Fred Allebach
member Sonoma Valley Housing Group
member SoCo/ Santa Rosa NAACP
1/2/24
2020 Census SVUSD (Sonoma Valley Unified School
District) Trustee Area Compliance Review notes
-see acronym list at bottom
-thanks to Trustee Troy Knox for responding and providing
the Davis Demographics materials
Initial questions
How will demographic lessons and context learned here
inform the LAFCO DUC (disadvantaged unincorporated communities) study in Sonoma
Valley (SV), as well as City and County General Plans existing conditions
maps and data charts?
Will a finer-grained Block and Block Group (BG) level
analysis as has been done here for SVUSD by Davis Demographics/ Scott Torlucci better and more
accurately serve General Plans, LAFCO, and the coming SVUSD reorganization
processes?
Are these finer grain studies accurate, what is the
underlying Census margin of error? Do professional demographers somehow
mitigate Census high margins of error with mathematical sleight of hand i.e.,
manipulate statistics?
How do CA Voting Rights Act (CVRA) principles of not
disenfranchising protected classes cross over to the way LAFCO and other state/
county entities like Housing Elements define disadvantaged communities (DACs) and disadvantaged
unincorporated communities (DUCs)?
Are DACs and DUCs protected classes as well as COIs or communities
of interest?*
SVUSD Trustee Area redistricting history and current
process
In 2019 SVUSD initiated a CA Voting Rights Act (CVRA)
process to switch from less-fair district-wide elections to more
representative, discreet Trustee Area elections. Five Trustee Areas were
established in the SVUSD service area which roughly parallels what I call the
lower Sonoma Valley, SV south of Kenwood. This initial CRVA-driven process
apparently never allowed for communities of interest (COIs) to be considered*,
only protected classes.
In a separate but related process after the 2020 Census,
SVUSD had to readjust the Trustee Areas to conform to new 2020 Census data. The
second process was a CA Education Code 5019.5 driven process with simpler
criteria than the CRVA process, only considering population number,
proportional population, and protected classes.
Davis Demographics sources
US Census; Statewide
Database, University of California, Berkeley Law, Center for
Research; Sonoma COE; SVUSD; Davis Demographics.
The Statewide Database site says: “We are able to fill
small requests and take on special projects that relate to redistricting and
districts, as well as to the demographic and political make-up of the State of
California. In this capacity, we have, for example, created maps of their
districts for legislators, and statewide maps for the Justice Department. We
have provided journalists with data and maps for articles, and helped students
with data analysis. Non-profit organizations have utilized the database in
creating demographic maps with densities of particular populations in order to
identify locations for new service providers.”
The US Census is the primary source of data. It seems like
those looking for social justice type data like myself can find it. But
not being a professional demographer, myself and the rest of the public are
captive to whatever agency studies there are, that may not be concerned with
social justice issues, nor care to look.
2020 SVUSD Trustee Area boundary adjustment methodology
Outer SVUSD boundaries were based on Census Block geography
and not on SVUSD geography. 2020 Census data was applied to the 2019 Trustee
Area boundaries which had @ 7,500 people per Area with a maximum population
variance between Areas of 10%. The goal was to draw new boundaries with 2020
Census updated population and racial data.
Populations were broken down by race and voting age by
race. Total population was looked at, not necessarily registered voters or
citizens. Population by Trustee Area needs to be nearly the same or
proportionally the same. Protected class voters can’t be disenfranchised, the
vote of members of a protected class can't be diluted. Protected class in
this case is non-white voters, or Latinos. A majority population in an Area
district cannot be disenfranchised without violating the CVRA.
Blocks and
Census units of measurement
The Trustee Area boundary readjustment process hinges on
Census Blocks which are the smallest geography for which you can get
basic demographic data for total population by age, sex, race. Census Block
Groups (BG) are an aggregation of Blocks. Census Tracts and Places are an
aggregation of BGs and Blocks.
