Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A Chronicle of the Application of Differential Privacy to the 2020 Census
V. Joseph Hotz, Joseph J. Salvo
Harvard data science review (2022)
Open Access | Times Cited: 13

Showing 13 citing articles:

Evaluating bias and noise induced by the U.S. Census Bureau’s privacy protection methods
Christopher T Kenny, Cory McCartan, Shiro Kuriwaki, et al.
Science Advances (2024) Vol. 10, Iss. 18
Open Access | Times Cited: 10
Protecting Vulnerable Respondents: A Critical Analysis of the Privacy-Preserving Methods of the 2010 and 2020 Decennial Census
Krishnamurty Muralidhar, Josep Domingo‐Ferrer, David Sánchez, et al.
Population Research and Policy Review (2025) Vol. 44, Iss. 1
Open Access | Times Cited: 1
Transparent Privacy is Principled Privacy
Ruobin Gong
Harvard data science review (2022), Iss. Special Issue 2
Open Access | Times Cited: 17
Comment: The Essential Role of Policy Evaluation for the 2020 Census DisclosureAvoidance System
Christopher Kenny, Shiro Kuriwaki, Cory McCartan, et al.
Harvard data science review (2023), Iss. Special Issue 2
Open Access | Times Cited: 8
General Inferential Limits Under Differential and Pufferfish Privacy
James Bailie, Ruobin Gong
International Journal of Approximate Reasoning (2024) Vol. 172, pp. 109242-109242
Open Access | Times Cited: 1
Statistical Imaginaries, State Legitimacy: Grappling With the Arrangements Underpinning Quantification in the U.S. Census
Jayshree Sarathy, danah boyd
Critical Sociology (2024)
Closed Access | Times Cited: 1
Harnessing the Known Unknowns: Differential Privacy and the 2020 Census
Ruobin Gong, Erica L. Groshen, Salil Vadhan
Harvard data science review (2022)
Open Access | Times Cited: 6
Evaluating Bias and Noise Induced by the U.S. Census Bureau's Privacy Protection Methods
Christopher T Kenny, Shiro Kuriwaki, Cory McCartan, et al.
arXiv (Cornell University) (2023)
Open Access | Times Cited: 3
The global politics of census taking in the 2020 census round
Walter Bartl, Alberto Veira-Ramos, Christian Suter
Routledge eBooks (2024), pp. 1-46
Open Access
Equitable differential privacy
Vasundhara Kaul, Tamalika Mukherjee
Frontiers in Big Data (2024) Vol. 7
Open Access
The Census
Justin Levitt
Oxford University Press eBooks (2024), pp. 665-692
Closed Access
Technical Comment on “Policy impacts of statistical uncertainty and privacy”
Yifan Cui, Ruobin Gong, Jan Hannig, et al.
Science (2023) Vol. 380, Iss. 6648
Closed Access
An Example of Combining Expert Judgment and Small Area Projection Methods: Forecasting for Water District Needs
David A. Swanson, Tom Bryan, Mark Hattendorf, et al.
Spatial Demography (2023) Vol. 11, Iss. 2
Closed Access
Page 1

Scroll to top