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