The Census has an inventory of collection blocks
from which they survey to get a representative sample of an area, not sure how
they random sample... Any data the Census is after can be collected with Block
level surveys, “Blocks are the basis for all tabulated data from a decennial
census”
Blocks can’t be used with American Community Survey (ACS)
because the ACS only goes to a BG level. (I have not seen a way to get Block
data directly from the Census, still learning here.) However, the SoCo BOS
Redistricting process used a tool called DistrictR with
which the public could and still can experiment with creating district
map scenarios at the Block level. DistrictR has many layers and options,
allowing the user to get super fine grained. An hour or so of fooling with the
options will show how Blocks can generate custom population data.
One issue then becomes if smaller geographies have a higher
margin of error**, how can custom districts be accurate and conform to the CVRA
and not disenfranchise protected classes? Is this a matter of time and money or
of margin of error only? Is voting the only way people get disenfranchised and
become disadvantaged?
What the Trustee Area and BOS redistricting processes
showed is that demographics can get more fine-grained than BGs and this
fine-grained approach can in effect create custom BGs, custom districts,
which is what the Trustee Areas are. In other processes, like LAFCO special
district formation, annexation, General Plans and Housing Elements, where
COIs are being looked for, there are methods and laws that call to go across
BGs to see where COIs exist on the ground at the Block level.
Take home point: Small-area geographic studies can be done.
Geographic
equivalency, geographic comparabilty
Since professional (and amateur) demographers all use the
same Census data, a geographic equivalency applies, which means that
Census products, the SVUSD Trustee Area boundary adjustment study, the BOS
Redistricting material, General Plan demographic analysis, and the coming Plan
West DUC study can be compared and be considered geographically equivalent
(across space) and geographically comparable (across time).
Since all studies are not made for the same purposes, care
should be taken to examine how statistics may be biased by agency framing, by
the type of questions asked or not asked, by the units of measurement used, by
scale of presentation. Nevertheless, stats like population, race, registered
voters, median household income, number of households etc. should cross over
more or less cleanly if you stay aware of not comparing apples and
oranges.
Davis Demographics Trustee Areas 2020 Census @ 7,500
people per Area
Area 1 is north Valley/ Glen Ellen. 27.2% Latino; 64.6%
white
Area 2 is Fetter’s/ Boyes/ Springs East. 51% Latino; 41.9%
white
Area 3 is Boyes/ El Verano. 36% Latino; 56.7% white
Area 4 is Sonoma west side/ southwest side. 17.9% Latino;
74.1% white
Area 5 is Sonoma east side, northeast side, southeast side.
15.8% Latino; 76.7% white
Davis Demographics Trustee Areas 2020 Census voting age
citizens
Area 1 9.4% Latino, 83.1% white
Area 2 23% Latino, 70.8% white
Area 3 20.8% Latino, 73.7% white
Area 4 9.7% Latino, 87% white
Area 5 13% Latino, 79.9% white
Davis Demographics Trustee Area findings from 2020 Census
Areas with the largest number of protected classes are
Areas 2 and 3. This shows the same geographic equivalency as my SV Census BG
studies published on my Blogspot page.
Areas with the biggest variance from 2019 to 2020 were
Areas 1 and 2.
Area 1, wealthier and primarily white had lost 16% of its
population, 1,203 people perhaps due to gentrification and higher cost
burdening, but had gained Latino residents. Cost burdening for lower income
Latinos in this Area would be extreme.
Area 2 had gained 11.9%, 891 people, many of these subject
to Springs-area housing overcrowding.
Areas 3 and 4 held about even, losing 41 and 21 people
respectively.
Area 5, the Valley’s east side, gained 5% of population,
375 people however this gain, while mostly white and wealthy, does not seem to
be primarily families with school age kids.
I think Davis Demographics said that Area 1 tripled its
percent Latino population and Area 2 doubled it; is that correct?
