DRUG SCIENCE

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Oklahoma Marijuana Possession Arrest Rates by County and Age Groups Under 30 (2007)

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  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% 8 444 26% 8 531 26% 4 248 13%
Alfalfa 0 0 0% 1 476 9% 2 676 18% 3 1,217 27%
Atoka 0 0 0% 8 879 22% 13 1,310 36% 2 162 6%
Beaver 0 0 0% 0 0 0% 5 1,519 56% 3 1,101 33%
Beckham 1 85 1% 23 1,950 30% 21 1,378 28% 11 665 14%
Blaine 0 0 0% 3 352 27% 5 447 45% 1 86 9%
Bryan 3 120 2% 41 1,440 32% 29 892 22% 19 606 15%
Caddo 2 89 2% 27 1,086 29% 30 1,403 32% 12 583 13%
Canadian 2 42 1% 80 1,661 41% 65 1,246 33% 21 375 11%
Carter 5 154 3% 55 1,829 28% 47 1,654 24% 30 871 15%
Cherokee 1 35 1% 26 687 22% 39 768 33% 19 522 16%
Choctaw 0 0 0% 4 359 17% 11 1,150 46% 4 415 17%
Cimarron 0 0 0% 0 0 0% 2 1,082 33% 0 0 0%
Cleveland 18 162 2% 232 1,690 31% 218 1,086 30% 115 738 16%
Coal 0 0 0% 10 2,470 26% 9 2,648 23% 9 2,510 23%
Comanche 3 37 1% 130 1,371 28% 132 1,339 29% 69 1,043 15%
Cotton 1 213 3% 3 675 9% 8 2,021 24% 5 1,135 15%
Craig 1 112 1% 26 2,589 28% 22 2,427 23% 13 1,256 14%
Creek 0 0 0% 62 1,247 40% 41 978 27% 16 327 10%
Custer 2 139 2% 41 1,993 37% 34 1,019 30% 11 588 10%
Delaware 2 75 2% 26 1,010 27% 15 628 15% 15 526 15%
Dewey 0 0 0% 1 360 4% 6 2,163 26% 3 1,276 13%
Ellis 0 0 0% 0 0 0% 5 2,313 50% 2 904 20%
Garfield 0 0 0% 44 1,233 24% 53 1,567 29% 27 682 15%
Garvin 1 56 1% 52 3,117 34% 37 2,311 24% 13 632 9%
Grady 3 87 4% 19 537 22% 17 452 20% 17 397 20%
Grant 0 0 0% 0 0 0% 0 0 0% 1 454 20%
Greer 0 0 0% 1 278 10% 1 202 10% 2 426 20%
Harmon 0 0 0% 2 821 33% 2 1,134 33% 0 0 0%
Harper 1 519 7% 1 545 7% 6 2,733 43% 2 1,191 14%
Haskell 1 118 3% 7 871 19% 7 903 19% 6 649 16%
Hughes 0 0 0% 3 346 38% 0 0 0% 0 0 0%
Jackson 0 0 0% 18 900 30% 21 1,168 35% 5 410 8%
Jefferson 0 0 0% 4 965 36% 4 1,103 36% 1 262 9%
Johnston 0 0 0% 3 374 4% 27 3,573 38% 12 1,673 17%
Kay 11 343 6% 69 2,103 36% 49 1,750 26% 24 864 13%
Kingfisher 0 0 0% 8 833 32% 3 289 12% 5 467 20%
Kiowa 0 0 0% 4 610 50% 3 497 38% 0 0 0%
Latimer 0 0 0% 1 101 8% 5 599 42% 2 278 17%
Le Flore 1 30 1% 18 526 14% 32 1,000 26% 20 465 16%
Lincoln 0 0 0% 14 577 27% 18 885 35% 8 340 15%
Logan 2 83 1% 59 1,890 31% 52 1,469 27% 22 752 12%
Love 0 0 0% 6 965 13% 14 2,438 30% 12 1,965 26%
Major 0 0 0% 3 630 17% 3 630 17% 4 842 22%
Marshall 1 108 1% 14 1,539 19% 15 1,604 21% 13 1,149 18%
Mayes 0 0 0% 35 1,265 27% 37 1,549 29% 17 525 13%
McClain 0 0 0% 38 1,733 27% 41 1,692 29% 20 817 14%
McCurtain 0 0 0% 30 1,187 29% 26 1,282 25% 14 606 14%
McIntosh 1 86 3% 9 715 23% 13 1,078 33% 5 381 13%
Murray 1 124 1% 16 2,119 17% 29 3,563 32% 14 1,403 15%
Muskogee 0 0 0% 50 1,074 22% 60 1,297 26% 40 714 17%
Noble 0 0 0% 8 1,068 28% 7 1,056 24% 4 610 14%
Nowata 0 0 0% 1 132 7% 10 1,536 71% 2 260 14%
Okfuskee 1 136 6% 4 576 24% 3 379 18% 1 117 6%
Oklahoma 51 99 2% 754 1,482 28% 785 1,444 30% 380 625 14%
Okmulgee 1 36 1% 26 873 23% 20 711 18% 23 791 20%
Osage 0 0 0% 9 365 25% 12 498 33% 2 76 6%
Ottawa 3 140 5% 26 964 44% 15 711 25% 1 46 2%
Pawnee 0 0 0% 6 487 13% 10 977 22% 9 847 20%
Payne 1 28 0% 107 1,611 34% 102 731 33% 37 498 12%
Pittsburg 2 72 1% 38 1,316 15% 78 2,585 31% 61 1,913 24%
Pontotoc 1 46 0% 71 2,684 28% 66 1,990 26% 37 1,389 15%
Pottawatomie 8 175 4% 42 801 22% 55 995 28% 22 407 11%
Pushmataha 1 131 2% 8 968 20% 7 959 17% 5 629 12%
Roger Mills 0 0 0% 1 501 20% 2 898 40% 0 0 0%
Rogers 2 31 1% 32 520 23% 48 821 34% 19 281 13%
Seminole 0 0 0% 12 681 19% 18 1,088 28% 14 801 22%
Sequoyah 0 0 0% 51 1,759 22% 63 2,500 27% 41 1,302 18%
Stephens 1 36 1% 23 831 30% 19 684 25% 13 448 17%
Texas 0 0 0% 8 516 33% 7 432 29% 4 310 17%
Tillman 0 0 0% 7 1,031 19% 10 2,064 27% 7 1,569 19%
Tulsa 45 109 2% 662 1,640 32% 536 1,326 26% 290 682 14%
Wagoner 1 27 1% 41 1,151 34% 34 940 28% 12 277 10%
Washington 2 64 1% 37 1,109 28% 43 1,322 32% 17 522 13%
Washita 0 0 0% 1 130 6% 7 871 44% 3 340 19%
Woods 0 0 0% 11 1,522 27% 12 1,133 29% 5 752 12%
Woodward 0 0 0% 12 924 35% 8 583 24% 6 373 18%

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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.