- Berkeley, California, United States
- 9173642301
Hannah Laqueur
University of California, Davis, Emergency Medicine, Faculty Member
- University of California, Berkeley, Jurisprudence and Social Policy, Graduate Studentadd
The problem of inconsistent legal and administrative decision making is widespread and well documented. We argue that predictive models of collective decisions can be used to guide and regulate the decisions of individual adjudicators.... more
The problem of inconsistent legal and administrative decision making is widespread
and well documented. We argue that predictive models of collective decisions can be
used to guide and regulate the decisions of individual adjudicators. This \synthetic
crowdsourcing" approach simulates a world in which all judges cast multiple indepen-
dent votes in every case. Synthetic crowdsourcing can extend the core bene ts of en
banc decision making to all cases while avoiding the dangers of group think. Similar to
decision matrices such as the Federal Sentencing Guidelines, synthetic crowdsourcing
uses statistical patterns in historical decisions to guide future decisions. But unlike
traditional approaches, it leverages machine learning to optimally tailor that guidance,
allowing for substantial improvements in the consistency and overall quality of deci-
sions. We illustrate synthetic crowdsourcing with an original dataset built using text
processing of transcripts from California parole suitability hearings.
and well documented. We argue that predictive models of collective decisions can be
used to guide and regulate the decisions of individual adjudicators. This \synthetic
crowdsourcing" approach simulates a world in which all judges cast multiple indepen-
dent votes in every case. Synthetic crowdsourcing can extend the core bene ts of en
banc decision making to all cases while avoiding the dangers of group think. Similar to
decision matrices such as the Federal Sentencing Guidelines, synthetic crowdsourcing
uses statistical patterns in historical decisions to guide future decisions. But unlike
traditional approaches, it leverages machine learning to optimally tailor that guidance,
allowing for substantial improvements in the consistency and overall quality of deci-
sions. We illustrate synthetic crowdsourcing with an original dataset built using text
processing of transcripts from California parole suitability hearings.
Research Interests:
In 2001, Portugal decriminalized the acquisition, possession, and use of small quantities of all psychoactive drugs. The significance of this legislation has been misunderstood. Decriminalization did not trigger dramatic changes in... more
In 2001, Portugal decriminalized the acquisition, possession, and use of small quantities of all psychoactive drugs. The significance of this legislation has been misunderstood.
Decriminalization did not trigger dramatic changes in drug-related behavior because, as an analysis of Portugal’s predecriminalization laws and practices reveals, the
reforms were more modest than suggested by the media attention they received. Portugal illustrates the shortcomings of before-and-after analysis because, as is often the case, the de jure legal change largely codified de facto practices. In the years before the law’s passage, less than 1 percent of those incarcerated for a drug offense had been convicted of use. Surprisingly, the change in law regarding use appears associated with a marked reduction in drug trafficker sanctioning. While the number of arrests for trafficking changed little, the number of individuals convicted and imprisoned for trafficking since 2001 has fallen nearly 50 percent.
Decriminalization did not trigger dramatic changes in drug-related behavior because, as an analysis of Portugal’s predecriminalization laws and practices reveals, the
reforms were more modest than suggested by the media attention they received. Portugal illustrates the shortcomings of before-and-after analysis because, as is often the case, the de jure legal change largely codified de facto practices. In the years before the law’s passage, less than 1 percent of those incarcerated for a drug offense had been convicted of use. Surprisingly, the change in law regarding use appears associated with a marked reduction in drug trafficker sanctioning. While the number of arrests for trafficking changed little, the number of individuals convicted and imprisoned for trafficking since 2001 has fallen nearly 50 percent.
Research Interests:
Objectives: The objective of this analysis is to address the data and conclusions of Lisa Stolzenberg and Stewart D’Alessio in their article “Co-offending and the Age-crime Curve,” published in The Journal of Research in Crime and... more
Objectives: The objective of this analysis is to address the data and conclusions of Lisa Stolzenberg and Stewart D’Alessio in their article “Co-offending and the Age-crime Curve,” published in The Journal of Research in Crime and Delinquency in 2008. The authors analyze National Incident–based Reporting System (NIBRS) 2002 arrests from seven states and conclude that most arrests at all ages involve only one offender, and therefore group offending is of little etiological significance.
Methods: To test their claims, we conduct offense-specific analyses of single and multiple arrests using the full 2002 NIBRS arrest data set.
Results: After disaggregating the data by type of offense, we find group involvement among young offenders dominates the arrest statistics for all serious crimes other than rape and aggravated assault. Conclusions: Contrary to the conclusions of Stolzenberg and D’Alessio, co-offending does appear to have a substantial impact on young offenders. The extent of adolescent crime as group behavior may be a cliché in criminological circles, but this is because the empirical evidence for it is substantial.
Methods: To test their claims, we conduct offense-specific analyses of single and multiple arrests using the full 2002 NIBRS arrest data set.
Results: After disaggregating the data by type of offense, we find group involvement among young offenders dominates the arrest statistics for all serious crimes other than rape and aggravated assault. Conclusions: Contrary to the conclusions of Stolzenberg and D’Alessio, co-offending does appear to have a substantial impact on young offenders. The extent of adolescent crime as group behavior may be a cliché in criminological circles, but this is because the empirical evidence for it is substantial.