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