This dataset includes information on how the Counter Threat Lead Development Unit (CTLD) identifies and disrupts state and non-state actors and dismantles transnational criminal enterprises and organizations that threaten the security of the United States through the xploitation of the nation's immigration system.

Since the inception of the Edward Byrne Memorial State and Local Law Enforcement Assistance Program in 1988, a large proportion of formula grant program funds has been allocated by state administrative agencies (SAA) to support multi-jurisdictional drug task forces (MJTFs). MJTFs are a subset of law enforcement task forces that were created in order to target the illegal distribution of drugs at the local and regional levels. While many policymakers, researchers, and practitioners express confidence in the task force approach generally, there remains insufficient understanding of the possible community and organizational impact of individual MJTFs and the kinds of evaluation methodologies that can elicit such information. The goal of this project was to identify several methodologies that could be used by state planning agencies, task forces, and others to assess the work of MJTFs. This project consisted of two surveys that were designed to ascertain the extent to which state administrative agencies (SAAs) and multi-jurisdictional drug task forces (MJTFs) collected various kinds of process and outcome information and conducted evaluations of task forces.

The Prosecutor's Management Information System (PROMIS) is a computer-based information system for public prosecution agencies. PROMIS was initially developed with funds from the United States Law Enforcement Assistance Administration (LEAA) to cope with problems of a large, urban prosecution agency where mass production operations had superceded the traditional practice of a single attorney preparing and prosecuting a given case from inception to final disposition. The combination of massive volumes of cases and assembly-line fragmentation of responsibility and control had created a situation in which one case was indistinguishable from another and the effects of problems at various stages in the assembly line on ultimate case disposition went undetected and uncorrected. One unique feature of PROMIS that addresses these problems is the automated evaluation of cases. Through the application of a uniform set of criteria, PROMIS assigns two numerical ratings to each case: one signifying the gravity of the crimes through the measurement of the amount of harm done to society, and the other signifying the gravity of the prior record of the accused. These ratings make it possible to select the more important cases for intensive, pre-trial preparation and to assure even-handed treatment of cases with similar degrees of gravity. A complementary feature of PROMIS is the automation of reasons for decisions made or actions taken along the assembly line. Reasons for dismissing cases prior to trial on their merits can be related to earlier cycles of postponement for various reasons and the reasoning behind intake and screening decisions. The PROMIS data include information about the defendant, case characteristics and processes, charge, sentencing and continuance processes, and the witness/victims involved in the case. PROMIS was first used in 1971 in the United States Attorney's Office for the District of Columbia. To enhance the ability to transfer the concepts and software to other communities, LEAA awarded a grant to the Institute for Law and Social Research (INSLAW) in Washington, DC. The St. Louis PROMIS data collection is a product of this grant.

The Prosecutor's Management Information System (PROMIS) is a computer-based information system for public prosecution agencies. PROMIS was initially developed with funds from the United States Law Enforcement Assistance Administration (LEAA) to cope with problems of a large, urban prosecution agency where mass production operations had superseded the traditional practice of a single attorney preparing and prosecuting a given case from inception to final disposition. The combination of massive volumes of cases and assembly-line fragmentation of responsibility and control had created a situation in which one case was indistinguishable from another and the effects of problems at various stages in the assembly line on ultimate case disposition went undetected and uncorrected. One unique feature of PROMIS that addresses these problems is the automated evaluation of cases. Through the application of a uniform set of criteria, PROMIS assigns two numerical ratings to each case: one signifying the gravity of the crimes through the measurement of the amount of harm done to society, and the other signifying the gravity of the prior record of the accused. These ratings make it possible to select the more important cases for intensive, pre-trial preparation and to assure even-handed treatment of cases with similar degrees of gravity. A complementary feature of PROMIS is the automation of reasons for decisions made or actions taken along the assembly line. Reasons for dismissing cases prior to trial on their merits can be related to earlier cycles of postponement for various reasons and the reasoning behind intake and screening decisions. The PROMIS data include information about the defendant, case characteristics and processes, charge, sentencing and continuance processes, and the witnesses/victims involved in the case. PROMIS was first used in 1971 in the United States Attorney's Office for the District of Columbia. To enhance the ability to transfer the concepts and software to other communities, LEAA awarded a grant to the Institute for Law xand Social Research (INSLAW) in Washington, DC. The Rhode Island PROMIS data collection is a product of this grant.