next slide is -- and it's not like one 15:23:07 group is more than the other because it's all 15:23:10 typed and the absolutely number of people who get 15:23:13 classified into that particular group. And next 15:23:17 one is the one that has these -- the disability status as 15:23:21 a 15:23:25 proportion. So 15:23:30 the blue is 2020 and the green 15:23:34 is 2015. I did the slides maybe I reversed them, 15:23:37 but I think noteworthy is about 15:23:41 12% to 13% of the people of the city live 15:23:45 in -- have disability status. And the standard 15:23:49 mark here is the American 15:23:53 Indian and Alaska can native alone. And you notice it doesn't have the little 15:23:56 asterisk. For those of you who are really 15:24:01 familiar with the whole significant difference, bear with 15:24:04 me. But what this essentially means 15:24:07 is the American 15:24:11 communities [indiscernible] and they don't ask everybody and it's 15:24:14 like 1 in 435 15:24:17 households get served. And it's a monthly severance. And 15:24:21 they put everything -- it's an ongoing survey. At the end 15:24:25 of one year they have a certain sample and they release a certain 15:24:28 data on demographics and housing. And they continue 15:24:31 collecting and at the end of the 15:24:34 fifth year, they put all this together and release 15:24:37 these estimates. That's what they're called, 15:24:42 estimates. And all these estimates, 15:24:46 there's a 90% confidence associated with it. That, you know, this 15:24:49 is likely definitely this might be the -- we 15:24:52 have 90% confidence that the 15:24:56 actual value lies somewhere between this. And 15:24:59 what -- what the -- when then use these bars 15:25:03 and compare two different periods of 15:25:06 time, it behooves us that we 15:25:09 do this test. Is it like any drug or, you know, 15:25:15 increase that you see, is it a significant drop or is 15:25:19 it just a random chance? That's why last time we 15:25:22 talked about probably 15:25:25 Bimal was talking about housing and there was 15:25:29 a precipitous drop and the committee said go back and look 15:25:32 at it. Today we're not revisiting 15:25:35 tenure, but he had done this test of significance for race 15:25:39 groups, and you would see there is no asterisks. That means 15:25:42 we cannot say with any confidence that there is a 15:25:48 drop in the share of 15:25:51 African-Americans who had disability status. And the 15:25:54 same is true for the Black population. 15:25:58 But I think -- I want to go back to the previous slide for 15:26:01 a minute. And you saw 15:26:05 in the second slide it's nearly a quarter 15:26:08 of the native population that's 15:26:11 reporting disability status. And you see a 15:26:15 drop. It's 15:26:19 2523. -- 25 to 23. You're 15:26:22 welcome for your insights. If you look at it, if 15:26:25 you have 4,300 people and thousand of them say they have 15:26:29 disability and then close to that 15:26:32 same amount report disability for the next cycle. 15:26:36 And this shows about 15:26:40 25% have disability status, and for you you're 15:26:43 much more connected to this issue. I think it would ring true that I 15:26:46 have heard from, you 15:26:51 know, folks from other 15:26:55 leaders that the community has a 15:27:00 disproportionately high 15:27:03 rate. So whether [indiscernible] the 25 to 15:27:06 23. I thought this is just my take of it and please 15:27:09 offer your insights that what's really important to 15:27:13 notice is that there is -- there 15:27:16 is differences among these race groups when 15:27:19 it comes to disability status. Some of 15:27:24 it could be maybe this group does not want to 15:27:27 self-report and coming with some experience from the Asian 15:27:30 groups, there is this 15:27:33 tendency not to self-report, say especially mental issues, 15:27:36 et cetera. But I think with the native 15:27:39 population, we ought to be less worried -- less 15:27:42 rejoiced over, you know, it's gone down from 25 15:27:47 to 23, though it's not statistically significant, more important is 15:27:51 probably it's true a quarter of those 15:27:54 who belong to that group have disability issues and 15:27:57 they have -- they're self-reporting that. That was 15:28:00 my thinking when I was looking at 15:28:05 these numbers. 15:28:08 So from disability we moved on to 15:28:11 poverty. And we had these lines of different 15:28:14 order and I convinced Niki that, you 15:28:17 know, the income at poverty 15:28:21 and income, they kind of go -- they're not 15:28:24 necessarily two sides of the same coin, but they kind of -- 15:28:27 they go together. 15:28:31 It's like -- there is a theme to it. The 15:28:34 poverty is 15:28:38 next. And I put up this definition because it's clear that the 15:28:41 federal definition of poverty threshold 15:28:44 is woefully inadequate. It's like, you know, 15:28:47 unless you are, like, that poor, you 15:28:51 don't even get classified as living in 15:28:54 poverty. But for this purpose, the definition is it's all 15:28:57 tied to there is a base from 15:29:01 1982, and actually it's adjusted to 15:29:04 family size. And 15:29:07 what the ACS does is for every year they take into account 15:29:10 inflation, that's what that big long paragraph is trying to 15:29:13 tell you. And I couldn't find a smart way of 15:29:17 shortening it, but you take that base and there are these 15:29:20 factors for each of the family size, and you 15:29:23 multiply that and you get to that 15:29:27 threshold. But the interesting example is a 15:29:30 family of three with one 15:29:33 child, two parents and the child, if they 15:29:36 have a calculated threshold of -- this is for 15:29:39 2020. If they have a threshold of 15:29:44 20,696, then they'll be counted as living in poverty. 15:29:47 And we all know it's like -- this is 15:29:50 really such a low threshold. And we talked 15:29:54 about -- Niki and I talked about this in the morning that 15:29:57 I felt this kind of stringent standard 15:30:00 definitions of 15:30:04 poverty is a sense of value, it's like when the 15:30:07 median income is upward 70,000 or something and then 15:30:10 there's a family even if they make 15:30:14 25,000 or something, then they're not going to be 15:30:17 counted as a household living in poverty. 15:30:22 It's interesting. To me for sure. 15:30:25 So this one is poverty by 15:30:28 age. And again, these are different 15:30:31 rates. And it was too late, I didn't -- I realized we 15:30:35 don't have the actual numbers and I can always send these out to 15:30:38 you later. But the city 15:30:41 has, you know, if you look 15:30:45 at the city level 15:30:50 for 2020, 13% of the city has people living in poverty. 