OpenAlex Citation Counts

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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:

Testing Causal Theories with Learned Proxies
Dean Knox, Christopher Lucas, Wendy K. Tam Cho
Annual Review of Political Science (2022) Vol. 25, Iss. 1, pp. 419-441
Open Access | Times Cited: 25

Showing 25 citing articles:

Artificial intelligence and illusions of understanding in scientific research
Lisa Messeri, Molly J. Crockett
Nature (2024) Vol. 627, Iss. 8002, pp. 49-58
Closed Access | Times Cited: 148

How to train your stochastic parrot: large language models for political texts
Joseph T. Ornstein, Elise Blasingame, Jake S. Truscott
Political Science Research and Methods (2025), pp. 1-18
Open Access | Times Cited: 2

Risk scores, label bias, everything but the kitchen sink
Michael Zanger-Tishler, Julian Nyarko, Sharad Goel
Science Advances (2024) Vol. 10, Iss. 13
Open Access | Times Cited: 7

“Born for a Storm”: Hard-Right Social Media and Civil Unrest
Daniel Karell, Andrew M. Linke, Edward C. Holland, et al.
American Sociological Review (2023) Vol. 88, Iss. 2, pp. 322-349
Open Access | Times Cited: 20

Political diversity in U.S. police agencies
Bocar Ba, Haosen Ge, Jacob Kaplan, et al.
American Journal of Political Science (2025)
Open Access

Measuring legislators’ ideological position in large chambers using pairwise-comparisons
Christian Breunig, Benjamin Guinaudeau
Political Science Research and Methods (2025), pp. 1-18
Closed Access

When Correlation Is Not Enough: Validating Populism Scores from Supervised Machine-Learning Models
Michael Jankowski, Robert Huber
Political Analysis (2023) Vol. 31, Iss. 4, pp. 591-605
Open Access | Times Cited: 10

Leveraging body-worn camera footage to assess the effects of training on officer communication during traffic stops
Nicholas P. Camp, Rob Voigt, MarYam G Hamedani, et al.
PNAS Nexus (2024) Vol. 3, Iss. 9
Open Access | Times Cited: 3

Estimating Racial Disparities When Race is Not Observed
Cory McCartan, Robin Fisher, Jacob Goldin, et al.
SSRN Electronic Journal (2024)
Open Access | Times Cited: 2

Causal inference with latent outcomes
Lukas F. Stoetzer, Xiang Zhou, Marco R. Steenbergen
American Journal of Political Science (2024)
Open Access | Times Cited: 2

An Introduction to Neural Networks for the Social Sciences
Gechun Lin, Christopher G. Lucas
Oxford University Press eBooks (2023)
Closed Access | Times Cited: 2

Measuring and Modeling Neighborhoods
Cory McCartan, Jacob R. Brown, Kosuke Imai
American Political Science Review (2024) Vol. 118, Iss. 4, pp. 1966-1985
Open Access

Improving Probabilistic Models In Text Classification Via Active Learning
Mitchell Bosley, Saki Kuzushima, Ted Enamorado, et al.
American Political Science Review (2024), pp. 1-18
Open Access

Can Human Reading Validate a Topic Model?
Bolun Zhang, Yimang Zhou, Dai Li
Sociological Methodology (2024)
Closed Access

Hard-Right Social Media and Civil Unrest
Daniel Karell, andrew linke, Edward C. Holland, et al.
(2021)
Open Access | Times Cited: 3

Using Cell-phone Mobility Data to Study Voter Turnout
Masataka Harada, Gaku Ito, Daniel M. Smith
SSRN Electronic Journal (2022)
Closed Access | Times Cited: 2

Evidence on the nature of sectarian animosity from a geographically representative survey of Iraqi and Iranian Shia pilgrims
Fotini Christia, Elizabeth Dekeyser, Dean Knox
Nature Human Behaviour (2022) Vol. 6, Iss. 9, pp. 1226-1233
Closed Access | Times Cited: 1

Causal Inference with Latent Outcomes
Lukas F. Stoetzer, Xiang Zhou, Marco R. Steenbergen
(2022)
Open Access | Times Cited: 1

Measuring and Modeling Neighborhoods
Cory McCartan, Jacob R. Brown, Kosuke Imai
arXiv (Cornell University) (2021)
Open Access | Times Cited: 1

Selecting More Informative Training Sets with Fewer Observations
Aaron Kaufman
Political analysis. (2023) Vol. 32, Iss. 1, pp. 133-139
Open Access

Improving Probabilistic Models in Text Classification via Active Learning
Mitchell Bosley, Saki Kuzushima, Ted Enamorado, et al.
arXiv (Cornell University) (2022)
Open Access

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