Area 2 has a Latino majority and according to the CVRA,
this majority should not be diluted, to choose the candidate of their choice.
Area 2 also has a denser population than others in the
Valley.
Davis Demographics Area Scenarios A, B, and C
Davis made three scenarios relative to the 2020 Census, the
first scenario was with the least changes and the most compact. The other two
added other criteria to make these options different; this criteria seemed to
be a gray area from the Davis Demographics informational item on the Trustee
meeting video starting at 2:31. On what criteria would the differences
be based? The counsel said that COIs* could not be taken into account,
but then seemed to say that with alternate scenarios, maybe they could…
The counsel said that it is a protected class criteria to
maintain an existent majority population, and she said, it’s not necessarily a
majority but that the district reflects the percent the protected class has in
the Area.
This is an example of how cross-BG DUCs can be loc ated and
counted on a percentage basis in the BGs they live in.
The Trustees choose Scenario A in 1/22, fir updated Trustee
Area boundaries.
Systemic disenfranchisement of a Sonoma Valley Latino
protected class
In lower SV there are two different municipalities, the
City of Sonoma and the unincorporated Sonoma County. A hodgepodge of County
Special Districts serves the unincorporated area. Several districts cross both
City and County lines: school, hospital, law enforcement, fire, sewer, water,
and groundwater
From a demographic standpoint it is easy enough to see that
the City, with less than one third of the people, has sequestered way more
resource opportunity candy than the other two thirds. The City is also much
whiter, making this segregation possibly into a CVRA protected class issue,
since the main district difference between SV City and County is one of agency
and political power, of disparity in voter representation, and of being able to
set their own respective planning, zoning and land use parameters. The City has five
representatives and a full local government for 11,000 people, the rest of the
lower valley has one representative for @25,000 people, and thanks to that
representative, Susan Gorin, a newly created County service hub in the lower
valley.
As well, there is local history of segregation and the City
has largely externalized its BIPOC, protected class population “across the
tracks” to the Springs and out of valley. The externalized BIPOC population in
the Springs area is routinely outmaneuvered and out hustled by much more
politically active and influential white COIs who are registered to vote at a
much higher percentage. This means that for politicians to be elected locally,
they have to cater to increasing white interests or lose, and that they don’t
have to worry about a Latino vote because it is so small. This is what systemic
disenfranchisement looks like here in SV. This is cumulative effect of a disparate, disadvantaged playing field for local Latino immigrants.
Sonoma Valley depends on low-income, Latino undocumented
immigrant labor to be essential workers in the wine-tourism-hospitality combine
economy. These people are like modern indentured servants, lacking rights and
proportional representation. In the case of SVUSD, Latino students now make up
over 60% of the SVUSD student population yet they are only majority in one
Trustee Area and the proportion of SVUSD voting age Latino citizens to Latino
undocumented residents is very low.
The attached BOS Redistricting process, 2021,1st District
Maptitude data sheet shows that 1st District and SVUSD Latinos are
way under-registered to vote relative to their population numbers. SV Latinos
get the short end of the stick in multiple ways that have to do with government
services, the structure of municipalities and special districts and local government.
They are structurally disadvantaged by what I call the Sleepy Hollow Stasis.
This is a fractal of segregated white American suburbia.
Something is not right here, to keep in-house indentured
servants, keep them poor with low wages, and then not afford them proper
representation or ability to plan their own future proportional to their
numbers. This is modern feudalism right here in sunny, great Sonoma Valley. No
bueno.
One cure: Here is where a San
Francisco law sets a precedent SVUSD could follow, to allow undocumented
residents to vote in school system elections. This could be taken up by
Trustees and staff. The lower numbers of voting age population in Areas 2 and 3
show this disparity. Governor Newsom and the State of CA also set precedents,
to offer health insurance, driver's licenses, and other citizen benefits to
essential worker, undocumented immigrants.
