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Thursday, November 7, 2019

Matchback 11.06.2019: State and local counties


Summary:

Exactly 1,761,288 ballots have been 'Accepted' or 'Received' in last night's (11/06/2019) statewide matchback Another 
22,180 have been rejected or 'challenged'.  As of 
11/06/2019 8:39 PM last night, Election Results WA has 1,217,468 tabulated (counted) with  623,814 ballots on hand to be processed (e.g. tabulated). Understanding ballot processing this time of year is complicated and Same Day Registration has increased that complexity. [Link to blog post coming here].  Although the previous matchbacks have  been dominated by those born in  1940s or 1950s (now ages 60 - 79), younger generations are catching up in these later returns and that trend can reasonably be expected to continue in tabulation throughout the rest of the certification period:

    Decade  Age Registered  Voted Turnout
 1:  1900s 110s         27      5    18.5
 2:  1910s 100s       1711    480    28.1
 3:  1920s  90s      44030  20260    46.0
 4:  1930s  80s     184015 110489    60.0
 5:  1940s  70s     492174 305422    62.1
 6:  1950s  60s     765293 395781    51.7
 7:  1960s  50s     756929 291213    38.5
 8:  1970s  40s     706611 210698    29.8
 9:  1980s  30s     784614 176487    22.5
10:  1990s  20s     672919  99524    14.8
11:  2000s  10s      71046  13494    19.0

Those born in 1940s or 1950s decades have a combined 701,203 ballots accepted. By comparison, those born 1980 or afterwards (ages 18 - 39) have a combined 41% of that (701,203total with 289, 505 ballots accepted.  That "youth" or millennial vote in WA is now weighing in at last. As this trend continues, close races should begin to skew more liberal.   GenXrs, those born in the 60s and 70s are  contributing 501,911 votes Please see 'Age by Status' below.  To see my updated and ongoing piece on WWU precinct turnout, see hereWomen are currently out voting men in all but 3 counties. The later balloting is now skewing heavily female. This is another sign that close races should begin to fall to more liberal candidates.  For the state as a whole:

   BallotStatus Female   Male
1:     Accepted 835186 781774 # Ready for tabulation or tabulated
2:     Received  72434  64566 # In the chute
3:     Rejected  10421  11544 # Challenged or Rejected

For our neck of woods (Whatcom, Skagit, San Juan), accepted female votes are ahead of male votes significantly now:

   BallotStatus Female  Male
1:     Accepted  56970 51329
2:     Received   2372  2128
3:     Rejected    554   648

Tables made from rdata.table code with output follow the break. Widescreen is best for viewing especially on a phone.


sMB110619[,.N,.(BallotStatus)]
   BallotStatus       N
1:     Accepted 1623853
2:     Received  137435
3:     Rejected   22180

# All status active as of October 1 (4.47M)
VR[StatusCode == "Active",.N]
[1] 4479369
# Percentage Accepted and Received as of 11.06.2019
(1623853+137435)/VR[StatusCode == "Active",.N] * 100
[1] 39.32

#[All State: Challenge Reason]
sMB110619[BallotStatus == "Rejected",.N]
[1] 22180

sMB110619[,.N,.(ChallengeReason)][order(-N)]
              ChallengeReason       N
 1:                           1761289
 2:  Signature Does Not Match    8972
 3:                    Review    4792
 4:                  Unsigned    4092
 5:             Undeliverable    1243
 6:                      HOLD     990
 7:          Other than Voter     889
 8:       Ballot Style Change     296
 9:      No Signature on File     163
10:               ID Required     161
11:          Other Than Voter     125
12:          Canvassing Board      85
13:              Marked Moved      79
14:                  Deceased      57
15:         Power of Attorney      46
16:                      Hold      40
17:         Voter Name Change      34
18: Witness Signature Missing      28
19:   Advanced Special Ballot      26
20:            Empty Envelope      24
21:               Id Required      15
22:      No Signature On File       9
23:                   Invalid       6
24:                  Too Late       6
25:         Power Of Attorney       1
              ChallengeReason       N

