15:05:36 to lead us through the roll call, so
15:05:39 I'll hand it over to
15:05:47
15:05:50 Marisa.
15:05:58 a.
>> MARISA: I don't know if I have the most up-to-date list of people in the
15:06:01 committee.
I'm wondering if I should be referring to that when I
15:06:05 do the roll call?
I apologize.
15:06:18 Is that just now you sent that or --
15:06:22 sorry?
>> NIKI: How about I just move forward
15:06:26 with it?
>> MARISA: Sure.
>> NIKI: As
15:06:29 I call, will you indicate you're present?
We'll start with
15:06:33 Ashley Miller?
>>
15:06:35 Present.
>> NIKI: Hi, Ashley.
>> Hello.
15:06:39 >> NIKI: Rachel?
>> Present.
>> NIKI:
15:06:44 Taylor?
>> Present.
>> NIKI:
15:06:47 Ada
15:06:51 Antonio?
15:06:56 Allen Lazo?
>> Present.
>> NIKI: Hi,
15:06:58 Allen.
Barbara Gaier?
>> Present.
15:07:02 >> NIKI:
15:07:05 Becky Straus?
15:07:18
15:07:22 Ellen?
>> Present.
>> NIKI: Hi, Ellen.
15:07:25 Holly Stevens?
15:07:28 Jay
15:07:32 Rutherford -- J. Rutherford?
>> Present.
>> NIKI:
15:07:38 Mara
15:07:41 Romero?
Marisa?
>> Present.
15:07:45 >> NIKI: Thank you, Marisa.
15:07:51 Vera Warren?
15:07:56 And Fanny
15:07:58 Adams?
>> Present.
>> NIKI: All right, great.
15:08:01 We did
15:08:06 hit
15:08:10 quorum.
Marisa called us to order.
I'll
15:08:13 go ahead and move us on some staff updates today.
15:08:16 It's good to see you guys.
15:08:19 So first off, I'll address that the meeting looks a little
15:08:22 bit different today, and I am on camera
15:08:26 in this conference room and I know --
15:08:29 can't quite see my face as well.
I have a couple of
15:08:36 PHB colleagues with me we'll hear from later.
Portland
15:08:39 housing bureau officially opened back up to the public to attend in-person
15:08:44 our public meetings.
15:08:48 That included our
15:08:51 PAC committee meetings.
You're welcome to come down to
15:08:55 the Portland Housing Bureau
15:08:58 and attend a
15:09:03 PAC meeting if you'd like.
If it's more comfortable for to
15:09:06 you attend virtually, that'll remain an option.
Thank you
15:09:09 for having patience with us while we're in the new hybrid environment
15:09:13 but this is how we'll be proceeding moving forward.
15:09:17 The public testimony may also be in person, folks from the community can
15:09:20 come in and sign up and give public testimony from
15:09:25 our offices for greater accessibility or they
15:09:28 can also still do so via zoom as they have in the past.
15:09:33 My next update
15:09:36 is just regarding that meet
15:09:39 the committee page we talked about on our bureau website.
15:09:43 So in our last meeting which was actually
15:09:47 April, we were asked to send in head shots
15:09:50 and bios.
I wanted to say thank you to everyone who took the
15:09:53 time to do that.
I really appreciate it.
If you haven't taken a look
15:09:57 at the published final page, I just dropped it in the chat for you.
15:10:01 And if you haven't had a moment to send those in,
15:10:04 if you can get those to me by the end of the week and I can make sure that everyone is
15:10:08 included, that would be wonderful.
15:10:16 Also from the last meeting, you may remember the appointment terms for
15:10:20 committee members end next month in September, so I did ask everybody to check in
15:10:24 one-on-one to see who will be moving forward with reappointments
15:10:27 and who may be just finishing
15:10:30 out their term with us next month.
We do have three committee members
15:10:34 that will be finishing their term with us.
That means this is
15:10:38 actually their last meeting.
So I'm going to announce their names
15:10:41 in a moment, but before I do, I'd
15:10:44 ask you please on mute, and we can
15:10:47 give a small -- unmute and we can give a small
15:10:51 round of applause for the committee members and thank them
15:10:54 for the time they served with us over the last two years.
The
15:10:57 first committee member is ada Antonio.
15:11:01 She's not here today but
15:11:04 we'll clap for Ada here.
Becky Straus who also is not here but I'll
15:11:09 give a clap for Becky.
Becky.
15:11:13 Finally our chair, Marisa Espinoza.
Thank
15:11:16 you so much, Marisa!
[applause]
Really appreciate it!
15:11:19 Personally, I'm very
15:11:23 thankful for your time spent with the committee and for
15:11:26 your leadership in particular, Marisa, in taking on
15:11:29 the chair position, so thank you!
And in
15:11:32 that vain, the rental services office has been working
15:11:35 on recruitment in order to fill those positions.
Thank you to each
15:11:39 committee member that took time to share those
15:11:43 names with your networks.
We were able to have a total
15:11:47 of 16 applicants for our three available seats.
We're
15:11:51 finalizing our recommendations and then once everything is confirmed, I'll send
15:11:54 out an update e-mail to share with all of you
15:11:57 where we're at on that.
We anticipate they'll
15:12:00 be fully appointed next month along with all the other
15:12:03 committee members scheduled for reappointment, so
15:12:06 -- in September.
I'll sent out council information as soon as I have it.
15:12:11 And that is all the staff updates that I have.
15:12:15 Thank you.
15:12:18 The next item on our agenda for today's meeting
15:12:22 is our demographic summary.
This is the
15:12:26 very first section of our Portland
15:12:30 Fair Housing plan.
The two
15:12:33 presenters is Uma Krishnan sitting here with me at
15:12:36 PHB along with billmal RajBhandary who is
15:12:40 on the other side of Uma here.
I will hand
15:12:43 it off to Uma to get us started on the presentation.
15:13:05 >> UMA:
15:13:12 OK.
15:13:17 Good afternoon.
Niki asked if we can introduce
15:13:20 ourselves.
I'm Uma Krishnan.
I do know some of you.
15:13:23 Others perhaps we don't know
15:13:26 each other.
I'm with the housing bureau, the data
15:13:29 team, and for several
15:13:33 years, I was the city
15:13:39 's coming toographer with the planning.
I
15:13:42 literally begged Niki to let me present.
I'm going to hand it to
15:13:47 Bimal, my colleague with the data team at PHB.
15:13:51 >> BIMAL: Hello, I'm Bimal
15:13:54 RajBhandary.
I've been here with the committee before over the last couple of years.
15:13:57 I'm excited to be here again.
And I'm hoping to
15:14:00 have a restart of the whole process.
Thank you.
15:14:09 >> NIKI: Thank you.
15:14:13 Before we launch into the demographic summary, we want to take a moment to outline the presentation for
15:14:16 you and lay some context.
This is the first part of the Portland
15:14:19 fair housing plan.
We'll cover the effort
15:14:23 and how it relates and compares to the traditional analysis
15:14:26 of impediments.
Uma will speak to the
15:14:30 impact and influence of population growth, competition, diversity, income, and poverty
15:14:33 on housing opportunities.
