Implementing Intelligence-Led Policing: An Application of Loose-Coupling Theory

Purpose

This research is intended to inform a knowledge gap in the literature and present the first national findings related to intelligence-led policing adoption among state and local agencies. Specific practices are identified to inform scholars and practitioners regarding intelligence-led policing behaviors.

Methods

Original survey research from a federally-funded project is gleaned to explore intelligence-led policing adoption through a loose-coupling theoretical perspective. Negative binomial and logistic regression models are employed to identify predictive relationships.

Results

Agencies nationwide appear to be closely following the National Criminal Intelligence Sharing Plan recommendations to enhance information sharing. Consistent with the Department of Homeland Security’s Target Capabilities List is also observed. Agency size appears to have a significant effect on key organizational information sharing behaviors. The findings are tempered due to limitations in the research design.

Conclusions

Local agencies appear to be tightly-coupled with the recommendations put forth in the National Criminal Intelligence Sharing Plan in their efforts to adopt intelligence-led policing. Agency size appears to enhance adoption across most dependent metrics. This research progresses the limited evidence base and progress regarding this emerging policing philosophy.     

Forecasts of Violence to Inform Sentencing Decisions

Objectives

Recent legislation in Pennsylvania mandates that forecasts of "future dangerousness" be provided to judges when sentences are given. Similar requirements already exist in other jurisdictions. Research has shown that machine learning can lead to usefully accurate forecasts of criminal behavior in such setting. But there are settings in which there is insufficient IT infrastructure to support machine learning. The intent of this paper is provide a prototype procedure for making forecasts of future dangerousness that could be used to inform sentencing decisions when machine learning is not practical. We consider how classification trees can be improved so that they may provide an acceptable second choice.

Methods

We apply an version of classifications trees available in R, with some technical enhancements to improve tree stability. Our approach is illustrated with real data that could be used to inform sentencing decisions.

Results

Modest sized trees grown from large samples can forecast well and in a stable fashion, especially if the small fraction of indecisive classifications are found and accounted for in a systematic manner. But machine learning is still to be preferred when practical.

Conclusions

Our enhanced version of classifications trees may well provide a viable alternative to machine learning when machine learning is beyond local IT capabilities.     

Tension in democratic administration: Does managerial confidence in administrative capacity reduce citizen participation in organizational decision-making?

The tension between bureaucratic and democratic values has characterized significant debates in the field of public administration. In this article, we ask, does public managers' confidence in their organizational administrative capacity affect citizen participation? Using managerial confidence in organizational response capacity (ORC) during crises as a vehicle to investigate the tension between democratic and administrative values, we examine whether an administration-centric approach to management influences citizen participation. We posit that higher levels of managerial confidence in organizational administrative capacity can lessen the pressure from political stakeholders which, in turn, might allow managers the autonomy to isolate themselves from the general public. The empirical analysis uses a structural equation model (SEM) to examine survey data from senior managers in 500 US cities. We find that managerial confidence in ORC reduces citizen participation, but only indirectly through diminishing influence from other governmental actors or by allowing managers to win the trust of political principals.     

Time series applications to intelligence analysis: a case study of homicides in Mexico

Abstract

The scale of lethal violence in Mexico seen in the past decade has been a pressing concern for both Mexican and US officials, including law enforcement organizations, intelligence agencies, and policy makers. With much of the homicides being a result of the trafficking of illegal drugs, it has been suggested that the homicides in Mexico follow seasonal patterns tied to the drug trade, specifically to the cultivation of heroin. In this paper, conventional econometric time series methods are applied to test this hypothesis. Results demonstrate that not only do the drug-related homicides in Mexico display evidence of seasonality, but also that seasonality appears empirically related to the heroin trade. The paper makes the larger argument that time series and other statistical methods are an untapped resource that can complement standard intelligence analysis to support defensible judgments based on the scientific method of inquiry. However, a fuller integration of statistics and traditional analysis would require sufficient support structures be developed to encourage and promote such analysis.     

Why Democratic Allies Defect Prematurely: Canadian and Dutch Unilateral Pullouts from the War in Afghanistan

Why do some democratic allies prematurely withdraw from ongoing military US-led coalition operations? Why are some democratic allies more reliable than others? This article proposes a multifactorial integrated framework consisting of several causal mechanisms drawn from ideological, domestic, and alliance explanations of premature defection. It compares and contrasts two neglected case studies, namely the Canadian and Dutch withdrawal of combat troops from NATO’s counterinsurgency mission in southern Afghanistan. The comparative analysis finds that democratic institutional designs, parliamentary war powers, leadership turnover, as well alliance dependence and threat perceptions did not play a meaningful role in both cases of premature defection. It rather finds that domestic elite consensus interacted with electoral calculations to account for pullout choices. Right-wing ideological beliefs held by state executives also slowed down the decision to withdraw, and alliance pressures interacted with domestic elite consensus to account for commitment renewal into a noncombat mission. The article concludes with some implications for the theory of democratic alliance reliability.     

On the Social Foundations for Crimmigration: Latino Threat and Support for Expanded Police Powers

Objectives

Because of the merging of immigration control and criminal justice, or “crimmigration,” state and local police increasingly drive interior immigration enforcement through the routine policing of crime. At the same time, growing evidence indicates that immigration is an ethnicity-coded issue that allows for the veiled expression of broader anti-Latino sentiments. Yet little research has examined whether public perceptions of either immigrants or Latinos influence support for police policies and practices that, in the context of crimmigration, may significantly shape immigration enforcement and, more broadly, may contribute to the subordination of Latinos. The current study addresses this research question.

Methods

The study draws on data from a recent nationally representative telephone survey and employs multivariate regression methods to evaluate whether perceptions of Latino economic and political threat are associated with support for granting police greater latitude in stopping, searching, and using force against suspects.

Results

This study provides the first evidence that, at least among Whites, perceived Latino threat is positively associated with support for expanding police investigative powers, especially the power to stop suspects based only on the way they look.

Conclusions

The results suggest that by increasing public support for aggressive policing, or, at minimum, by reducing opposition to discriminatory social controls such as police profiling, Latino threat perceptions may increase the political attractiveness and viability of crimmigration as a “solution” to the “Latino problem.”

     

Perceptions of Gender Bias in the Promotional Process of a Detention Staff

With growing numbers of female staff in correctional settings, issues relating to promotional fairness are certain to occur. Historically, female detention staff held perceptions of being discriminated against in the promotional process due to gender biases. However, there is almost no recent examination of these perceptions. The current study addresses this shortcoming in the literature by using a sample of 362 sworn detention deputies ranked Sergeant and below at a large southern-central United States jail. Contrary to the data from a generation ago, more male detention staff perceive gender biases in the promotional process than females, and report that promotional decisions are based on arbitrary and informal factors. Women are more likely to perceive promotions to be fair and based on merit. Results are discussed in relation to two theoretical perspectives: the importation-differential experiences model, and the work-role prisonization model.