# [Whatcom County]
sMB110619[County == "Whatcom",.N,.(ChallengeReason)][order(-N)]
             ChallengeReason     N
 1:                          80293
 2: Signature Does Not Match   330
 3:         Other than Voter   113
 4:                 Unsigned    90
 5:                     HOLD    72
 6:                   Review    70
 7:      Ballot Style Change    42
 8:              ID Required    12
 9:           Empty Envelope     2
10:                 Deceased     1

sMB110619[County == "Whatcom",.N,.(BallotStatus)]
   BallotStatus     N
1:     Accepted 75778
2:     Received  4515
3:     Rejected   732

# [All State]
VR[,Age:=as.numeric(year(ymd_hms(Sys.time()))) - year(ymd(Birthdate))]

sMB110619[,.N,.(Decade=paste0(year(mdy_hm(DOB))%/%10,"0s"),BallotStatus)][,
+ dcast(.SD, BallotStatus ~ Decade, value.var="N",fun.aggregate=fsum)]


Age By Status

   BallotStatus 1900s 1910s 1920s  1930s  1940s  1950s  1960s  1970s  1980s 1990s 2000s
1:     Accepted     5   480 20260 110489 305422 395781 291213 210698 176487 99524 13494
2:     Received     0    21   770   4552  15511  29128  29319  24128  20409 11834  1763
3:     Rejected     1    10   217    799   1955   3300   3398   3589   3934  4170   807

sMB <- allotstatus="" ecade="paste0(year(mdy_hm(DOB))%/%10," font="" s="" smb110619="">
dcast(.SD, BallotStatus ~ Decade, value.var="N",fun.aggregate=fsum)]


cbind(setnames(VR[StatusCode == "Active",.N,.(Decade=Age%/%10)][order(-Decade)],
c("Age","Registered"))[],
setnames(as.data.table(t(sMB),keep.rownames=TRUE)[2:12,1:2],
c("Decade","Voted"))[])[,
.(Decade,Age=paste0(Age,"0s"),Registered,Voted)][,
.SD[,.(Turnout=round(as.numeric(Voted)/as.numeric(Registered),3) * 100)],.(Decade,Age,Registered,Voted)]

    Decade  Age Registered  Voted Turnout
 1:  1900s 110s         27      5    18.5
 2:  1910s 100s       1711    480    28.1
 3:  1920s  90s      44030  20260    46.0
 4:  1930s  80s     184015 110489    60.0
 5:  1940s  70s     492174 305422    62.1
 6:  1950s  60s     765293 395781    51.7
 7:  1960s  50s     756929 291213    38.5
 8:  1970s  40s     706611 210698    29.8
 9:  1980s  30s     784614 176487    22.5
10:  1990s  20s     672919  99524    14.8
11:  2000s  10s      71046  13494    19.0

sMB110619[Gender == "M" | Gender == "F",.N,.(Gender,BallotStatus)][,setnames(dcast(.SD, BallotStatus ~ Gender, value.var="N",fun.aggregate=fsum),
c("BallotStatus","Female","Male"))]

   BallotStatus Female   Male
1:     Accepted 835186 781774
2:     Received  72434  64566
3:     Rejected  10421  11544

sMB110619[County %in% c("Whatcom","Skagit","San Juan"),
.N,.(Decade=paste0(year(mdy_hm(DOB))%/%10,"0s"),BallotStatus)][,
dcast(.SD, BallotStatus ~ Decade, value.var="N",fun.aggregate=fsum)]

   BallotStatus 1910s 1920s 1930s 1940s 1950s 1960s 1970s 1980s 1990s 2000s
1:     Accepted    36  1388  7763 22286 26444 16895 13229 11465  7940  1200
2:     Received     0    21   105   389   762   876   833   888   552    89
3:     Rejected     1    12    57   139   198   162   162   192   249    43

sMB110619[County %in% c("Whatcom","Skagit","San Juan"),][
Gender == "M" | Gender == "F",.N,.(Gender,BallotStatus)][,
setnames(dcast(.SD, BallotStatus ~ Gender, value.var="N",fun.aggregate=fsum),
c("BallotStatus","Female","Male"))]