15:14:36 And then Bimal will spotlight
15:14:39 some selected characterize of
15:14:43 Portland's households.
15:14:47 So, it has been a while since we've met.
I wanted to take a moment to
15:14:50 remind us all about
15:14:54 the Portland Fair Housing plan and about what led us to this work to start with
15:14:57 .
Remember back in 2020 and
15:15:00 early 2021, we were looking originally at the 2011
15:15:04 analysis of impediments to fair housing choice.
That was
15:15:08 the last time the comprehensive
15:15:11 Fair
15:15:14 Housing planning was done.
It's consortium-wide.
It includes
15:15:20 multijurisdictional planning.
City of Gresham, Multnomah county
15:15:23 and Portland all going through the process of fair
15:15:26 housing planning together.
It's also related to the other Hud-required
15:15:30 planning.
That's why we're waiting from HUD
15:15:33 to give all us information.
And
15:15:37 in the interim, this body has decided to move forward
15:15:41 with the support of the housing
15:15:46 bureau on a Portland
15:15:49 Fair Housing plan.
It's different.
We're only looking at the
15:15:52 Portland jurisdiction when we look at these areas of analysis.
We'll cover the
15:15:55 topics as outlined in our project plan.
If you'll
15:16:00 recall the memo which committee member, we did a presentation on and everybody gave
15:16:03 feedback to incorporate in that plan.
And then we will
15:16:07 expand upon this work whenever the analysis of impediments or a similar
15:16:12 fair housing planning requirement is
15:16:15 announced by Hud.
The first section
15:16:18 , the demographic analysis we're entering into is to set the context as we look at
15:16:21 all of those other areas and policy recommendations moving forward.
15:16:30 There's going to be a few words we hear within the
15:16:35 AI.
We'll probably hear them again as we move through the
15:16:37 Portland fair housing plan.
I want to take a moment to define those.
15:16:41 When we talk about barriers and housing barriers in this
15:16:44 context, it's any factor or condition that has the potential to
15:16:47 create a disparity impact on
15:16:51 a person's housing choice.
15:16:54 That could be a variety of different things.
We talk about an impediment
15:16:57 , and that's a defined term.
It specifically means
15:17:02 actions, omissions or decisions by a jurisdiction that
15:17:05 effectively restrict a person's housing choice because of race,
15:17:08 color, religion, gender, disability,
15:17:11 familial status or national origin.
So
15:17:15 those two have different meanings.
We'll hear them as we move through this work
15:17:19 and as we compare it to the recommendations that
15:17:22 were made in the analysis of impediments in
15:17:25 2011, so keep that in mind and that all barriers
15:17:28 , we expect, will limit housing choice, but some barriers become
15:17:32 impediments when they're related to protected class status
15:17:36 specifically and actions, omissions or decisions made by a jurisdiction
15:17:39 .
And with that, I will hand it
15:17:42 over to Uma.
>> UMA:
15:17:46 Thank you.
I hope you all can hear me and
15:17:50 -- this is probably the loudest I can talk, but I
15:17:53 really hope you can hear me.
And
15:17:57 before I explain this slide, I just wanted to --
15:18:00 because Niki just talked about when we did the last
15:18:04 plan.
That was in 2011.
15:18:07 Most of the data came from
15:18:11 the 2005-2009
15:18:18 ACSD, American survey.
Then there was new
15:18:22 data.
Ten years have gone by.
A lot has happened, including the fact
15:18:26 that in 2020, the census did a full census, census as
15:18:29 in counting everybody through
15:18:33 their form, and then they released their data last year
15:18:40 in 2021.
Even if the full analysis of
15:18:45 impediments is not due -- this work probably need not start until 2024
15:18:49 , it really makes sense for us to start
15:18:53 looking at the 2020 census, because the
15:18:56 city changes so quickly, right?
And for most of you
15:19:02 , -- and Niki talks about this all the time -- lived
15:19:05 expediency.
You do have a good idea where
15:19:09 Portland stands not just in terms of its housing or for the
15:19:13 issues or population growth, but these numbers
15:19:16 kind of substantiate what perhaps we see on the crown.
15:19:24 More people.
More traffic.
Reduced rental vacancy
15:19:27 rates.
This work
15:19:30 around Portland's fair housing plan is a great
15:19:35 opportunity for us to get grounded and form this
15:19:38 base that, you know, it's 2022, but we did take a look at
15:19:44 2020 data.
So the slides I'm going to talk about
15:19:49 , lastly, it's going to be about the population and the competition
15:19:53 , and Bimal will cover
15:19:58 really interesting slides around power
15:20:01 via income and tenure, and we really hope that
15:20:05 it's not just the two of us giving you a lot
15:20:08 of numbers and then
15:20:12 you get bored or get overwhelmed, but the whole idea is at the end of this
15:20:17 presentation, hopefully we'll have time left, because we have 10 or 15 slides
15:20:21 , um, but that you as a committee help us
15:20:24 kind of better understand how these
15:20:28 are barriers and what we can do in terms of planning to address
15:20:33 some of the barriers which could potentially become impediments.
15:20:36 So bringing us back to this slide, I wanted to put
15:20:39 it up, because it's fascinating, and I
15:20:42 found this in the -- it's an atlas Portland
15:20:47 cultural atlas.
It came out of PSu.
If
15:20:50 you look at the -- PSu.
If
15:20:54 you look at the graphics, it shows how the
15:20:57 city grew spatially it begins back in the 80's and the 90's and goes
15:21:00 from '94 to present.
But it shows
15:21:04 annexation.
19th and 20th
15:21:07 centuries, it was spatially expanding Portland.
In 1845
15:21:11 , it was just 36 blocks.
The early
15:21:14 part of
15:21:19 1900, neighborhoods like
15:21:23 Montavilla, St. John were an nexted.
There was limited
15:21:28 an sexation between 1980.
There was a lot
15:21:32 between 1980 and 1998.
15:21:36 When you annex land, you also --
15:21:39 you know, brings in people, right?
Many of them, they've already lived here
15:21:42 and we are just bringing them into the fold of
15:21:46 the city's boundaries so that we can do a
15:21:50 services provision or whatever that is.
15:22:04 The next slide is about population.
It's about the total
15:22:07 number of people in the city grew from 1890 all the
15:22:10 way to 2020, and it's
15:22:14 really clear, we continue to
15:22:17 grow, and there was maybe one or two periods
15:22:20 of decline, but then if you come to the -- the moment
15:22:23 you come to -- since 1990 and 2000
15:22:27 , the
15:22:31 slow growth, that regression line, it goes up.
That means
15:22:34 the rate of growth -- by
15:22:38 no means its exponential or anything, but it's
15:22:41 very steep.
It's fast.
More people just means, right, we
15:22:45 need to house them.
So the city actually grew
15:22:48 -- not a surprise we grew faster than the nation in
15:22:51 the 21st century, and here
15:22:55 is the important thing: much of the growth
15:22:58 since 2000, it's attributable to net migration as
15:23:01 opposed to annexation, and
15:23:04 this is interesting, because when it's migration
15:23:08 , this group of people who come, the
15:23:12 new people who come into the city, they
15:23:15 might bring, they have different characteristics, potentially.