15:30:54 And it was back in 2015, it's 15:30:57 18%. And you see that asterisks. And I 15:31:00 want to mention here that when 15:31:03 the geography gets larger, 15:31:06 that means we're talking about a larger sample and the estimate 15:31:09 has a better accuracy. And I feel that drop 15:31:13 from 18% to 13%, even if 15:31:17 it's not precisely 5%, there was this 15:31:21 uplift and reduction in poverty during that period, you 15:31:24 know, from 2015 15:31:28 up until 2019, I 15:31:31 think, and then down in the whole Covid. 15:31:35 It's been going downhill so quickly, but it's so hard to climb 15:31:38 up. But that drop 15:31:41 in poverty intrudes against that 15:31:44 of the nation. Nation as a whole was 15:31:49 going -- doing better. Some of these other 15:31:52 groups, some statistically significant, others are not. 15:31:56 But the -- also 15:31:59 interesting is the 15:32:02 23% poverty for under 18. And you probably at least some of you 15:32:05 must have heard quite a bit that not just 15:32:08 in the nation, in the city and in the 15:32:11 state we have significantly large number of children living 15:32:14 in poverty. And the child 15:32:18 poverty is sort of and it's hard 15:32:22 to comprehend, but we have far more children living in 15:32:26 poverty compared to the 15:32:29 adults. So that relatively high proportion 15:32:32 is -- it's quite 15:32:40 worrisome. Then we have poverty by sex. And they all 15:32:43 look very close to each other, as it should be. Because the city, 15:32:47 it has a balanced sex ratio, 15:32:50 49/51, something like that. So you're going to see that it's 15:32:53 really close. And 15:32:57 there could be one more, the poverty 15:33:00 by ethnicity. And this, 15:33:04 again, you see some differences between 15:33:07 the race factors and if you look at it closely, the one -- 15:33:11 I was looking at these numbers and if you 15:33:14 look at the Black population and 15:33:17 the American Indian population, it 15:33:21 is statistically 15:33:24 -- significantly drops. 15:33:27 And you kind of go around looking for an 15:33:32 explanation. For this I thought -- I don't have slides 15:33:35 that speak to this, but it was just that 15:33:38 in 2015 -- like if we focus on the Black 15:33:42 population, in 2015 we had about 15:33:45 13,500 people living in poverty. And then in 15:33:50 15:33:53 2020, this was 11,400 or something. So we see 15:33:57 a decline 15:34:00 of 2000 people dropping out of poverty, which is 15:34:03 conceivable. So when you do this test of significance, it does seem to 15:34:06 make sense. Though there are some other situations 15:34:09 where this kind of testing does not make sense. But I thought this 15:34:13 one, you know, it's conceivable that between 15:34:18 15 15:34:24 and 20, 2000 households may have been lifted out 15:34:27 of poverty, you know, it's possible 15:34:30 they made just a little bit more, 15:34:33 that they didn't fit into the stringent definition of poverty. One or 15:34:36 the other. I like to think that their 15:34:39 lives became better, but that big drop, if you 15:34:42 look at the numbers, the drop itself makes a little bit more 15:34:46 sense from 39 to 30%. 15:34:49 So we have to -- it's just that you can look 15:34:52 at these trends and when you try 15:34:55 to make meaning out of it, you have to be a little bit 15:34:58 more thoughtful. In this case, I truly 15:35:01 feel it's 15:35:06 conceivable that 2,000 people did get out of poverty. That's 15:35:09 where you see this big difference. And the same for the American 15:35:12 Indian community, works out to be close to 600 people who were lifted 15:35:16 out of poverty. And 15:35:19 that's conceivable. That's where you see that big 15:35:22 declines for those two race groups and you 15:35:26 see that it is 15:35:31 statistically significant. So we're going to move on to the median income. 15:35:33 These are the set of slides I was working on. 15:35:36 So if you have any questions on the ones we just talked 15:35:39 about, feel free to ask. If not, 15:35:42 we can wait towards the end of the 15:35:51 presentation. >> Could it also be conceivable with 15:35:54 the -- the -- mine, I Seine flux 15:35:57 of diversity, equity, inclusion, that Portland specifically is 15:36:02 bringing in Black and Brown or Black and native people from other 15:36:07 places and so -- and putting them in positions? So could 15:36:10 there be a growth 15:36:13 in -- a population growth where folks 15:36:17 are coming here working at the Intels and Nikes or 15:36:20 places where they're hiring outside of and they're coming in and 15:36:24 making it more? >> UMA: Oh, absolutely. I 15:36:29 think my recollection is every race group 15:36:32 saw some increase. That was the last presentation. But it 15:36:35 you look at actually number of people, it's just that it's so 15:36:39 hard to tie who came and what 15:36:43 exactly is the characteristics. But 15:36:46 Jamila, if I may call you that. >> Certainly. 15:36:50 Please do. >> UMA: I wasn't sure, 15:36:54 maybe there was an official title 15:36:57 or something. Okay. 15:36:59 [Laughter] But it's absolutely possible. 15:37:03 You know, the people who came from 15:37:06 elsewhere, you know, they came with 15:37:09 better income. But then if you look 15:37:12 back, and if you look at the nation as a whole, or 15:37:15 the state as a whole, that definitely 15:37:18 was a period of economic 15:37:22 prosperity. Not shared equally, I do want to mention 15:37:25 that. But the median income did go 15:37:28 up for most race groups, as did the 15:37:32 poverty rate did go down. So you're absolutely 15:37:35 right, that could be a possible 15:37:40 explanation. And 15:37:44 I -- >> Mara and Taylor had questions. 