Inventory of U.S. Public Data Sources to Measure the Socioeconomic Impact of Experiencing Interpersonal Violence.

Introduction: There is limited recent information regarding the impact of interpersonal violence on an individual's non-health-related experiences and attainment, including criminal activity, education, employment, family status, housing, income, quality of life, or wealth. This study aimed to identify publicly available representative data sources to measure the socioeconomic impact of experiencing interpersonal violence in the U.S. Methods: In 2022, the authors reviewed data sources indexed in Data.gov, the Inter-university Consortium for Political and Social Research data archive, and the U.S. Census Bureau's Federal Statistical Research Data Center network to identify sources that reported both nonfatal violence exposure and socioeconomic status-or data sources linking opportunities to achieve both measures-over time (i.e., longitudinal/repeated cross-sections) at the individual level. Relevant data sources were characterized in terms of data type (e.g., survey), violence measure type (e.g., intimate partner violence), socioeconomic measure type (e.g., income), data years, and geographic coverage. Results: Sixteen data sources were identified. Adverse childhood experiences, intimate partner violence, and sexual violence were the most common types of violence faced. Income, education, and family status were the most common socioeconomic measures. Linked administrative data offered the broadest and the most in-depth analytical opportunities. Conclusions: Currently, linked administrative data appears to offer the most comprehensive opportunities to examine the long-term impact of violence on individuals' livelihoods. This type of data infrastructure may provide cost-effective research opportunities to better understand the elements of the economic burden of violence and improve targeting of prevention strategies.

Hierarchical approaches to Text-based Offense Classification.

Researchers working with administrative crime data often must classify offense narratives into a common scheme for analysis purposes. No comprehensive standard currently exists, nor is there a mapping tool to transform raw descriptions into offense types. This paper introduces a new schema, the Uniform Crime Classification Standard (UCCS), and the Text-based Offense Classification (TOC) tool to address these shortcomings. The UCCS schema draws from existing efforts, aiming to better reflect offense severity and improve type disambiguation. The TOC tool is a machine learning algorithm that uses a hierarchical, multilayer perceptron classification framework, built on 313,209 hand-coded offense descriptions from 24 states, to translate raw descriptions into UCCS codes. We test how variations in data processing and modeling approaches affect recall, precision, and F1 scores to assess their relative influence on model performance. The code scheme and classification tool are collaborations between Measures for Justice and the Criminal Justice Administrative Records System.

The Criminal Justice Administrative Records System: A next-generation research data platform.

The Criminal Justice Administrative Records System (CJARS), a joint project of the U.S. Census Bureau and the University of Michigan, is a nationally integrated data infrastructure project designed to transform research and policymaking on the United States criminal justice system. At the University of Michigan, CJARS collects longitudinal electronic records from criminal justice agencies and harmonizes these records to track a criminal episode across all stages of the system. At the U.S. Census Bureau, harmonized criminal justice records can be linked anonymously at the person-level with extensive social, demographic, and economic information from national survey and administrative records.

Effect of Registered Partnership on Labor Earnings and Fertility for Same-Sex Couples: Evidence From Swedish Register Data.

The expansion of legal rights to same-sex couples is a foot in a number of Western countries. The effects of this rollout are not only important in their own right but can also provide a window on the institution of marriage and the rights bundled therein. In this article, using Swedish longitudinal register data covering 1994-2007, we study the impact of the extension of rights to same-sex couples on labor earnings and fertility. In 1994, registered partnership for same-sex couples was introduced, which conferred almost all rights and obligations of marriage--a notable exception being joint legal parenting, by default or election. The latter was added in the 2002 adoption act. We find registered partnership to be important to both gays and lesbians but for different reasons. For gays, resource pooling emerges as the main function of registered partnerships. For lesbians, registered partnership appears to be an important vehicle for family formation, especially after the 2002 adoption act. In contrast to heterosexual couples (included for comparison), we find no evidence of household specialization among lesbians. The lack of specialization is noteworthy given similar fertility effects of registered partnership (after 2002) and the fact that lesbian couples were less assortatively matched (on education) than heterosexual couples--children and unequal earnings power being two factors commonly believed to promote specialization.