The Gateway Belief Model (GBM): A review and research agenda for communicating the scientific consensus on climate change

2021 ◽  
Vol 42 ◽  
pp. 7-12
Author(s):  
Sander van der Linden
2019 ◽  
Vol 41 (5) ◽  
pp. 659-673 ◽  
Author(s):  
Matthew H. Goldberg ◽  
Sander van der Linden ◽  
Matthew T. Ballew ◽  
Seth A. Rosenthal ◽  
Abel Gustafson ◽  
...  

Research on the gateway belief model indicates that communicating the scientific consensus on global warming acts as a “gateway” to other beliefs and support for action. We test whether a video conveying the scientific consensus on global warming is more effective than a text transcript with the same information. Results show that the video was significantly more effective than the transcript in increasing people’s perception of scientific agreement. Structural equation models indicate indirect increases in the beliefs that global warming is happening and is human-caused, and in worry about global warming, which in turn predict increased global warming issue priority.


2017 ◽  
Vol 16 (05) ◽  
pp. A04 ◽  
Author(s):  
Sander van der Linden ◽  
Anthony Leiserowitz ◽  
Edward Maibach

In this paper, we respond to the critiques presented by [Kahan, 2017]. Contrary to claims that the scientific consensus message did not significantly influence the key mediator and outcome variables in our model, we show that the experiment in [van der Linden et al., 2015] did in fact directly influence key beliefs about climate change. We also clarify that the Gateway Belief Model (GBM) is theoretically well-specified, empirically sound, and as hypothesized, the consensus message exerts a significant indirect influence on support for public action through the mediating variables. We support our conclusions with a large-scale replication.


Author(s):  
Inmaculada de Melo-Martín ◽  
Kristen Intemann

Current debates about climate change or vaccine safety provide an alarming illustration of the potential impacts of dissent about scientific claims. False beliefs about evidence and the conclusions that can be drawn from it are commonplace, as is corrosive doubt about the existence of widespread scientific consensus. Deployed aggressively and to political ends, ill-founded dissent can intimidate scientists, stymie research, and lead both the public and policymakers to oppose important policies firmly rooted in science. To criticize dissent is, however, a fraught exercise. Skepticism and fearless debate are key to the scientific process, making it both vital and incredibly difficult to characterize and identify dissent that is problematic in its approach and consequences. Indeed, as de Melo-Martín and Intemann show, the criteria commonly proposed as means of identifying inappropriate dissent are flawed, and the strategies generally recommended to tackle such dissent are not only ineffective but could even make the situation worse. The Fight against Doubt proposes that progress on this front can best be achieved by enhancing the trustworthiness of the scientific community and being more realistic about the limits of science when it comes to policymaking. It shows that a richer understanding is needed of the context in which science operates so as to disarm problematic dissent and those who deploy it in the pursuit of their goals.


2020 ◽  
pp. 107554702098137
Author(s):  
Leticia Bode ◽  
Emily K. Vraga ◽  
Melissa Tully

We experimentally test whether expert organizations on social media can correct misperceptions of the scientific consensus on the safety of genetically modified (GM) food for human consumption, as well as what role social media cues, in the form of “likes,” play in that process. We find expert organizations highlighting scientific consensus on GM food safety reduces consensus misperceptions among the public, leading to lower GM misperceptions and boosting related consumption behaviors in line with the gateway belief model. Expert organizations’ credibility may increase as a result of correction, but popularity cues do not seem to affect misperceptions or credibility.


2008 ◽  
Vol 17 (4) ◽  
pp. 437-470 ◽  
Author(s):  
Richard S.J. Tol

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