It could
15:23:18 be different household types, size, educational attainment and
15:23:22 you can immediately realize, right, the
15:23:26 last 10-20 years we've become the most educated city -- I mean
15:23:29 mean, I don't even know is it just --
15:23:33 [indiscernible]
Not quite sure.
So that's what this
15:23:39 population graph shows us.
It clearly tells us we have continued to grow and
15:23:43 since 2000, it's at a much faster
15:23:48 pace than we did in the past.
So this slide
15:23:51 , it's the last bit that
15:23:54 focuses on the last 10 years.
So in 2020, according to
15:23:57 the census numbers, our population
15:24:01 is 652,503.
That's a pretty big number.
You
15:24:05 know, we have really -- we have crossed the
15:24:08 half a million.
In the
15:24:11 last 10 years, we added
15:24:14 69,000 people, and the percentage change is close
15:24:17 to 12%
15:24:21 .
To put that 69,000 in some perspective,
15:24:24 it means every year, we could have potentially added, you
15:24:28 know, if I was doing cumulative averaging the annual growth rate,
15:24:32 it's about 6,900 people which is 18 or 19
15:24:36 people every day and right away, we can tell, you
15:24:39 know, we're getting people faster than we can build
15:24:43 our homes.
So that's -- the table you see that to
15:24:46 the right kind of compares us to all of the
15:24:52 relatively close areas geographically.
How do
15:24:56 we compare to the nation as a whole?
The nation grew by
15:25:00 7.4%.
We grew by about 12%.
That's a much higher
15:25:03 rate.
Oregon state -- you know, and we get a lot of the
15:25:07 increase within the state
15:25:11 , so the state grew 10.6%.
15:25:15 The fact we have a new congressional
15:25:18 member in the seat kind of tells us, yes,
15:25:21 we did grow pretty fast.
15:25:27 The decade before this, they were not growing as fast
15:25:30 .
They grew at 21%
15:25:34 , Seattle did, and they added
15:25:38 120,000 people.
I'm taking this
15:25:41 from memory but I think between 2000 and 2010, that was
15:25:44 the first time that Portland added more people than Seattle
15:25:50 , and even I probably should go back and check, but
15:25:53 that's my recollection.
The last 10 years have been so different.
15:25:57 San Francisco on the other hand, they grew,
15:26:00 you know, a little bit faster than the nation at 8.5%
15:26:04 , added just about the same amount or close to
15:26:09 the number of people that we added.
For those
15:26:12 of us kind of looking at people and housing, you
15:26:16 know, we can kind of
15:26:19 clearly relate these two things that Frisco doesn't
15:26:23 have affordable housing.
People have to move.
15:26:26 The migration is always from higher density to lower
15:26:29 density, so Portland is well positioned to receive people
15:26:33 from the north and from the south.
We
15:26:36 should look for people moving from Seattle.
15:26:42 So this -- this is -- I have to
15:26:45 confess, this is a graph I totally find
15:26:48 fascinating, and I love this!
And for those of
15:26:52 you to whom it seems like really busy, these are called the population
15:26:56 pyramids.
It allows us to look at the population
15:27:00 of a city but then by age and sex
15:27:03 .
So it tells us, you know, what is
15:27:06 the composition of the city?
You know, do we have a whole lot
15:27:09 of old people?
Young people?
People in the middle?
15:27:12 And, so if you look at this, this is the
15:27:16 pyramid from 2020 and the reassuring
15:27:19 factors -- because we have a stable base
15:27:22 -- it is -- it's a stable pyramid, but, you
15:27:26 know, bulging in the middle, which is a good thing, because that means we
15:27:29 have a lot of people in the labor force,
15:27:33 but I think we should also note that as we
15:27:36 keep moving up and 65 and over,
15:27:39 that is a sizable block as well
15:27:42 , so this is a city
15:27:46 that does have a significant number of
15:27:49 older adults
15:27:52 and we think about it in terms of what could be the potential
15:27:59 impediment?
We really need accessible housing and
15:28:02 I know we've been talking about this for a long
15:28:05 time, but the fact we have at least 13% or 14%
15:28:09 of older adults in this city, we
15:28:12 need to start thinking how well does the
15:28:16 housing -- does our available
15:28:19 housing stock match that?
So -- and I forgot
15:28:23 this, I should have said this right at the beginning when I put up
15:28:26 this slide -- so this is
15:28:29 the percentage of population.
Each bar, whether
15:28:32 it's the blue bar or the pink bar, it kind of shows
15:28:35 the share of that particular group.
You can
15:28:39 see 0-4.
We have
15:28:46 2.6 or 2.9 percentage of younger children otherwise
15:28:50 on the other side it's 2.5
15:28:53 or 2.6.
Each of the clustered body
15:28:57 is the shared population, and
15:29:00 for this particular graph, in terms of composition, we
15:29:04 have gender equality, because we have almost
15:29:08 same number of -- same share of men
15:29:11 versus women.
I think the men are a little bit more
15:29:15 , but close to 50% or something, and if you start looking at
15:29:19 charts from some of the other countries, even
15:29:23 my own country in India,
15:29:26 the sex ratio is actually in favor of men, so you can actually see
15:29:29 it in the population pyramid, but we're in
15:29:33 a good place.
But the other thing to note, say if I
15:29:36 put up a pyramid for
15:29:39 Albania or Kenya or something, you would have seen a broad base, meaning
15:29:44 older or younger people.
15:29:48 It tapers toward the top.
That means not a lot of older people.
Those
15:29:51 countries have a certain set of problems which are very different
15:29:54 from what we need to think about.
15:29:57 By no means, that would be balanced.
If you take a
15:30:02 look at the pyramid for Germany, you would see there's a huge top
15:30:05 but then the bottom Teaters out.
That means they
15:30:08 don't have enough young people.
But that's
15:30:11 the value of these pyramids.
They help us understand
15:30:15 the composition of the population and
15:30:20 -- which helps us plan for them.
15:30:25 This one, with some debate from Niki to the right and
15:30:29 Bimal to the left, they say leave it off.
It's got
15:30:32 two factors.
You see 2020 and 2010.
When you put one
15:30:36 pyramid on top of the other, it tells us, you know, which cohort
15:30:40 grew or shrank.
You
15:30:43 can tell the darker blue and the
15:30:47 darker pink are recent numbers, and that
15:30:51 share grew 1.6%.
The share of older adults, if
15:30:54 you see 65+,
15:30:57 they grew close to 2%, and -- but then you
15:31:00 will also see a decline.
You'll see the lighter blue
15:31:04 pinpointing out -- that means in 2010, we had more children that age
15:31:08 , so if you look at the group 0-17
15:31:11 , that decline as a group,
15:31:15 1.5%, and I know we're not here to talk about
15:31:18 fertility trends and all of that good stuff, but
15:31:22 the fertility rate has dropped, and you see that in fewer children
15:31:25 , so for
15:31:30 demographer
15:31:33 s, it really makes sense.
We're done with the
15:31:36 population group and composition.