Rather than put the undocumented on a bus to NYC, CA is
taking the total opposite approach. I recommend that SVUSD take up the same
approach and begin a process to allow undocumented family adults to vote in
SVUSD elections.
Another cure: The City annexes the rest
of the unincorporated SV urban service area so as to make the most efficient
and just municipality possible, rather than have one third hoard all the
resources at the expense of the others. If we shrink from imagining the vagaries
of feudal life, why would we accept that here in our own backyard now in
2024?
Sonoma Valley district studies context
For SV-level demographic studies, for example City General
Plan existing conditions maps, there seems to be no fundamental limit on using
Tracts or Places only. Blocks, BGs, and DistrictR-type tools can be used,
rather than erase valid on the ground valid geographies by insisting on only a
Tract-level view.
A demographer and/or planning consultant can create
custom BGs, districts, or Areas for protected classes and COIs and this would
be a reasonable expectation for the Plan West demographic consultant doing the
SoCo DUC study, and of City and County General Plan maps and data sheets.
In the BOS Redistricting process, the wealthy, white
Bennett Valley cohort was identified as a COI and was unified in the 1st
District so as to not spit a COI. COIs* can be a reason for further
Balkanization or for unification, depending on who has the political will to
direct the districting show.
Davis Demographics public access to Trustee Area web-based
map
On the 11/16/21 Davis Demographics presentation to the
SVUSD Trustees and staff, a link was provided to a “web-based map for public
information.” Fyi, this is not publicly accessible because it is Esri and the
public needs an ARCGIS membership to view the map. Not fair to put a paywall in
the public’s information that the public already paid for.
It is curious that businesses can buy software to
create marketing districts when profit is at stake but social justice advocates
have to fight the powers that be to get social justice data on their
maps.
Questions for Trustees and SVUSD staff
What were the principal differences between scenarios A, B
and C? Why A over B and C? What was the Trustee vote to approve Scenario A,
unanimous?
*Cracking and packing districts, protected classes, and
COIs
It seems that looking to cover the interests of COIs
potentially qualifies as a cracking and packing exercise in district creation.
Why? Because with COIs special interests are what is specifically at stake. For
example, in SV, the Sonoma Mountain Preservation/ Glen Ellen anti-high density/
market rate housing at SDC cohort is a COI; the Donald St. neighbor
anti-inclusion in the Springs Specific Plan cohort is a COI; Sonoma Valley
Collaborative is a COI that supports balanced triple bottom line sustainability
policy outcomes and more affordable housing. In SV, COIs that are also
protected classes can be demonstrated by Census stats, as in the case of lower
income immigrant Latinos, or for COIs that are not protected classes, by
petition drives to show how many are against or for whatever.
COIs want influence and to be heard and to win, this runs out
on a spectrum of seeking more political power and to dominate other interests.
Cracking and packing is gerrymandering and we
see this happening nationwide with efforts to control and/or limit the vote.
There are two strategies here: either the powers that be are unafraid of the
voters and let them vote as much as possible, or they are afraid of the voters
and try to distort elections so as to win.
For SVUSD, I suggest to let the undocumented Latinos vote because
this is protected class issue and not a COI issue.
Since LAFCO creates special districts, it’s easy to see the
gray area where special interests and COIs cross over. For example, COIs are
explicitly referenced in an annexation process.
What if a COI is also a protected class? Then COI
prohibitions are out? It would seem yes DACs and DUCs are protected classes in
SV for race, color, and national origin, which makes Sonoma Valley Latinos a
protected class. This protected class status may add some oomph to DUC/ DAC
demographic studies to be more fine-grained. For example, the SoCo
Environmental Justice Element only looks at the Tract level, is it not less
just to intentionally not see more poor people that are really there?
The BOS Redistricting final decision overrode a map with
districts favoring protected classes along Hwy 101 and showed the undue influence
of a few older white men, and also showed that unincorporated areas are lower
on the districting totem pole and have less oomph than SoCo city’s interests.
