Oklahoma Marijuana Possession Arrest Rates by County and Age Groups Under 30 (2006)
  Age 10 to 14 Age 15 to 19 Age 20 to 24 Age 25 to 29
County
Arrests
Rate
Pct.
Arrests
Rate
Pct.
Arrests
Rate
Pct.
Arrests
Rate
Pct.
Adair 0 0 0% 3 176 20% 3 198 20% 5 305 33%
Alfalfa 0 0 0% 5 1,632 56% 1 233 11% 1 350 11%
Atoka 0 0 0% 13 1,431 23% 14 1,342 25% 10 865 18%
Beaver 0 0 0% 1 248 13% 5 1,504 63% 0 0 0%
Beckham 1 77 1% 21 1,715 27% 18 1,283 23% 12 836 15%
Blaine 0 0 0% 2 230 8% 7 620 28% 1 90 4%
Bryan 1 39 1% 44 1,609 22% 55 1,759 27% 39 1,281 19%
Caddo 3 128 4% 19 767 26% 19 840 26% 11 550 15%
Canadian 4 84 2% 76 1,581 40% 47 877 25% 18 355 10%
Carter 6 186 4% 31 1,021 19% 50 1,683 30% 25 750 15%
Cherokee 0 0 0% 22 566 27% 28 549 34% 12 338 15%
Choctaw 0 0 0% 8 694 36% 9 917 41% 1 101 5%
Cimarron 0 0 0% 0 0 0% 0 0 0% 0 0 0%
Cleveland 19 172 3% 246 1,831 36% 204 1,059 30% 77 528 11%
Coal 0 0 0% 5 1,212 16% 4 1,259 13% 7 2,002 22%
Comanche 3 33 1% 120 1,244 25% 131 1,466 27% 86 1,295 18%
Cotton 0 0 0% 4 921 8% 18 4,205 38% 8 1,998 17%
Craig 0 0 0% 35 3,459 29% 37 3,881 31% 18 1,847 15%
Creek 6 122 4% 44 891 32% 42 971 31% 17 368 13%
Custer 1 66 1% 21 976 27% 21 621 27% 16 953 21%
Delaware 3 115 2% 34 1,346 24% 40 1,664 29% 13 479 9%
Dewey 0 0 0% 2 722 25% 3 994 38% 2 783 25%
Ellis 0 0 0% 0 0 0% 0 0 0% 1 494 33%
Garfield 0 0 0% 38 1,032 25% 40 1,123 26% 20 521 13%
Garvin 0 0 0% 17 998 18% 28 1,595 30% 16 831 17%
Grady 1 29 1% 30 836 25% 29 722 24% 14 349 12%
Grant 0 0 0% 1 287 10% 1 292 10% 3 1,470 30%
Greer 0 0 0% 6 1,723 32% 8 1,515 42% 2 430 11%
Harmon 0 0 0% 0 0 0% 1 483 100% 0 0 0%
Harper 0 0 0% 1 498 7% 0 0 0% 3 2,178 21%
Haskell 0 0 0% 2 256 10% 4 490 20% 5 576 25%
Hughes 0 0 0% 6 709 43% 3 311 21% 3 315 21%
Jackson 0 0 0% 15 706 23% 24 1,318 36% 10 837 15%
Jefferson 0 0 0% 6 1,448 17% 12 2,976 34% 6 1,628 17%
Johnston 0 0 0% 9 1,140 21% 6 773 14% 9 1,315 21%
Kay 9 261 5% 47 1,430 28% 43 1,474 25% 11 418 6%
Kingfisher 0 0 0% 8 836 15% 15 1,357 29% 14 1,412 27%
Kiowa 0 0 0% 5 747 13% 11 1,640 28% 7 1,276 18%
Latimer 0 0 0% 3 310 33% 1 110 11% 1 142 11%
Le Flore 0 0 0% 8 234 17% 13 388 27% 9 218 19%
Lincoln 0 0 0% 14 601 33% 12 556 29% 4 183 10%
Logan 2 83 1% 31 975 21% 50 1,365 33% 19 703 13%
Love 0 0 0% 3 472 17% 5 831 28% 4 671 22%
Major 0 0 0% 4 810 15% 7 1,406 26% 2 477 7%
Marshall 0 0 0% 17 1,887 30% 9 926 16% 9 844 16%
Mayes 2 73 2% 25 905 19% 41 1,650 32% 23 737 18%
McClain 0 0 0% 30 1,433 33% 21 915 23% 14 670 15%
McCurtain 0 0 0% 16 628 19% 18 831 21% 17 735 20%
McIntosh 1 84 4% 8 636 30% 8 644 30% 1 77 4%
Murray 0 0 0% 19 2,531 24% 19 2,105 24% 11 1,150 14%
Muskogee 0 0 0% 48 1,039 16% 109 2,270 36% 60 1,122 20%
Noble 0 0 0% 3 395 43% 1 143 14% 1 165 14%
Nowata 0 0 0% 11 1,424 23% 20 2,964 43% 8 1,044 17%
Okfuskee 0 0 0% 1 143 13% 2 251 25% 1 121 13%
Oklahoma 64 123 3% 730 1,447 29% 744 1,363 29% 377 627 15%
Okmulgee 0 0 0% 17 564 26% 12 414 18% 6 212 9%
Osage 2 82 3% 6 238 10% 17 696 28% 13 524 21%
Ottawa 0 0 0% 22 808 42% 17 747 32% 6 278 11%
Pawnee 0 0 0% 10 843 14% 23 2,133 32% 15 1,422 21%
Payne 1 29 0% 93 1,468 31% 107 830 36% 33 502 11%
Pittsburg 0 0 0% 28 997 13% 74 2,376 34% 41 1,343 19%
Pontotoc 5 222 2% 53 2,022 22% 72 2,219 30% 35 1,309 15%
Pottawatomie 2 43 1% 34 669 23% 45 814 30% 23 436 16%
Pushmataha 0 0 0% 14 1,618 27% 12 1,631 23% 7 934 13%
Roger Mills 0 0 0% 3 1,501 17% 3 1,315 17% 3 1,815 17%
Rogers 2 32 1% 58 956 26% 66 1,095 30% 24 380 11%
Seminole 1 60 2% 6 330 10% 12 691 20% 21 1,254 34%
Sequoyah 1 33 0% 62 2,207 16% 104 4,042 27% 75 2,365 19%
Stephens 2 71 3% 18 642 26% 15 512 21% 12 448 17%
Texas 1 65 2% 20 1,299 40% 15 936 30% 6 462 12%
Tillman 0 0 0% 8 1,139 33% 7 1,342 29% 2 504 8%
Tulsa 32 76 2% 502 1,264 29% 466 1,169 27% 242 585 14%
Wagoner 2 55 2% 34 995 31% 28 763 25% 20 510 18%
Washington 1 30 1% 21 629 19% 33 1,003 29% 19 625 17%
Washita 1 133 5% 2 246 10% 3 360 15% 3 381 15%
Woods 0 0 0% 11 1,503 22% 19 1,787 37% 6 943 12%
Woodward 0 0 0% 10 773 26% 12 867 31% 4 265 10%

Return to Oklahoma Index

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Notes:

Rates: Arrrest rates are per 100,000 population.

Source: Uniform Crime Reporting Program Data

Because of incomplete reporting the arrest totals presented in tables with data on age, sex, and race will NOT always correspond to totals presented in other tables. Please review the following background material for More Information on Source Data.
 
 
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