I
15:31:40 have two more slides which talk about the race and ethnicity.
15:31:44 These have come from the 2020 data.
15:31:48 And you see in about 2010 and then 2020
15:31:52 , it's clear, right?
In 2020
15:31:55 , just over 72% of the population
15:31:59 were white.
Come 2020, that
15:32:02 share has declined.
This is the first
15:32:05 time there's been a significant drop of 6%.
15:32:09 But that doesn't mean, you know,
15:32:12 we're anywhere close to becoming a diverse city.
That's a
15:32:15 table that ranks all the large cities in terms of diversity in 2010, we used to be
15:32:21 very last, meaning least diverse, so we've moved
15:32:24 up a spot, I think, about collateral,
15:32:28 something, I forget, but -- ha-ha.
15:32:31 But this is the composition
15:32:35 , and -- we're definitely getting
15:32:39 diverse, and I don't have a slide for that, but if you look at the
15:32:43 same break up for children, you know, 0-17
15:32:46 and 17-20 or something, the children are definitely
15:32:50 much more diverse than adults as a group
15:32:53 , and that certainly means, you know, we have implications for
15:32:57 educational, you know, institutions
15:33:00 , and everything ties to housing that then families
15:33:04 with children ought to be able to live near good schools,
15:33:07 not just any schools.
But this is
15:33:11 the last of the slides that I have before I give it to -- hand
15:33:14 it over to Bimal.
This kind of shows,
15:33:18 you know, the
15:33:22 new changes and the 2+ races.
That's where
15:33:25 we're adding the most number of people.
15:33:34 Race could be how
15:33:37 the people
15:33:42 identify themselves.
When you see drop
15:33:45 of 108 for American-Indian/Alaska Native
15:33:50 , those don't fully count.
Traditionally, all people
15:33:53 of color was undercounted, particularly so -- and this
15:33:56 is true in case of the American-Indian,
15:34:00 Alaskan-indian community, so I don't even -- you know, though
15:34:04 it sounds so precise, drop of 108, I'm not even
15:34:08 sure, you know, which need to really go --
15:34:11 we need to really go by that.
In the past,
15:34:14 it's been some years, but we tended to also
15:34:18 make a note when we use the census provided
15:34:23 by the state, the data, for
15:34:26 the Native community, we used a
15:34:29 community-validated number.
That was around 36,000 for the county.
15:34:41 This lays the base for us how we gain the 69,000 people
15:34:45 .
I think the next slide is on income.
So I'm going to
15:34:48 hand it over to Bimal,
15:34:52 but I'll run the slides.
>> BIMAL: Thank you, Uma.
15:34:59 Thank you for the demographic changes in Portland based on census
15:35:03 data.
What I'll do is briefly highlight just a
15:35:06 few points just so the disparities
15:35:09 in income quality level and home
15:35:12 ownership and rentership rates across various rates in the
15:35:15 city groups, which I think -- I'm hoping that
15:35:19 this information will frame us as we move ahead
15:35:24 with our Fair Housing work.
This is the first slide
15:35:28 .
Median house income by race and ethnicity
15:35:31 from 2014-2019.
And you can
15:35:35 see that median household income actually increased for almost
15:35:38 all of the groups, but then if you dig in and
15:35:42 look at the specific
15:35:46 race groups, you see they do vary a lot.
If you just
15:35:50 look at the income for the whites versus
15:35:54 the income for the Black/African-American,
15:35:58 they're not up to par even though
15:36:01 the income has risen for all of the groups in general.
Next slide
15:36:04 .
So this slide shows the poverty rates
15:36:08 , poverty rates are based on the
15:36:12 poverty data.
They're all from 2014-2019
15:36:15 .
You can see that poverty rate actually decreased
15:36:20 .
But then again, if you start
15:36:24 looking at specific race or specific groups, you find
15:36:28 they do vary from each other.
Certain groups
15:36:31 have poverty rates higher than others.
But they have
15:36:35 actually decreased from 2014 to 2019.
15:36:38 One of the reasons I think
15:36:42 there's a speculation for the decrease
15:36:45 in poverty rate is that the rising of the
15:36:50 minimum wages have contributed to the
15:36:53 lowering of the poverty rates.
Next slide, please.
15:36:57 So this slide shows the
15:37:01 number of households from 2014-2019.
The
15:37:05 number of households actually increased by 6.6%, but if
15:37:10 you look at the
15:37:14 owner-occupied households as opposed to
15:37:18 renter-occupied house holds, they differ.
15:37:21 Owner-occupied households go up by 8%.
15:37:24 Renter-occupied households up by 6%.
What's really interesting is that
15:37:31 owner-occupied household.
[indiscernible]
Coming
15:37:36 to a disparity.
Almost
15:37:40 like.
[indiscernible]
So that
15:37:45 will.
[indiscernible]
15:37:50 [low audio]
So this
15:37:54 slide shows the homeownership rates by race and ethnicity.
15:38:01 The rates --
15:38:05 overall --
>> Bimal, can you speak
15:38:08 up?
Sorry
15:38:12 to interrupt
15:38:14 .
>> BIMAL: Homeownership rates increased overall.
15:38:18 Almost all the groups, except for the
15:38:21 African-American and
15:38:23 .
[indiscernible]
Groups.
15:38:28 Homeownership rates increased by these particular groups.
15:38:31 The rentership is different.
It's the flip side of the homeownership.
15:38:35 You'll see the rentership increased
15:38:40 overall, and also it increased over all the groups.
15:38:46 Rentership is up.
15:38:50 These are some of the
15:38:53 basic things I'd like to highlight.
15:38:56 I'm assuming it will help us as we
15:39:01 move along with
15:39:06 our Fair Housing work.
15:39:09 Our continuation of demographic data
15:39:12 , we are going to keep collecting and analyzing data.
We're hoping
15:39:15 to come up with the
15:39:18 housing types next time.
We'll start focusing
15:39:22 on disability rate as well as low-income housing analysis.
15:39:25 So at this point, I
15:39:29 would like to get
15:39:34 your guidance.
15:39:42 I'm sorry, my voice soft.
15:39:45 >> NIKI: Thank you, guys.
Sounds like the volume was a little bit
15:39:51 low.
I have a loud voice.
I hope I'm
15:39:54 not yelling at you.
I'm yelling in person to make sure that the
15:39:57 mic picks me up.
Thank you to Bimal.
Thank you to Uma for
15:40:01 putting together that work.
I don't know if you heard Bimal at the
15:40:04 end there, but we would love to get the
15:40:08 committee's feedback on this demographic summary.
15:40:12 We do have more work planned to bring it back
15:40:15 and, again, this would kind of be the first section of the overall
15:40:18 plan.
This is to provide context.
I know
15:40:21 everyone is very excited to get
15:40:26 to policy recommendations and more of the meat of the work, but we'd love to
15:40:29 get your thoughts on this first section.
15:40:36 Marisa, feel free to unmute.
>> MARISA:
15:40:40 Thank you so much for all of this information,
15:40:43 Bimal and Uma.
