Governing-by-the numbers – Résumé after one and a half years

Radermacher WJ . Governing-by-the-numbers – reflections on the future of official statistics in a digital and globalised society. Statistical Journal of the IAOS. 2019; 35: 519-37.

Meyer R Madrigal AC . Why the Pandemic Experts Failed – We’re still thinking about pandemic data in the wrong ways. The Atlantic. 2021 March 15, 2021; Sect. Science.

Radermacher WJ . Medium [Internet]. Policy D, ed: Medium. 2021. [cited 2021]. Available from: https://medium.com/data-policy/official-statistics-language-for-public-discourse-part-1-294d31e56b6e.

Radermacher WJ . Medium [Internet]. Policy D, ed: Medium. 2021. [cited 2021]. Available from: https://medium.com/data-policy/official-statistics-language-for-public-discourse-part-2-b9e912621523.

Rancourt E . The scientific approach as a transparency enabler throughout the data lifecycle. Statistical Journal of the IAOS. 2019; 35(4): 549-58.

Alleva G Baldacci E Falorsi PD . Methodological, technological and design challenges in the new multisource statistics ecosystem. Statistical Journal of the IAOS. 2021; 37: 245-54.

Cook L . Evidence, accountability and legitimacy: the oversight of child welfare services. Statistical Journal of the IAOS. 2020; 36(2): 365-73.

Lehtonen M . The multiple faces of trust in statistics and indicators: a case for healthy mistrust and distrust. Statistical Journal of the IAOS. 2019; 35(4): 539-48.

Radermacher WJ . Guidelines on indicator methodology: a mission impossible? Statistical Journal of the IAOS. 2021; 37: 205-17.

Kenett RS Maggino F . Techniques for analyzing and presenting official statistics indicators. Statistical Journal of the IAOS. 2021; 36(2).

Umbach G . Of numbers, narratives and challenges: data as evidence in 21st century policy-making. Statistical Journal of the IAOS. 2020; 36: 1043-55.

Bartl W Papilloud C . Measuring “equivalent living conditions”? The use of indicators in german federal spatial planning. Statistical Journal of the IAOS. 2020; 36(2): 375-99.

Prutsch MJ . Science, numbers and politics in a “post-truth” world. Statistical Journal of the IAOS. 2020; 36: 1035-41.

Diaz-Bone R Horvath K . Official statistics, big data and civil society. Introducing the approach of “economics of convention” for understanding the rise of new data worlds and their implications. Statistical Journal of the IAOS. 2021; 37: 219-28.

König A Pickar K Stankiewicz J Hondrila K . Can citizen science complement official data sources that serve as evidence-base for policies and practice to improve water quality? Statistical Journal of the IAOS. 2021; 37: 189-204.

Carranza-Torres JA . How can traditional statistical relationships be redefined through citizen to government partnerships? Statistical Journal of the IAOS. 2021; 37: 229-43.

Pullinger J . Trust in official statistics and why it matters’. Statistical Journal of the IAOS. 2020; 36(2): 343-6.

Habermann H Louis T . Can the fundamental principles of official statistics and the political process co-exist? Statistical Journal of the IAOS. 2020; 36(2): 347-53.

Prévost J-G . Past, present and future of canadian statistics. Statistical Journal of the IAOS. 2020; 36(2): 355-63.

Bodin J-L . A view on 50 years of life of the ISI: with a focus on ISI relations with official statistics. Statistical Journal of the IAOS. 2020; 36(2): 303-8.

Radermacher WJ . Governing by the numbers – editorial. Statistical Journal of the IAOS. 2020; 36(2): 341-2.

Radermacher WJ . Governing by the numbers – editorial. Statistical Journal of the IAOS. 2020; 36(4): 1033-4.

Radermacher WJ . Governing by the numbers. Statistical Journal of the IAOS. 2021; 37: 185-7.

Ammicht Quinn R . Artificial intelligence and the role of ethics. Statistical Journal of the IAOS. 2021; 37: 75-7.

Open Data Policy Lab. ,The Third Wave of Open Data Toolkit, New York: TheGovLab – NYU Tandon School of Engineering; 2021.

The World Bank. World Development Report 2021 – Data for Better Lives. Washington D.C.: World Bank Group; 2021.

Davies W . How statistics lost their power – and why we should fear what comes next. The Guardian. 2017.

Dang H-AH Pullinger J Serajuddin U Stacy B . Statistical Performance Indicators and Index – A New Tool to Measure Country Statistical Capacity. Washington D.C.: World Bank Group; 2021.

He X Lin X . Challenges and Opportunities in Statistics and Data Science: Ten Research Areas. Harvard Data Science Review [Internet] [Internet]. 2020 2021 Apr 08. Available from: https://hdsr.mitpress.mit.edu/pub/da99kl2q.

MacDonald AL . Of science and statistics: the scientific basis of the census. Statistical Journal of the IAOS. 2020; 36: 17-34.

Porter TM . Trust in numbers: the pursuit of objectivity in science and public life. Princeton, N.J.; Chichester: Princeton University Press; 1995.

Grohmann H . Vom theoretischen Konstrukt zum statistischen Begriff – Das Adäquationsproblem. Allgemeines Statistisches Archiv. 1985; Allg. Statist. Archiv 69: 1-15.

Desrosières A . The Politics of Large Numbers – A History of Statistical Reasoning. Cambridge Massachusetts: Harvard University Press; 1998.

Diaz-Bone R . Convention theory, classification and quantification. Historical Social Research. 2016; 41(2): 48-71.

Box GEP . Science and Statistics. Journal of the American Statistical Association. 1976; 71(356 (Dec., 1976)): 791-9.

Radermacher WJ . Official Statistics 4.0 – Verified Facts for People in the 21st Century. Heidelberg: Springer Nature Switzerland AG; imprint Springer; 2020.

von der Lippe P , ed. The political role of official statistics in the former German Democratic Republic. ISI World Statistics Congress 2003; 2003; Berlin.

Seltzer W . Politics and Statistics: Independence, Dependence, or Interaction? In: Analysis UDoEaSIaP, editor. New York: UN; 1994.

Pullinger J . Misuse of statistics: time to speak out. Statistical Journal of the IAOS. 2021; 37: 79-84.

Georgiou AV . The manipulation of official statistics as corruption and ways of understanding it. Statistical Journal of the IAOS. 2021; 37: 85-105.

O’Connor M Faucheux S Gans Combe C Petousi V . Responsibility within without: the challenges of misconduct and quality assurance in scientific research. 2018.

Pemstein D Marquardt KL Tzelgov E Wang Y-t Medzihorsky J Krusell J , et al. Variable Analysis for Cross-National and Cross-Temporal Expert-Coded Data. V-Dem Institute DoPS, University of Gothenburg, editor. Gothenburg: University of Gothenburg; 2019. 34 p.

Schüller K . Future Skills: a Framework for Data Literacy. Working Paper No. 53. Berlin: Hochschulforum Digitalisierung; 2020 July 2020.