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New York All Drugs Possession

New York Metropolitan Area Counties
1995 Drug Possession Arrests by Race

(Data Source: Uniform Crime Reports. See below for notes.)


ALL

BLACK

WHITE

AM. INDIAN

ASIAN-PAC.

METROPOLITAN AREA

JURISDICTION

TL

POP

RATE

TL

POP (est)

RATE

TL

POP (est)

RATE

TL

POP (est)

RATE

TL

POP (est)

RATE

All listed below.

All listed below.

32,600 10,338,918 315.31 13,190 881,341 1,496.58 19,274 9,158,195 210.46 43 32,479 132.39 93 267,036 34.83

Albany-Schenectady-Troy, N.Y.

Albany

2,326 287,191 809.91 1,337 26,651 5,016.64 983 253,532 387.72 2 574 348.20 4 6,433 62.18

Albany-Schenectady-Troy, N.Y.

Montgomery

178 49,743 357.84 11 562 1,956.96 167 48,788 342.30 0 104 0.00 0 289 0.00

Albany-Schenectady-Troy, N.Y.

Rensselaer

556 156,057 356.28 147 5,774 2,545.85 407 147,177 276.54 1 312 320.40 1 2,793 35.80

Albany-Schenectady-Troy, N.Y.

Saratoga

454 188,515 240.83 19 2,620 725.09 433 183,614 235.82 1 302 331.54 1 1,979 50.52

Albany-Schenectady-Troy, N.Y.

Schenectady

517 149,307 346.27 220 7,122 3,089.04 295 139,393 211.63 0 299 0.00 2 2,493 80.21

Albany-Schenectady-Troy, N.Y.

Schoharie

101 32,975 306.29 4 488 819.62 97 32,263 300.66 0 76 0.00 0 145 0.00

Binghamton, N.Y.

Broome

736 200,093 367.83 148 4,562 3,244.11 582 190,589 305.37 0 360 0.00 6 4,562 131.52

Binghamton, N.Y.

Tioga

146 53,326 273.79 4 389 1,027.54 142 52,403 270.97 0 96 0.00 0 432 0.00

Buffalo-Niagara Falls, N.Y.

Cattaraugus

3 3,106 96.59 0 30 0.00 3 2,985 100.49 0 74 0.00 0 16 0.00

Buffalo-Niagara Falls, N.Y.

Erie

4,574 942,990 485.05 2,269 117,685 1,928.03 2,287 806,256 283.66 10 6,035 165.70 8 13,108 61.03

Buffalo-Niagara Falls, N.Y.

Niagara

468 218,245 214.44 209 13,117 1,593.41 256 201,898 126.80 3 2,139 140.27 0 1,091 0.00

Dutchess County, N.Y.

Dutchess

883 253,129 348.83 397 22,731 1,746.51 485 222,399 218.08 0 405 0.00 1 7,594 13.17

Elmira, N.Y.

Chemung

211 73,945 285.35 57 4,496 1,267.83 154 68,517 224.76 0 177 0.00 0 754 0.00

Glens Falls, N.Y.

Warren

226 59,354 380.77 7 338 2,069.06 219 58,523 374.21 0 119 0.00 0 374 0.00

Glens Falls, N.Y.

Washington

160 59,724 267.90 1 2,096 47.70 159 57,347 277.26 0 113 0.00 0 167 0.00

Jamestown, N.Y.

Chautauqua

541 141,908 381.23 130 3,079 4,221.60 407 137,452 296.10 3 653 459.58 1 738 135.52

Nassau-Suffolk, N.Y.

Nassau

1,730 1,288,805 134.23 547 122,050 448.18 1,173 1,112,110 105.48 1 2,062 48.49 9 52,583 17.12

Nassau-Suffolk, N.Y.

Suffolk

2,114 1,332,640 158.63 801 92,352 867.33 1,304 1,205,906 108.13 2 3,598 55.58 7 30,784 22.74

Newburgh, N.Y.-Pa.

Orange

2,106 312,818 673.23 674 24,619 2,737.75 1,430 282,412 506.35 0 938 0.00 2 4,849 41.25

New York, N.Y.