I just have
15:40:46 a couple questions or actually, one thing I'll ask is
15:40:51 would it be easier for me to ask multiple questions
15:40:54 at once right now just to kind of keep the
15:40:58 -- keep it flowing or should I, like,
15:41:01 maybe ask a question and let someone else go?
Just wondering
15:41:04 for process sake.
>> NIKI:
15:41:08 Ask away.
>> MARISA:
15:41:11 Just go for it.
OK.
So my first
15:41:15 question is about the decrease
15:41:18 in poverty, and this may have been where the sound was a little
15:41:21 fuzzy, but it kind of sounded, Bimal, like you were saying
15:41:28 that you were suspecting there was a relationship between
15:41:31 the adoption of minimum wage increase and
15:41:34 the decrease in poverty, and I was wondering if you can say more about
15:41:37 that or, you know, if there are maybe
15:41:41 alternative explanations for
15:41:45 that.
>> BIMAL: Yes, Marisa.
It actually
15:41:48 came up in our last meeting when
15:41:52 I presented this
15:41:55 information.
15:42:03 [indiscernible]
Because of the overall -- the
15:42:07 impediment of the economy, the economy was doing good.
That
15:42:10 also made some difference, but
15:42:14 I think it pays to do more analysis to figure out what other causes
15:42:18 lead into that.
>> MARISA: If I heard you
15:42:21 right, that could be a contributing factor but there would need to be
15:42:24 more analysis to know
15:42:27 what the reason is?
Is that what you said?
I'm sorry
15:42:31 .
>> BIMAL: At this point, like I was just presented basically
15:42:36 basic facts about what the rates
15:42:39 are, but I haven't dug into what are the reasons for the poverty rates
15:42:44 to come down.
It's important to look
15:42:47 at that as a part of our work.
I'm definitely happy to look at it.
>> MARISA:
15:42:50 OK, great.
15:42:55 >> UMA: I wanted to add to what Bimal is telling you.
This drop you see
15:42:59 -- and you will see, you know, a companion increase in the median
15:43:02 income, and that was actually true
15:43:05 across the board
15:43:10 meaning even at the national level and the literature has evidence that this was before
15:43:13 Covid hit us, towards like, you
15:43:17 know, 2018-2019, and it's hard to kind of
15:43:21 point this one thing causes the effect, so it's not
15:43:24 like the minimum, you know, the minimum wage was increased
15:43:28 , but there was this -- and it's so hard
15:43:31 to remember, because we fell on such hard
15:43:35 times as a world, but there was this
15:43:38 period of prosperity which hadn't happened until way back in the 1970's, so
15:43:45 that data, the drop in poverty is actually
15:43:50 -- it's valid across the nation and the state
15:43:53 and the city.
15:43:57 >> MARISA: Oh, OK.
15:44:00 Yeah, because I guess what I wanted to maybe more to the
15:44:04 point of my question is, like, is
15:44:07 there any possibility that you see that drop in the share of folks
15:44:10 who are experiencing poverty because they're now
15:44:13 elsewhere?
Right?
So like would it be possible that
15:44:16 people who are experiencing poverty don't
15:44:20 live here anymore as much because they can't afford to?
I mean, I
15:44:24 guess I just wonder if that's possible.
15:44:29 >> UMA: That would be circumstantial and certainly possible, because
15:44:32 we can map -- and that could be part of the
15:44:36 work.
We have thought about it.
15:44:39 If you map the geography, nothing is
15:44:43 affordable.
Even across the world, things
15:44:46 are getting not affordable, but it's just that it'd be hard to
15:44:49 say it's not -- because you can't follow people unless it's done
15:44:53 delicately, because
15:44:58 my -- you know, I'm inclined to think the
15:45:01 share of people working
15:45:04 poverty has probably gone up compared to
15:45:09 poverty rates for the number of people compared to
15:45:13 the last time.
It's hard for us to tell, but at least
15:45:17 the same people have to move away.
But I
15:45:21 think based on what you're saying, it
15:45:24 really would be good to kind of map this
15:45:27 geography of poverty, and that would be good to
15:45:31 look at.
>> MARISA: Yeah, I totally agree.
I'm
15:45:34 really glad that you used the word "map" in part because I think this
15:45:38 was some of the thoughts I had shared a while back with Niki about the
15:45:43 Fair Housing assessment.
The need at some point in the future to
15:45:48 really incorporate multiple geographies and jurisdictions in
15:45:51 that analysis given the fact when we talk about
15:45:55 homelessness and housing instability, we know it's regional.
It's
15:45:58 really difficult to think about the issues and how people are pushed out of communities
15:46:04 , especially people of color, when we only kind of focus
15:46:07 in on one jurisdiction, so, yeah, I
15:46:10 think that would be really interesting to look at.
My
15:46:13 other question which I hope I'm not taking too much time but
15:46:16 it's very similar in a way, because -- so
15:46:20 with the slides you showed, I don't know if I absorbed this correctly because
15:46:24 it was going quickly and I didn't have a chance to look at it beforehand,
15:46:27 but one of the things I thought I saw on there was a decrease
15:46:31 in Native American renttorship.
15:46:35 Again, one of the things we see a lot in homelessness is really significant
15:46:40 racial disparities for Black households and Native American households
15:46:43 who are much more likely to experience homelessness, not only in this area
15:46:47 in Portland, Multnomah county but also across
15:46:50 Oregon, so I'm just wondering if you can say more about that decrease
15:46:54 in rentership and whether that also tells us something about
15:46:58 a displacement type of situation for
15:47:01 Native American households.
15:47:14
>> BIMAL: I think it's duly noted.
The city
15:47:17 of Portland hasn't.
[indiscernible]
So
15:47:20 I think it's more for the work to
15:47:24 be able to find out what are the reasons
15:47:28 for the rentership being down.
There are
15:47:31 housing programs specifically meant for --
[indiscernible]
15:47:36 So I think
15:47:41 .
[indiscernible]
>> UMA: Marisa, actually keep this in
15:47:45 mind because 2021, they did the -- what was
15:47:48 it?
In '22, they did the point in time challenge.
15:47:51 This summer, they were
15:47:55 releasing details about the demographics on the unsheltered
15:48:02 community/unsheltered homelessness.
It'd be good to see
15:48:06 where that stands.
15:48:09 We can't directly draw a line, but that's definitely,
15:48:13 you know, -- and I think the two would be
15:48:16 helpful and we could say, you know, have we see
15:48:19 dramatic increases
15:48:24 in the Native population, homeless
15:48:27 or something?
Very good point.
We'll definitely keep this in mind
15:48:31 .
>> NIKI: Just a side note,
15:48:34 Bimal, people still can't hear you very well.
We'll try to turn off the fan
15:48:38 and project, Bimal
15:48:41 .
Yeah, I'll hand it back to Marisa.
15:48:44 I didn't know if you had another question or comment there.
>> MARISA: Yeah, thank
15:48:47 you, again so much, Bimal and Uma.
My
15:48:51 last thing is more of a comment.
I think it was Bimal --
15:48:54 no, Uma, it was you who had showed the
15:48:58 demographics slide.
I think about age
15:49:01 .
And I think about this question of
15:49:05 increase in older adult population.