15:37:47 >> NIKI: Mara, I think I saw your hand 15:37:50 up first. >> MARA: Hello, all. Thank you so much for the presentation 15:37:53 information. It's always fascinating and I appreciate your commentary 15:37:56 too, just so you know. And what I was -- 15:38:00 I had a couple of thoughts, I guess. So the 15:38:04 first one was I 15:38:08 appreciate the qualifying factor of, 15:38:11 like there is older data and things change. Because one of the 15:38:14 things, like, I learned about recently was 15:38:17 nationwide child poverty rates went down, but it 15:38:22 was directly tied to kind of the child tax credit thing that we were 15:38:25 doing, like where we were automatically giving it rather than 15:38:28 relying on folks marking it on their taxes or something. And now 15:38:31 that that's over, like we think that probably 15:38:35 those kids will fall back into poverty again and those numbers will 15:38:38 go up. So I also -- and then also I'm 15:38:41 thinking, like, sometimes even if people are lifted out of poverty, 15:38:44 they're just lifted into a place where they no longer 15:38:48 qualify for some of these programs too. So it's interesting to see 15:38:51 kind of how that -- 15:38:55 those numbers kind of go around and 15:38:59 how they can be interpreted. And then the 15:39:02 last thing is in the world of disability we talk a lot about 15:39:07 labels and language and surveys. And one thing we found 15:39:10 is that obviously self-reporting is a little tricky, especially 15:39:13 for different, 15:39:19 like, racial [broken audio] to talk about them in terms of medical 15:39:22 conditions or to make sure that we're defining the 15:39:25 disabilities that we have 15:39:28 listed. So I'm wondering, was that 15:39:31 something that was taken into consideration when they were gathering this data? 15:39:35 Was helping people understand the definition of disability, 15:39:39 I guess? >> 15:39:47 UMA. So thank you. To me it sound like 15:39:51 rambling, but I'm glad. But to answer your 15:39:54 -- I think sort of your 15:39:57 comment, when it comes to these surveys, you 15:40:00 know, they made 15:40:04 them to mees -- these households and 15:40:07 some of it is done online. I really have my 15:40:11 doubts that it's explained as well. 15:40:14 It's, you know, as good as it 15:40:18 gets. Unless [indiscernible] there is -- there is 15:40:22 a form that hasn't gone back, 15:40:25 the [indiscernible] comes 15:40:28 and can explain these data. But you're absolutely right 15:40:31 that it could be a slip between the cup and the lip when 15:40:35 it comes to their -- these 15:40:39 definitions and how people fill out the 15:40:43 forms. So though if you look at the actual form, they give 15:40:46 a little bit more explanation. But 15:40:50 not necessarily simplified or anything. 15:40:54 It's something like -- my recollection is, you 15:40:57 know, if you're -- if you have any of these 15:41:00 disabilities, then -- so they make it a little bit better, 15:41:04 but not necessarily a whole 15:41:07 lot. So it's 15:41:12 -- it is possible that some who get these forms they don't get 15:41:15 the definition of disability and mark one way or the 15:41:19 other. You're right about that. 15:41:22 >> MARA: Yeah, I know that's been an issue in terms of issues 15:41:25 of race as well or national origin or whatnot, 15:41:29 because I think sometimes people just default to, like, not 15:41:32 answering or, like, the White default in the race category and 15:41:35 the way that that impacts how the reporting 15:41:38 looks. And then of course how people either do or 15:41:42 do not get help or attention around, like, for 15:41:45 housing issues, for example. So yeah, it's just 15:41:49 fascinating and I appreciate you presenting 15:41:53 the data in a way that can be understood. But also 15:41:56 just thinking about how important just like one policy, 15:41:59 like the child tax credit can shift the numbers so 15:42:03 dramatically and then also take that progress away so quickly too. 15:42:06 That's just something I've really been thinking about a 15:42:09 lot. So it's helpful. Thank 15:42:12 you. Thank you. >> NIKI: Taylor. 15:42:15 >> TAYLOR: Thank you so much for the presentation, Uma, it was 15:42:19 wonderful. And my question is, 15:42:22 is really about definition of terms and if you could 15:42:25 help give us some context around how the 15:42:28 Federal Government defines the poverty level and the 15:42:31 limitations of that definition, especially as it relates 15:42:34 to I think what we're here to really understand, which 15:42:39 is, like, 15:42:42 disparate impact that might impact groups based on racial 15:42:47 disparities and poverty levels. It would be helpful if you could speak to the definition, whether it's a 15:42:50 helpful tool in terms of understanding whether families could 15:42:54 afford housing in Portland. I know that that's not the focus 15:42:57 of your presentation today, but specifically just the poverty -- 15:43:01 how poverty's defined and how that connects 15:43:04 to living wages in the area, 15:43:07 if at all. >> UMA: 15:43:11 Taylor, I wish I had been better prepared. I 15:43:14 remember reading how they do it. But all the census, 15:43:17 you know how you can pass the buck 15:43:21 when you look at their side, they say we follow the ideas of 15:43:24 office of management and budget that actually -- you know, 15:43:27 they come up with all these definitions and 15:43:30 likewise, even for race groups they say and 15:43:33 refer back to it. And to the best of my recollection, I think the 15:43:37 process itself works, you know, 15:43:40 I'm sure that there are policy folks who put together these definition, it 15:43:44 goes through these. They publish it 15:43:47 in the federal register, it goes through a public comment period and 15:43:50 then eventually they settle on a definition which is in the 15:43:53 federal register. And with the 15:43:56 poverty threshold, they still have -- 15:44:00 they have a very 15:44:04 -- they haven't updated the way they calculate things, 15:44:07 and it still -- it kind of goes by these -- they have 15:44:10 these measures, you know, if someone has a certain 15:44:14 income, that's where the whole cost burden also comes 15:44:17 in. It's like 15:44:21 only non[indiscernible] household 15:44:24 spends 30% of their [indiscernible] and this should be for 15:44:27 food. So they have those indexing. I will look -- I promise 15:44:31 I will look up this paper and send it to Niki and 15:44:34 she can share with you. And some 15:44:37 years back, and probably one of you might know, the New York 15:44:40 had the whole issue with the cell 15:44:43 phone is no longer a luxury. So 15:44:46 they calculate their 15:44:50 poverty limits somewhat differently than the rest of the 15:44:55 nation. But because there was this acceptance that, you know, cell phone 15:44:58 is no longer a luxury item because I don't think 15:45:01 that factors into this other 15:45:05 calculation. But I'm almost certain they still 15:45:08 have some archaic way of calculating it. That's what it comes 15:45:11 out ridiculously 15:45:14 low. And their argument would be, you know, we are doing it 15:45:18 for a nation as a whole so there are states that make more 15:45:21 money, less money, and we'll have to balance it all 15:45:24 out. But even then it is hard to 15:45:28 justify that -- that low limit. It's like they're talking 15:45:32 20,000 or 30,000. And 15:45:36 if it's not controlled for household 15:45:39 sizing, it is pretty 15:45:42 laughable. But I will find that and send that 15:45:45 to you. >> TAYLOR: Thank you very much. >> MARA: This is Mara. 15:45:51 The social worker joke when people ask how do they define poverty, we say I don't 15:45:54 know but it has something to do with the cost of a gallon of 15:45:57 milk. So I don't really know, but that's funny because I don't know 15:46:00 the full breakdown, but I know that 15:46:03 it's really based on these ideas that actually aren't really based in 15:46:06 reality as much anymore in terms of what people actually need 15:46:10 to afford to 15:46:13 live. So, yeah. That's so fascinating. 