什么保护联邦统计机构的自主权?对保护美国官方统计数据独立性和客观性的现行程序的评估

IF 1.5 Q2 SOCIAL SCIENCES, MATHEMATICAL METHODS Statistics and Public Policy Pub Date : 2023-03-10 DOI:10.1080/2330443x.2023.2188062
C. Citro, Jonathan Auerbach, Katherine Smith Evans, E. Groshen, J. Landefeld, J. Mulrow, Tom Petska, Steve Pierson, N. Potok, C. Rothwell, John Thompson, James L. Woodworth, Edward Wu
{"title":"什么保护联邦统计机构的自主权?对保护美国官方统计数据独立性和客观性的现行程序的评估","authors":"C. Citro, Jonathan Auerbach, Katherine Smith Evans, E. Groshen, J. Landefeld, J. Mulrow, Tom Petska, Steve Pierson, N. Potok, C. Rothwell, John Thompson, James L. Woodworth, Edward Wu","doi":"10.1080/2330443x.2023.2188062","DOIUrl":null,"url":null,"abstract":"The Abstract We assess the professional autonomy of the 13 principal U.S. federal statistical agencies. We define six components or measures of such autonomy and evaluate each of the 13 principal statistical agencies according to each measure. Our assessment yields three main findings: 1. Challenges to the objectivity, credibility, and utility of federal statistics arise largely as a consequence of insufficient autonomy. 2. There is remarkable variation in autonomy protections and a surprising lack of statutory protections for many agencies for many of the proposed measures. 3. Many existing autonomy rules and guidelines are weakened by unclear or unactionable","PeriodicalId":43397,"journal":{"name":"Statistics and Public Policy","volume":" ","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"What Protects the Autonomy of the Federal Statistical Agencies? An Assessment of the Procedures in Place to Protect the Independence and Objectivity of Official U.S. Statistics\",\"authors\":\"C. Citro, Jonathan Auerbach, Katherine Smith Evans, E. Groshen, J. Landefeld, J. Mulrow, Tom Petska, Steve Pierson, N. Potok, C. Rothwell, John Thompson, James L. Woodworth, Edward Wu\",\"doi\":\"10.1080/2330443x.2023.2188062\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Abstract We assess the professional autonomy of the 13 principal U.S. federal statistical agencies. We define six components or measures of such autonomy and evaluate each of the 13 principal statistical agencies according to each measure. Our assessment yields three main findings: 1. Challenges to the objectivity, credibility, and utility of federal statistics arise largely as a consequence of insufficient autonomy. 2. There is remarkable variation in autonomy protections and a surprising lack of statutory protections for many agencies for many of the proposed measures. 3. Many existing autonomy rules and guidelines are weakened by unclear or unactionable\",\"PeriodicalId\":43397,\"journal\":{\"name\":\"Statistics and Public Policy\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-03-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistics and Public Policy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/2330443x.2023.2188062\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"SOCIAL SCIENCES, MATHEMATICAL METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics and Public Policy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/2330443x.2023.2188062","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SOCIAL SCIENCES, MATHEMATICAL METHODS","Score":null,"Total":0}
引用次数: 2

摘要

摘要我们评估了美国13个主要联邦统计机构的专业自主权。我们定义了这种自主权的六个组成部分或衡量标准,并根据每个衡量标准对13个主要统计机构中的每一个进行评估。我们的评估得出了三个主要结论:1。联邦统计数据的客观性、可信度和实用性面临挑战,主要是由于自主权不足。2.在自治保护方面存在显著差异,许多拟议措施中许多机构缺乏法定保护,这令人惊讶。3.许多现有的自治规则和指导方针因不明确或无法实施而被削弱
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
What Protects the Autonomy of the Federal Statistical Agencies? An Assessment of the Procedures in Place to Protect the Independence and Objectivity of Official U.S. Statistics
The Abstract We assess the professional autonomy of the 13 principal U.S. federal statistical agencies. We define six components or measures of such autonomy and evaluate each of the 13 principal statistical agencies according to each measure. Our assessment yields three main findings: 1. Challenges to the objectivity, credibility, and utility of federal statistics arise largely as a consequence of insufficient autonomy. 2. There is remarkable variation in autonomy protections and a surprising lack of statutory protections for many agencies for many of the proposed measures. 3. Many existing autonomy rules and guidelines are weakened by unclear or unactionable
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Statistics and Public Policy
Statistics and Public Policy SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
3.20
自引率
6.20%
发文量
13
审稿时长
32 weeks
期刊最新文献
State-Building through Public Land Disposal? An Application of Matrix Completion for Counterfactual Prediction Clusters of Jail Incarcerations in US Counties: 2010-2018 Comment on ‘What protects the autonomy of the Federal Statistics Agencies? An Assessment of the Procedures in Place That Protect the Independence and Objectivity of Official Statistics” by Pierson et al. On Coping in a Non-Binary World: Rejoinder to Biedermann and Kotsoglou Commentary on “Three-Way ROCs for Forensic Decision Making” by Nicholas Scurich and Richard S. John (in: Statistics and Public Policy)
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1