Just
15:49:08 coming from that area of focus, I would just throw out there
15:49:12 really quickly -- because I try to say this as much as I can as far as the
15:49:15 housing needs of older adults is, you know, a lot of times we do really
15:49:18 focus on accessibility for
15:49:22 disabilities, right?
Like
15:49:26 ADA and mobility and ramps and handle bars and things like that but one of the things I know
15:49:30 we need to also really remember is just that affordability
15:49:34 is such a huge factor, the incredible
15:49:41 gargantuan need for deeply affordable units for older dolts who
15:49:44 are increasingly -- older adults who are increasingly
15:49:48 relying on incomes that can't pay rent.
Also low-barrier housing.
15:49:52 Housing that's accessible to people who may have financial difficulties
15:49:58 , might have experience with the cultural system because they were disproportionately
15:50:02 impacted by it.
Things like that
15:50:05 just throwing it out there.
I know we always talk about
15:50:10 ADA when it comes to older adults.
Want to put those things out there.
Thank
15:50:13 you, again.
>> NIKI: Thank
15:50:16 you, Marisa.
I think I saw J.'s hand up for
15:50:19 a moment.
15:50:29 >> I'm sorry.
I wanted to ask clarifying questions there I
15:50:32 think Marisa got to it.
I lost service in the middle.
15:50:36 One question was, because
15:50:39 I didn't
15:50:43 get it -- there was one slide and all I caught was the
15:50:47 black population hadn't changed since
15:50:50 the two centuries -- I could ask all of these questions off line.
I missed
15:50:53 a lot of it because my Wi-Fi lost
15:50:56 it, so don't worry about me.
That's why I put my hand down.
15:51:00 >> NIKI: I'll send out the presentation as well.
I
15:51:03 apologize we weren't able to get it to you too
15:51:06 far in advanced.
We had to reschedule and other things.
15:51:10 Now, we can digest it and review and certainly send out questions
15:51:15 or comments or feedback, too.
When I send that
15:51:21 out, j, check out the last -- when I sent
15:51:24 that out, J check out the last
15:51:29 slide.
Mara?
>> Thank you so much.
15:51:32 Hello, everybody.
Thank you for the presentation.
What I think I'm understanding more
15:51:35 and more is that data is going to become very important,
15:51:39 but it is hard to get the data that we need
15:51:42 , and I think, you know, I just support everything that
15:51:45 Marisa said because of the reality of it all,
15:51:48 you know?
It's like these numbers are important, but so
15:51:51 that we can put them together with what we're seeing out there on the ground and
15:51:55 hopefully figure out how to change this for folks and
15:51:59 make a, you know, make some policy changes to
15:52:02 try to help, because, yeah, it is -- I don't know,
15:52:05 it's fascinating to see the numbers, like,
15:52:08 the growth stuff and all of that.
It really informs a lot of the
15:52:11 direct service that I do, but it also feels very disconnected from
15:52:15 it, too, so, um -- but,
15:52:18 yeah, but I appreciate all of that it definitely helps put things in perspective
15:52:22 , but I also have a lot of questions about what it means, right?
Because
15:52:26 right away when I heard that about the incomes going up, my first thought was
15:52:29 , well, that's because people are being pushed out and people
15:52:32 with higher incomes are moving in.
That's just been my experience, you know?
15:52:35 But you're right.
Without better data, it's hard to show
15:52:39 people that's actually what's happened.
Thank you for that
15:52:42 presentation.
15:52:46 >> NIKI: Thank you for your
15:52:50 comments, Mara.
15:52:53 Allan?
Allan, I think you're muted.
15:53:02 >> ALLAN: Good to see you all.
Thank you for the presentation.
I think what I would say in
15:53:05 general -- and Marisa touched on it -- I think because of the way
15:53:08 we're looking that the data from a
15:53:12 -- especially from a fair housing
15:53:16 perspective, the spatial connection might be important, too.
15:53:20 Marisa pointed out that the connection
15:53:24 of poverty may be important spatially in communities.
That's
15:53:28 important for racial demographics.
Are we seeing certain areas of the city that are
15:53:31 becoming more or less
15:53:34 exclusionsary or inclusionary?
Because that will
15:53:37 really help frame when we talk about
15:53:41 housing choice what it means for folks, not just necessarily the population is going up
15:53:44 up or down in the city over all but is it going up
15:53:48 or down in certain parts of the city relative to
15:53:51 what, you know, the residents that might have been there in the past?
I don't
15:53:55 know if that's kind of in the next steps in looking
15:53:59 at demographic or not.
>> UMA:
15:54:04 Allan, it definitely is.
Fair housing, it's not just the numbers but it's also about
15:54:08 where they're living, so are they
15:54:12 segregated?
It's all in the work plan.
So this is
15:54:16 -- we just wanted to make sure
15:54:19 that we establish this base with you
15:54:23 .
15:54:32 >> ALLAN: Thank you.
>> NIKI:
15:54:36 J, your hand is back up.
15:54:43 >> J: With the lack of clarity, there were really high numbers.
I saw 21%
15:54:47 African-American and Native Americans -- there's maybe like
15:54:50 a 4% decrease since the last census
15:54:54 .
I'm trying to -- I'm having a hard time understanding --
15:54:57 are we saying 21% of Native
15:55:01 American and African-American people are houseless of the total population
15:55:04 of people collected in the
15:55:08 census?
>> NIKI: Let's get a second for Uma to pull it up
15:55:11 and see if she
15:55:14 can clarify.
>> UMA: Talk about the housing tenure -- is it OK
15:55:18 to call you J?
I'm not sure I could
15:55:22 take liberty but
15:55:26 thanks.
15:55:40 >> J: So there was a slide.
The rentership in the city
15:55:43 of Portland.
So this
15:55:46 is the rentership.
It's the next slide after this?
15:55:53 >> NIKI: This one with
15:55:56
15:55:59 homeownership?
>> J: Nope, next.
Housing tenure.
15:56:02 Nope, next.
15:56:05 Poverty rates by race and ethnicity.
15:56:08 This is it -- the poverty rates by race and
15:56:11 ethnicity.
Yes.
This is what I'm talking about here.
15:56:14 So I'm looking at this 29%
15:56:18 -- this is what we're looking at -- I'm look at this
15:56:21 29% for black Americans and native Americans,
15:56:24 but these high, high numbers and we're talking about of the
15:56:27 total population that -- of all
15:56:30 of that collected by the census, this is the rate, the poverty rate?
15:56:40 >> This is the poverty rate households that they established the poverty rates.
15:56:43 This is based on the poverty, depending on the number
15:56:46 of households.
So
15:56:55 --
>> J: It feels
15:56:58 important to note that
15:57:01 Black and Native folks, there's not very many in Portland at
15:57:05 all.
For us looking at numbers of 29% collected, it feels
15:57:08 -- it feels like the inbalance is not
15:57:12 captured because this is the whitest city in America, right?
15:57:16 For you to have -- something
15:57:19 feels wrong here.
You guys know how I am.
15:57:22 I get sweaty and my heart starts beating
15:57:25 fast.
Something is here.