Nassau

1,730 1,288,805 134.23 547 122,050 448.18 1,173 1,112,110 105.48 1 2,062 48.49 9 52,583 17.12

New York, N.Y.

Putnam

361 89,053 405.38 46 988 4,653.57 315 86,844 362.72 0 134 0.00 0 1,078 0.00

New York, N.Y.

Rockland

982 268,011 366.40 337 29,213 1,153.59 632 223,655 282.58 2 750 266.51 11 14,419 76.29

New York, N.Y.

Westchester

2,508 699,361 358.61 1,199 103,855 1,154.49 1,300 560,468 231.95 0 1,329 0.00 9 33,779 26.64

Rochester, N.Y.

Genesee

230 60,409 380.74 26 1,196 2,173.73 203 58,168 348.99 1 755 132.43 0 296 0.00

Rochester, N.Y.

Livingston

142 64,849 218.97 7 2,289 305.79 135 61,885 218.15 0 227 0.00 0 447 0.00

Rochester, N.Y.

Monroe

3,004 725,620 413.99 1,725 94,548 1,824.46 1,267 611,770 207.10 0 2,322 0.00 12 16,980 70.67

Rochester, N.Y.

Ontario

368 90,717 405.66 45 1,869 2,408.00 322 87,959 366.08 0 227 0.00 1 653 153.10

Rochester, N.Y.

Orleans

79 40,760 193.82 16 3,473 460.73 63 36,884 170.81 0 200 0.00 0 204 0.00

Rochester, N.Y.

Wayne

468 92,816 504.22 95 3,388 2,804.19 372 88,658 419.59 0 269 0.00 1 501 199.52

Syracuse, N.Y.

Cayuga

301 82,961 362.82 42 3,177 1,321.83 259 79,029 327.73 0 307 0.00 0 448 0.00

Syracuse, N.Y.

Madison

149 72,880 204.45 9 867 1,037.74 138 71,160 193.93 1 292 343.03 1 554 180.54

Syracuse, N.Y.

Onondaga

2,794 537,513 519.80 1,688 47,409 3,560.53 1,093 475,807 229.72 13 4,031 322.47 0 10,266 0.00

Syracuse, N.Y.

Oswego

241 122,370 196.94 5 673 742.90 236 120,571 195.74 0 477 0.00 0 649 0.00

Utica-Rome, N.Y.

Herkimer

120 55,111 217.74 4 198 2,016.13 116 54,648 212.27 0 99 0.00 0 165 0.00

Utica-Rome, N.Y.

Oneida

1,093 243,811 448.30 417 15,384 2,710.52 667 225,013 296.43 2 561 356.66 7 2,828 247.51

 

Notes:

TL: Total arrests.

POP: Coverage population of reporting law enforcement agencies.

RATE: Arrest Rate per 100,000 population.

Original Source: Uniform Crime Reports, 1995.

Data are total for reporting agencies. Population estimates by race are based on application of U.S. Census percentages of total population to the coverage population in which the arrests occurred. The racial categories and labels are as defined and used in the Uniform Crime Reports. Unfortunately separate data on arrests of Hispanics are not available.

The Uniform Crime Reports provides data on all drug arrests as well as data of arrests for drug possession and sales. Four categories are used to provide more specific data on arrests for different types of controlled substances: 1) Opium and Cocaine and their derivatives (such as Crack, Morphine, Heroin); 2) Marijuana; 3) Synthetic Narcotics - Manufactured Narcotics which can cause true drug addiction (such as Demerol, Methadone); 4) Other Dangerous Non-Narcotic Drugs (such as Barbiturates, Benzedrine, and Methamphetamine).

Primary Source: Chilton, Rowland, and Dee Weber. UNIFORM CRIME REPORTING PROGRAM [UNITED STATES]: ARRESTS BY AGE, SEX, AND RACE FOR POLICE AGENCIES IN METROPOLITAN STATISTICAL AREAS, 1960-1995[Computer file]. ICPSR version. Amherst, MA: University of Massachusetts [producer], 1998.Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor],1999.

Citation: Gettman, Jon B. "US Marijuana Arrests. Part Two - Racial Differences in Drug Arrests". Washington, D.C.: National Organization for the Reform of Marijuana Laws. (2000)