Protecting and Accessing Data from the Survey of Earned Doctorates


Book Description

The Survey of Earned Doctorates (SED) collects data on the number and characteristics of individuals receiving research doctoral degrees from all accredited U.S. institutions. The results of this annual survey are used to assess characteristics and trends in doctorate education and degrees. This information is vital for education and labor force planners and researchers in the federal government and in academia. To protect the confidentiality of data, new and more stringent procedures were implemented for the 2006 SED data released in 2007. These procedures suppressed many previously published data elements. The organizations and institutions that had previously relied on these data to assess progress in measure of achievement and equality suddenly found themselves without a yardstick with which to measure progress. Several initiatives were taken to address these concerns, including the workshop summarized in this volume. The goal of the workshop was to address the appropriateness of the decisions that SRS made and to help the agency and data users consider future actions that might permit release of useful data while protecting the confidentiality of the survey responses.




Protecting and Accessing Data from the Survey of Earned Doctorates


Book Description

The Survey of Earned Doctorates (SED) collects data on the number and characteristics of individuals receiving research doctoral degrees from all accredited U.S. institutions. The results of this annual survey are used to assess characteristics and trends in doctorate education and degrees. This information is vital for education and labor force planners and researchers in the federal government and in academia. To protect the confidentiality of data, new and more stringent procedures were implemented for the 2006 SED data released in 2007. These procedures suppressed many previously published data elements. The organizations and institutions that had previously relied on these data to assess progress in measure of achievement and equality suddenly found themselves without a yardstick with which to measure progress. Several initiatives were taken to address these concerns, including the workshop summarized in this volume. The goal of the workshop was to address the appropriateness of the decisions that SRS made and to help the agency and data users consider future actions that might permit release of useful data while protecting the confidentiality of the survey responses.




Principles and Practices for a Federal Statistical Agency


Book Description

Publicly available statistics from government agencies that are credible, relevant, accurate, and timely are essential for policy makers, individuals, households, businesses, academic institutions, and other organizations to make informed decisions. Even more, the effective operation of a democratic system of government depends on the unhindered flow of statistical information to its citizens. In the United States, federal statistical agencies in cabinet departments and independent agencies are the governmental units whose principal function is to compile, analyze, and disseminate information for such statistical purposes as describing population characteristics and trends, planning and monitoring programs, and conducting research and evaluation. The work of these agencies is coordinated by the U.S. Office of Management and Budget. Statistical agencies may acquire information not only from surveys or censuses of people and organizations, but also from such sources as government administrative records, private-sector datasets, and Internet sources that are judged of suitable quality and relevance for statistical use. They may conduct analyses, but they do not advocate policies or take partisan positions. Statistical purposes for which they provide information relate to descriptions of groups and exclude any interest in or identification of an individual person, institution, or economic unit. Four principles are fundamental for a federal statistical agency: relevance to policy issues, credibility among data users, trust among data providers, and independence from political and other undue external influence. Principles and Practices for a Federal Statistical Agency: Fifth Edition explains these four principles in detail.




Principles and Practices for a Federal Statistical Agency


Book Description

Publicly available statistics from government agencies that are credible, relevant, accurate, and timely are essential for policy makers, individuals, households, businesses, academic institutions, and other organizations to make informed decisions. Even more, the effective operation of a democratic system of government depends on the unhindered flow of statistical information to its citizens. In the United States, federal statistical agencies in cabinet departments and independent agencies are the governmental units whose principal function is to compile, analyze, and disseminate information for such statistical purposes as describing population characteristics and trends, planning and monitoring programs, and conducting research and evaluation. The work of these agencies is coordinated by the U.S. Office of Management and Budget. Statistical agencies may acquire information not only from surveys or censuses of people and organizations, but also from such sources as government administrative records, private-sector datasets, and Internet sources that are judged of suitable quality and relevance for statistical use. They may conduct analyses, but they do not advocate policies or take partisan positions. Statistical purposes for which they provide information relate to descriptions of groups and exclude any interest in or identification of an individual person, institution, or economic unit. Four principles are fundamental for a federal statistical agency: relevance to policy issues, credibility among data users, trust among data providers, and independence from political and other undue external influence. Principles and Practices for a Federal Statistical Agency: Sixth Edition presents and comments on these principles as they've been impacted by changes in laws, regulations, and other aspects of the environment of federal statistical agencies over the past 4 years.




Increasing Diversity in Doctoral Education: Implications for Theory and Practice


Book Description

Diversity is defined as those numerous elements of difference between groups of people that play significant roles in social institutions, including (but not limited to) race and ethnicity, gender, socioeconomic class, sexual orientation, and culture. Since doctoral degree recipients go on to assume roles as faculty and educators, diversity in doctoral programs is significant. By supporting graduate diversity across the academic disciplines, universities ensure that the nation’s intellectual capacities and opportunities are fully realized. The authors consider diversity broadly from multiple perspectives, from race and ethnicity to institutional type, academic discipline, and national origin. They demonstrate how diversity operates through these venues and definitions, and hope to stimulate a conversation about a key aspect of American higher education. This volume is the 163rd volume of the Jossey-Bass quarterly report series New Directions for Higher Education. Addressed to presidents, vice presidents, deans, and other higher education decision makers on all kinds of campuses, New Directions for Higher Education provides timely information and authoritative advice about major issues and administrative problems confronting every institution.




Project Summaries,


Book Description




Privacy in Statistical Databases


Book Description

This book constitutes the refereed proceedings of the International Conference on Privacy in Statistical Databases, PSD 2020, held in Tarragona, Spain, in September 2020 under the sponsorship of the UNESCO Chair in Data Privacy. The 25 revised full papers presented were carefully reviewed and selected from 49 submissions. The papers are organized into the following topics: privacy models; microdata protection; protection of statistical tables; protection of interactive and mobility databases; record linkage and alternative methods; synthetic data; data quality; and case studies. The Chapter “Explaining recurrent machine learning models: integral privacy revisited” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.




Communicating Science and Engineering Data in the Information Age


Book Description

The National Center for Science and Engineering Statistics (NCSES) of the National Science Foundation (NSF) communicates its science and engineering (S&E) information to data users in a very fluid environment that is undergoing modernization at a pace at which data producer dissemination practices, protocols, and technologies, on one hand, and user demands and capabilities, on the other, are changing faster than the agency has been able to accommodate. NCSES asked the Committee on National Statistics and the Computer Science and Telecommunications Board of the National Research Council to form a panel to review the NCSES communication and dissemination program that is concerned with the collection and distribution of information on science and engineering and to recommend future directions for the program. Communicating Science and Engineering Data in the Information Age includes recommendations to improve NCSES's dissemination program and improve data user engagement. This report includes recommendations such as NCSES's transition to a dissemination framework that emphasizes database management rather than data presentation, and that NCSES analyze the results of its initial online consumer survey and refine it over time. The implementation of the report's recommendations should be undertaken within an overall framework that accords priority to the basic quality of the data and the fundamentals of dissemination, then to significant enhancements that are achievable in the short term, while laying the groundwork for other long-term improvements.




The Production of Knowledge


Book Description

A wide-ranging discussion of factors that impede the cumulation of knowledge in the social sciences, including problems of transparency, replication, and reliability. Rather than focusing on individual studies or methods, this book examines how collective institutions and practices have (often unintended) impacts on the production of knowledge.