I don't know
15:57:28 what it is.
I want to speak it.
Maybe someone is feeling
15:57:31 this way.
There's something about this slide that needs to be more added to it.
15:57:35 There needs to be more information about the overall demographics
15:57:38 about Portland unless I'm understanding this wrong.
15:57:45 >> BIMAL: I fully agree with you.
15:57:49 African-Americans and Native Americans are always undercounted.
15:57:53 The portion of the whole city is smaller compared to other groups.
15:57:57 So maybe it does look like there's disparity but at the same time this
15:58:00 is the data on what we have in the census, and
15:58:05 maybe there's a better way in presenting the information
15:58:10 .
I
15:58:14 definitely.
[indiscernible]
15:58:21 >> UMA: Just adding to that -- you were breaking
15:58:25 up, so -- and I don't speak for Bimal,
15:58:28 we're not fully clear on what your question is, and my guess is
15:58:32 you're saying, you know what?
15:58:35 Was this kind of -- this is a pretty substantial drop,
15:58:38 right?
Is that what you were saying, right?
From 42% to
15:58:43 29% or something?
Is that what
15:58:46 you're saying?
And in which case, we'll make sure
15:58:50 these numbers
15:58:54 are given what they are.
If you can just send
15:58:57 us the question tied to this, we'll take a little bit
15:59:00 better look at it and try to explain to the best
15:59:04 extent possible, and the one other thing -- you
15:59:07 see, these are estimates, right?
Estimates is not
15:59:11 the same as the actual perimeter
15:59:14 .
You're estimating based on a sample, so what
15:59:17 we could do is, you know, this is the best that can be
15:59:21 done with estimates.
You can run a test of confidence that
15:59:24 , you know, we're
15:59:27 95% confident that this is a true change, and it's not some
15:59:30 random number you're seeing.
So if, In fact, that's
15:59:34 your concern -- and you're right, it's pretty -- it's a dramatic
15:59:37 drop.
We'll go back and take a second look and try to address the question
15:59:41 and concern
15:59:44 .
This is completely -- these kinds of
15:59:47 concerns are relevant for the work around fair housing.
It's
15:59:50 like, you know what?
This data
15:59:53 -- there's a big drop, but
15:59:57 the truth is, it's not visible in the community or something.
I
16:00:00 hope that will be acceptable for you -- to you.
16:00:08 >> J: Thank you so much.
When Niki sends it, I'll take a look
16:00:11 at it and ask more
16:00:14 questions offline.
I don't think I'm understanding what I'm seeing.
16:00:18 >> UMA: No worries.
Fair enough.
16:00:22 >> NIKI: OK.
Um, I know
16:00:26 Bimal has a hard out with us, and it is
16:00:29 4:00 p.m., and we have public testimony coming up, but
16:00:33 I did see Mara's hand and Uma could stay with us
16:00:37 here and also I can take more questions and comments
16:00:40 specifically for Bimal as well after he leaves
16:00:45 , so let's do Mara and I see a couple more hands
16:00:48 and then maybe we can come back to this after we
16:00:51 provide an opportunity for public testimony just so
16:00:56 that we respect any community members' times to get here.
16:01:04 Mara?
>> MARA: Going back to the other thing about data, again, making sure we're
16:01:07 using it in a way that's going to be beneficial, and so I guess when I see that
16:01:10 number, I mean, it re-enforces
16:01:13 my understanding that there is systemic racism
16:01:16 and people of color, um, you
16:01:20 know, while maybe poverty for them is dropping, it
16:01:23 does still seem disproportionately high that so many
16:01:26 people of color live in poverty, you know, even
16:01:29 if that drop was more drastic than in the white community
16:01:32 .
I get that that just feels like an important
16:01:36 number to investigate the fact that don't look at the drop but more look at the
16:01:39 percentage, and that may just be my
16:01:42 social work brain but that's what I see there, you know?
But, again, I think it's about
16:01:46 numbers can be useful but also I think they could be used
16:01:49 to manipulate and control and sort of dictate the narrative and so that's why I
16:01:53 like all of these questions that people are asking about the data, and I
16:01:56 love the people who gather the data, so I appreciate you all
16:02:00 .
>> UMA:
16:02:04 We don't gather it.
We just look at it.
16:02:07 Mara, that was a great point.
This is just the beginning,
16:02:10 right?
I'm glad you all find it interesting, because
16:02:13 there's a companion piece around
16:02:17 nothing substantiate the difference between the income potential
16:02:21 , you just look at median household income by race
16:02:25 .
It is absolutely stunning.
It's like, you know,
16:02:28 the city is out there and you look at the
16:02:31 African-American or Native, it's like literally half of
16:02:35 that, so even if they made a little bit more but
16:02:38 it's still well below, um, you
16:02:41 know, what needs to be able to survive
16:02:45 , that drop itself is not as meaningful
16:02:49 and it doesn't behoove us to just conclude, you know
16:02:51 what?
There was this 20% drop and everything is good.
16:02:55 So point well taken.
Thank you.
16:03:01 >> J: Thank you, Mara.
That's what I was getting to.
If
16:03:04 the black people in Oregon are at 1%
16:03:08 or 1.7% and 29% of them are living in poverty, that's huge, you know
16:03:12 what I mean?
It's completely different than, you
16:03:15 know, 97% of the rest of Oregon is white and
16:03:19 12 of them -- 12% are -- thank
16:03:22 you, Mara.
I couldn't articulate it, but it's a way
16:03:26 bigger disparity that what we're looking at in the joy
16:03:29 of it dropping, although it is a great thing that it dropped also
16:03:33 also, it's still out of control.
16:03:36 >> NIKI: OK, Marisa and Allan, if you don't
16:03:40 mind holding on until after public testimony, and we can circle back
16:03:43 .
Uma is not running away.
We'll hold her here
16:03:46 to the benefit of being in person.
She can't
16:03:51 sneak off.
I will go ahead and call -- we
16:03:54 had one participant signed up for public testimony
16:03:58 .
Kim Nguyen, if you're on the line, feel free
16:04:02 to unmute yourself.
16:04:09 I don't see Kim in our participant list.
So anyone else from the community
16:04:15 is here and would like to provide public testimony or comment, I
16:04:18 invite you now to go ahead and unmute or send something in the chat
16:04:21 .
16:04:30 OK.
All right, thank you, everyone, for taking that quick pause and we
16:04:33 can turn right back around and I will call on Marisa
16:04:37 for continuing comments.
16:04:46 >> MARISA: Yeah, thank you.
I want to express my
16:04:51 appreciation for J's question, but I think maybe
16:04:56 this is just a good time to think again about that
16:05:00 relationship between poverty and housing instability, and, you know,
16:05:05 again, as J is pointing out and other folks are pointing out, we still need
16:05:08 to look at disproportionate
16:05:12 poverty among members of color,
16:05:15 especially Black-american and African-American households.
16:05:18 Where it made some of our notions about what is going
16:05:22 on with racial disparities in housing stability and
16:05:26 homelessness, because, like, the most recent data I've seen at
16:05:29 the statewide level would say, um, specifically that
16:05:33 Black Oregonians are represented in homelessness more than three times their share of the population
16:05:37 in Oregon, and American-Indian and
16:05:41 Alaskan Native Oregonians are representing more than four
16:05:45 times their share of the Oregon population.