15:46:16 Thanks for asking that question, Taylor. 15:46:23 >> NIKI: Okay, I think unless there's any more comments on this first 15:46:26 half of the presentation, Uma has a little bit more to present 15:46:31 on income inequities. >> 15:46:34 UMA: Right, right, I almost 15:46:39 forget. [Laughter] You know, the credit goes to 15:46:42 Bimal, he did all the 15:46:46 work. He's in [indiscernible] 15:46:49 continent and I hope he's having a good time. 15:46:52 Moving on to income. The first one up is the whole 15:46:57 Median Household Income. And at the bottom you'll see -- 15:47:00 and he told me this morning not to zoom 15:47:03 anything. But median income, right, it's the 15:47:08 middle. It's the central tendency. What it means is 15:47:11 then we have equal number of households on one side of the 15:47:15 spectrum and we have 50% on the other side of the 15:47:19 spectrum. And you would see this and some of 15:47:23 you -- Mara, looks like you track the policy folks. 15:47:26 This is a measure they love. It's like -- because it's so easy 15:47:29 to comprehend. It's elegant, 15:47:31 right? It's the middle. MHI. 15:47:35 And it's going up or down. I mean, it really is 15:47:38 a decent measure. And 15:47:41 it's true. And I got colors mixed 15:47:44 up, I think, so the green is the 2020 and 15:47:47 the blue -- Bimal and I were trying to coordinate, but 15:47:51 we are not probably fully coordinated, I don't 15:47:55 know. But 15:47:58 since -- and 2015 and 2020, and you see the income 15:48:02 for the step -- at the city level 15:48:05 went up. But what I did was, 15:48:09 so to 15:48:12 make these comparisons easy, I 15:48:15 took the fist and adjusted it for 2020. That 15:48:18 way if we're saying you know what, compared to 15:48:22 2015 we make 30, the households in general make 15:48:25 $13,000 more, that's a straightforward comparison. Because now they 15:48:28 are both in $2,020. Often 15:48:33 you see it's people forget to -- analysts forget 15:48:36 to make this adjustment, but I went 15:48:39 ahead and adjusted it so this is a 15:48:42 data comparison. At the city level, income looks like income 15:48:45 did go up about 14,000, 15:48:51 15,000. And then again we look at these other 15:48:56 race groups and he talks about this income disparity I've 15:48:59 seen on other slides. If you 15:49:02 look at the African American, the Median Household Income, you 15:49:05 know, it's like literally half or close to 15:49:09 half. And these numbers you see, 15:49:13 like in 2016 15:49:20 African-American house household MHI was 15:49:23 33,000. And the White alone, 15:49:28 because we're a largely White city, will make 15:49:32 what the city is [indiscernible] Asians, subgroups, other folks within the 15:49:35 Asian groups will tell you it is not every Asian 15:49:38 group makes all this huge amounts. But in 15:49:41 general, they have higher 15:49:45 Median Household Income. And you have all these other race 15:49:48 groups. And if you look at it, like it's 15:49:51 conceivable, right, between, you 15:49:56 know, in 2015 a Black household was making about 15:49:59 30,000 and by 2020 they got to 36. So 15:50:03 that's an increase. But then you have to look at it in the 15:50:06 context of the city, because everything is priced 15:50:09 at the city level. 15:50:13 And the one bar which I don't have an explanation 15:50:16 and we will look into this, if you look 15:50:20 at the Native American household, you see it went up from 31 15:50:23 to 55,000. And I know you're all 15:50:26 thinking, you know, 24,000 increase 15:50:30 not possible. That's absolutely true. Though it 15:50:33 came out statistically significant this 15:50:36 difference, we have a feeling that there 15:50:39 might be some issues with the estimate itself. 15:50:43 So we should hold off, but let's -- you know, hold on 15:50:46 to that group and we will look at it 15:50:49 further. But the rest of it 15:50:53 at the city level, you know, 15:50:56 every group did collectively better compared 15:50:59 to -- between 2015 and 2020. And then it 15:51:02 has all been economic hardship 15:51:07 since 15:51:16 then. 15:51:22 Besides the ACS, there are two or three other 15:51:25 sources. Was it you, Mara, talking about the child credits and 15:51:28 all, those programs make use of this dataset. But this 15:51:32 is not done the same as a census, so 15:51:35 it's called the small area income and poverty estimate. 15:51:37 And you get numbers at the county level. 15:51:41 And it's a really -- and they also put out data at the school 15:51:44 district level. And I think it's very widely 15:51:47 used by -- by people, you know, 15:51:50 in the education field. But 15:51:54 noteworthy is the fact that the green line up there, that's the 15:51:57 county. We have outpaced the 15:52:00 state as a whole and the nation as a 15:52:04 whole. So the fact that we see 15:52:11 really high incomes at the 15:52:15 county level, the 73,000 or whatever it was, 15:52:20 we have stayed above from 2015 15:52:23 onwards. So this is actually -- this is 15:52:26 measure I was quite excited about, not the 15:52:30 message that it can 15:52:33 raise and I refer to kind of explain the whole 15:52:38 median versus distribution. The median household 15:52:41 that we talked about is the 15:52:44 central tendency. You line up all the 15:52:48 values and individuals in the middle that becomes the Median Household 15:52:51 Income. But it doesn't take into account all the other 15:52:54 values when we look at the income of household. 15:52:57 So the big advantage of looking at a 15:53:00 distribution is then we take a look at every 15:53:04 single observation. And here by observation I mean the 15:53:08 income of households that we 15:53:12 have. So 15:53:15 besides the median which seems 15:53:18 to take up all of the attention in the room, 15:53:21 there are these measures that are also part of ACS. And 15:53:25 they publish something called the income -- they publish the 15:53:28 upper limit of the Quinn tile. So when 15:53:31 you talk about 15:53:35 quintile, you take everyone and put them 15:53:38 in five equal parts. When you have equal number of people 15:53:42 in these five parts, then you have a relative 15:53:45 balance. And that's where this whole talk of, you know, we have 15:53:48 to have -- we should have a disappearing middle. 