UAAJC Working Papers
UAAJC Working Papers was an occasional papers series designed for faculty, staff, and exceptional students from UAA to present research on issues of crime, law, and justice to the world. It was published by the Justice Center at University of Alaska Anchorage from 2005 to 2007.
Recent Submissions
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Collective Efficacy and Firearms Violence in Anchorage, Alaska: Preliminary FindingsThis paper seeks to advance the discussion of the utility of collective efficacy, as captured by Sampson, Raudenbush and Earls, in understanding community levels of crime by exploring the relation between community structure, collective efficacy, and in this case firearms violence, in Anchorage, Alaska. The specific aims of this paper are to report the results of a test of the collective efficacy thesis, modeled loosely after the test presented in the 1997 Science paper by Sampson, Raudenbush and Earls, as an explanation of neighborhood rates of firearms violence in Anchorage.
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Drugs and Crime in Anchorage, Alaska: A NoteThis research note examines the relationship between drug use and offense charged through data collected in 2003 from 259 recent arrestees in Anchorage, Alaska using the Arrestee Drug Abuse Monitoring (ADAM) protocol. The analysis is restricted to examining those ADAM participants who tested positive for marijuana and cocaine use.
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Seasonal Use of Marijuana and Cocaine by Arrestees in Anchorage, AlaskaThis paper explores the relation between season (fall, winter, spring and summer) and drug use among arrestees. The analysis examines seasonal differences of proportions of drug tests positive for marijuana or cocaine among recently arrested and booked suspects in Anchorage, Alaska. The study is based on Arrestee Drug Abuse Monitoring (ADAM) data collected in Anchorage during the period between 1999 and the third quarter of 2003.
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ADAM-Anchorage Data: Are They Representative?This paper presents the results of a study designed to assess the representativeness of realized samples of recent arrestees selected for the Arrestee Drug Abuse Monitoring (ADAM) program in Anchorage, Alaska. Because one of the most important goals of the ADAM program is to produce scientific information on the prevalence of alcohol and drug use behaviors among arrestees that is generalizable to an entire local arrestee population, establishing the representativeness of realized samples (or isolating inherent biases) is an essential first step to meaningful use of these data to address locally defined problems. In order to determine the reasonableness of inferences grounded in realized samples of ADAM respondents, an analysis was done comparing various characteristics between each stage of the sample selection process including the census of eligible arrestee population, the designed ADAM arrestee sample, arrestees available for interview, arrestees actually interviewed (“realized” sample), and arrestees that provided urine sample (“realized” sample). If the realized samples are similar to the census we can have a greater degree of confidence in our capacity to describe the population of Anchorage arrestees using ADAM data. Also, if it happens that departures are detected between realized samples and the arrestee census we are better positioned to condition the inferences made by integrating these discerned biases into our conclusions.
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Anchorage Community Survey 2007 Survey Sampling Design: Power and Sample SizeThis working paper documents the power analysis, literature review, and precision considerations contemplated in designing the Anchorage Community Survey’s (ACS) 2007 sampling design. The ACS will obtain at least 30 completed surveys from individuals in each of the 55 census tracts that make up the Anchorage Municipality, allowing us to discern a fairly small effect size of 0.30 with our smallest anticipated intraclass correlation and a moderate effect size of 0.40 with our largest anticipated intraclass correlation, both at 0.80 power level. This cluster sample size and number of clusters should yield sufficient precision to allow good estimation of variance components and standard errors, acceptable reliability estimates, and reasonable aggregated measures of constructed neighborhood variables from individual survey item responses.