16,845 42nd LD Precinct Votes "left on the table" from those precincts with over 300 'not voting'. 32K voters registered in the 42nd LD did not participate. Click on chart too enlarge. |
The matchback totals include 1102 duplicates registration numbers which are caused by voters attempting to "cure" their undeliverable or challenged ballots. Those first tries become void unless "cured" before certification. Undeliverable ("return to sender") is the largest category of ballot loss, follow by "Too Late" and "No signature match". But no challenge or ballot delivery issue creates as much voter loss as those that simply don't cast their ballots:
length(unique(duplicated$RegistrationNumber))
[1] 1102
count(MB_2014_Consolidated_status,"AVReturnStatus")
AVReturnStatus freq
1 Not Voted 48205
2 Challenged 695
3 Good 76089
4 Undeliverable 2457
5 Void 992
count(MB_2014_Consolidated_status,"AVReturnChallenge")
AVReturnChallenge freq
1 125286
2 Electronic 8
3 ID Required 9
4 Letter doesn't match env. 28
5 No Ballot 5
6 No Signature 55
7 No Signature Match 263
8 Power of Attorney 1
9 Second Ballot Received 21
10 Too Late 293
11 Undeliverable 2457
12 Wrong Voter's Signature 10
13 Z - Deceased 1
14 Z - Other 1
Among those that did cast their ballots, these were the top 20 precincts:
arrange(data.frame(with(MB_2014_Consolidated_Good,(table(PrecinctID)))),desc(Freq))
PrecinctID Freq
1 601 743
2 201 730
3 140 729
4 208 715
5 169 714
6 222 698
7 250 672
8 127 665
9 213 662
10 134 653
11 145 648
12 144 647
13 146 644
14 609 643
15 610 637
16 126 634
17 181 629
18 168 624
19 182 618
20 151 616
...
These precincts had the greatest number of votes not cast:
arrange(subset(Test,PrecinctID %in% ld42$precincts42),desc(NoVote))
These precincts had the greatest number of votes not cast:
arrange(subset(Test,PrecinctID %in% ld42$precincts42),desc(NoVote))
PrecinctID | No Vote | Challenged | Good | Undeliverable | Void | Undel_Void | PCT_Good | PCT_Undel_Void |
133 | 606 | 7 | 361 | 14 | 51 | 65 | 35.0 | 1.4 |
137 | 568 | 15 | 366 | 7 | 50 | 57 | 36.9 | 0.7 |
229 | 528 | 4 | 488 | 23 | 7 | 30 | 46.7 | 2.2 |
201 | 521 | 4 | 730 | 18 | 7 | 25 | 57.2 | 1.4 |
206 | 491 | 6 | 515 | 22 | 13 | 35 | 49.5 | 2.1 |
208 | 469 | 4 | 715 | 26 | 8 | 34 | 58.7 | 2.1 |
108 | 449 | 5 | 605 | 3 | 7 | 10 | 56.9 | 0.3 |
225 | 448 | 7 | 482 | 33 | 12 | 45 | 49.4 | 3.4 |
148 | 436 | 2 | 487 | 11 | 3 | 14 | 52.0 | 1.2 |
101 | 421 | 7 | 476 | 9 | 4 | 13 | 52.3 | 1.0 |
302 | 416 | 7 | 608 | 14 | 7 | 21 | 58.2 | 1.3 |
505 | 414 | 1 | 575 | 16 | 7 | 23 | 56.8 | 1.6 |
211 | 398 | 6 | 481 | 7 | 5 | 12 | 54.0 | 0.8 |
142 | 395 | 3 | 373 | 11 | 11 | 22 | 47.2 | 1.4 |
220 | 388 | 4 | 383 | 20 | 6 | 26 | 48.1 | 2.5 |
140 | 385 | 6 | 729 | 3 | 4 | 7 | 65.0 | 0.3 |
508 | 383 | 4 | 518 | 7 | 8 | 15 | 56.6 | 0.8 |
136 | 373 | 3 | 459 | 7 | 15 | 22 | 53.7 | 0.8 |
166 | 370 | 4 | 562 | 7 | 3 | 10 | 59.7 | 0.7 |
135 | 369 | 6 | 458 | 5 | 7 | 12 | 54.6 | 0.6 |
506 | 368 | 0 | 486 | 8 | 3 | 11 | 56.2 | 0.9 |
134 | 362 | 4 | 653 | 4 | 9 | 13 | 63.5 | 0.4 |
126 | 355 | 2 | 634 | 9 | 9 | 18 | 63.0 | 0.9 |
146 | 354 | 7 | 644 | 3 | 9 | 12 | 63.8 | 0.3 |
203 | 350 | 1 | 520 | 15 | 9 | 24 | 58.2 | 1.7 |
106 | 348 | 3 | 422 | 5 | 0 | 5 | 54.5 | 0.6 |
204 | 344 | 1 | 225 | 13 | 4 | 17 | 38.4 | 2.2 |
301 | 343 | 9 | 600 | 14 | 10 | 24 | 62.0 | 1.4 |
219 | 337 | 5 | 444 | 8 | 7 | 15 | 55.8 | 1.0 |
233 | 337 | 2 | 489 | 11 | 7 | 18 | 57.9 | 1.3 |
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