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Friday, October 25, 2019

Matchback 10.24.2019: State and local counties

Summary:

Exactly 275,000 have been 'Accepted' or 'Received' in last night's (10/24/2019) statewide matchback. Another 4,707 have been rejected or 'challenged'.  The WA SoS counts this as 279,694 'Ballots Received' for a turnout of 6.2%.  However,  this total is  ~18% of the approximately 1.5M votes received for each of the 2015 and 2017  ('off year') general elections.  

The current vote is dominated by those born in the 1940s or 1950s (now ages 60 - 79). These two decades have a combined 134,462 ballots accepted. By comparison, those born 1980 or afterwards (ages 18 - 39) have a combined 24% of that (134,462) total with 31,721 ballots accepted.  The "youth" or millennial vote in WA has yet to emerge with strength or volume.

Men are currently out voting women in almost every county and this is remarkable given the current political environment and the fact that  ~170K more women are registered than men statewide. I am reminded that I noticed this trend in July 2018. For the state as a whole:

   BallotStatus Female   Male
1:     Accepted 123592 134681 # ready for tabulation
2:     Received   7870   7834 # in the chute
3:     Rejected   2176   2479 # challenged

For our neck of woods: Whatcom, Skagit, San Juan:

   BallotStatus Female Male
1:     Accepted   7007 7416
2:     Rejected     57   73

Tables made from rdata.table code with output follow the break. Widescreen is best for viewing:

# [All State Matchback: 11.24.2019] 
sMB102419[,.N,.(BallotStatus)]
   BallotStatus      N
1:     Accepted 259254
2:     Received  15746
3:     Rejected   4707

# All status active as of October 1 (4.47M)
VR[StatusCode == "Active",.N]
[1] 4479369

# Percentage 'Accepted' plus 'Received' as of 10.23.2019
(259254+15746)/VR[StatusCode == "Active",.N] * 100
[1] 6.13
# See also https://www.sos.wa.gov/elections/research/ballot-return-statistics.aspx

#[All State: Challenge Reason]
 sMB102419[BallotStatus == "Rejected",.N,]
[1] 4707

sMB102419[,.N,.(ChallengeReason)][order(-N)]
              ChallengeReason      N
 1:                           275009 # Not Challenged
 2:  Signature Does Not Match   1276
 3:                  Unsigned   1184
 4:             Undeliverable   1053
 5:                    Review    651
 6:                      HOLD    225
 7:          Other than Voter     92
 8:       Ballot Style Change     44
 9:                  Deceased     29
10:      No Signature on File     25
11:               ID Required     23
12:   Advanced Special Ballot     22
13:          Canvassing Board     15
14:         Power of Attorney     15
15:                      Hold      9
16:              Marked Moved      8
17:                   Invalid      8
18:            Empty Envelope      6
19:         Voter Name Change      5
20:          Other Than Voter      3
21: Witness Signature Missing      3
22:               Id Required      2
              ChallengeReason      N

# [Whatcom County]
sMB102419[County == "Whatcom",.N,.(BallotStatus)]
   BallotStatus    N
1:     Accepted 9240
2:     Rejected   59

sMB102419[County == "Whatcom",.N,.(ChallengeReason)][order(-N)]
            ChallengeReason    N
1:                          9240 # Not Challenged
2:                 Unsigned   22
3: Signature Does Not Match   18
4:         Other than Voter    9
5:                     HOLD    9
6:                 Deceased    1

sMB102419[,.N,.Decade=paste0(year(mdy_hm(DOB))%/%10,"0s"),BallotStatus)][,dcast(.SD, BallotStatus ~ Decade, value.var="N",fun.aggregate=fsum)]

   BallotStatus 1900s 1910s 1920s 1930s 1940s 1950s 1960s 1970s 1980s 1990s 2000s
1:     Accepted     2   106  4495 25233 65295 69167 38653 24582 19900 10558  1263
2:     Received     0     7   251  1448  3865  4252  2465  1494  1178   707    79
3:     Rejected     0     1    90   327   609   859   725   650   683   670    93

sMB102419[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 123592 134681
2:     Received   7870   7834
3:     Rejected   2176   2479

sMB102419[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     9   305  1537  4111  3909  1785  1210   956   544    73
2:     Rejected     0     7    15    28    26    22    12    11     8     2

# Gender registration in 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

sMB102419[County %in% c("Whatcom","Skagit","San Juan"),][
Gender == "M" | Gender == "F",.N,.(Gender,BallotStatus)][,
aetnames(dcast(.SD, BallotStatus ~ Gender, value.var="N",fun.aggregate=fsum),.("BallotStatus","Female","Male"))]

   BallotStatus Female Male
1:     Accepted   7007 7416
2:     Rejected     57   73

[From MatchBack]
sMB102419[(Gender == "M" | Gender == "F") & County %in% c("Whatcom","Skagit","San Juan"),
.N,.(County,Gender)][order(County,-Gender)]
     County Gender    N
1: San Juan      M  401
2: San Juan      F  375
3:   Skagit      M 2330
4:   Skagit      F 2159
5:  Whatcom      M 4758
6:  Whatcom      F 4530

[From October 1,2019 VRDB Registration]
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:      U   14549
4:           5806
5:      O     127

sMB102419[(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)]

          County  Male Female Pct.Male
 1:        Adams   187    179     51.1
 2:       Asotin   602    577     51.1
 3:       Benton  3159   2873     52.4
 4:       Chelan  1923   1805     51.6
 5:      Clallam  2212   2157     50.6
 6:        Clark  6596   5972     52.5
 7:     Columbia    57     62     47.9
 8:      Cowlitz   882    769     53.4
 9:      Douglas  1038   1007     50.8
10:        Ferry   308    272     53.1
11:     Franklin   879    812     52.0
12:     Garfield    39     39     50.0
13:        Grant  1626   1458     52.7
14: Grays Harbor  2372   2498     48.7
15:       Island  2342   2144     52.2
16:    Jefferson  1357   1258     51.9
17:         King 42124  37788     52.7
18:       Kitsap  7062   6442     52.3
19:     Kittitas   981    883     52.6
20:    Klickitat   306    311     49.6
21:        Lewis  1959   1773     52.5
22:      Lincoln   415    386     51.8
23:        Mason  2543   2274     52.8
24:     Okanogan   843    778     52.0
25:      Pacific   349    313     52.7
26: Pend Oreille   513    411     55.5
27:       Pierce 14334  13027     52.4
28:     San Juan   401    375     51.7
29:       Skagit  2330   2159     51.9
30:     Skamania    35     34     50.7
31:    Snohomish 10476   9443     52.6
32:      Spokane 15485  15240     50.4
33:      Stevens  1513   1434     51.3
34:     Thurston  7340   6922     51.5
35:    Wahkiakum    61     54     53.0
36:  Walla Walla   857    774     52.5
37:      Whatcom  4758   4530     51.2
38:      Whitman   642    588     52.2
39:       Yakima  4088   3817     51.7
          County  Male Female Pct.Male

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