G. T. Goldman

710 total citations
21 papers, 460 citations indexed

About

G. T. Goldman is a scholar working on Sociology and Political Science, Health, Toxicology and Mutagenesis and Environmental Engineering. According to data from OpenAlex, G. T. Goldman has authored 21 papers receiving a total of 460 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Sociology and Political Science, 8 papers in Health, Toxicology and Mutagenesis and 4 papers in Environmental Engineering. Recurrent topics in G. T. Goldman's work include Air Quality and Health Impacts (8 papers), Air Quality Monitoring and Forecasting (4 papers) and Climate Change Communication and Perception (3 papers). G. T. Goldman is often cited by papers focused on Air Quality and Health Impacts (8 papers), Air Quality Monitoring and Forecasting (4 papers) and Climate Change Communication and Perception (3 papers). G. T. Goldman collaborates with scholars based in United States, Netherlands and Australia. G. T. Goldman's co-authors include Matthew J. Strickland, James A. Mulholland, Paige E. Tolbert, Armistead G. Russell, Mitchel Klein, Lance A. Waller, Francesca Dominici, Katherine Gass, Abhishek Kumar Srivastava and Eric S. Edgerton and has published in prestigious journals such as Nature, Science and Environmental Science & Technology.

In The Last Decade

G. T. Goldman

19 papers receiving 448 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
G. T. Goldman United States 10 313 127 70 66 47 21 460
Adam F Benson United States 8 342 1.1× 75 0.6× 126 1.8× 46 0.7× 44 0.9× 14 511
Jonathan Colmer United States 8 235 0.8× 60 0.5× 124 1.8× 29 0.4× 43 0.9× 20 476
Okhee Yi South Korea 7 359 1.1× 92 0.7× 32 0.5× 49 0.7× 27 0.6× 8 468
Sante Minerba Italy 6 247 0.8× 59 0.5× 45 0.6× 42 0.6× 38 0.8× 21 331
Vijay S. Limaye United States 12 318 1.0× 52 0.4× 113 1.6× 104 1.6× 84 1.8× 25 463
Patrick F. DeLuca Canada 10 391 1.2× 108 0.9× 60 0.9× 53 0.8× 40 0.9× 14 522
Susan Chemerynski United States 7 319 1.0× 62 0.5× 38 0.5× 65 1.0× 23 0.5× 13 440
Hermano Albuquerque de Castro Brazil 15 333 1.1× 60 0.5× 34 0.5× 58 0.9× 84 1.8× 59 616
Haley M. Lane United States 4 182 0.6× 74 0.6× 106 1.5× 29 0.4× 130 2.8× 4 371
Juan Felipe Franco Colombia 11 175 0.6× 114 0.9× 68 1.0× 21 0.3× 57 1.2× 31 388

Countries citing papers authored by G. T. Goldman

Since Specialization
Citations

This map shows the geographic impact of G. T. Goldman's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by G. T. Goldman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. T. Goldman more than expected).

Fields of papers citing papers by G. T. Goldman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G. T. Goldman. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by G. T. Goldman. The network helps show where G. T. Goldman may publish in the future.

Co-authorship network of co-authors of G. T. Goldman

This figure shows the co-authorship network connecting the top 25 collaborators of G. T. Goldman. A scholar is included among the top collaborators of G. T. Goldman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with G. T. Goldman. G. T. Goldman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Bond, Allison E., et al.. (2025). Frequency of Black and American Indian/Alaskan Native US Residents Screened for Firearm Access. Journal of Racial and Ethnic Health Disparities. 13(2). 1299–1306.
2.
Goldman, G. T., et al.. (2023). An equity and environmental justice assessment of anti-science actions during the Trump administration. Journal of Public Health Policy. 44(1). 147–162. 9 indexed citations
3.
Goldman, G. T., et al.. (2021). Assessment of Air Pollution Impacts and Monitoring Data Limitations of a Spring 2019 Chemical Facility Fire. Environmental Justice. 15(6). 362–372. 8 indexed citations
4.
Hendlin, Yogi Hale, et al.. (2021). The disinformation playbook: how industry manipulates the science-policy process—and how to restore scientific integrity. Journal of Public Health Policy. 42(4). 622–634. 32 indexed citations
5.
Goldman, G. T., Cesunica E. Ivey, Fernando Garcia–Menendez, & Sivaraman Balachandran. (2021). Beyond the Lab: Early Career Researchers May Find Purpose through Policy, Advocacy, and Public Engagement. Environmental Science & Technology. 55(5). 2720–2721. 1 indexed citations
6.
Goldman, G. T., et al.. (2021). Strengthen scientific integrity under the Biden administration. Science. 371(6530). 668–671. 3 indexed citations
8.
Goldman, G. T., et al.. (2020). Perceived losses of scientific integrity under the Trump administration: A survey of federal scientists. PLoS ONE. 15(4). e0231929–e0231929. 17 indexed citations
9.
Declet‐Barreto, Juan, et al.. (2020). Hazardous air pollutant emissions implications under 2018 guidance on U.S. Clean Air Act requirements for major sources. Journal of the Air & Waste Management Association. 70(5). 481–490. 3 indexed citations
10.
Goldman, G. T. & Francesca Dominici. (2019). Don't abandon evidence and process on air pollution policy. Science. 363(6434). 1398–1400. 35 indexed citations
11.
Goldman, G. T., et al.. (2017). Ensuring scientific integrity in the Age of Trump. Science. 355(6326). 696–698. 20 indexed citations
12.
Carroll, Carlos, Brett Hartl, G. T. Goldman, et al.. (2017). Defending the scientific integrity of conservation‐policy processes. Conservation Biology. 31(5). 967–975. 27 indexed citations
13.
Goldman, G. T. & Andrew A. Rosenberg. (2017). See no evil. The New Scientist. 235(3133). 22–23.
14.
Rosenberg, Andrew A., Lewis M. Branscomb, Peter C. Frumhoff, et al.. (2015). Congress's attacks on science-based rules. Science. 348(6238). 964–966. 7 indexed citations
15.
Gundersen, Linda, J. W. Geissman, G. T. Goldman, et al.. (2014). Spotlight on Scientific Integrity and Geoethics at the 2014 AGU Fall Meeting. Eos. 95(49). 465–465. 1 indexed citations
16.
Strickland, Matthew J., Katherine Gass, G. T. Goldman, & James A. Mulholland. (2013). Effects of ambient air pollution measurement error on health effect estimates in time-series studies: a simulation-based analysis. Journal of Exposure Science & Environmental Epidemiology. 25(2). 160–166. 43 indexed citations
17.
Goldman, G. T., James A. Mulholland, Armistead G. Russell, et al.. (2012). Characterization of ambient air pollution measurement error in a time-series health study using a geostatistical simulation approach. Atmospheric Environment. 57. 101–108. 32 indexed citations
18.
Goldman, G. T., James A. Mulholland, Armistead G. Russell, et al.. (2011). Impact of exposure measurement error in air pollution epidemiology: effect of error type in time-series studies. Environmental Health. 10(1). 61–61. 163 indexed citations
19.
Goldman, G. T., James A. Mulholland, Armistead G. Russell, et al.. (2010). Ambient Air Pollutant Measurement Error: Characterization and Impacts in a Time-Series Epidemiologic Study in Atlanta. Environmental Science & Technology. 44(19). 7692–7698. 54 indexed citations
20.
Goldman, G. T., et al.. (2009). Assessment of Ambient Air Pollutant Measurement Error Associated with Instrument Precision and Spatial Heterogeneity. Epidemiology. 20. S80–S80. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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