Pub Date : 2021-10-28DOI: 10.1162/99608f92.c1237762
Stefan Schweinfest, Ronald Jansen
{"title":"Data Science for Official Statistics: Views of the United Nations Statistics Division","authors":"Stefan Schweinfest, Ronald Jansen","doi":"10.1162/99608f92.c1237762","DOIUrl":"https://doi.org/10.1162/99608f92.c1237762","url":null,"abstract":"","PeriodicalId":250931,"journal":{"name":"Issue 3.4, Fall 2021","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122109348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.1162/99608f92.48466abe
W. Yung
{"title":"The Evolution of Official Statistics in a Changing World","authors":"W. Yung","doi":"10.1162/99608f92.48466abe","DOIUrl":"https://doi.org/10.1162/99608f92.48466abe","url":null,"abstract":"","PeriodicalId":250931,"journal":{"name":"Issue 3.4, Fall 2021","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130489067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.1162/99608f92.f0a7df71
Pip Arnold, Leticia Pérez, Sheri Johnson
Column Editor’s note: This Issue’s "Minding the Future" continues our introduction to the revised GAISE guidelines. Pip Arnold, Leticia Perez, and Sheri Johnson present lesson plans for engaging “Level B” students (roughly middle school age in the US, 10-14 year olds) in data science through the use of photographs. As a nontraditional but still easily understood data format, photographs give this second level of students a window into what modern statistics and data science work looks like. We hope you will find these lessons inspiring in your own classrooms.
{"title":"Using photographs as data sources to tell stories GAISE II, Level B","authors":"Pip Arnold, Leticia Pérez, Sheri Johnson","doi":"10.1162/99608f92.f0a7df71","DOIUrl":"https://doi.org/10.1162/99608f92.f0a7df71","url":null,"abstract":"Column Editor’s note: This Issue’s \"Minding the Future\" continues our introduction to the revised GAISE guidelines. Pip Arnold, Leticia Perez, and Sheri Johnson present lesson plans for engaging “Level B” students (roughly middle school age in the US, 10-14 year olds) in data science through the use of photographs. As a nontraditional but still easily understood data format, photographs give this second level of students a window into what modern statistics and data science work looks like. We hope you will find these lessons inspiring in your own classrooms.","PeriodicalId":250931,"journal":{"name":"Issue 3.4, Fall 2021","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126459299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.1162/99608f92.c28d2a68
N. Fisher
Performance measures permeate our lives, whether or not we are aware of them. They can support or frustrate what we are trying to do, help or hinder enterprises going about their business, encourage or distort behaviors, clarify or confuse purpose. We illustrate some of the consequences of poor performance measurement, explore some of the reasons why poor metrics are in use, and describe a systematic way to look for performance measures in a variety of settings. There are real opportunities and challenges awaiting an inquiring and creative data scientist.
{"title":"Performance Measurement: Issues, Approaches, and Opportunities","authors":"N. Fisher","doi":"10.1162/99608f92.c28d2a68","DOIUrl":"https://doi.org/10.1162/99608f92.c28d2a68","url":null,"abstract":"Performance measures permeate our lives, whether or not we are aware of them. They can support or frustrate what we are trying to do, help or hinder enterprises going about their business, encourage or distort behaviors, clarify or confuse purpose. We illustrate some of the consequences of poor performance measurement, explore some of the reasons why poor metrics are in use, and describe a systematic way to look for performance measures in a variety of settings. There are real opportunities and challenges awaiting an inquiring and creative data scientist.","PeriodicalId":250931,"journal":{"name":"Issue 3.4, Fall 2021","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114773892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.1162/99608f92.591917c6
E. Groshen
Official statistics are a pure public good and a key element of our national data infrastructure. They support our well-being by informing a vast set of public and private decisions. Yet, today they stand at a crossroads in the United States. With new technologies, today’s official statistics could be more relevant, interoperable, granular, and timely. Recent experience during the pandemic clarifies the need for improvement. The agencies could tap the new wealth of non-survey data to accomplish these goals without increasing burdens on survey respondents. They could operate more in sync with each other (to facilitate combining and sharing data) and more independently from politics (to reinforce public trust in their integrity). They could be better protected from defunding and requirements to combine operations with non-statistical agencies. These changes are possible, but not without effort by the statistical system’s stakeholders. The agencies cannot do it alone. The alternative, I fear, is a downward spiral in official statistics. Current funding neglect and erosion of independence threaten to reduce public trust and data quality. Less reliable products would then lead to further cuts and lower response rates, and suppress quality further. Hence the spiral. To secure a promising future for official statistics and avoid the death spiral, the statistical system’s stakeholders must actively advocate changes that include data-sharing legislation, flexible and dependable funding, adopting common data schema, and a modernized, more coordinated statistical system. The statistical and data science communities—including you—have an important role to play in choosing the path ahead.