This was quite the political spectacle!
**Margin of error
Davis Demographics cited the US Census as a primary source.
Davis Demographics, who did the 2020 Trustee Area
readjustment, in its presentation did not mention Census margin of error as a
factor in accuracy of new Trustee Area boundaries.
They did say that the Trustee Area study was done “using
population figures as validated by the Demographics Research Unit of the Dept
of Finance.”
I have some questions as to 2020 Census margin of
error.
One element of 2020 Census margin of error is that it was
done under Covid-19 conditions and was intentionally sabotaged to be less
thorough by the Trump administration. 2020 numbers began at a compromised
level. I was hired as an enumerator for the 2020 Census but chose not to work becausew of Covid.
A critique of BG-level analysis (made by City General Plan
consultant DeNovo Planning Group and Census Reporter.org website staff) is that
the sample size is too small to make anything other than broad-bucket, general
calls. Permit Sonoma has also said that BG level mapping costs too much and
takes too much staff time. Staff time cost is a frequent excuse, and it rests
with electeds and their political will to tell staff what to do
This is interesting for margin of error because Blocks
would theoretically have the largest margin of error of all; they are much
smaller than Block Groups. The fact that aggregate Block-level data was taken
as the gospel truth for Trustee Area percents is interesting in light of margin
of error/ accuracy concerns of DeNovo and Census Reporter staff.
I’d be interested to see a Davis Demographics statement on
Trustee Area data margin of error. What if the margin of error percent is 10%
or greater? If Davis can produce fine, low margin of error, granular results
like the new Trustee Area numbers, how are they doing that? Why can’t I or
DeNovo or Census Reporter or maybe Plan West do that with Blocks and BGs too?
Some of this may have to do with proprietary ESRI
software and the pay per play ARCGIS website. These entities have figured out
how to customize and then put a paywall on the data. To get more fine grained,
perhaps there is a higher cost and thus the best social science becomes a
matter of money, and those unwilling to spend end up living with a less
accurate calibration of their demographics.
Another aspect of margin of error: by only taking a Tract
or Place-level view, many COI membership cohorts (and protected classes)
(seniors, mobile home park residents, white working class, immigrant Latinos)
get erased. Higher-order Tract generalizations create a false impression of
what is really on the ground; fine calibration potential is lost. For example,
central Sonoma Tract 1502.04 has a very poor BG2 which meets majority DAC
status for MHI but mixing in two much wealthier BGs, 2 and 3, erases that DAC
status. By only looking at the Tract, the poor side COI of Tract 1502.04 is
diluted and erased. Where is the margin of error in that?
Acronyms
ACS US Census American Community Survey
ADU accessory dwelling unit
SVUSD Sonoma Valley Unified School District
COI community of interest
CDC Sonoma County Community Development Commission
HCD CA Department of Housing and Community
Development
HE Housing Element
GP General Plan
BOS Sonoma County Board of Supervisors
LAFCO Sonoma County Local Agency Formation Commission
AFFH Affirmatively Furthering Fair Housing
SV Sonoma Valley
USA urban service area
BG US Census block group
MFH multifamily home
SFH single family home
TCAC CA state Tax Credit Allocation Committee
DWR CA Dept of Water Resources
SDAC severely disadvantaged community
DAC disadvantaged community
DUC disadvantaged unincorporated community
MHI median household income
COLA cost of living adjustment
COL cost of living
MHV median home value
SoCo Sonoma County
MA median age
MHP mobile home park
MH mobile home
BA Bachelor of Arts degree
EJ environmental justice
CEQA CA Environmental Quality Act
RHNA Regional Housing Needs Assessment
VMT vehicle miles traveled
MSR LAFCO Municipal Services Review
SSP SoCo Springs Specific Plan
CDC SoCo Community Development Commissions
COC SoCo
Continuum of Care
CVRA CA Voting Rights Act
