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 (701,203) total 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 here. Women 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
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 2000s1: 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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