16:05:49 Those are figures that feel as if they're in
16:05:52 conflict here.
It doesn't -- those are numbers that feel as if
16:05:56 they're in
16:05:56 conflict here.
It doesn't necessarily mean one or another is correct.
16:06:00 I want to see
16:06:03 how those numbers comport.
My other piece is I don't think we talked about this as
16:06:07 much recently in this space -- I know in Multnomah
16:06:10 county, we talked a bit about some of the work around
16:06:13 racial disparities and homelessness in some of the research of
16:06:16 -- there was a spark collaborative years ago that has kind of
16:06:20 put out some research that, you know, I know folks
16:06:23 have talked a lot about, and one of the things they
16:06:27 talked a lot about
16:06:30 when we were first getting introduced to the work on
16:06:33 the deep qualitative and quantitative work they were doing around race
16:06:36 and homelessness kind of spoke to something like this which is
16:06:40 where you see poverty
16:06:44 in communities of color that are disproportionately impacted by
16:06:47 homelessness, it
16:06:51 isn't necessarily that there's these extreme values of -- or extreme rates of poverty
16:06:54 , and then
16:06:57 it always equals an extreme rate of homelessness, so my understanding
16:07:01 as a layperson is the breakdown there is it isn't just
16:07:04 about poverty, right?
Because if it was
16:07:08 just about poverty, then all we would have to do is
16:07:11 end poverty, right?
And we do but I
16:07:15 think it's also about the systemic impacts of discrimination.
It's about,
16:07:18 you know, the lack of affordable housing.
It's
16:07:21 about the systems that feed into homelessness and housing
16:07:24 instability, like the criminal justice system or
16:07:28 carceral system or our health system, things like that.
16:07:32 So I guess I don't want
16:07:35 to complicate things too much by always introducing these
16:07:38 multi-sector types of questions but I think it's so important to think about, because if we're talking about
16:07:42 , you know, access to housing and, like, really
16:07:45 making it so we have a community that promotes fair access
16:07:48 and what are the needs people
16:07:51 have, then I just kind of want to bring it back to
16:07:55 there don't seem to be easy solutions
16:07:58 , and often when we do kind of presume that, like,
16:08:02 this one specific Domain of poverty is, like, the thing to
16:08:05 look at, we miss a lot
16:08:08 of other things.
I'm sure everyone here kind of knows that but I want
16:08:12 to reiterate that.
16:08:17 >> NIKI: Thank you, Marisa.
Allan, you have your hand
16:08:21 up as well?
16:08:25 >> ALLAN: The points I wanted to make
16:08:26 were covered in parts of the discussion.
Thank you, though.
16:08:30 >> NIKI: Thank you, again, Uma.
16:08:33 I've made notes of everybody's feedback and questions and
16:08:36 I'm hearing a greater need for context and care
16:08:39 and understanding each of these points
16:08:43 and we will be bringing more back to you as
16:08:47 Bimal noted in our next fall meeting scheduled for October
16:08:51 and then we're going to be digging in deeper as we get into
16:08:57 disparate means and lower income housing analysis and
16:09:00 all the other things we sent out in the plan and I'll go ahead and send
16:09:04 that memo, that project plan memo again now that
16:09:07 we have gotten our input into
16:09:10 the first section of work.
I'll send it along with the slides as well so that you can
16:09:13 keep that in mind with what you're looking at.
16:09:16 >> UMA: Thank you so much.
We're very appreciative.
16:09:21 >> NIKI: OK.
So I will go ahead and move us to
16:09:25 our next agenda item, and we might be able to
16:09:29 wrap up as we don't
16:09:32 have too much public testimony, but it's very important that we talk once again
16:09:35 about
16:09:39 our subcommittees which we've been talking about since the beginning
16:09:43 of this year, and so back at our last
16:09:46 meeting in April, we got
16:09:50 a clearer picture of the subcommittees that folks
16:09:53 were most interested in, and we got some light commitments.
I
16:09:56 went ahead and sent out a poll to make sure that we
16:09:59 would have enough interest to sustain that creation.
16:10:03 And we did.
So right now
16:10:06 , we have the community engagement subcommittee
16:10:10 as well as the policy
16:10:13 and best practices subcommittees that would like to meet on
16:10:16 a more than quarterly schedule and dig into some of this work
16:10:22 , however, in order to get those moving,
16:10:25 we do need all of you to
16:10:29 formally vote and create them
16:10:33 and so J is going to assist us through this
16:10:36 process as well, because we have not taken
16:10:39 a vote before.
I'll quickly go over what that looks like.
16:10:42 We need someone to make a motion to
16:10:45 create the subcommittee.
We'll need another committee
16:10:48 member to volunteer to second that motion and
16:10:51 then we'll go through who is here and ask
16:10:55 for a vote, yes
16:10:58 or no, in order to -- the vote to pass and
16:11:01 the subcommittee to be created,
16:11:05 we need
16:11:09 nine yeses
16:11:12 .
>> J: I motion to commit an
16:11:17 engagement subcommittee.
Is there
16:11:20 a second?
>> I'll second.
>> NIKI:
16:11:21 Perfect!
Love it.
OK.
16:11:25 So from there, I will go ahead and read off who
16:11:28 is here.
Please unmute and vote yes or no on
16:11:34 J's motion to create a community engagement subcommittee.
Ashley
16:11:39 Miller?
>>
16:11:47
[roll call]
16:15:20 Or were you not able to respond to the poll, now
16:15:23 would be fine.
OK.
16:15:27 Great, Mara, Allan and Barbara, I'll reach out
16:15:30 to you about scheduling that.
For the policy and best practices
16:15:34 subcommittee, I have Allan, Taylor, Barbara
16:15:37 and
16:15:41 one unnamed committee member.
16:15:47 >> J: Probably
16:15:51 J!
>> NIKI: Allan, Taylor,
16:15:54 Barbara and J!
Wonderful!
16:15:57 I will go ahead and reach
16:16:00 out to you guys and we'll get that scheduled as well.
16:16:05 Thank you.
16:16:09 I think that's everything we have on the agenda
16:16:12 .
I don't know if any committee
16:16:16 members, our chair, our vice-chair have any other business they would
16:16:19 like to include on today's meeting?
16:16:25 >> J: Thank you to Marisa for
16:16:29 serving as chair!
You'll be missed!
>> MARISA: Thank
16:16:33 you so much, J,thank you to all of you on the committee.
16:16:36 You're all doing important work.
I'll miss you all.
>> NIKI: Mara
16:16:41 , you have your hand raised?
16:16:51 OK.
Mara put her hand down.
16:17:01 OK.
All right.
Well, I will follow up
16:17:05 with the items that we have discussed today with the presentation
16:17:09 , project memo and setting up those meetings and other than that
16:17:13 , I think we can go ahead and end today's meeting early.
16:17:16 Thank you so much, everyone!
Really appreciate it!
16:17:19