U.S. agencies with responsibilities for enforcing equal employment opportunity laws have long relied on detailed information that is obtained from employers on employment in job groups by gender and race/ethnicity for identifying the possibility of discriminatory practices. The U.S. Equal Employment Opportunity Commission (EEOC), the Office of Federal Contract Compliance programs of the U.S. Department of Labor, and the Civil Rights Division of the U.S. Department of Justice have developed processes that use these employment data as well as other sources of information to target employers for further investigation and to perform statistical analysis that is used in enforcing the anti-discrimination laws. The limited data from employers do not include (with a few exceptions) the ongoing measurement of possible discrimination in compensation. The proposed Paycheck Fairness Act of 2009 would have required EEOC to issue regulations mandating that employers provide the EEOC with information on pay by the race, gender, and national origin of employees. The legislation was not enacted. If the legislation had become law, the EEOC would have been required to confront issues regarding currently available and potential data sources, methodological requirements, and appropriate statistical techniques for the measurement and collection of employer pay data. The panel concludes that the collection of earnings data would be a significant undertaking for the EEOC and that there might be an increased reporting burden on some employers. Currently, there is no clearly articulated vision of how the data on wages could be used in the conduct of the enforcement responsibilities of the relevant agencies. Collecting Compensation Data from Employers gives recommendations for targeting employers for investigation regarding their compliance with antidiscrimination laws.
U.S. agencies with responsibilities for enforcing equal employment opportunity laws have long relied on detailed information that is obtained from employers on employment in job groups by gender and race/ethnicity for identifying the possibility of discriminatory practices. The U.S. Equal Employment Opportunity Commission (EEOC), the Office of Federal Contract Compliance programs of the U.S. Department of Labor, and the Civil Rights Division of the U.S. Department of Justice have developed processes that use these employment data as well as other sources of information to target employers for further investigation and to perform statistical analysis that is used in enforcing the anti-discrimination laws. The limited data from employers do not include (with a few exceptions) the ongoing measurement of possible discrimination in compensation. The proposed Paycheck Fairness Act of 2009 would have required EEOC to issue regulations mandating that employers provide the EEOC with information on pay by the race, gender, and national origin of employees. The legislation was not enacted. If the legislation had become law, the EEOC would have been required to confront issues regarding currently available and potential data sources, methodological requirements, and appropriate statistical techniques for the measurement and collection of employer pay data. The panel concludes that the collection of earnings data would be a significant undertaking for the EEOC and that there might be an increased reporting burden on some employers. Currently, there is no clearly articulated vision of how the data on wages could be used in the conduct of the enforcement responsibilities of the relevant agencies. Collecting Compensation Data from Employers gives recommendations for targeting employers for investigation regarding their compliance with antidiscrimination laws.
The National Science Foundation (NSF) has long collected information on the number and characteristics of individuals with education or employment in science and engineering and related fields in the United States. An important motivation for this effort is to fulfill a congressional mandate to monitor the status of women and minorities in the science and engineering workforce. Consequently, many statistics are calculated by race or ethnicity, gender, and disability status. For more than 25 years, NSF obtained a sample frame for identifying the target population for information it gathered from the list of respondents to the decennial census long-form who indicated that they had earned a bachelors or higher degree. The probability that an individual was sampled from this list was dependent on both demographic and employment characteristics. But, the source for the sample frame will no longer be available because the census long-form is being replaced as of the 2010 census with the continuous collection of detailed demographic and other information in the new American Community Survey (ACS). At the request of NSF's Science Resources Statistics Division, the Committee on National Statistics of the National Research Council formed a panel to conduct a workshop and study the issues involved in replacing the decennial census long-form sample with a sample from the ACS to serve as the frame for the information the NSF gathers. The workshop had the specific objective of identifying issues for the collection of field of degree information on the ACS with regard to goals, content, statistical methodology, data quality, and data products.
