Introduction to the GASP Special Issue✩
Volume 22, Issue 3 (2024): Special issue: The Government Advances in Statistical Programming (GASP) 2023 conference, pp. 353–355
Pub. online: 26 August 2024
Type: Editorial
Open Access
Open Access
✩
This paper represents the views of the authors and does not necessarily reflect those of the United States Government or any agency thereof.
Published
26 August 2024
26 August 2024
References
Chen S, Xu C (2024). Predictive mean matching imputation procedure based on machine learning models for complex survey data. Journal of Data Science, 22(3): 456–468. https://doi.org/10.6339/24-JDS1135
Emmet RL, Hunt K, Jennings R, Daniel K, Abreu DA (2024). Evaluating a method for georeferencing agricultural fields. Journal of Data Science, 22(3): 423–435. https://doi.org/10.6339/24-JDS1146
Hadley E, Marcial L, Quattrone W, Bobashev G (2024). Traditional and GenAI text analysis of COVID-19 pandemic trends in hospital community benefits IRS documentation. Journal of Data Science, 22(3): 393–408. https://doi.org/10.6339/24-JDS1144
Knappenberger C (2024). Bringing search to the economic census – the NAPCS classification tool. Journal of Data Science, 22(3): 409–422. https://doi.org/10.6339/24-JDS1147
Preiss AJ, Arbeit CA, Berghammer A, Bollenbacher J, McCarthy JV, Brom MG, et al. (2024). Evaluation of text cluster naming with generative large language models. Journal of Data Science, 22(3): 376–392. https://doi.org/10.6339/24-JDS1149
Sartore L, Chen L, van Wart J, Dau A, Bejleri V (2024). Identifying anomalous data entries in repeated surveys. Journal of Data Science, 22(3): 436–455. https://doi.org/10.6339/24-JDS1136
Shrivastava R, Korkmaz G (2024). Measuring public open-source software in the federal government: An analysis of Code.gov. Journal of Data Science, 22(3): 356–375. https://doi.org/10.6339/24-JDS1148