15:53:52 There was so much conversation around the disappearing 15:53:55 middle, have they really disappeared? Are they moving out 15:53:58 of the city? That conversation becomes relevant. Especially 15:54:01 relevant when it comes to housing. 15:54:04 So I looked at these quintiles and they 15:54:07 do publish the upper limit of the quintile. And 15:54:10 you see these quintiles. But then I -- then 15:54:13 I calculated the number of households that would fit 15:54:17 into each of these quintiles and that's what you see 15:54:20 in the middle column. And roughly, you 15:54:23 know, you would think it's 15,000 15:54:28 to 55,000. But it's 15:54:32 just that then what's noteworthy is 15:54:35 say if you focus on what we do, we're worried 15:54:39 about the unmet housing needs and if you look at the 15:54:43 lowest quintile, when talking about a certain number 15:54:46 of households who make anywhere 15:54:49 between -- you know, it's less than 15:54:54 equal to 10,000 or less or equal to 29,000. And this is in 15:54:57 a city which has a median income of 15:55:01 73,000. And it's -- we're talking about 55,000 15:55:04 households. That's a lot of 15:55:07 households. And for those we're 15:55:10 saying you put so much money into these issues, 15:55:13 homelessness, it's just that we do have a lot 15:55:17 of households that we need to serve and it's getting 15:55:20 harder for them and possibly even people 15:55:24 in the second quintile who don't make 15:55:28 anymore than 57, finding affordable housing 15:55:31 option is getting increasingly 15:55:34 hard. But that's why I like this, it's a simple measure, 15:55:37 but it kind of communicates the gravity 15:55:41 of the housing situation and 15:55:45 people's capacity to house themselves 15:55:49 relatively well. So this is the last 15:55:54 slide. And we have a 15:55:58 measure, ACS puts up this measure. It's called the 15:56:01 aggregate household income. Really 15:56:04 simple. They 15:56:07 put together -- testimony -- it's 15:56:12 like a sum of income that 15:56:15 households repeat. They know how many households 15:56:18 in each quintile. The income inequity is so -- 15:56:21 so big, so huge it's -- 15:56:25 it's -- it's equal to saying if you just look at the 15:56:29 15:56:32 2.9%, it's literally what it translates to we have 15:56:35 55,000 households who collectively earn the 15:56:38 $2.90. Whereas, we have other -- the blue 15:56:42 bar, the 15%, that's the highest 15:56:45 income quintile, we have 50,000 households who get 15:56:48 to keep 50%. So it's a completely inequitable 15:56:51 distribution of what we have and when we are 15:56:54 talking about. And you'll find plenty of this in the 15:56:57 literature also, that the income 15:57:01 inequity is growing. And I thought this would be 15:57:04 a good measure to keep in consideration. It's 15:57:08 literally as simple as that, when 15:57:11 we put households in quintile, they don't get to keep the 15:57:16 same amount of money. 15:57:19 They're keeping vastly different amounts 15:57:22 of money. I think that's the last slide 15:57:27 I have. >> NIKI: I will open up for questions 15:57:30 in just a moment, but to finish off Uma's 15:57:34 presentation, I just wanted to highlight our next 15:57:37 steps. So we've done two full 15:57:40 meetings about a demographic data. 15:57:43 And summaries that Bimal and 15:57:46 Uma have put together. I have everyone's feedback regarding the 15:57:49 first set. And I will also take note of any 15:57:52 feedback provided today. That's going to be 15:57:55 drafted into a report format that we will 15:57:59 share with you all so that we can finalize that as we 15:58:04 move forward. At the same time, 15:58:07 Bimal and Uma are working on 15:58:11 our low-income housing analysis. That's where we'll take all of this that 15:58:14 we've developed over the last six months and connect it to housing and 15:58:17 we'll review the fair housing 15:58:20 recommendations from 2011 and then draft new 15:58:25 recommendations that FHAC would like to participate, provide feedback on 15:58:28 and finalize with us. So that's kind of next steps 15:58:32 from here. What are we doing with this 15:58:35 information and in the meetings to come. With that said, we 15:58:38 have about 15 minutes that I left at the end of the 15:58:42 presentation for comments and questions. And I'm sure 15:58:45 Uma can back us into the 15:58:50 slides if you want to look 15:58:53 more at the median income or at 15:58:56 income and inequities. 15:59:01 >> Jamila: It's stagger to 15:59:04 me the income. I'm sorry, I just be 15:59:07 talking. Taylor, go ahead, your hand 15:59:10 was raised. >> You go 15:59:14 ahead. >> I don't know if something this something you're going to 15:59:17 consider, but the serial displacement 15:59:22 of the Black community in Multnomah County is directly tied 15:59:25 to health disparities and poverty and what we know is 15:59:29 the Black community in Portland has been displaced 15:59:32 in the last hundred years three different times. So 15:59:35 it makes sense that these numbers are what they are for the Black 15:59:38 community. And actually for the native 15:59:41 community. But to me, it's so 15:59:44 staggering to see that the median Black income 15:59:47 is less, is like half of and 15:59:50 it's not -- 15:59:54 it's to me there needs to be some weight in 15:59:57 this, the recommendations here. Because this 16:00:00 is ridiculous. And to me, it seems like it's 16:00:03 directly tied to the displacement of the Black community over and over 16:00:07 again. You can't set up roots, you can't build a community, 16:00:10 you can't have a local store. There's nothing you 16:00:14 can do when you're completely -- you're always displaced. And there's 16:00:17 health disparities, behavioral disparities, like it's shocking. 16:00:20 So I just wanted to put that 16:00:24 out 16:00:35 there. >> TAYLOR: Similarly, looking at the 16:00:38 Median Household Income changes over time, it brought me to the question 16:00:42 around whether you had assessed 16:00:46 changes in zis -- disparities in those two areas. The 16:00:49 fact that they were gains 16:00:53 that were so small for the 16:00:56 Black group made me wonder if the gaps were closed 16:00:59 order widened for the other groups. And that 16:01:02 would be interesting to see in the report to inform potential recommendations of this 16:01:05 group. And then my second -- not question, but 16:01:08 recommendation was around looking at the poverty level statistics again. 