Climatic Change

, Volume 131, Issue 4, pp 487–503 | Cite as

Scientists’ views and positions on global warming and climate change: A content analysis of congressional testimonies

  • Xinsheng LiuEmail author
  • Arnold Vedlitz
  • James W. Stoutenborough
  • Scott Robinson


Among many potential causes for policymakers’ contention over whether there is a largely unified scientific agreement on global warming and climate change (GWCC), one possible factor, according to the information deficit theory, is that the scientists who testified in congressional hearings might be substantially divided in their views and positions associated with GWCC. To clarify this, we perform content analysis of 1350 testimonies from congressional GWCC hearings over a period of 39 years from 1969 to 2007 and use the data derived from this content analysis to provide an overview of scientist witnesses’ stances on GWCC. The key findings include: (1) among the scientists’ testimonies with an expressed view on whether GWCC is real, a vast majority (86 %) indicates that it is happening; (2) among the scientists’ testimonies with an identified stance on whether GWCC is anthropogenic, a great majority of them (78 %) indicates that GWCC is caused, at least to some degree, by human activity; (3) even under Republican controlled congresses, there is still a supermajority (75 %) - among the scientists’ testimonies with an expressed position on GWCC existence or GWCC cause - that believes that GWCC is real and that GWCC is anthropogenic; (4) most scientists’ testimonies (95 %) endorse pro-action policy to combat GWCC; and (5) the percentages of scientists’ views and positions are consistent across different types of scientist testimony groups. Our findings suggest that the scientific information transmitted to Congress is not substantially different from the general agreement in the climate science community.


Climate Science Policy Position Scientist Group Organizational Affiliation Congressional Hearing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The material used in this study is based upon research conducted by the Institute for Science, Technology and Public Policy in the George Bush School of Government and Public Service at Texas A&M University and supported under Award No. award NA04OAR4600172 by the National Oceanic and Atmospheric Administration (NOAA), U.S. Department of Commerce. The statements, findings, conclusions, and recommendations are those of the authors and do not necessarily reflect the views of the National Oceanic and Atmospheric Administration or the Department of Commerce. We would like to thank the following people for their assistance: Carol Goldsmith, Ivy Cui, Jessie Wang, and Charles Lindsey. We would also like to thank the anonymous reviewers for their insightful comments and suggestions.


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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Xinsheng Liu
    • 1
    Email author
  • Arnold Vedlitz
    • 1
  • James W. Stoutenborough
    • 2
  • Scott Robinson
    • 3
  1. 1.Texas A&M UniversityCollege StationUSA
  2. 2.Idaho State UniversityPocatelloUSA
  3. 3.University of OklahomaNormanUSA

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