   BallotStatus Female  Male
1:     Accepted  56970 51329
2:     Received   2372  2128
3:     Rejected    554   648

sMB110619[(Gender == "M" | Gender == "F") & County %in% c("Whatcom","Skagit","San Juan"),
.N,.(County,Gender)][order(County,-Gender)]

     County Gender     N
1: San Juan      M  3169
2: San Juan      F  3558
3:   Skagit      M 12748
4:   Skagit      F 13795
5:  Whatcom      M 38188
6:  Whatcom      F 42543

VR[(Gender == "M" | Gender == "F") & StatusCode == "Active" & CountyCode %in% c("WM","SK","SJ"),
+ .N,.(CountyCode,Gender)][order(CountyCode,-Gender)]
   CountyCode Gender     N

1:         SJ      M  6481
2:         SJ      F  7164
3:         SK      M 36785
4:         SK      F 40808
5:         WM      M 69437
6:         WM      F 75676

# October 1st VRDB WA ('whole enchilada')
VR[StatusCode == "Active",.N,.(Gender)]
   Gender       N
1:      M 2145204
2:      F 2313683
3:           5806
4:      U   14549
5:      O     127

# Just our neck of woods: Whatcom, Skagit, San Juan
VR[StatusCode == "Active" & CountyCode %in% c("WM","SK","SJ"),.N,.(Gender)]
   Gender      N
1:      M 112703
2:      F 123648
3:           425
4:      U     52
5:      O     14

sMB110619[(Gender == "M" | Gender == "F"),
.N,.(County,Gender)][order(County,-Gender)][,
dcast(.SD, County ~ Gender,value.var="N",fun.aggregate=fsum)][,
.(County,Male=M,Female=F)][,
.SD[,.(Pct.Male=round(Male/(Male+Female),3) * 100)],
.(County,Male,Female)]

y= Counties where male outvotes female

          County   Male Female Pct.Male
 1:        Adams   1050   1141     47.9
 2:       Asotin   3136   3304     48.7
 3:       Benton  16588  16967     49.4
 4:       Chelan   9711  10353     48.4
 5:      Clallam   9870  10893     47.5
 6:        Clark  50907  54835     48.1
 7:     Columbia    723    788     47.8
 8:      Cowlitz  12040  12704     48.7
 9:      Douglas   4422   4625     48.9
10:        Ferry   1255   1229     50.5 y
11:     Franklin   5405   5574     49.2
12:     Garfield    525    540     49.3
13:        Grant   7546   7681     49.6
14: Grays Harbor   7863   8477     48.1
15:       Island  10213  11058     48.0
16:    Jefferson   6506   7202     47.5
17:         King 277775 293898     48.6
18:       Kitsap  37063  39041     48.7
19:     Kittitas   5006   5133     49.4
20:    Klickitat   2222   2245     49.7
21:        Lewis   9350   9662     49.2
22:      Lincoln   1964   1982     49.8
23:        Mason   8098   8176     49.8
24:     Okanogan   4378   4478     49.4
25:      Pacific   2789   2902     49.0
26: Pend Oreille   2283   2286     50.0 y
27:       Pierce  96622 104856     48.0
28:     San Juan   3169   3558     47.1
29:       Skagit  12748  13795     48.0
30:     Skamania   1776   1762     50.2 y
31:    Snohomish  67777  71699     48.6
32:      Spokane  73103  81429     47.3
33:      Stevens   5215   5302     49.6
34:     Thurston  31939  35367     47.5
35:    Wahkiakum    769    808     48.8
36:  Walla Walla   5032   5424     48.1
37:      Whatcom  38188  42543     47.3
38:      Whitman   3716   3884     48.9
39:       Yakima  19142  20440     48.4
          County   Male Female Pct.Male

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