scholarly journals Bias versus bias: Harnessing hindsight to reveal paranormal belief change beyond demand characteristics

2010 ◽  
Vol 17 (2) ◽  
pp. 206-212 ◽  
Author(s):  
M. J. Kane ◽  
T. J. Core ◽  
R. R. Hunt
2021 ◽  
Vol 204 ◽  
pp. 105043
Author(s):  
Kerry Brew ◽  
Taylar Clark ◽  
Jordan Feingold-Link ◽  
Hilary Barth

2021 ◽  
Author(s):  
Antti Gronow ◽  
Maria Brockhaus ◽  
Monica Di Gregorio ◽  
Aasa Karimo ◽  
Tuomas Ylä-Anttila

AbstractPolicy learning can alter the perceptions of both the seriousness and the causes of a policy problem, thus also altering the perceived need to do something about the problem. This then allows for the informed weighing of different policy options. Taking a social network perspective, we argue that the role of social influence as a driver of policy learning has been overlooked in the literature. Network research has shown that normatively laden belief change is likely to occur through complex contagion—a process in which an actor receives social reinforcement from more than one contact in its social network. We test the applicability of this idea to policy learning using node-level network regression models on a unique longitudinal policy network survey dataset concerning the Reducing Deforestation and Forest Degradation (REDD+) initiative in Brazil, Indonesia, and Vietnam. We find that network connections explain policy learning in Indonesia and Vietnam, where the policy subsystems are collaborative, but not in Brazil, where the level of conflict is higher and the subsystem is more established. The results suggest that policy learning is more likely to result from social influence and complex contagion in collaborative than in conflictual settings.


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