Identifying Sex Trafficking
Sex trafficking is a crime of extraordinary violence. Its frequency is likely severely underreported, given the isolation within which its victims are kept. We are extracting structured content from a very large corpus of online commercial sex ads and provider reviews crawled over a period of several years, and integrating this content with law enforcement records on sex trafficking cases. We are then looking for features in the ad and review data that are predictive of the presence of sex trafficking, and that may assist law enforcement agencies in identifying newly posted ads and reviews associated with trafficking. We are particularly focusing on urban school district calendars, which typically include days when high school-aged children are not in school, but adults (including teachers) are at work. Initial results suggest that school calendars may be a good predictor of the incidence of sex trafficking, highlighting for agencies the importance of investigating online sex ads posted on days when high school-aged children are not in school, but adults are at work.
Criminal Appeals Equity Project
Using content extracted from the scraped text corpus of the approximately 38,000 slip opinions in criminal appeals heard by New York State's intermediate appellate courts between 2003-2017, appellate judge election and appointment data sourced from the New York State Board of Elections and the New York State Judicial Screening Committee, and defendant demographic and conviction data scraped from the New York State Department of Corrections' inmate database, we report the first within-judge estimates of the effects of both reelection and reappointment incentives on judicial votes on criminal appeals. Our findings indicate that impending judicial reappointment induces a 33 - 36\% decrease in appellate votes in favor of black defendants, but has no effects on votes in cases involving white or non-Hispanic white defendants. We find no additional effects of impending reelection on appellate judge votes in criminal appeals. Our findings may indicate the need for greater attention devoted both to potential selection effects, and to heterogeneous effects by race of defendant, in studies of judicial retention institutions. (PAPER HERE)
Policing for Revenue
In recent years numerous observers have raised concerns about “policing for profit,” or the deployment of law enforcement resources to raise funds for cash-strapped jurisdictions. However, identifying the causal effect of fiscal incentives on law enforcement behavior has remained elusive. We leverage a discontinuity in the rules allocating fine revenue from traffic citations issued by a large highway patrol agency, finding that the frequency and severity of traffic accidents increase sharply just above the threshold reducing the share of fine revenue captured by the agency. We also find that cited drivers in towns just below this threshold are given fewer days to pay their fines and are less likely to pay their fines on time, leading to higher risks of late fees and license suspension. These findings suggest that fiscal concerns can in fact impact public safety decisions. (PAPER HERE)
Detecting Domestic Violence
Domestic violence is both distressingly common and significantly underreported to law enforcement authorities. Its widespread presence is costly to its victims, to their children, and to society more generally. Yet there may be strategies to assist both law enforcement and social service agencies in detecting and addressing the presence of unreported domestic violence. For example, we know that the timing of reported domestic violence responds to the timing of the distribution of social benefits. In partnership with NYU Wagner’s Policies For Action Health Hub, and leveraging the randomly assigned timing of the distribution of social benefits to individual households, we are working with New York State’s Medicaid data to identify female and child injuries that may be due to unreported domestic violence. We are then looking for features that may help to explain both the incidence of domestic violence, and its relative underreporting.
Recent events have directed renewed attention to the question of whether increasing the proportion of nonwhite officers in law enforcement agencies would lead to different public safety outcomes. Increasing the proportion of nonwhite police officers may lead to an increased acceptance of policing in nonwhite communities, fewer instances of the use of force, and fewer citizen complaints, leading in turn to increases in the reporting of crime and in the willingness of civilians to cooperate with police investigations. Nonwhite officers may also exert greater effort, or be better equipped, to clear crimes in largely nonwhite communities. Working with both survey and law enforcement administrative data, we are investigating the impacts of police force diversity on public safety outcomes. (PAPER HERE)
911 Response Field Experiment
Many policing agencies seek to improve their relationships with the communities they police, yet struggle to find effective means to do so. Working with a large urban policing agency, we are developing a randomized controlled trial of a platform that pushes an SMS-based survey to recent 911 callers, asking them to provide feedback on how they were treated by responding officers. Responding patrol officers may then access their average survey ratings, as well as those of the other officers in their unit, through a web-based interface. The platform may both incentivize responding officers to treat 911 callers with greater professionalism, and increase caller satisfaction with the police response to their call. More generally, the platform may provide an effective means for agencies to receive real time feedback from the communities they police.
911 Response Analytics
Calls to 911 in large urban jurisdictions are typically first assigned to a responding service (e.g., police, medical, fire), and are then assigned priority codes determining the speed and nature of the service's response. These human-assigned call and priority codes may not be optimal. For example, calls involving mental health and substance abuse issues may be assigned to policing agencies when they might more appropriately be assigned to medical professionals. Calls involving behavioral health issues assigned to policing agencies may or may not be assigned codes providing for response by officers trained in crisis intervention. Call taker biases may affect the assignment of call and priority codes. Working with a large urban policing agency, we are exploiting the as-if random assignment of 911 calls to call takers to evaluate the causal effects of call taker discretion on the assignment of call and priority codes, and subsequently on call outcomes, and to design call response protocols that may reduce the risks of escalated encounters.