16:01:11 It would be very helpful from like an affordable housing mindset if 16:01:15 it's possible to maybe translate those numbers in some way into 16:01:19 AMI categories, like to just show that these different 16:01:22 levels of FPL correspond with 16:01:25 this level of area median income for the Portland area. That's 16:01:28 how we structure a lot of our affordable housing is based 16:01:32 on affordability related to AMI, not the poverty 16:01:35 level. I think that would be interesting to see and might help to ground us in 16:01:38 some housing recommendations. And then my last thought 16:01:41 was just thinking about the different income quintiles that you put 16:01:44 up there. Home forward is the largest provider 16:01:47 of affordable housing in Multnomah County, and we serve 16:01:51 15,500 households, which is only 28% of that bottom quintile. So 16:01:54 that just drives home for me again how underresourced we 16:01:57 are in terms of serving people who could be 16:02:01 eligible or need affordable 16:02:06 federally subsidized housing. I wonder 16:02:09 if we could collaborate a little bit on our eligibility 16:02:12 bands and the folks that are in that bottom quintile 16:02:16 to get, yeah, more clarification on that 16:02:19 gap. Like we know that 1 in 4 households who qualify 16:02:22 for federal assistance get it, three quarters don't. But 16:02:25 that number just was, yeah, hard to see on paper. Thank you so much 16:02:28 for the presentation. 16:02:41 >> UMA: Thanks for those comments. And 16:02:44 the first one there is, you know, 16:02:50 kind of the 16:02:54 MHI means the AMI, and years back I think they might have 16:02:57 done something like that. I think that's a really good idea. When we start 16:03:01 looking at the data which is more about the housing condition and 16:03:06 which kind of [indiscernible] the household size 16:03:09 and race with the kind of housing problems people 16:03:13 have, that also 16:03:16 has some -- which has these bags around, 16:03:19 you know, 30, 16:03:23 60, whatever and see how -- but I think your 16:03:26 suggestion that we do some 16:03:29 cross-match between the ACS and the [indiscernible] is a 16:03:32 good one. We'll do follow-up on that. So thanks for that. 16:03:48 >> NIKI: Any final comments 16:03:52 or questions for Uma? 16:03:57 All right. Yes, thank you, Uma. 16:04:00 Taylor's sending a message in the chat. We really appreciate you and all of 16:04:06 your work. For everything that you do. 16:04:09 Matthew's adding a comment for those 16:04:12 that may be unfamiliar to kind of give them a reference around 16:04:15 income and AMI levels. 16:04:19 Okay. We have a time for 16:04:22 public testimony at 16:04:26 4:15. Which we're ten minutes shy of. So I'm going to move 16:04:29 us ahead to the 16:04:33 subcommittee updates and start there. We can circle back to public 16:04:36 testimony, just in case someone's planning on taking a work 16:04:39 break or logging on right at that time. We will 16:04:42 be on the safe side there for public 16:04:46 participation. So the two subcommittees that 16:04:49 we voted to create last time were the policies and best 16:04:53 practices subcommittee. And the community 16:04:56 engagement subcommittee. Each of those had their 16:05:00 50 meetings just last week on Wednesday and Thursday 16:05:05 respectively. And each of them are going to give you an update 16:05:08 around what we discussed and what we'll 16:05:12 be doing moving forward. So I'll get started 16:05:15 with the policy and 16:05:18 best practices and, Taylor, if you can give us an update on the 16:05:22 subcommittee. >> TAYLOR: Thank you. Our subcommittee met for the first 16:05:26 time very recently and we spent the meeting really talking about our scope of 16:05:29 work, what we wanted to take on and sort of our 16:05:32 purpose. And so we generally discussed 16:05:35 wanting to both -- wanting to do an inventory of the different 16:05:38 policy tools that are available in Oregon 16:05:42 related to their housing policies. And we've defined 16:05:46 those as both individual racism that occurs, 16:05:49 racism and/or other types of discrimination related 16:05:52 to fair housing in the market in which, like, fair housing 16:05:57 enforcement increasement on an individual level would be helpful, but we 16:06:00 talked about wanting to review and think about policies that result 16:06:03 in a disparate impact 16:06:07 based on groups with protected classes. So our scope will include 16:06:10 both of those things and we're starting specifically with individual 16:06:14 discrimination, which is oftentimes more connected to the 16:06:17 enforcement mechanisms that we have available. So that's kind of what we 16:06:20 discussed as our general scope and we're building out a work plan 16:06:24 in earnest at our next meeting. Is 16:06:28 there anything that anyone remembers or would add 16:06:31 that I 16:06:35 missed? Okay. All right. 16:06:37 That's our update then. Thank you. 16:06:40 >> NIKI: Thank you, Taylor. If anybody has any kind of feedback 16:06:43 or areas of work or something that might be interesting that you would like 16:06:47 the policy best practices subcommittee to take a 16:06:51 look at or think about and you're not part of that subcommittee, still 16:06:54 feel free to shoot it over to me and I can pass it 16:06:57 along to Allan, 16:07:04 Taylor, Jae, and Barbara who sit on that subcommittee. They'll be 16:07:07 meeting monthly and we hope to bring interesting things back to you. For 16:07:10 our second subcommittee was community engagement, and 16:07:13 Barbara is going to go ahead and give us an update 16:07:17 there. >> BARBARA: 16:07:20 Hi. Okay. There were just -- 16:07:24 there were two of us, Mara and myself, 16:07:28 well, Niki also was in the meeting. We explored our personal 16:07:31 experiences, some of our personal experiences with those affected by housing 16:07:36 discrimination. And we had a lot of thoughts. It was a 16:07:39 really good meeting. We wanted to identify 16:07:43 targeted groups and then reach those 16:07:46 targeted groups telling them about our committee and 16:07:49 what our committee does. Which is 16:07:52 -- will be determined at some 16:07:56 future point. We noticed how hard it 16:07:59 is for those in housing to 16:08:02 identify fair housing violations, even when 16:08:05 we