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The U.S. Department of Labor’s (DOL) Employee Benefits Security Administration (EBSA) seeks to identify approaches to measure the impact of its work. The objectives of EBSA and CEO for this Health Outcomes Metrics project were to better understand the current landscape, best practices, and data sources related to approaches that federal and state agencies and the insurance industry use to estimate the impacts of their health-related enforcement actions/interventions.
In 2023, the Chief Evaluation Office (CEO) partnered with the Employment and Training Administration (ETA) to fund contractor Westat Insight to explore approaches to measure and increase equity in ETA’s discretionary grantmaking programs under the Administrative Data Research and Analysis portfolio of studies.
In 2022, the Chief Evaluation Office (CEO) funded contractor Westat Insight (formerly Insight Policy Research) to conduct the Vulnerable Populations Study. Using secondary data analysis, this study aims to demonstrate the value of leveraging publicly available survey data to analyze the changing demographic landscapes of vulnerable populations impacted by labor policies and programs.
In 2022, the Chief Evaluation Office (CEO) partnered with the Veteran Employment and Training Service (VETS) to fund contractor Westat to conduct the 2024 Veteran Employment Data Catalog under the Administrative Data Research and Analysis portfolio of studies. The data catalog aims to assist researchers by identifying existing public and restricted datasets related to the post-separation civilian transition, racial equity, and support for underserved veteran communities.
The 2024 Veteran Employment Data Catalog is a document-based catalog of existing datasets that could be used to answer research questions related to veterans’ employment outcomes. The U.S. Department of Labor’s (DOL) Chief Evaluation Office (CEO) collaborated with the Veterans’ Employment and Training Services (VETS) to commission Insight Policy Research (now Westat) to identify both public and restricted datasets that align with topic areas derived from VETS’ mission.
In 2022, the Chief Evaluation Office (CEO) funded contractor Westat Insight to conduct the Vulnerable Populations Study to highlight examples of analyses that researchers and policymakers can conduct using publicly available population surveys. This report underscores the value of leveraging publicly available survey data to analyze the changing demographic landscapes of populations impacted by labor policies and programs.
The Chief Evaluation Office of the U.S. Department of Labor (DOL CEO) is committed to using innovative tools to meet the Department’s research, evaluation, and data analytics needs. In December 2021, DOL CEO commissioned the Westat Insight and American Institutes for Research® (AIR®) study team to explore potential opportunities to use machine learning methods to facilitate the automated data collection of labor-relevant data.
The report synthesizes findings from third-party evaluator (TPE)-conducted implementation evaluations and subsequent interim reports, supplemented by submitted quarterly narrative reports (QNRs) from March 2023. The synthesis aims to provide an overarching description of the first round of SCC (SCC1) grantees’ progress in implementing their workforce development and career pathways programming and highlight promising practices, implementation barriers, and lessons learned across the grantees.
In 2014, the Chief Evaluation Office (CEO) partnered with the Office of Federal Contract Compliance Programs (OFCCP) and funded contractor Abt Associates to conduct the OFCCP Community-Based Organization Outreach Evaluation under the Advancing Behavioral Interventions in Labor Programs portfolio of studies.
In 2014, the Chief Evaluation Office (CEO) contracted with Mathematica Policy Research and ideas42 to examine whether insights from behavioral science can be used to improve outcomes in the U.S. Department of Labor (DOL) programs under the Advancing Behavioral Interventions in Labor Programs portfolio of studies.