{"title":"The Future of Official Statistics","authors":"E. Groshen","doi":"10.1162/99608f92.591917c6","DOIUrl":"https://doi.org/10.1162/99608f92.591917c6","url":null,"abstract":"Official statistics are a pure public good and a key element of our national data infrastructure. They support our well-being by informing a vast set of public and private decisions. Yet, today they stand at a crossroads in the United States. With new technologies, today’s official statistics could be more relevant, interoperable, granular, and timely. Recent experience during the pandemic clarifies the need for improvement. The agencies could tap the new wealth of non-survey data to accomplish these goals without increasing burdens on survey respondents. They could operate more in sync with each other (to facilitate combining and sharing data) and more independently from politics (to reinforce public trust in their integrity). They could be better protected from defunding and requirements to combine operations with non-statistical agencies. These changes are possible, but not without effort by the statistical system’s stakeholders. The agencies cannot do it alone. The alternative, I fear, is a downward spiral in official statistics. Current funding neglect and erosion of independence threaten to reduce public trust and data quality. Less reliable products would then lead to further cuts and lower response rates, and suppress quality further. Hence the spiral. To secure a promising future for official statistics and avoid the death spiral, the statistical system’s stakeholders must actively advocate changes that include data-sharing legislation, flexible and dependable funding, adopting common data schema, and a modernized, more coordinated statistical system. The statistical and data science communities—including you—have an important role to play in choosing the path ahead.","PeriodicalId":250931,"journal":{"name":"Issue 3.4, Fall 2021","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125159084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.1162/99608f92.7c172aac
O. Awad
As new data actors arise and data become more accessible, official statistics' role as the primary creator of statistics and distributor of information for policymaking is being tested. A data actor can be any entity involved in production, manipulation, and analysis or dissemination of any type of data. The need for more resources grows. New technologies enable a level of recording, integration, and analysis that have never been possible before. This article addresses National Statistical Offices’ changing role, taking into consideration a lack of investment in data and outdated data, out-of-date legal frameworks and data-access laws, and privacy restrictions.
{"title":"Will Official Statistics Become Obsolete?","authors":"O. Awad","doi":"10.1162/99608f92.7c172aac","DOIUrl":"https://doi.org/10.1162/99608f92.7c172aac","url":null,"abstract":"As new data actors arise and data become more accessible, official statistics' role as the primary creator of statistics and distributor of information for policymaking is being tested. A data actor can be any entity involved in production, manipulation, and analysis or dissemination of any type of data. The need for more resources grows. New technologies enable a level of recording, integration, and analysis that have never been possible before. This article addresses National Statistical Offices’ changing role, taking into consideration a lack of investment in data and outdated data, out-of-date legal frameworks and data-access laws, and privacy restrictions.","PeriodicalId":250931,"journal":{"name":"Issue 3.4, Fall 2021","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127655977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.1162/99608f92.ada7ddb1
J. Pullinger
{"title":"The Future of Federal Statistics: World Statistics Day Webinar—20 OCTOBER 2020","authors":"J. Pullinger","doi":"10.1162/99608f92.ada7ddb1","DOIUrl":"https://doi.org/10.1162/99608f92.ada7ddb1","url":null,"abstract":"","PeriodicalId":250931,"journal":{"name":"Issue 3.4, Fall 2021","volume":"1992 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128613131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.1162/99608f92.d0871196
J. Bailer, Wendy Martinez
{"title":"Official Statistics from the Changing World of Data Science","authors":"J. Bailer, Wendy Martinez","doi":"10.1162/99608f92.d0871196","DOIUrl":"https://doi.org/10.1162/99608f92.d0871196","url":null,"abstract":"","PeriodicalId":250931,"journal":{"name":"Issue 3.4, Fall 2021","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117178654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.1162/99608f92.2617629d
O. Awad, X. Meng, L. Vittert
{"title":"A Conversation with Ola Awad, President, Palestinian Central Bureau of Statistics","authors":"O. Awad, X. Meng, L. Vittert","doi":"10.1162/99608f92.2617629d","DOIUrl":"https://doi.org/10.1162/99608f92.2617629d","url":null,"abstract":"","PeriodicalId":250931,"journal":{"name":"Issue 3.4, Fall 2021","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132464172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.1162/99608f92.d35b59a0
A. Donnelly
Column Editors’ Note: Collecting data from students and schools is one of the prime ways in which people across the globe have come to understand the impact of education. As Andrew Donnelly shows, there is nothing obvious about how to collect or interpret these numbers. By looking at the early statistics collection at the federal level in late nineteenth-century America, he argues that educational data have always been political and politicized. As a “fact-getting device,” American educational statistics served from the start as a basis for larger debates about racial and regional equality, as well as a mechanism for highlighting the success of partisan policies.
{"title":"The Yankee Leviathan Collects Statistics: Federal Education Policy During Reconstruction","authors":"A. Donnelly","doi":"10.1162/99608f92.d35b59a0","DOIUrl":"https://doi.org/10.1162/99608f92.d35b59a0","url":null,"abstract":"Column Editors’ Note: Collecting data from students and schools is one of the prime ways in which people across the globe have come to understand the impact of education. As Andrew Donnelly shows, there is nothing obvious about how to collect or interpret these numbers. By looking at the early statistics collection at the federal level in late nineteenth-century America, he argues that educational data have always been political and politicized. As a “fact-getting device,” American educational statistics served from the start as a basis for larger debates about racial and regional equality, as well as a mechanism for highlighting the success of partisan policies.","PeriodicalId":250931,"journal":{"name":"Issue 3.4, Fall 2021","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116256152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：