notice that there are 16:08:09 violations. And that would be part of the education 16:08:12 component. It's hard to talk about fair housing 16:08:15 violations, many people just simply don't want to believe that 16:08:18 it's happening. Sometimes 16:08:23 this differential treatment results in embarrassment or 16:08:29 anger, a sense of victimzation or 16:08:32 fear. And 16:08:36 this prevents people from asserting their housing 16:08:39 rights often. They want to keep their housing and that's very important so 16:08:42 there's that fear component of losing your housing when you do attempt to 16:08:46 assert your housing rights. But as we 16:08:49 discussed, many, many individuals, they're not 16:08:52 even sure what their housing rights are or how to go 16:08:55 about asserting their housing rights. We 16:08:58 talked about 16:09:02 seeking out organizations for mutual help, helping the 16:09:05 organizations or having them come to us. We want to get the word 16:09:08 out, what are our rights? And Niki said that she would be 16:09:12 putting together something on fair housing laws and 16:09:15 actually it was so hard to hear, I'm sorry, 16:09:18 Niki, I didn't get whether you were only speaking of local fair 16:09:24 housing laws. >> NIKI: I think I spoke to the 16:09:27 policy and best practices. I would get together 16:09:30 a list of the last four community 16:09:33 engagement. I think my task was to get together a list of 16:09:36 some organizations that we know do fair 16:09:42 housing work. But if I have that wrong, please correct me, Barbara. 16:09:54 I think we might have lost you, Barbara. 16:10:05 I can't quite hear you. >> MARA: I can chime in if folks can hear me and Barbara can 16:10:08 just cut me off. I was just 16:10:11 going to say just to kind of go back over that a little 16:10:14 bit, I think, you know, we talked about maybe 16:10:19 increasing public comment and public participation. And that was sort of led 16:10:22 into this place where, but how do we safely do 16:10:26 that, right? Where people aren't just dropping stuff and it's 16:10:29 on public record and then nothing really comes from their 16:10:33 disclosure. So that, I think, is something we're exploring as 16:10:36 part of our community engagement group is how do 16:10:39 we make sure people are aware of what's involved 16:10:42 with, you know, fair 16:10:46 housing advocacy or, you know, all of that. So 16:10:49 anyway, that came up. But education, huge focus. Just 16:10:52 making sure people know we're here and what we 16:10:56 do, especially if we actually eventually get, like, 16:10:59 you know, goals outside of the ones we're 16:11:03 setting for ourselves where we need maybe more public comment 16:11:06 or want more public feedback. But again, we're thinking 16:11:09 about how do we do that safely by maybe talking with 16:11:12 organizations and gatekeepers and folks who can help us 16:11:16 do that 16:11:21 well. >> NIKI: Thank you so much for jumping in, 16:11:26 Mara. >> 16:11:29 JAMILA: It's also so they're not targeted but to get up and tell 16:11:32 your story over and over without anything happening, it's a personal -- it 16:11:35 impacts you personally, right? If I'm going to come and speak to 16:11:39 everyone, and that's what it is, it's apathy. Nobody 16:11:43 -- the people of color that I know that are living in 16:11:46 Portland, when something happens, they're like, what's going 16:11:49 to happen? Nothing. Nothing is going to happen. 16:11:52 There's no teeth in any of our policies, so it's just I'm going to tell 16:11:55 on you, it's going to go through all the things, maybe a 16:11:58 couple people will talk to me, I'll have to tell the story over and over and 16:12:01 over. Every time I tell it it's going to hurt worse and 16:12:05 then nothing's going to happen. I feel like it's beyond, and 16:12:08 that's white community engagement, it's a horrible group 16:12:11 to be in because you get to hear the 16:12:15 stories and you can't do anything about it, you know. It's -- what are we doing 16:12:19 about it? >> MARA: Well thankfully that's my 16:12:22 bread and butter is listening all day and not being able to do anything about 16:12:25 most of 16:12:28 it. [Laughter] >> 16:12:36 JAMILA: It's all this time, all this energy, four years and then what 16:12:39 comes of it, you know? >> MARA: We talked about like the 16:12:43 engagement that happens at the rental services, you know, those kinds of 16:12:46 things and, you know, what could 16:12:49 happen if we tried to increase engagement and how do we keep it -- 16:12:52 I guess not focused, I don't want to use that 16:12:55 word. But anyway, we were really looking for feedback 16:12:59 from the larger group how you all felt about this concept of, 16:13:02 you know -- because I get that. A lot of times the people I work 16:13:07 with are in a place where they're not going to be working 16:13:10 on keeping themselves alive and going to do public testimony, right? Like 16:13:13 maybe -- I mean, they always say let me know in the 16:13:16 future, you know, I'd love to help in the future. But 16:13:19 yeah, I think a lot of times it's about finding the right person at the 16:13:22 right time and maybe connecting to organizations that know those 16:13:25 people and then maybe 16:13:29 around specific actions that we're involved in the community engagement group can do that kind of thing, 16:13:32 maybe have some folks that we can call on 16:13:35 to provide testimony or whatever, you know, not that advocacy 16:13:39 driven, but just community engagement 16:13:42 around FHAC and making sure people know we're here and 16:13:45 that we are a vessel 16:13:48 I guess is the right word, for 16:13:52 communicating, if that's something that they wish to do. And that we are a group of 16:13:55 people who are maybe interested in 16:13:58 moving that forward. But not wasting people's 16:14:01 time at the same 16:14:06 measure. >> JAMILA: I feel like maybe 16:14:09 there's a way there's strength in numbers. Commissioner Ryan 16:14:12 doesn't even know what we did. So maybe if 16:14:16 there's 300 people standing behind us and giving these, 16:14:19 you know, and our recommendations are informed by the 16:14:23 community members, maybe then he'll know what we do. You know 16:14:26 what I'm saying? Like we can use the community -- how can we 16:14:29 leverage the community to push -- to really 16:14:32 lean in to whatever these recommendations are 16:14:36 instead of just -- and 16:14:41 making it we Air Force -- are a force to be reckoned 16:14:45 with because we've had so many community members participating in 16:14:49 this, it's not