The National Science Foundation's National Center for Science and Engineering Statistics (NCSES), one of the nation's principal statistical agencies, is charged to collect, acquire, analyze, report, and disseminate statistical data related to the science and engineering enterprise in the United States and other nations that is relevant and useful to practitioners, researchers, policymakers, and to the public. NCSES data, based primarily on several flagship surveys, have become the major evidence base for American science and technology policy, and the agency is well respected globally for these data. This report assesses and provides guidance on NCSES's approach to measuring the science and engineering workforce population in the United States. It also proposes a framework for measuring the science and engineering workforce in the next decade and beyond, with flexibility to examine emerging issues related to this unique population while at the same time allowing for stability in the estimation of key trends
Beginning in 2006, the Census Bureau embarked on a program to reengineer the Survey of Income and Program Participation (SIPP) to reduce its costs and improve data quality and timeliness. The Bureau also requested the National Academies to consider the advantages and disadvantages of strategies for linking administrative records and survey data, taking account of the accessibility of relevant administrative records, the operational feasibility of linking, the quality and usefulness of the linked data, and the ability to provide access to the linked data while protecting the confidentiality of individual respondents. In response, this volume first examines the history of SIPP and reviews the survey's purpose, value, strengths, and weaknesses. The book examines alternative uses of administrative records in a reengineered SIPP and, finally, considers innovations in SIPP design and data collection, including the proposed use of annual interviews with an event history calendar.
Since the early days of the nation, the federal government has collected information on the revenues, expenditures, and other features of state and local jurisdictions and their operations. Today, these data are collected primarily by the Governments Division of the U.S. Census Bureau, which has conducted a census of governments every 5 years since 1957. The division also manages a program of related annual and quarterly surveys, as well as a comprehensive directory of state and local governments. All of this work is now taking place in an environment of constrained resources, and there have been cutbacks in the availability and dissemination of the data. In this context, State and Local Government Statistics at a Crossroads documents the uses of the state and local data and assesses the quality of the data for those uses. This book provides in-depth consideration of the efficiency of the surveys; the user base; and the timeliness, relevance, and quality of the data series. It also provides valuable background information and analysis and offers suggestions for program improvements. This information will be valuable to policy makers, state and local government workers, government contractors, budget analysts, economists, demographers, and others who rely on these data on government at the state and local levels and have a stake in ensuring that limited resources do not compromise the quality of the data on which they rely.
Since the early days of the nation, the federal government has collected information on the revenues, expenditures, and other features of state and local jurisdictions and their operations. Today, these data are collected primarily by the Governments Division of the U.S. Census Bureau, which has conducted a census of governments every 5 years since 1957. The division also manages a program of related annual and quarterly surveys, as well as a comprehensive directory of state and local governments. All of this work is now taking place in an environment of constrained resources, and there have been cutbacks in the availability and dissemination of the data. In this context, State and Local Government Statistics at a Crossroads documents the uses of the state and local data and assesses the quality of the data for those uses. This book provides in-depth consideration of the efficiency of the surveys; the user base; and the timeliness, relevance, and quality of the data series. It also provides valuable background information and analysis and offers suggestions for program improvements. This information will be valuable to policy makers, state and local government workers, government contractors, budget analysts, economists, demographers, and others who rely on these data on government at the state and local levels and have a stake in ensuring that limited resources do not compromise the quality of the data on which they rely.
Historically, the U.S. national data infrastructure has relied on the operations of the federal statistical system and the data assets that it holds. Throughout the 20th century, federal statistical agencies aggregated survey responses of households and businesses to produce information about the nation and diverse subpopulations. The statistics created from such surveys provide most of what people know about the well-being of society, including health, education, employment, safety, housing, and food security. The surveys also contribute to an infrastructure for empirical social- and economic-sciences research. Research using survey-response data, with strict privacy protections, led to important discoveries about the causes and consequences of important societal challenges and also informed policymakers. Like other infrastructure, people can easily take these essential statistics for granted. Only when they are threatened do people recognize the need to protect them. Toward a 21st Century National Data Infrastructure: Mobilizing Information for the Common Good develops a vision for a new data infrastructure for national statistics and social and economic research in the 21st century. This report describes how the country can improve the statistical information so critical to shaping the nation's future, by mobilizing data assets and blending them with existing survey data.
Widely available, trustworthy government statistics are essential for policy makers and program administrators at all levels of government, for private sector decision makers, for researchers, and for the media and the public. In the United States, principal statistical agencies as well as units and programs in many other agencies produce various key statistics in areas ranging from the science and engineering enterprise to education and economic welfare. Official statistics are often the result of complex data collection, processing, and estimation methods. These methods can be challenging for agencies to document and for users to understand. At the request of the National Center for Science and Engineering Statistics (NCSES), this report studies issues of documentation and archiving of NCSES statistical data products in order to enable NCSES to enhance the transparency and reproducibility of the agency's statistics and facilitate improvement of the statistical program workflow processes of the agency and its contractors. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies also explores how NCSES could work with other federal statistical agencies to facilitate the adoption of currently available documentation and archiving standards and tools.
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