just us. So how can you 16:14:52 not know who we are as we're coming in the 16:14:55 door? >> NIKI: Thank you, 16:15:01 everyone. I -- Barbara, I think you're back on the 16:15:05 line. >> BARBARA: Can you hear me? >> NIKI: I can 16:15:08 hear you now. Can you hear us okay? >> BARBARA: Yeah. 16:15:11 I would like to contribute a little bit more too. I'm sorry I got cut 16:15:14 off. I don't know what happened. I had expressed a lot of 16:15:17 concern about people speaking up about 16:15:21 violations that they feel they've 16:15:25 experienced. Because it's been my experience to look at 16:15:28 that and say oh, my goodness, there is possible danger 16:15:32 for them. There is exposure. I 16:15:35 know when the antiharassment 16:15:38 ordinance was proposed by a certain group to 16:15:41 the resident services committee, they had 16:15:44 people coming forward. But very, very few 16:15:48 people, they feel that this is a huge 16:15:51 issue that warrants an ordinance, a city ordinance 16:15:58 preventing harassment in 16:16:02 housing and yet they were really hard pressed to get very many 16:16:05 people to come forward. And there's a good reason 16:16:08 for that. I mean, I'm not sure I would come into 16:16:11 a public forum and start speaking about some 16:16:15 of the things that are being done knowing I'm 16:16:18 speaking about things that possibly are very 16:16:21 illegal. You know. Harassment in itself may not 16:16:24 be, but violating fair housing 16:16:28 laws or landlord tenant laws or real 16:16:31 estate laws, that's a 16:16:35 pretty serious accusation. So you have to be 16:16:38 very, very 16:16:42 careful about what you say. So that's a dilemma. 16:16:45 I also was on the policy 16:16:49 committee best practices, I get it all mixed 16:16:52 up, and I think what -- what is generated 16:16:55 out of that committee could help us on the community outreach 16:16:59 committee as well. Because I think it would 16:17:03 identify where some of this enforcement that 16:17:06 we talked about is. Part of our mission is to 16:17:10 hold jurisdictional partners accountable. So where is that? 16:17:13 Where does that happen? Where does that come in? 16:17:16 And that's information that we can use in the 16:17:19 outreach committee as well when speaking to 16:17:22 organizations or individuals. So from that standpoint, I'm 16:17:26 actually quite optimistic. Otherwise, I often 16:17:30 sound like I'm pessimistic. I'm just 16:17:34 -- I just want to 16:17:37 caution people about what's happening. And by the 16:17:41 way, that ordinance hasn't moved very far. 16:17:45 It did get the 16:17:48 recommendation of the residents services commission, and they're waiting for it to 16:17:51 go before the City Council. But it doesn't contain 16:17:54 a lot of what I would like it to 16:17:58 contain. And so there's -- there's some room 16:18:03 there, maybe, for other people to contribute 16:18:06 to that ordinance before it's actually presented to City Council 16:18:09 and voted on. >> NIKI: Thank you, 16:18:12 Barbara. And thank you, Taylor, thank you both for the updates. 16:18:15 We'll continue to update you 16:18:18 and we'll be meeting a lot in the 16:18:22 subcommittee groups. If you do want to join either of those, 16:18:25 please feel free to reach out and let me know. And very 16:18:28 timely, we have public testimony scheduled for just a few minutes 16:18:31 ago. And we do have one member of 16:18:35 the public who registered, so I will 16:18:39 start there. Tova Hirschman, 16:18:42 if you are signed up and still would like 16:18:46 to provide public testimony, feel free to 16:18:49 16:18:53 unmute. >> TOVA: 16:18:56 Sorry, I didn't mean to sign for that. 16:18:58 My bad. >> MARA: But I bet you have something 16:19:04 good to say, 16:19:07 Tova. She works in housing in the community and it's nice to see you in 16:19:10 this meet and even if you're not providing a comment, thank you so much and I hope things 16:19:13 are going well over there at community vision. >> 16:19:17 TOVA: Thank you. >> NIKI: 16:19:21 Thank you, Tova. And I'll open it up to anyone else who may 16:19:24 be in the meeting from the 16:19:27 public, if you'd like to provide testimony, feel free to raise your hand, 16:19:30 say something in the chat. 16:19:42 Okay. Well, with that, that completes our 16:19:45 agenda. It is 16:19:49 4:19 p.m. I will be following up with policies and best 16:19:52 practices subcommittee next month with the community engagement 16:19:57 subcommittee in December. Uma, 16:20:00 myself, Bimal will work on a draft for you 16:20:03 of the demographic summary. Uma will be working on a 16:20:07 low income household means analysis, very exciting 16:20:10 as well. We are blessed to have Uma 16:20:13 present so much wonderful data to us. And so we'll 16:20:16 have that ready for the January 16:20:19 meeting. Given the timing, that means that our presentation 16:20:24 is probably set to go out right after the 16:20:27 holiday. So keep an eye 16:20:30 there. There will be some 16:20:34 vacations and such, we'll get that to you right away. I 16:20:37 will update everyone if there is any movement in terms of new 16:20:41 recruitments being appointed to the body between now and the beginning 16:20:44 of the 16:20:48 year. Mara. >> MARA: Really quick. 16:20:51 Speaking of data, Taylor, you mentioned earlier something about only 16:20:55 28% of, like, that first -- I don't know what the word was, 16:20:58 I'm going to be honest, but something meaning probably the 16:21:01 first group of folks in sort of the deepest level of poverty or 16:21:05 something, and there were only reaching 28% of those 16:21:08 folks. So -- and that's just that first level. 16:21:11 Is that kind of sort of how a 16:21:14 layman could interpret 16:21:17 that information? >> TAYLOR: It was looking at -- it was 16:21:21 the lowest quintile of the income spectrum, that was 16:21:24 about 55,000 households. I was doing in my head 16:21:27 comparison between the number of folks 16:21:30 at home court serves which is 5,500, but the folks we serve 16:21:33 are not exclusively in that first income quintile. So 16:21:36 we'd have to do a dealership assessment the current incomes of folks we're 16:21:40 serving. We tend to serve folks in the 0 16:21:47 to 30% with an average of 16:21:50 15% income. So not always 16:21:53 in that first quintile, but possibly 16:21:56 within that. >> MARA: It's shock will. People are 16:21:59 constantly dropping shocking information on me and I'm like can you say 16:22:03 that again, like when that measure 110 came out about 16:22:06 behavioral health services and stuff, it's like what? Is